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        <dcterms:issued>1995</dcterms:issued>
        <dc:language>es</dc:language>
        <dc:creator>Corden, W. Max</dc:creator>
        <dc:contributor>Corden, W. Max</dc:contributor>
        <dcterms:title>Una zona de libre comercio en el Hemisferio Occidental: posibles implicancias para América Latina</dcterms:title>
        <dcterms:isPartOf>En: La liberalización del comercio en el Hemisferio Occidental - Washington, DC : BID/CEPAL, 1995 - p. 13-40</dcterms:isPartOf>
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Valuation of Tr
Coastal Resources:
Theory and Application
of Linear Programming

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United Nations

i Economic Commission
for Latin America and the Caribbean

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International Center for Living Aquatic
Resources Management

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Valuation of Tropical Coastal R esoui0 * ^
Theory and Application of Linear Programming

Edited by
Annabelle Cruz-Trinidad

1996

900026276
y w v ¿ b z /b - BIBLIOTECACËPÂL

United Nations
Economic Commission
for Latin America and the Caribbean

International Center for Living Aquatic
Resources Management

f (o H (o 3
e

Valuation of Tropical Coastal Resources:
Theory and Application of Linear Programming
Edited by
A

nnabelle

C r u z - T r in id a d

1996

Printed in Manila, Philippines

Published by the United Nations Econom ic Com mission for Latin A m erica and the Caribbean (ECLAC),
Casilla 179-D, Santiago, Chile; and the International Center for Living Aquatic Resources M anagement (ICLARM ),
MCPO Box 2631, 0718 M akati City, Philippines.

ICLARM s technical services were developed in response to the lack of existing publishing
outlets for longer papers on tropical fisheries research.
The ICLARM Studies and Reviews series consist of concise documents providing thorough
coverage o f topics of interest to the Center, which are undertaken by staff or by external specialists
on commission.
Essentially, all documents in the series are carefully peer reviewed externally and internally.
A num ber have been rejected. Those published are thus primary literature. Between 600 and 1,000
copies o f each title are dissem inated - sold or provided in exchange or free of charge.

Cruz-Trinidad. A., Editor. 1996. Valuation o f tropical coastal resources: theory and application o f linear
program m ing. ICLARM Stud. Rev. 25, 108 p.

Copyediting and indexing: Leticia B. Dizon
Graphs and artwork: Albeit B. Contemprate
Layout: Ariel C. Aquisap and Ma. Graciela R. Balleras

Cover: An abstraction o f the multiactivity feature o f the coastal zone. Lines represent the diverse resource use
constraints and the hatched (shaded) area, the optimal allocation of resources. Illustration by Chris Bunao.

ISSN 0115-4389
ISBN 9 7 1-8709-72-X

ICLARM Contribution No. 1223

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C o n ten ts

1 7 O 1997
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NEb U iüÁS
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SANTIAGO-CHILE

JV

F o re w o rd • M .J. W illiam s, IC L A R M a n d A. D ou rojean n i, E C L A C ................................................................... v
F o re w o rd • D . P a u ly ............................................................................................................................................................. vi
P re fa c e • A. C ru z-T rin id a d ............................................................................................................................................... viii
T h e In te g ra te d F u n c tio n a l C o e ffic ie n ts M e th o d fo r C o a sta l R e so u rc e s V aluation
• M. A gü ero, A. C ruz-T rin idad, E. G o n za lez a n d F. B e ll

1 L--

V a lu a tio n C o n c e p ts a n d T e c h n iq u e s w ith A p p lic a tio n s to C o a sta l R e so u rc e s
• M. A g ü e ro a n d X. F lo r e s .................................................................................................................................................... 9
O p tio n s fo r M a n g ro v e M a n a g e m e n t in th e G u lf o f G u a y a q u il, E c u a d o r
• F. B e ll a n d A. C ru z-T rin id a d ........................................................................................................................................ 17
O p tim iz a tio n o f E c o n o m ic B e n e fits fro m F ish e ry , F o re stry a n d T o u rism in B io -B io , C h ile
• E. A ra n e d a , A . C ruz-T rin idad, F. M o ra le s a n d A. A r e l l a n o ............................................................................. 32
O p tio n s fo r L a n d U se M a n a g e m e n t in L in g a y e n G u lf, P h ilip p in e s
• A. C ru z-T rin idad, Z. A lo ja d o a n d A. C a rg a m e n to

64 ¿

O p tim a l F le e t C o n fig u ra tio n in S a n M ig u e l B ay, P h ilip p in es:
A S im p le L in e a r P ro g ra m m in g A p p ro a c h
• A. C ru z-T rin id a d a n d L.R. G a r c e s ...............................................................................................................................78
O P U S : In te ra c tiv e S o ftw a re fo r S o lv in g L in e a r P ro g ra m m in g M o d e ls U sin g
th e S im p le x A lg o rith m • M. A g ü ero an d S ta ff o f IC L A R M -E C L A C P r o j e c t ................................................ 87
A p p e n d ix 1 - D o c u m e n ta tio n o f L P T a b l e a u s ........................................................................................................... 97
A p p e n d ix 2 - G lo ss a ry o f T e c h n ic a l T e r m s .................................................................................................................97
A u th o r/N a m e I n d e x ............................................................................................................................................................ 100
G e o g ra p h ic I n d e x ................................................................................................................................................................. 102
S p e c ie s I n d e x ........................................................................................................................................................................ 104

iii

£■

Foreword
T h is v o lu m e m a rk s th e c u lm in a tio n o f IC L A R M a n d E C L A C s c o lla b o ra tio n w h ic h s ta rte d in 1990
v ia th e p ro je c t e n title d  S o c io e c o n o m ic V a lu a tio n o f C o a sta l R e so u rc e s in S o u th w e s t L a tin A m eric a.
T h e w o rld w id e tre n d in e n v iro n m e n ta l d e g ra d a tio n h as n o t sp a re d L a tin A m e ric a , p a rtic u la rly th at
in v o lv in g la rg e -s c a le m a n g ro v e c o n v e rsio n in to sh rim p p o n d s, a n d c o n flic tin g u se o f a q u a tic re so u rc e s
su c h as b y fish e rie s a n d b y o th e r in d u strie s. T h e p ro je c t aim s to d e riv e a p p ro p ria te so c ia l a n d e c o n o m ic
v a lu e s fo r s e le c te d c o a sta l re so u rc e s in o rd e r to h elp ra tio n a liz e th e ir p re se n t u se a n d m a n a g e m e n t. T h e
p ro je c ts im p o rta n t a c h ie v e m e n ts in c lu d e a lin e a r p ro g ra m m in g so ftw a re p a c k a g e , O P U S ; ap p lic a tio n s
o f lin e a r p ro g ra m m in g m o d e ls to fo u r se le c te d sites in L a tin A m e ric a a n d th e P h ilip p in e s; a n d a re v ie w
o f e x is tin g v a lu a tio n m e th o d s fo r e n v iro n m e n ta l a n d n a tu ra l re so u rc e s. T h e e ss se n c e o f th e w o rk d o n e
b y IC L A R M a n d E C L A C is fu lly c a p tu re d in th is v o lu m e.
W e w o u ld lik e re se a rc h e rs a n d m a n a g e rs to u se a n d re v ie w o u r w o rk in o rd e r to b e tte r u n d e rsta n d
th e d y n a m ic s o f c o a sta l m a n a g e m e n t p ro b le m s a n d to a p p re c ia te d e c isio n to o ls su c h as O P U S . W e
c o m m e n d all th e au th o rs in c lu d in g IC L A R M a n d E C L A C s ta ff w h o c o n trib u te d th e ir e ffo rts to this
book.

M

eryl

J. W

il l ia m s

A x e l D o u r o je a n n i

D ir e c to r G e n e ra l

Chief, D iv isio n o f N a tu ra l

IC L A R M

R eso u rces a n d E n ergy
E C L A C -U n ited N a tio n s

Foreword
T h is b o o k c o n c lu d e s a jo in t p ro je c t o n “ S o c io e c o n o m ic V aluation o f C o a sta l R e so u rc e s in S o u th w e st
L a tin A m e ric a ” b e tw e e n th e U n ited N a tio n s E c o n o m ic C o m m issio n fo r L atin A m e ric a a n d th e C arib b ea n
(E C L A C ), S a n tia g o , C h ile , a n d th e In te rn a tio n a l C e n te r fo r L iv in g A q u a tic R e so u rc e s M a n a g e m e n t
(IC L A R M ), M a n ila , P h ilip p in e s , in itia te d in 1990, b u t w h o se a n te c e d e n ts re a c h m u c h d eep er. O n e k ey
sta rtin g p o in t w a s th e d o c to ra l th esis o f th e le a d e r o f th a t p ro je c t, Dr. M a x A g ü e ro , o n C h ile a n fish e rie s,
w h ic h u s e d L in e a r P ro g ra m m in g (L P ) as its m a jo r tool. Dr. M a x A g ü e ro jo in e d IC L A R M in M a rc h
1986 a n d h a d s o o n c o n v in c e d h is c o lle a g u e s th a t L P c o u ld serv e as fra m e w o rk fo r stu d ie s o f c o m p le x
b io s o c io e c o n o m ic sy ste m s su ch as th e p elag ic fish eries o f P eru, o r th e flo o d p lain fish erie s o f B a n g la d e sh ,
stu d ie d in th e c o n te x t o f a P h .D . th e sis th at h e su p erv ise d .
It w a s lo g ic a l th u s to a ssu m e th a t L P w o u ld also b e a p p lic a b le to th e stu d y o f c o a sta l a re a s, w h o se
a p p a re n t c o m p le x ity th e n se e m e d to d e fy fo rm a l an a ly sis, a llo w in g o n ly c o n c e p tu a l d e sc rip tio n . A
p ro je c t to te s t th e su ita b ility o f L P -b a se d a p p ro a c h e s fo r th e a n a ly sis o f in te rs e c to ra l in te ra c tio n a n d th e
v a lu a tio n o f c o a s ta l re s o u rc e s w a s th u s co n c e iv e d , a n d E C L A C id e n tifie d as th e b e s t p o s sib le p a rtn e r
fo r su c h v e n tu re .
D r. M . A g ü e ro re lo c a te d fro m M a n ila to S a n tia g o in A p ril 1990, a n d im m e d ia te ly b u ilt a te a m
c o n s is tin g o f y o u n g re s e a rc h e rs a n d a p ro g ra m m e r to d e v e lo p a n d te st su ita b le L P so ftw a re , a n d to
a p p ly th e L P a p p ro a c h to v a rio u s sites in C h ile an d the E c u a d o ria n co ast.
F o r th e p ro je c t to h a v e d e v e lo p e d its o w n L P so ftw a re (“ O P U S ” , see b elo w ) m ay a p p e a r u n n ecessary ,
as c o m m e rc ia l p a c k a g e s e x ist - as stan d a lo n e ap p lic a tio n s, o r as p a rt o f sp re a d sh e e t p ro g ra m s (e.g .,
M ic ro s o ft E x c e l, Q u a ttro P ro) - w h ic h c a n h a n d le su c h p ro b le m s. H o w e v e r, sp re a d sh e e ts w ith L P
a p p lic a tio n s d id n o t e x is t w h e n th e p ro je c t started , a n d w e re n o t a n ticip ated .
O n e p a rtic u la r p ro b le m w h ic h th e p ro je c t h a d to ta c k le w as th e c o s tin g o f n o n m a rk e t g o o d s an d
se rv ic e s, i.e ., th e “ in te rn a liz a tio n ” o f (or: e x p lic itly a c co u n tin g for) w h a t e c o n o m ists ca ll “e x te rn a litie s ” .
T h e c o n trib u tio n s in this b o o k p ro v id e so m e p ra ctical ap p ro ach e s fo r d o in g this. Still, this v e x in g p ro b le m
is g o in g to c o n tin u e to b e w ith us a n d c o n tin u e to b e a m a jo r c a u se fo r e n v iro n m e n ta l d e g ra d a tio n an d
p o llu tio n .
T h e IC L A R M -E C L A C C o a sta l V alu atio n P ro je c t w as fo re se e n to h a v e tw o p h a se s, P h a s e I fo r
c o n c e p t a n d s o ftw a re d e v e lo p m e n t a n d P h a se II, fo r th e ir a p p lic a tio n to v a rio u s sites in C h ile an d
e lse w h e re in S o u th A m eric a. In Ju n e 1992, an e x tern al re v ie w p an e l le d b y Dr. L. F a llo n -S c u ra c o n c lu d e d
th a t th e p ro je c t w a s “tech n ica lly sound, the m eth ods d e v e lo p e d p o te n tia lly useful, is c o m p a tib le w ith
the fu tu re IC L A R M a n d therefore, sh o u ld con tinu e w ith P h a se I I ”. U n fo rtu n a te ly , IC L A R M d id n o t
h a v e th e c o re fu n d s re q u ire d fo r P h a se II o f th e p ro ject.
M s. A b b ie C ru z -T rin id a d , an IC L A R M re se a rc h e r w h o h a d p re v io u sly c o lla b o ra te d w ith Dr. A g ü ero ,
to o k o v e r th e ta s k o f c o m p le tin g a n d ed itin g th e p u b lic a tio n fro m th e n u m e ro u s in te rn a l re p o rts p re p a re d
d u rin g P h a s e I o f th e p ro je c t, a n d th u s d o c u m e n tin g th e a p p lic a tio n o f O P U S to v a rio u s sites in C h ile
a n d E c u a d o r. M o re o v e r, she te a m e d u p w ith sta ff fro m tw o o th e r IC L A R M re s e a rc h p ro je c ts - o n e
c o v e rin g S a n M ig u e l B ay, the o ther, L in g a y e n G ulf, b o th in the P h ilip p in es, to sh o w th at the L P a p p ro a c h
d e v e lo p e d b y th e IC L A R M -E C L A C te a m also w o u ld w o rk in th e S o u th e a st A sia n c o n te x t.
W e ta k e th e s u c c e ss o f th is tra n s fe r fro m S o u th A m e ric a to S o u th e a s t A s ia as im p ly in g th a t th e
a p p ro a c h d o c u m e n te d in this b o o k c a n b e a p p lie d to an y c o a stlin e . H o w e v e r, w e d o n o t s u g g e st th a t th is
a p p ro a c h s h o u ld e v e r b e u se d alone: th e c o m p le x itie s w ith in an d a m o n g se c to ra l in te ra c tio n s o c c u rrin g
alo n g th e c o a s tlin e s o f th e w o rld c a n n o t b e d esc rib e d , le t a lo n e p re d ic te d b y th e v a ria b le s - h o w e v e r
n u m e ro u s th e y m a y b e - o f a n y sin g le m o d el. T h is im p lie s th at w h e re v e r p o ssib le , a w id e v a rie ty o f
vi

m e th o d o lo g ic a l a p p ro a c h e s sh o u ld b e u se d w ith th e o n e p re se n te d in th is b o o k b e in g o n e a m o n g o th ers.
I c o n g ra tu la te th e au th o rs o f th e c o n trib u tio n s in c lu d e d in this b o o k , e sp e c ia lly D r. M a x A g iiero , fo r
th e ir d a rin g to q u a n tify a n d th u s re n d e r a v a ila b le fo r an a ly sis c o a sta l in te ra c tio n s w h ic h o th e rs w o u ld
h a v e o n ly ta lk e d a b o u t, a n d M s. A b b ie C ru z -T rin id a d , fo r risin g to th e c h a lle n g e o f e d itin g th is v o lu m e.
F in a lly , I th a n k th e E c o n o m ic C o m m issio n fo r L a tin A m e ric a a n d th e C a rib b e a n (E C L A C ) fo r
b e in g a g ra c io u s h o s t to th e p ro je c t th a t le d to th is b o o k , a n d fo r its h e lp in m a in ta in in g c o m m u n ic a tio n s
b e tw e e n th e e d ito rs a n d th e n o w sc a tte re d co n trib u to rs.

D a n ie l P a u ly

P rin c ip a l S cien ce A dvisor, IC L A R M

Preface

T h is v o lu m e c o n ta in s se v e n p a p e rs , tw o o f w h ic h ta c k le th e c o n c e p tu a l e le m e n ts o f L in e a r
P ro g ra m m in g a n d re so u rc e s v a lu a tio n ; fo u r are a p p lic a tio n p a p e rs w h ile th e la s t is th e u s e rs ’ m a n u a l in
s u p p o rt o f O P U S , th e L P so ftw a re d e v e lo p e d b y th is p ro jec t. T w o a p p lic a tio n p a p e rs are fro m L atin
A m eric a: o n e fro m th e B io -B io re g io n in C h ile a n d th e o th e r fro m th e G u lf o f G u a y a q u il, E c u a d o r. T h e
o th e r tw o are fro m th e P h ilip p in e s: S an M ig u e l B ay, in B ic o l p ro v in c e , fo r w h ic h IC L A R M c o n d u c te d
m u ltid is c ip lin a ry stu d ie s in 1980 a n d 1992; a n d L in g a y e n G u lf, also th e site o f IC L A R M ’s c o a sta l a re a
m a n a g e m e n t p ro je c t (1 9 8 6 -1 9 9 1 ) a n d later, G e o g ra p h ic In fo rm a tio n S y ste m s (G IS ) a p p lic a tio n s. T h e
L P ta b le a u s u s e d fo r th e se a p p lic a tio n p a p e rs are a v a ila b le in sp re a d sh e e t fo rm a n d are d e s c rib e d in
A g iie ro e t al. (th is v o l.)
I e x a m in e in m a n y w a y s th e lim ita tio n s p o se d b y L P a n d th e im p o rta n c e o n e m u st m u st g iv e to th e
d a ta u se d b y th e m o d el. B u t th en , e v e ry m o d el, n o m a tte r h o w e la b o ra te , h as its lim ita tio n s. It is h o w w e
in te rp re t th e m o d e ls a n d th e ir o u tp u ts th a t m atters. A s fo r th e u se fu ln e ss o f th is e x e rc ise , I in v ite th e
re a d e rs to d ecid e.
I le a v e fo r la st th a t w h ic h I re lish m o st— to g iv e c re d it to th o se w h o m a d e th is v o lu m e p o ssib le . I
th a n k M r. A le x is F a b u n a n w h o p a in s ta k in g ly re c o n stru c te d th e L P ta b le a u s u n d e r th e m o s t c o n stra in in g
c irc u m sta n c e s (a 2 8 6 c o m p u te r w ith so m e 4 m e g a b y te s o f R A M to h a n d le a 7 8 0 x 5 6 0 m a trix !); M r.
A lv in C a ta la n w h o h e lp e d m e c o m p le te th e b ib lio g ra p h ic e n trie s, d e v e lo p e d th e g lo ss a ry o f tec h n ic a l
term s, a n d fin a liz e d th e in d ic e s; M r. F .S .B . T orres, Jr. fo r h e lp in g m e w ith th e sp e c ie s in d e x a n d th e
A p p e n d ix to th e p a p e r b y A ra n e d a et al.; Dr. W illia m S u n d e rlin , fo rm e r IC L A R M staff, n o w w ith th e
C e n te r fo r In te rn a tio n a l F o re s try R e se a rc h (C IF O R ) w h o h e lp e d m e re c o n s tru c t th e sp ec ie s ap p e n d ix
fo r th e fo re s try se c to r o f B ío -B ío ; M r. F.C . G a y a n d o , Jr. a n d M r. E li G a rn a c e fo r re v ie w in g th e so ftw a re
a n d fo r re v is in g th e u sers m an u al; M s. M e rly M e d in a fo r h e r a ss ista n c e in th e ty p in g a n d p rin tin g o f
m a n u sc rip ts a n d tab le s; D rs. R o b e rt P o m e ro y a n d M a h fu z A h m e d , fo r ta k in g tim e o u t to re a d th e
c o n c e p t p a p e rs a n d fo r freely p ro v id in g so m e c o n stru c tiv e co m m e n ts; a n d Dr. M e ry l W illia m s, fo r h er
s u p p o rt o f th e w h o le project.
T h is w o rk w o u ld n o t h av e b e e n p o ss ib le w ith o u t th e fo re sig h t, in d u stry a n d ta le n t o f D r. M ax
A g ü e ro a n d h is te a m o f e x p e rts fro m th e IC L A R M -E C L A C p ro je c t, sp e c ific a lly M s. F a b io la B e ll, M s.
A n g e lic a A re lla n o , M r. E d g a rd o A ra n e d a , M r. F ra n c isc o M o ra le s, all au th o rs o f th e p a p e rs in th is
v o lu m e. I th a n k m y c o -a u th o rs, sp ec ific ally , M s. Z o ra id a A lo jad o a n d M r. L en G a rc e s o f IC L A R M an d
M s. A g n e s G ra c e C a rg a m e n to o f the N a tio n a l E c o n o m ic an d D e v e lo p m e n t A u th o rity o f th e P h ilip p in e s
(N E D A -R e g io n I) fo r th e ir c o o p e ra tio n d e sp ite th e sh o rt n o tic e a n d e x tre m e ly tig h t sc h e d u le s.
I th a n k D r. D a n ie l P au ly w h o se u n fa ilin g su p p o rt a n d e n c o u ra g e m e n t I b e g a n to e x p e rie n c e in 1986
w h e n h e w as th e n D ire c to r o f th e R e s o u rc e A sse ssm e n t a n d M a n a g e m e n t P ro g ra m , la te r to b e c o m e th e
C a p tu re F ish e rie s M a n a g e m e n t P ro g ram . I th a n k h im m o st esp e cially b e c a u se as a sc ie n tist fro m a n o th e r
d isc ip lin e , h e d id n o t h a m p e r m y p ro fe ssio n a l a n d in te lle c tu a l in te re sts in th e ‘o th e r ’ sc ie n c e s (i.e.,
ec o n o m ic s ) a n d h ad in fa ct e n c o u ra g e d m e to p ro d u c e w o rk th at I a m v e ry p ro u d o f today.

A n n a b e l l e C r u z - T r in id a d

R esea rch A sso c ia te , IC L A R M

The Integrated Functional Coefficients
Method for Coastal Resources Valuation*

in c lu d in g : o p tim a l d e v e lo p m e n t s tr a te g ie s fo r
m angroves in the G ulf o f G uayaquil, Ecuador (Bell
and C ruz-T rinidad, this vol.) and land use in the
Lingayen G ulf area, Philippines (C ruz-Trinidad et al.,
this vol.); optim al fleet allocation in San M iguel Bay,
Philippines (Cruz-Trinidad and G arces, this vol.); and
o p tim a l p ro d u c tio n and m a rk e tin g stra te g ie s fo r
fisheries and forestry in B io-B io, C hile (A raneda et
al., this vol.).
The IFC m ethod was designed to consolidate all
negative (costs) and positive (revenues) flows resulting
from different levels o f resource exploitation activities
into a single num eraire, i.e., econom ic value. The IFC
m ethod derived its nam e from its features, nam ely: (i)
the highly integrated approach to m anag em en t o f
re s o u rc e sy ste m s an d (ii) th e u se o f fu n c tio n a l
coefficients to represent input-output efficiency.

M a x A g ü e r o  , IC L A R M -E C L A C Project on the
Socioeconomic Valuation o f Coastal Resources in Southwest
Latin America, Casilla 179-D, Santiago, Chile

A n n a b e l l e C r u z - T r i n i d a d , International Centerfo r Living
Aquatic Resources Management (ICLARM), MCPO Box
2631, 0718 Makati City, Philippines
E x e q u e l G o n z a l e z 1, ICLARM -ECLAC Project on the
Socioeconomic Valuation of Coastal Resources in Southwest
Latin America, Casilla 179-D, Santiago, Chile

B e l l 2, IC L A R M -E C L A C Project on the
Socioeconomic Valuation of Coastal Resources in Southwest
Latin America, Casilla 179-D, Santiago, Chile

F a b io la

Framework for Analyzing
Coastal Resource Systems

AGÜERO, M „ A. CRUZ-TRINIDAD, E. GONZALEZand F. BELL. 1996.
The integrated functional coefficients method for coastal resources
valuation, p. 1-8. In A. Cruz-Trinidad (ed.) Valuation o f tropical
coastal resources, theory and application o f linear program m ing.
ICLARM Stud. Rev. 25, 108 p.

A coastal resource system can be conceptualized
as encom passing the interactions betw een and am ong
the biophysical, terrestrial and m arine environm ents
a n d h u m a n a c tiv itie s , in c lu d in g th e g o v e rn in g
institutional and organizational arrangem ents (Scura
et al. 1992). T he coastal area is ch a rac te rized by
m ultiple resources and by m ultiple users and uses o f
resources leading to potential conflict, m ism anage­
ment, and ultim ately, econom ic loss.
Two b asic paradigm s w ere used: i) th e Total
E conom ic Value (T E V ) w hich is used to identify
different sources o f value em anating from various
coastal resources, and ii) the system s approach, to
a n a ly z e th e w h o le sysjgiji, its c o m p o n e n ts, and
interactions.
‘
Several sources of value can be attributed to coastal
resources including its use and n o nuse values. A
resource, such as a fish stock or charcoal, can either
be directly valued as an econom ic good, or indirectly
valued for its potential or ecological functions. The
valuation o f indirect goods and services is not as
straightforw ard as those o f the m arketable kind but
p o ten tially ap p licab le m ethods are av a ila b le (see
Agiiero et al., this vol.). A useful exercise in valuation
is the identification o f in terrelatio n sh ip s betw een
resources and their com ponents.
In te rre la tio n s h ip s b e tw e e n a re s o u rc e o r its
com ponent is m arked by a (+) if it is used as an input

Abstract
The integrated functional coefficients method is described as a linear
program m ing algorithm that perm its analysis o f coastal system s with
diverse and conflicting econom ic uses. A sim ple guide to the application
o f the technique is provided.

Introduction
T h e In teg rated F u n ctio n al C o efficien ts (IFC )
m ethod is a tool based on linear program m ing theory
th at w as en h an ced and tested by a pro ject jo in tly
im p lem en ted by the In tern atio n al C enter fo r L iving
A quatic R esources M anagem ent (IC LA R M ) and the
E co n o m ic C om m ission fo r L atin A m erica and the
C arib b ean (E C L A C ) on S ocioeconom ic V aluation
o f C o astal R esources in L atin A m erica fro m M ay
1990 to J a n u a ry 1993. C o m p le m e n tarily , lin e a r
program m ing softw are3 was developed and applied in
various sites and problem s o f varying com plexity,
* ICLARM Contribution No. 1217.
Present address: International C enter for Sustainable Ecological
Developm ent (ICSED), Casilla 27004, Santiago, Chile.
2Present address: Calle Edinburgo 520, Depto. 102, Las Condes,
Santiago, Chile.
‘OPUS is linear program m ing software developed by the ICLARMECLAC Project on Socioeconom ic Valuation o f Coastal Resources in Latin
America. The users m anual is on p. 89.

1

2

to another activity and a (-) if use o f a resource impinges
on the current and potential use o f another (Table 1).
A quaculture and urban expansion often necessitate
m angrove conversion (see Bell and Cruz-Trinidad, this
vol.) and are thus m arked as (-). M angroves and, to a
certain extent, seagrass beds, provide critical habitats
for the juveniles o f coral reef fish and crustaceans as
well; these are m arked (+) in the m atrix. The negative
im p a c t o f a q u a c u ltu re , a g ric u ltu re , an d m in era l
ex tractio n on capture fisheries and coral re e f and
seagrass ecosystem s is via pollutants em anating from
productive processes. For each resource category, there
are m arket and nonm arket goods and services that add
to the econom ic value. The matrix is particularly helpful
in identifying indirect values or externalities im posed
on certain resources.
A fter relevant valuation work has been made, the
m ode o f analysis conform s to the “system s approach”
which M attessich (1984) described as having strong
em p h asis on in p u t-o u tp u t featu res and a pu rp o se
orientation. In addition, Laszlo (1972) noted that it is a
“way o f thinking about phenomenon in terms o f wholes,
including a ll o f the parts, components or subsystems
and their interrelationships.”
T he c o a sta l zone can be view ed as an entity
com prised o f several interacting sources o f value. The
m agnitude and direction o f interrelationships between
these sources should then be identified and, if possible,

quantified, such that the effect on TEV o f changes in
resource endow m ent or linkages can be anticipated.
T he T E V fo r the c o a sta l system is no t a sim p le
sum m ation o f the value o f different sectors. Instead,
the TEV accounts for dynam ic functions within the
system. This dynam ism is em bedded in the constraints
posed by the use and dependency on a single resource
base (natural, hum an and technological), the functional
relationships between and among production inputs and
output, and by the sequence o f activities leading to an
econom ic good. Thus, negative externalities caused by
m ism anagem ent o f a particular resource would lead to
the detrim ent o f those m arked (-) in the m atrix and
would ultim ately cause a reduction in the TEV.
Perhaps the m ost com m on conflicts occur at the
level o f goal-setting. In the paper by A raneda et al.
(this vol.) the choice as to w hether fishery, forestry or
tourism should be developed is o f im portance because
the priority given to one activity im plies that few er
resources are m ade available for other possible uses.
Bell and Cruz-Trinidad (this vol.) also posed a crucial
question as to the conversion vis-à-vis conservation of
m angroves, which involves foregoing present short­
term gains from shrim p aquaculture for longer-term
benefits. Such is also the problem recognized by C ruz­
Trinidad et al. (this vol.) in the conversion o f lowyielding rice farm s to shrim p and/or m ilkfish culture.
W ithin the San M iguel Bay fishery (C ruz-Trinidad and

Table 1. Exam ple o f som e coastal resources/activities and related influences and impacts.
Influences and impacts2
R esources/activities1

MG

AQ

CF

M angrove/nipa sw am p (MG)
Aquaculture (AQ)
Capture fishery (CF)
Coral reefs (CR)
Seagrass beds (SG)
Agriculture (AG)
Mineral extraction (MN)
Oil and gas (OG)
Salt production (SP)
Sand m ining (SM)
Habitat nesting (HB)
Urban developm ent (UD)
Coastal vegetation (CV)

XXX
0
+
+
+
+

XXX
0
+
-

_

CR

+
o
XXX
+
+
0
+
0

+
o
XXX
+
0
+
+

MN

HB

AG

+
+
XXX
0
+
+

_

_

.

.

_

0
XXX
0
0
-

-

0

0
0
0
-

0
0
0
0

A dapted from Dixon (1989).
Prepared by Mr. K eene Haywood, Reefbase volunteer, February-June 1995.
+ = input.
- = negative impact,
o = minimal im pact, may be (+) or (-).

OG

SM

SG

XXX

SP

0
0
+

XXX
0
+

XXX
0
+

XXX

-

-

-

-

+

UD
4
*
O
0
+
+
0
0
-

XXX
+

CV
_

.

■ +
+
+
-

XXX

0
+
+
-

-

XXX

G arces, this vol.) conflicts arise from the choice of
particular gear types.

The preceding section indicates that for a particular
resource system , several decisions are to be made. This
section presents a range o f possible tools to enable the
d e c isio n m a k e r to arrive at a decision and fu rth er
an ticip ate im pacts caused by changes in resource
e n d o w m e n ts or in the in terre latio n sh ip s betw een
activities on the decision variable.

F eatu res
Linear program m ing (LP) is an operations research
m ethod developed in the 1940s for use in m ilitary
applications, and now w idely used in business and
agriculture. Early applications o f the m ethod assum ed
profit m axim izing behavior, a single-period planning
horizon, and no consideration for risk and uncertainty.
S u b s e q u e n t d e v e lo p m e n ts, h ow ever, p ro v e d th at
program m ing models can be more realistic and flexible.
A dvanced m odeling techniques include m ultiperiod
lin e a r p ro g a m m in g , m u lti-o b je c tiv e m o d e lin g ,
n o n lin ear p ro g ram m in g , gam e theory m odels and
stochastic program m ing (Hazell and Norton 1986).
L P m o d els ad d ress a sin g le, lin e a r o b jectiv e
function that is optim ized subject to a set of rigid linear
constraints (Ignizio 1985). Assum ptions im plicit in the
productive processes, resources and activities in the
lin ear p ro g ram m in g m odel include: optim ization,
fix e d n e ss, fin ite n e ss, d eterm in ism , hom ogeneity,
ad d itiv ity and pro p o rtio n ality (H azell and N orton
1986).
T he general form ation of a linear program is as
follows:
M axim ize
+ P2x2 + ...... + Pnxn

+ a nin x n = b

x., x,,..., x  = 0

Linear Programming

P.x,

a m ,x, + a m2 2
,x .+
il

... 1)

subject to
a iix ] + a 2x2 +

+ a ]nxn  = b ,

...2)

a2x , + a 22x2 +

+ a2nxn = b2

...3)

•4)

...5)

E quation (1) is the objective function , here, a
m axim ization problem . The X ’s are the unknowns or
d ec isio n v a ria b le s w h ile th e P ’s are th e re la tiv e
co n trib u tio n o f each v ariab le to the v alu e o f the
objective function. The a inn ’s represent the am ount of
J
-r
resource b needed by activity or sector, X. The b ’s are
the upper or low er lim it of a resource use and in an LP
tableau are usually referred to as the right-hand side
(RHS) limits. Equations (2) to (4) are the constraints;
Equation (5) is the nonnegativity clause. The above
form ulation is also called the prim al problem .
The dual, which is the converse o f the prim al, is
form ulated as follows:
M inim ize
b.w,] + b 2.w 2.+ .... + b m w m
I
subject to
a 111 + a .,w . 2
nw,
1 +
2
a.,w .I + a,,w . 2+
12
22

+ a m m rp,
,w = I
I
+ a m2 m =r p,
_w
2

a,In w.I + a,2nw , 2+

+ a innw in= rp
n

w., w,,...,’ w in = 0.
I’
2’

Note that the dual formulation is actually equivalent
to the prim al, i.e., the m axim ization problem (prim al)
and the inverse of the m inim um (dual) are one and the
same. The solution to the prim al problem provides the
optim izing values of the variables and the resulting
value o f the objective function.
T h e e x is te n c e o f th e d u a l s o lu tio n in any
c o n v e n tio n a l L P fo rm u latio n is one o f th e m ore
im portant reasons for its popularity. T he dual can be
interpreted as shadow price or opportunity cost o f a
particular resource. As such, it is also a m easure of the
m arginal increase in the objective function given an

4

increase in the availability o f the resource. Sensitivity
analysis permits further analysis by varying coefficients
in both the objective and input-output m atrices, righthand side limits, and the inclusion of a new goal or
constraint. This was done for the San M iguel Bay study,
i.e., level o f fishery net revenues as affected by changes
in total allow able catch rates and m inim um wage rates
(Cruz-Trinidad and Garces, this vol.).

Applications
Linear program m ing was first applied to fisheries
by Rothschild and B alsiger (1971) to allocate the catch
of sockeye salm on during a run in B ristol Bay. Siegel
et al. (1979) used LP to m axim ize catches o f the New
England otter trawl fishery subject to total allowable
catch, processing and harvesting capacity, based on an
earlier work by M ueller (1976). Agiiero (1987) used
L P to m odel th e P eruvian fishery and utilized six
sequential activity blocks beginning from harvesting
to processing, storage, transport, m arketing and sales
to arrive at, am ong o ther things, o ptim al rates o f
resource exploitation, plant rated capacities and prices.
Subsequent developm ents perm it the incorporation
o f m ultiple-planning periods, risk and uncertainty into
the model. M cC arl and Spreen (1980) have suggested
that price need not be an exogenous variable in LP
fo rm u latio n s w h ile S h ep h erd and G a rro d (1980)
developed a method o f cautious nonlinear optim ization
w hich re so lv e s the ten d en c y o f L P re su lts to be
“extrem e, sparse and ruthless” and which “considers
the in itial state o f th e system w hen se e k in g the
optim um ” . These im provem ents are incorporated via
a co m posite o b jectiv e function w hich co n sists o f
penalties for (i) failing to conform to one or m ore
constraints, i.e., quota allocations and (ii) a penalty for
departing from the status quo, i.e. historical average
catch rates, and (iii) one or m ore objectives to be
minimized. H uppert and Squires (1986) applied this
technique to the Pacific coast groundfish trawl fishery
and estim ated maxim um econom ic surplus and optimal
fleet configuration.
Further developm ent in the area o f mathematical
programming has resulted in dynamic optimization as
used by Dow (1993) in the regulation o f bowhead whales
and Kennedy and Watkins (1986) in the southern bluefin
tuna fishery. Wallace and Brekke (1986) used stochastic
optimization in the Norwegian purse seiner and summer
capelin fishery in the Barents Sea.

T he a p p lic a tio n s o f p ro g ra m m in g m o d els to
econom ic-environm ental system s are diverse, ranging
fro m fo rest m an ag em en t, en v iro n m e n ta l quality
m o d e ls, p e tro le u m re fin in g a n d e le c tric p o w e r
generation, to com plex regional and national m odels
for optim al utilization o f w ater resources (H ufschm idt
et al. 1983).
D espite the fast-paced dev elo p m en t in m ath e­
m atical program m ing techniques, L P applications in
developing countries in both fisheries and coastal
environm ents are few. Two have been identified in the
lite r a tu r e , th e w o rk s o f P a d illa ( 1 9 9 1 ) , u s in g
m ultiobjective program m ing to d eterm in e optim al
effort in the sm all pelagics fishery in the Guim aras
S trait, W estern V isayas, P h ilip p in e s, and A hm ed
(1991), using price endogenous linear program m ing
to estim ate net social benefits o f different types of
fisheries, i.e., hilsa, praw n, catfish and carp in the
floodplains o f B angladesh. T he latter also involved
segmentation o f both objective function and constraints
into harvesting, postharvest and m arketing blocks. The
apparent underutilization o f m athem atical program ­
m ing and its enorm ous potential for use in fisheries
and coastal system s in developing econom ies, show
that the applications in this volum e, and the use of
OPUS, the L P softw are developed for this purpose,
can be a significant contribution to the literature.

Potentially Applicable Techniques
H u f s c h m id t e t a l. ( 1 9 8 3 ) s u g g e s te d tw o
analytical fram ew orks fo r m u ltiactiv ity econom ice n v iro n m e n ta l m o d els: lin e a r p ro g ra m m in g and
input-output (I-O ) m odels. T he latter w as developed
by L eo n tief (1936) [thus, the alternate term , L eo n tief
m a trix ] a n d e m p h a s iz e s th e in te r r e la tio n s h ip s
b etw e en p ro d u c tio n a c tiv itie s . E a c h p ro d u c tiv e
activity assum es dual roles: first, as a su p p lier o f
o u tp u t to o th e r a c tiv itie s a n d fin a l b u y e rs and
second, as a b u y er o f inputs including land, labor,
ca p ita l and the o u tp u ts o f o th er ac tiv itie s. A s in
standard econom ic system s, the final dem an d for
goods and services determ in es the 1 -0 coefficien ts
o f e c o n o m ic -en v iro n m en tal m odels. 1 -0 an aly sis
perm its the d ecisio n m ak er to sim ulate ch an g es in
e c o n o m ic a n d e n v iro n m e n ta l q u a lity v a ria b le s
related to d ifferent econom ic developm ent scenarios
a n d /o r c h a n g e s in fin a l d e m a n d fo r g o o d s and
services (H ufschm idt e t al. 1983).

The following analytical techniques are extracted
The IFC Method and Its Implementation
from a list provided by H ym an and Stiftel (1988) for
Environmental Impact Assessment (EIA), which we have
The integrated functional coefficients m ethod was
identified to be relevant to coastal resources as well. designed to determ ine the social and econom ic value
Sorenson (1971) devised a network or stepped matrix for o f coastal resources within an integrated concept o f
which the prim ary focus is the environmental cost of the coastal ecosystem and its functions. T he elem ents
coastal land uses. Fifty-five coastal zone uses are entered
are the sam e as that o f standard L P form ulation except
in the matrix rows. The columns represent i) causal factors, that the definitions are largely expansive. The objective
i.e., specific activities associated with particular land uses; function (N et Social Benefit Function) is structured in
ii) initial conditions; iii) secondary impacts; iv) ultimate term s o f the Total E conom ic Value concept (Randall
environmental effects and v) management interventions.
1987) allow ing externalities and nonm arket goods,
The Sorenson network has been applied to commercial,
services and functions to be considered. U n it cost
resid e n tia l and tran sp o rtatio n d ev e lo p m e n t in the
coefficients and prices are exogenous to the m odel and
C alifornian coastal zone.
d e te rm in e d u s in g s ta tis tic a l te c h n iq u e s a n d /o r
Hill (1968) developed the multiple objective analysis econom etrics, w hichever is applicable. T he resulting
or goals achievement matrix. This procedure involves the m easure o f net revenue is a m easure o f N et Social
definition o f im portant objectives and the subsequent B enefit valued at the best alternative use given the
assignment o f weights. The crucial step is the anticipation constraints im posed on the system .
o f impacts o f each objective. Hill and Alterman (1974)
E a c h a c tiv ity is c o n s tr a in e d by re s o u rc e s
used multiple objective analysis to assess alternative sites availability, technological efficiency, cost structures,
for pow er plants. A related procedure is decision analysis input and output m arket conditions and institutional
(Keeney and Raffia 1976) although this technique places fa c to rs . T h e m e th o d o lo g y is d e riv e d fro m th e
greater em phasis on systems modeling and evaluation
integration of several sources o f value under several
u n d e r ris k an d u n c e rta in ty . T h e firs t step is the
restraining conditions.
identification o f objectives and assignment of “attributes”
The elem ents o f an IFC linear program as applied
per objective. The next steps involve prediction o f future in a coastal resource system are as follows:
v alu es fo r each a lte rn a tiv e p lan and selectio n o f
p re fe re n c e s a m o n g th e v a rio u s a lte rn a tiv e s.
(i) O b je c tiv e F u n c tio n
Decisionmakers base their final decision on the alternative
which maximizes utility. Decision analysis was used to
M axim ize n
predict the impact o f a nuclear power plant on salmonid
stocks (Keeney and Robilliard 1977).
The United States Fish and W ildlife Service (1980)
11 — ^ -(P ijk lm n o p  ^ i jk l m n o p ) ~ ^ -(C jjk lm n o p  ^ ijk lm n o p )
dev elo p ed a H abitat E valuation P rocedure (H E P),
which evaluates the effects o f developm ent on a single
where
aspect o f the environm ent — fish and wildlife habitats.
T he H E P enables decisionm akers to select am ong
= net social benefit function
n
different project alternatives and to design m itigation
and com pensation m easures. First, the habitat types in
,.
= good or service corresponding to
the area are mapped out and indicator species identified X ijk lm n o p
on th e b asis o f e c o n o m ic o r so c ia l im p o rta n c e ,
= spatial location o f the reso u rce, i.e.,
1
sensitivity to proposed actions, role in nutrient cycling
country, region, zone, subzone;
and energy flow s, and representativeness in various
ecological niches. T he decision rule is then based on
= econom ic sector, i.e., fisheries, tourism ,
p o ten tial ch an g es in “h a b ita t u n its” (h a b ita t area
forestry, m ining, aquaculture;
m ultiplied by habitat sustainability index).

k

= e c o n o m ic a c tiv ity , i.e , h a rv e s tin g ,
p r o c e s s in g , tra n s p o r tin g , s to ra g e ,
m arketing, consum ption;

1

= re s o u rc e , i.e ., fish , tre e , m an g ro v e,
beach, coral reef;

m

= product, i.e., in the fishery, fishm eal, oil,
frozen fish; from the forestry sector,
b o a rd s , c h ip s, p u lp ; fro m to u rism ,
re c re a tio n a l fa c ilitie s, h o tels, b each
resort;

n

= technology, i.e., capital intensive, labor
intensive;

o

= scale, i.e., large scale, m edium scale,
sm all scale; and

A n a d d itio n a l s ta n d a r d r e s tr ic tio n is th e
n o n n e g a tiv ity c o n s tra in t w h ich p ro v id e s fo r all
X.... n o p ’s to be r
positive or equal to zero.
ijk lm
*
T he m ath e m a tic a l p ro g ra m m in g p ro b le m is
solved by m eans o f the sim plex algorithm (R evised
Sim plex M ethod) using OPUS, a com puter software
package (see Agtiero et al., this vol.). The optim ization
process, i.e., the search for the best (optim al) value of
the control variables (level o f resource use/exploitation)
within the feasible set o f alternatives, determ ines the
econom ic value o f each resource in its best alternative
use. The vector o f shadow prices indicates how the net
social benefits change as one additional u n it o f a
resource is m ade available, reflecting in this way, its
social value.

Use and Implementation o f the IFC Method

M odeling the coastal ecosystem for valuation
purposes under a m athem atical program m ing structure
p
= gear or equipm ent, i.e., in the fishery,
net, boat, hook, harpoon; in the forestry
requires a sound know ledge and understanding o f the
sector, axe, electric chain; and in the
various resources, activities and processes taking place
in the coastal area. It is essential to fully understand
tourism industry, car, bicycle, train.
the various interactions to establish the limits defining
each system and their linkages w ith each other.
P..,,lm n o p a n d C ijk lm n o p =
,,
price and cost estim ates
ijk
r
o f each variable.
The use o f the IFC m ethod involves tw o phases:
(i) co n cep tu al fo rm u latio n and (ii) ap p lica tio n o f
Further specifications to distinguish features of m athem atical program m ing. C onceptual form ulation
is the m ore critical o f the tasks and involves steps 1 to
the resource, products or m arkets can be m ade, e.g.,
6 in th e list p ro v id e d below . T h is p h a se en ta ils
distinguishing frozen fish in blocks (round or fillets)
or boxes o f d iffe ren t w eights or grade. Sim ilarly,
understanding the hum an and natural dynam ics o f the
coastal zone, determ ining the sources o f econom ic
m arkets can be distinguished as local, dom estic and
value and its com ponents, and assigning appropriate
fo reig n , etc. B ecau se o f the nu m ero u s o p tio n s to
m easures o f value. These elem ents, w hen translated
disaggregate any one variable, each application paper
into algebraic term s, becom e the elem ents o f the LP
in this volum e provides a detailed explanation o f the
tableau. The program m ing application, especially with
LP elem ents.
the use o f available softw are, i.e., O PU S, becom es
purely m echanical.
T he follow ing is a list o f steps n ecessary to
(ii) Functional Restrictions
accom plish this task.
1. Characterize the coastal system. This is done
by preparing a “profile” or description o f the
AX = b
j
j
coastal area. The profile describes the macro­
environm ent, both natural and hum an, in
A X indicates technical coefficients associated to
which the relevant economic sectors operate.
t h e X ijk lm np o
,,
S o m e e x a m p le s o f p r o f ile s a re th o s e
b.
in d ic a te s re s o u rc e en d o w m e n ts, y ie ld at
•p re p a re d by th e A S E A N /U S C o a s ta l
d ifferen t lev els o f use, dem and fo r d ifferent price
R esources M anagem ent Project in B runei
(C hua et al. 1987), South Johore, M alaysia
ranges, installed capacities, balance indicators, etc.

7

(A SEA N /U S C R M P 1991), Lingayen Gulf,
Philippines (M cM anus and Chua 1990), Ban
Don Bay and Phangnga Bay, Thailand (Paw
e t al. 1 9 8 8 ), S e g a r a A n a k a n -C ila c a p ,
Indonesia (W hite et al. 1989).
2. D eterm ine relevant sectors and activities.
E conom ic activities should be based on the
fo llo w in g factors: o u tp u t (production in
ph y sical and m onetary term s); yield (net
n a tu ra l g ro w th p e r u n it o f in p u t); e m ­
ploym ent (per category o f skills required);
in c o m e (p e r lo c a tio n , c a te g o ry o f e m ­
ploym ent; local/foreign); spatial location,
and im pact on other sectors.
3. Identify variables that either contribute to or
m inim ize econom ic value and determ ine
th e r e a f te r , th e a c tiv itie s o r e le m e n ts
influencing such. For example, if the relevant
sectors are aquaculture and forestry, the
variables that add to econom ic value may
include shrim ps and logs, respectively. The
export o f shrim p would require the following
activities: clearing o f m angroves, stocking
o f p o nds, h arv estin g , p ro c essin g , tra n s­
porting, and m arketing, each o f w hich is
characterized by different price vectors as
well as constraints.
4. C ollect data required, including m arket and
n o n m a rk e t p r ic e s , p ro d u c tio n le v e ls ,
technological capacities and m agnitude of
externalities.
5. Establish functional relationships am ong the
com ponents, determ ining production, yield
and dem and functions.
6. C onstruct the m athem atical program m ing
tab leau structure including the objective
function, input-output matrix, and restriction
vector (right-hand side).
7. F eed the tableau and conduct prelim inary
c o n s is te n c y te s ts , i.e ., d e g e n e ra c y ,
unboundness, etc.
8. R u n O P U S a n d d e te r m in e n e c e s s a ry
im provem ents in data quality.
9. A nalyze and validate results. Verify that
results obtained in actual application are
consistent with theory and the control factors
pre-established for this purpose
10. Interpret final results and conduct sensitivity
analysis. The final results provide estim ates

o f econom ic (prim al) as well as social (dual­
shadow vector) values. Sensitivity analysis
m easures the effect o f exogenous changes
in prices and resources availability on the
net social benefit (Value o f the O bjective
Function) and those o f the variables.

Discussion
There are no hard and fast rules in the use o f IFC
m ethods especially w hen applied to diverse environ­
m ents such as coastal zones. The list show n above,
th o u g h u n c o m fo rta b ly lo o se, p ro v id e s th e b asic
e lem e n ts fo r th e an a ly sis and a p p lic a tio n o f the
technique. This is borne by the four application papers
in this volum e w hich may have varied applications but
which, nevertheless, m anifest all these elem ents.
A critica l, though ex o g en o u s, asp e ct o f this
exercise is the use o f appropriate price coefficients,
especially when im perfect m arket conditions exist or
w hen nonm arket transactions occur. The w hole area
o f valuation and applicable techniques are discussed
in Agiiero and Flores (this vol.).
T his volum e does no t attem p t to b reak new
ground in m ethodological developm ent; rather, the
em phasis is on using tested techniques on broader
applications. Thus, the developm ent o f the conceptual
issues is o f greater w eight than the application o f the
technique itself. Complementarily, we invoke H olling’s
(1978) caveat on the use o f m athem atical program m ing
techniques: while we should not be slaves o f the model,
it offers a sensible start for analytical and predictive
purposes.

References
Agiiero, M. 1987. A bioeconom ic model o f the Peruvian pelagic fishery,
p. 307-324. In D. Pauly and I. T sukayam a (eds.) T he Peruvian
anchoveta and its upw elling ecosystem : three decades o f change.
ICLARM Stud. Rev. 15, 351 p.
Ahm ed, M. 1991. A m odel to determ ine benefits obtainable from the
m anagem ent o f riverine fisheries o f Bangladesh. ICLA RM Tech.
Rep. 28, 133 p.
ASEA N /U S CRMP. 1991. The coastal environm ental profile o f South
Johore, M alaysia. ICLARM Tech. Rep. 24, 65 p.
Chua, T.E., L.M. Chou and M .S.M Sadorra, Editors. 1987. The coastal
environm ental profile o f Brunei D arussalam : resource assessm ent
and m anagem ent issues. ICLARM Tech. Rep. 18, 193 p.
Dixon, J.A. 1989. Coastal resources: assessing alternatives, p. 153-162.
In T.-E. C hua and D. Pauly (eds.) C oastal area m anagem ent in
Southeast Asia: policies, m anagem ent strategies and case studies.
ICLARM Conf. Proc. 19, 254 p.

8
Dow, J.P., Jr. 1993. D ynam ic regulation o f fisheries: the case o f the
bow head w hale. Mar. Res. Econ. 8:145-154.
Hazell, B.R. and R.D . N orton. 1986. M athem atical program m ing for
econom ic analysis in agriculture. M acm illan, New York.
H ill, M. 1968. A goal achievem ent m atrix for evaluating alternative
plans.” J. Am. Inst. Planners 34:19-28.
Hill, M. and R. A lterm an. 1974. Pow er plant site evaluation: the case o f
the Sharon plant in Israel.” J. Env. Econ. M anage. 2:179-196.
H o llin g , C „ E ditor. 1978. A daptive en v iro n m en tal a ssessm en t and
m anagem ent. W iley-Interscience, N ew York.
H ufsch m id t, M .M ., D .E . Jam es, A .D . M eister, B.T. B ow er and J.A .
D ixon. 1983. E nvironm ent, natural system s, an d developm ent:
an eco n o m ic valuation guide. John H opkins P ress L td., L ondon.
H u ppert D .D . and D. S quires. 1986. P otential eco n o m ic b en efits o f
lim ite d a c c e s s in th e P a c if ic c o a s t tra w l f is h e r y : a lin e a r
p ro g ram m in g ap p ro ach . A d m in istrativ e R ep o rt L J-8 6 -0 1 . US
S o u th w est F isheries C enter, N O A A , C a lifo rn ia . 59 p.
H ym an, E .L. and B. S tifte l. 1988. C o m b in in g fa c ts an d v alu es in
e n v iro n m e n ta l im p a c t a s se s sm e n t: th e o rie s an d te c h n iq u e s .
W estview Press, London.
ig n izio , J.P. 1985. In tro d u c tio n to lin e a r g o al p ro g ram m in g . S age
Publications, California.
K eeney, R. and H. R affia. 1976. D ecision w ith m ultiple objectives:
preferences and value tradeoffs. Wiley, N ew York.
K een e y , R . an d G . R o b illia r d . 1977. A s s e s s in g a n d e v a lu a tin g
environm ental im pacts at proposed nuclear pow er plant sites. J.
Env. Econ. M anage. 4:153-166.
Kennedy, J. O. S. and J. W. Watkins. 1986. Tim e-dependent quotas for the
southern bluefm tuna fishery. Mar. Res. Econ. 2 (4):293-313.
Laszlo, E. 1972. Introduction to system s philosophy - tow ards a new
paradigm o f contem porary thought. G ordon and B reach Science
Publishers, New York.
Leontief, W. W. 1936. Quantitative input and output relations in the economic
system o f the United States. Rev. Econ. Stat. 28(3): 105-125.
M attessich, R„ 1984. The system s approach: its variety o f aspects. General
System s 18:3-12.
M cCarl, B.A. and T.H. Spreen. 1980. Price endogenous m athem atical
p ro g ram m in g as a to o l fo r se cto r an aly sis. A m . J. Ag. E con.
62( 1):8 7 -102.

M c M a n u s , L .T . a n d T .-E . C h u a , E d ito r s . 1 9 9 0 . T h e c o a s ta l
en v iro n m en tal p ro file o f L ingayen G ulf, P h ilip p in es. ICLA RM
Tech. R ep. 22, 69 p.
M u e lle r, J.J . 1976. A lin e a r p ro g ra m m in g d is c u s s io n m o d el fo r
m axim izing th e net rev en u es from a m u ltisp ecies fishery. US
N ational M arine F ish eries S ervice. 13 p.
P a d illa, J.E . 1991. M a n ag in g tro p ic a l m u ltisp e c ie s fish e rie s w ith
m u ltip le o b je c tiv e s . S im o n F ra se r U n iv ersity , C a n a d a . PhD
d issertatio n .
Paw, J.N ., S. B unpapong, A.T. W hite and M .S .M . S ad o rra, E ditors.
1988. T h e co astal e n v iro n m en tal p ro file o f B an D on B ay and
P h an g n g a Bay, T h ailan d . IC L A R M T ech. R ep. 20, 78 p.
R andall, A. 1987. Total eco n o m ic v alu e as a b asis fo r policy. Trans.
A m . F ish. Soc. 116:325.
R o th s c h ild , B .J. an d J.W . B a lsig er. 1971. A lin e a r p ro g ra m m in g
solution to salm on m anagem ent. U .S. Fish. B ull. 69:117-139.
S cura, L .F., T.-E. C hua, M .D . P ido and J.N . Paw. 1992. L essons fo r
in teg rated co astal zone m anagem ent: th e A S E A N ex p erien ce, p.
1-70. in T.-E. C h u a and L.F. S cu ra (eds.) In teg rativ e fram ew ork
and m ethods fo r co astal are a m anagem ent. IC L A R M C onf. Proc.
37, 169 p.
S heperd, J.G . and D .J. G arro d . 1980. M o d e lin g th e re sp o n se o f a
fishing fleet to changing circum stances, using cautious n o n-linear
optim ization. J. C ons. C IE M 39:231-238.
S ie g e l, R .A ., J .J . M u e lle r an d B .J . R o th s c h ild . 1 9 7 9 . A lin e a r
p ro g ram m in g ap p ro ach to d e te rm in in g h a rv e stin g cap ac ity : a
m ultiple species fishery. U .S. F ish. B ull. 77:425-433.
S o re n so n , J. 1971. A fram ew o rk fo r id e n tific a tio n an d c o n tro l o f
re so u rc e d e g ra d a tio n an d c o n flic t in th e m u ltip le u se o f th e
co astal zone. U n iv ersity o f C alifo rn ia, D epartm ent o f L andscape
A rch itectu re, B erkeley.
U nited S tates F ish an d W ild life S erv ice. 1980. H a b ita t ev alu atio n
p r o c e d u r e s . R e v is e d e d . D o c u m e n ts E S M 101 to 104.
G overnm ent P rin tin g O ffice, W ashington, DC.
W allace, S.W. and K. B rekke. 1986. O p tim al fleet size w hen national
q u o tas can be trad ed . M ar. Res. E con. 2:315-330.
W hite, A.T., P. M artosubroto and M .S .M . S adorra, E ditors. 1989. T he
co astal en v iro n m en tal p ro file o f S eg ara A n ak an -C ilacap , S outh
Java, Indonesia. IC L A R M Tech. R ep. 25, 82 p.

Valuation Concepts and Techniques
with Applications to Coastal Resources*

effectiveness o f resource exploitation activities. As a
con seq u en ce, develo p in g n atio n s are increasin g ly
view ing the exploitation o f their coastal renew able
resources as a source o f foreign exchange, em ploym ent
and food supply. In fact, m ost governm ent policies of
developing countries, in one way or another, prom ote
coastal exploitation to solve pressing social needs.
T h e lim its to w h ich th e se re s o u rc e s can be
exploited on sustained basis, however, are not yet well
known or understood, but decreasing yields in many
renew able resources such as fish stocks, indicate that
very probably, they are already being overexploited
(G arcia and Newton 1995).
One of the causes of the abovem entioned problem
is the absence o f well developed m arkets for many
goods, services and functions perform ed by coastal
resources like m angroves and coral reefs. The failure
o f existing methods to properly account for them results
in undervaluation of total benefits and consequently, a
b ias to w a rd s o v e re x p lo ita tio n o r c o n v e rs io n o f
resources to alternative options. E xam ples o f this
p ro c e ss are th e in c re a s in g te n d e n c y to c o n v e rt
m angrove areas into shrim p ponds, the increasing
d e g r a d a tio n o f th e e n v iro n m e n t ( p o llu tio n ,
sedim entation, etc.) and discharge o f urban waste into
the ocean w ithout prior treatm ent. The overall result is
rent dissipation and resource degradation (Fig. 1).
M oreover, coastal resources exploitation does not
take place in isolation. The allocation o f inputs to a
specific process prevents its use in others, changing
their relative availability to alternative activities. Also,
exploitation activities generate several residuals and
spill-over effects affecting the perform ance o f others.
These effects, better know n as “ex tern alitie s” , are
generally not accounted for by their generating source,
but borne by society w ithout due com pensation. A
divergence betw een social and private costs is thus
created with m isleading signals for an efficient resource
allocation process. These signals, namely, unrealistic
high profit m argins and larger expected long-term
yields, by default do not account for resource users’
costs (value o f fish in the water, clean air, etc.) nor for
negative externalities im posed on society (like water
pollution from fishm eal plants, siltation/sedim entation
from logging, and solid wastes from tourism ). W hen
the outputs o f these resource exploitation activities are
exported to m arkets with very high price elasticities,
e.g., fishm eal, considerable rents are transferred to the
importing country, creating a paradoxical flow o f value

ICLARM -ECLAC
Collaborative Project on the Socioeconomic Valuation of
Coastal Resources in Southwest Latin America, Casilla 179D, Santiago, Chile
M a x A g u e r o 1 a n d X i m e n a F l o r e s 1,

AGUERO, M. and X. FLORES. 1996. Valuation concepts and techniques
with applications to coastal resources, p. 9-16. In A. Cruz-Trinidad
(ed.) Valuation of tropical coastal resources: theory and application
of linear program m ing. ICLARM Stud. Rev, 25, 108 p.

Abstract
Overexploitation of natural resources is linked to the use of valuation
techniques that do not consider nonm arket environm ental goods and
services. The Total Economic Value (TEV) concept is discussed and its
relevance to natural resources valuation is highlighted. Lastly, techniques
for resources valuation are presented, along with an exam ple referring to
the mangroves around the G ulf of Guayaquil, Ecuador.

Introduction
Coastal ecosystem s and their resources throughout
th e d ev elo p in g w orld are being increasingly m is­
m anaged and exploited beyond the lim its o f their
sustainability. Furtherm ore, destructive techniques for
resource exploitation are proliferating in many poor
coastal areas w here both resources and the functional
integrity of the ecosystem are being seriously threatened
by illegal or uncontrolled hum an activities (C hua and
F allon-Scura 1992).
In recent times, research efforts and policy analysis
em phasize the need to properly m anage and preserve
natu ral reso u rces and the environm ent. A bundant
lite ra tu re fro m all d iscip lin e s has been pro d u ced
describing, quantifying and denouncing undesirable
hum an interventions in the ecosystem , namely, those
related to pollution, w aste disposal and other global
environm ental dam age (Panayotou 1993; Pearce and
M oran 1994).
M oreover, population growth and higher incomes,
especially in developed nations, have increased trade
opportunities for developing coastal nations with rich
r e n e w a b le re s o u rc e s . In c re a se d te c h n o lo g ic a l
efficiency, on the other hand, has im proved the cost
* ICLARM Contribution No. 1218.
P resent address: International C enter for Sustainable Ecological
Developm ent (1CSED), Casilla 27004, Santiago, Chile.
9

10

Fig. 1. Nonaccountability o f externalities and other nonuse values
results in exploitation beyond econom ically optimum levels (M E Y )
in A : the divergence between M E Y and O A E , or the downward
shift o f supply curve, SI to S2, results in rent dissipation equivalent
to IJKL in B.

(a sort o f subsidy) from poor to rich countries. The
increasing rate of resource exploitation now taking
place in many developing countries is a clear evidence
o f the above problem . It also shows the urgent need to
in co rp o rate new v alu atio n techniques to im prove
resource m anagem ent.

Valuation Concepts and Techniques
Total Econom ic Value

Interest in natural resources valuation stems from
the realization that the economic sector is part of a wider
a re n a th a t c o n s is ts o f m u ltip le life -s u p p o rtin g

ecosystems (Aylward and Barbier 1992). Valuation then
becom es an interface betw een ecology and econom ics
because of the use of certain com m onalities from two
otherw ise divergent realms. First is the equivalence of
w hat econom ists w ould refer to as “g o ods” to the
structural com ponent o f an ecosystem , i.e., wood, fish,
and w ater, and w hat econom ists w ould refer to as
“services” with environmental functions such as natural
protection from storm s and breeding grounds for fish.
Actual valuation is the next step and can be defined
as a quantitative assessm ent o f the value o f these
“goods” and “services” . M oney is usually used as a
num eraire for this purpose, since it allows aggregation
and com parison o f heterogenous elem ents through a
com m on unit. It is then possible to com pare values of
fishery resources with forestry or industrial output for
example. Furtherm ore, it allows consistency in ranking
priorities for investm ent decisions and policy design.
S everal criteria are used for this purpose, but
relative scarcity and human appreciation of the resource
are m ost relevant. F or valuation purposes, coastal
resources are viewed in their capacity to generate a
flow o f goods, services and ecological functions that
can satisfy hum an needs o f various kinds, w hether
directly or indirectly. In this capacity, they are valued
by individuals and society according to the net benefits
they provide. In other words, natural resources are
considered in econom ic term s only in their capacity to
satisfy human needs and therefore, valued as far as they
enter in human preference scales. This approach is also
shared in cost-benefit analysis, in which scarcity is also
considered as a determ ining factor.
Although the concept o f value, indicating worth,
has been analyzed and form alized in various ways and
given several interpretations over time, it is becom ing
w ell a c c e p te d now w ith in th e c o n c e p t o f T otal
E c o n o m ic V alue (T E V ). T h is c o n c e p t w as firs t
articulated by W eisbrod (1964) and K rutilla (1967)
stating that the total value o f a resource includes its
use and nonuse values.
The total value o f a private good is usually defined
as the m axim um am ount o f money an individual is
w illing to pay for it over and above the consum er
surplus. F or a natural resource, how ever, the total
econom ic value is defined as “use value” plus “nonuse
value” . Use value is referred to costs and benefits of a
resource for which a market exists; it can be direct (in
situ) or indirect use. Direct use may be “consum ptive”
(that is, used/enjoyed by som eone, thus, depriving

11

others o f its u s e ) o r n o n c o n s u m p t iv e , m e a n in g that
o thers m a y a ls o e n jo y its b e n e fits.
T h e c o n c e p t o f n o n u se v a lu e h a s r e c e iv e d s p e c ia l
attention in re ce n t y e a rs d u e to the g ro w in g co n ce rn

G r e g o r y ( 1 9 8 7 ) f o u n d it u s e f u l to a s s e s s th e
n o n m o n e tary b e n e fits o f e xtra m ark e ts o f e n v iro n m e n ta l
s e r v i c e s , a lb e it t h e ir i n c l u s i o n in T E V

w as not

c o n sid e re d .

fo r the e n v ir o n m e n t a n d s u s ta in a b le u se o f re so u rce s ,

A lth o u g h these p re se rv a tio n a n d n o n u s e v a lu e s are

as it a p p lie s to the v a lu e in d iv id u a ls p la c e o n re so u rce s,

n ot c le a r ly a ttach ed to a n y p a r tic u la r c o m p o n e n t o f a

r e g a r d le s s o f th e ir p re s e n t /f u t u re o r c o n s u m p t iv e /

g iv e n re so u rce , th e y tend to b e a s s o c ia te d w ith it as a

n o n c o n s u m p tiv e u se . S e v e r a l ca te g o rie s are in c lu d e d ,

w h o le . T h u s , the ro le o f a re s o u rc e ( lik e m a n g ro v e s ) in

n a m e ly , e xisten ce valu e (v a lu e o f a re so u rce fo r ju s t

p re se rv in g b io d iv e r s it y o r the ro le in d e te r m in in g the

k n o w in g it e x is ts or w ill be p re se rv e d ); o ption value

u n iq u e n e s s to cu ltu re an d h e rita g e (the c o n d o r in C h ile ,

(w illin g n e s s to p a y fo r the o p tio n o f u s in g /c o n s u m in g

the b a ld e a g le in the U S A , the P ir in e o s in E u r o p e , etc.)

the re so u rce in the fu tu re ); q u a si-o p tio n (w illin g n e s s

c o n trib u te to the e x is te n c e , b e q u e s t a n d o p tio n v a lu e

to p a y to h a v e the o p tio n o f d e c id in g in the future a b o u t

that in d iv id u a ls attach to p re s e rv a tio n .

its u s e ); a n d b eq u est/h erita g e a n d p reserva tio n value

T h e T E V co n ce p t w a s a p p lie d b y S p u rg e o n ( 1 9 9 2 )

( v a l u e to k n o w f u t u r e g e n e r a t io n s w i l l h a v e th e

on c o ra l reefs. U s e v a lu e s w ere c la s s if ie d as e x tra c tiv e

o p p o rtu n ity to u s e the re so u rce ).

or n o n e x tra ctive . A m o n g the e x tra c tiv e v a lu e s are those

H y m a n a n d S t i f t e l ( 1 9 8 8 ) p o in t e d o u t f i v e

o f f is h in g , p h a r m a c e u tic a l, a n d c o n s tru c tio n a n d the

a lte rn a tiv e u se s o f o p tio n v a lu e : risk a v e rsio n ; q u a si­

n o n e x tra c tiv e are to u ris m , e d u c a tio n a n d s o c ia l v a lu e .

o p tio n dem and, existen ce value, vica rio u s use value,
a n d b e q u e s t v a lu e w h ic h a lto g e th e r p o s s e s s so m e

A m o n g the te ch n iq u e s liste d that u s e m a rk e t o r p se u d o ­

in te rc h a n g e a b le featu res.

p r o d u c t iv it y a n d m e a s u r e s o f c o n s u m e r s u r p lu s .

S t ill a n o th e r ca te g o ry o f re so u rce u s e , the indirect

m a rk e t p r ic e s are c o s t -b e n e f it a n a ly s is , c h a n g e in
S im u la t e d m a rk e ts are u s e d in c o n tin g e n t v a lu a tio n

use fo r w h ic h the v a lu a tio n d e p en d s on the “p ro ce sse s”

m e th o d s ( C V M ) a n d tra v e l c o s t ( T C ) t e c h n iq u e to

that u ltim a te ly p ro v id e e c o n o m ic v a lu e , w a s p ro p o se d

e v a lu a te v a lu e o f to u ris m sp o ts, fo r e x a m p le . A s fo r

b y A y lw a r d a n d B a r b ie r ( 1 9 9 2 ) . S o m e in d ire c t u se s o f

the in d ire c t u s e s o f c o ra l re e fs, lik e b io lo g ic a l su p p o rt,

w e tla n d s in c lu d e g ro u n d w a te r re ch arg e o r d isc h a rg e ,

the a u th o r su g g e ste d the u s e o f c h a n g e in p r o d u c tiv ity

flo o d a n d flo w c o n tro l, s h o re lin e or b a n k s t a b iliz a tio n ,

in “w ith or w ith o u t the r e e f ’ situ a tio n s a n d a perce n tag e

s e d im e n t r e te n tio n a n d n u t rie n t re te n tio n ( B a r b ie r

d e p en d en ce te ch n iq u e fo r w h ic h the b io lo g ic a l supp ort

19 8 9 ). T h e s e e n v iro n m e n ta l fu n ctio n s m u st b e a n a ly z e d

v a lu e is the v a lu e o f the su p p o rte d a c t iv it y m u ltip lie d

w ith in the b ro ad e r fra m e w o rk o f b io lo g ic a l d iv e r s it y

b y an e stim ate d p e rce n ta g e d e p e n d e n c e o f th at a c t iv it y

as th is im p lie s a co rre s p o n d in g a n a ly s is o f the lin k a g e s

o n the r e e f ’s p re s e n c e . F o r n o n u s e v a lu e s , s u c h as

in the e c o lo g ic a l c h a in a n d h o w ch a n g e s w ith in the

e x is te n c e an d o p tio n v a lu e , an e x te n s iv e C V M s u rv e y

sy s te m affe ct the e n v iro n m e n ta l fu n c tio n s su p p o rte d

is su g g e ste d as w as im p le m e n te d b y H u n d lo e ( 1 9 8 9 )

b y it.

in the e stim a tio n o f the v ic a r io u s v a lu e (o p tio n p lu s

M e a s u r e s o f in d ire c t uses are b a se d on w h e th e r
su ch f u n c tio n s su p p o rt e c o n o m ic p ro d u ctio n o r p ro tect

e x is t e n c e v a lu e ) o f the G r e a t B a r r ie r R e e f w h ic h
a m o u n te d to A U S $ 4 5 m illio n /y e a r .

the c o n d u c t o f e c o n o m ic a c tiv ity . A m e a su re o f the

T h e a p p lic a tio n o f T E V in th is v o lu m e h a s been

c o n s u m e r ’s w illin g n e s s to p a y ( W T P ) o r w illin g n e s s

s lig h t ly m o d ifie d in the net s o c ia l b e n e fit fu n c tio n o f

to a c c e p t ( W T A ) m a y ta k e the fo rm o f c h a n g e s in

th e “ in te g r a te d f u n c t io n a l c o e f f ic ie n t m e t h o d ” to

p r o d u c t iv it y , a lt e r n a t iv e /s u b s t it u t e c o s t s , o r a c t u a l

c a p t u r e th e n e t v a lu e ( p o s i t i v e o r n e g a t iv e ) o f

e x p e n d itu re s. V a lu a t io n te c h n iq u e s u s e d to e stim a te

e x te rn a litie s ( F ig . 2 ).

W T A in c lu d e p re v e n tiv e e x p e n d itu re , d a m a g e co sts

A y lw a r d a n d B a r b ie r ( 1 9 9 2 ) p o in t e d o u t so m e

a v o id e d , a lte rn a tiv e or su b stitu te co st and re lo c a tio n

c a v e a ts in the u se o f the T E V e s p e c ia lly w ith re sp e ct

co sts. In b oth c a s e s , an im m e n s e a m o u n t o f d a ta is

to d o u b le a cco u n tin g o f g o od s a n d s e r v ic e s . T h i s o c cu rs

re q u ire d e s p e c ia lly in d e v e lo p in g -c o u n try s itu a tio n s.

w h en the d ire ct u s e o f the re so u rce is v a lu e d in a d d itio n

M o re o v e r, so m e m e a su re s m a y p ro v e irre le v a n t d u e to

to th e in d ire ct fu n c tio n s that su p p o rt th e se d ir e c t u se s.

the a b s e n c e o f te c h n o lo g y that w o u ld , fo r in sta n ce ,

F o r e x a m p le , m a n g ro v e fo re st litte r that p r o v id e s fo o d

restore the n u trie n t reten tio n c a p a b ilitie s o f m a n g ro v e s.

fo r f is h and sh rim p la rv a e is an e n v ir o n m e n t a l fu n c tio n

12

N BSF

=

I (TR-TC)
X X

saro

XX

* p so - X X
EC

C

+XX

Subject to:

N B SF =

B io m a ss abu nd ance
Infrastructure cap acity
C ap ital a v a ila b ility
L abor a v a ila b ility
E n viron m en tal carryin g c a p a city

TR
TC
X

=
=
=

saro

* FB sr

net benefit
social function
total revenue
total cost
quantity o f goods/
service produced

P
C
EC
FB

=
=
=
=

price
cost o f production
environmental cost
foregone benefits

w h ere
Sectors (s)

Fishery

Forestry

Tourism

A ctivities (a)

Preparation
Stocking
Harvesting
Processing
M arketing

Preparation
Planting
Logging
Processing
M arketing

Preparation
Building
Visiting
T ransporting
M arketing

Produce

Produce

Service

Fresh fish
Processed
Fish meal
Others

Wood
Logs, timber
Charcoal
Cellulose
Others

Parks, beach
and camping visit
Motel, hotel, restaurant
Package use, etc.
Others

Resource use (r)

Output (o)

Environment
—

—

—

—

—


Transportation
(D estruction/
enhancem ent)
Externality

(+ -)
Function

Fig. 2. A typical objective function characterizing a multiresource coastal zone and elaboration o f coefficients.

w h ic h “c a n ” b e v a lu e d . H o w e v e r , i f g o o d s s u c h as

e re n ce s fo r c lo s e ly re late d g o o d s that d iffe r m a r g in a lly

s h r im p s are v a lu e d lik e w is e , so m e d o u b le a c c o u n tin g

in the q u a n tity o r q u a lit y o f th e ir attrib ute.

m a y o c c u r. L ik e w is e , so m e a m b ig u itie s a ris e as to the

C la s s if ic a t io n o f v a lu a tio n te c h n iq u e s as d is c u s s e d

c la s s if ic a t io n o f o p tio n v a lu e w h ic h c a n b e c la s s if ie d

h e r e w i l l b e b a s e d o n th r e e m a r k e t c a t e g o r i e s :

as a n o n u se v a lu e , b e c a u s e it is n ot a c t u a lly u s e d , at

conventional, implicit

present. A g a in , w e in v o k e the in flu e n c e o f n e o c la s s ic a l

a u th o rs

e c o n o m ic s o n n a tu ra l re s o u rc e s v a lu a t io n , i.e ., that

c la s s if ic a t io n . F o r e x a m p le , M u n a s in g h e a n d L u t z

in d iv id u a l sa tis fa c tio n is p a ra m o u n t.

have

or

artificial

d e v e lo p e d

( 1 9 9 3 ) a ls o u s e d a c tu a l

a lt h o u g h o th e r

a d d it io n a l

versus p o te n tial

le v e ls

of

b e h a v io r w h ile

D ix o n et a l. ( 1 9 8 8 ) u s e d th e c a t e g o r ie s : g e n e r a lly
a p p lic a b le , p o t e n tia lly a p p lic a b le , s u r v e y -b a s e d and

Valuation Techniques

n o n w illin g n e s s to p a y -b a s e d m e th o d s.
V a l u a t io n t e c h n iq u e s b a s e d o n c o n v e n t io n a l

M a n y te ch n iq u e s fo r v a lu a tio n o f n o n m a rk e t g o o d s

m a rk e ts are b ase d o n m a rk e t p ric e s . T h e s e te c h n iq u e s

a n d s e r v ic e s are b a se d o n the h e d o n ic p ric e th e o ry o f

are p a r t ic u la r ly u s e fu l w h e n e n v ir o n m e n ta l im p a c ts

c o n s u m e r c h o ic e . G o o d s a re n o t v a lu e d in a n d o f

h a v e d ire c t e ffe cts o n g o o d s a n d s e r v ic e s w h ic h are

t h e m s e lv e s b u t r a th e r a s a c o m p o s it e o f d if f e r e n t

p r ic e d . U n d e r p e r f e c t c o m p e t it io n , m a r k e t p r ic e s

attributes. T h u s , the v a lu a tio n o f e a ch o f these attributes

in d ic a te the re al v a lu e to both c o n s u m e rs a n d s u p p lie rs.

c a n be co m p u te d b a c k w a rd s i f the m a rk e t v a lu e o f the

H o w e v e r , w h en m a rk e t c o n d itio n s are im p e rfe c t (i.e .,

p ro d u ct is k n o w n or i f the m a rk e t v a lu e o f related g o od s

m o n o p o ly , c o llu s io n ) , o r d o not e x is t ( i.e ., e n v ir o n ­

a n d s e r v ic e s is k n o w n . T h e d e riv e d d e m a n d c u r v e c a n

m e n ta l g o o d s a n d s e rv ic e s ), or e x ist b ut f a il (i.e ., p u b lic

thu s be co n stru c te d b y c o m p a r in g e a ch attrib ute w ith

g o o d s a n d e x te rn a litie s ), m a rk e t p ric e s m a y not b e an

c o m p a r is o n s o f a c tu a l e x p e n d itu re s o r s u r v e y p re f­

a p p ro p riate m e a su re . A p ro p o se d a lte rn a tiv e is the use

13
o f s h a d o w p r i c i n g w h ic h c a n b e u s e d in im p a c t

m it ig a t e e n v ir o n m e n t a l im p a c t s , e .g ., w a s te w a te r

a s s e s s m e n t o f e n v ir o n m e n t a l s e r v ic e s ( H y m a n a n d

tre atm e n t f a c ilit ie s . In th is c a s e , the v a lu e o f w ater

S tift e l 1 9 8 8 ) a n d w h e n c o m p e n s a tin g fo r d isto rtio n s

p o llu tio n is ta ke n to be the e q u iv a le n t o f p re v e n tin g it

in the co sts o f c a p ita l, fo re ig n e x c h a n g e , la n d a n d labor.

b y w a y o f te c h n o lo g ic a l co sts. R ep la c e m e n t co st is the

A l l te c h n iq u e s , w h e th e r th e y b e s u rv e y b a se d or

c o s t o f su b stitu tin g p a r tic u la r fe atu re s o f a re so u rce to

o th e rw ise , attem pt to ca p tu re the w illin g n e s s to p a y

a p p ro x im a te its n a tu ra l c h a r a c te r is t ic . F o r e x a m p le ,

( W T P ) [in so m e c a s e s , w illin g n e s s to a c c e p t ( W T A )

F o lk e a n d K a r b e r g e r ( 1 9 9 1 ) e s tim a te d r e p la c e m e n t

 c o m p e n s a t io n  ] c r it e r ia d is c u s s e d a b o v e as th e

c o sts fo r lo s s o f w e tla n d p r o d u c t iv ity w h ile A r a n e d a

u ltim a te m e a su re o f u tility . A s o c ie ta l d e m a n d c u r v e is

et a l. (th is v o l.) u se d the v a lu e o f fre s h w a te r n e ed ed to

th e n c o n s t r u c t e d b y h o r iz o n t a lly s u m m in g u p the

d ilu te p o llu te d b a y w aters to a c c e p ta b le le v e ls .

in d iv id u a l d e m a n d c u rv e s as d is c u s s e d b e lo w . R a n d a ll
( 1 9 8 7 ) su g g e sts th at a c r o s s -c o r r o b o r a tio n te c h n iq u e

IMPLICIT MARKETS

is d e s ir a b le in n o n m a rk e t v a lu a tio n .
A t a x o n o m y o f v a lu a t io n te c h n iq u e s b a s e d on
m a rk e t c a te g o ry is p re se n te d in T a b le 1 .
Table 1. Techniques currently used for natural resources valuation
according to market category.
Implicit

Conventional

Constructed

V a lu a t io n te c h n iq u e s f a llin g u n d e r th is ca te g o ry
are b a se d o n th e p re m is e that so m e m a rk e t g o o d s ca n
b e re late d to p a r tic u la r e n v ir o n m e n ta l attrib utes that
a re n o t p r ic e d . T h u s , p r o p e r ty v a lu e s a n d w a g e
differences, b oth h e d o n ic m e th o d s, are a p p ro x im a tio n s
o f the o v e r a ll e n v ir o n m e n ta l q u a lity . P ro p e rty v a lu e s ,
f o r e x a m p le , a re d e p e n d e n t o n th e e n v ir o n m e n t a l

Change of productivity

Travel cost

Artificial market

Loss o f earnings
Defensive expenditures

Wage differences
Property values

n.a.
n.a.

c a u s e s a d ro p in a sse ssm e n t rate; fo r the sa m e reaso n ,

Replacem ent cost
Shadow project

n.a.
n.a.

Contingent
valuation

to a t tr a c t la b o r . B e l l ( 1 9 8 9 ) u s e d th e la n d v a lu e

q u a lity o f a p a r tic u la r h o u s in g site, e .g ., a p o llu te d site
th is sa m e p o llu te d site w o u ld h a v e to offer h ig h e r w ages
a p p ro a c h in th e v a lu a t io n o f F lo r id a f is h e r ie s . T h e

tra vel co st m e th o d is c o m m o n ly u se d fo r d e te rm in in g
CO N VENTIO NAL MARKETS

the v a lu e o f a re cre a tio n a l site. T r a v e l e x p e n se s, fees
p a id on site, a n d the o p p o rtu n ity c o s t o f tra v e l tim e are

W h e n e n v iro n m e n ta l fu n c tio n s result in m e a su ra b le
c h a n g e s in the p ro d u c tio n or p ro d u c tiv e c a p a c ity o f a
ce rta in g o o d o r s e rv ice , co n v e n tio n a l m arket te ch n iq u e s
c a n b e u s e d , i.e ., the W T P is ta ke n to be e q u a l to the
m a rk e t p ric e . In c a se s w h e re n o n c o m p e titiv e m ark e ts
e x is t, the sh a d o w p ric e o r o p p o rtu n ity co st is ta ke n in
lie u o f cu rre n t p ric e .

ta k e n to represen t “e n tra n ce fe e s ” . T h i s in fo rm a tio n
w i l l a llo w th e r e s e a r c h e r to c o n s t r u c t a d e m a n d
s c h e d u le b a se d on the n u m b e r o f p o te n tia l v a c a tio n is ts
as a fu n c tio n o f tra v e l co st; th u s, c o n s u m e r su rp lu s ca n
b e e stim a te d . T h e tra v e l c o st m e th o d w a s a p p lie d b y
C o s t a n z a et a l. ( 1 9 8 9 ) in the v a lu a tio n o f w e tla n d s an d
b y H u n d lo e ( 1 9 8 9 ) in the G r e a t B a r r ie r R e e f.

C h a n g e in p r o d u c tiv ity e s t im a t e s c h a n g e s in
p ro d u c tio n a r is in g fro m a p a r tic u la r in te rv e n tio n or

CONSTRUCTED MARKETS

n a tu ra l re so u rc e state. T h is a p p ro a c h is b y fa r the m o st
c o m m o n m e th o d u s e d in co a s ta l re so u rce s ( B e ll 1 9 8 9 ;

A ls o c a lle d “h y p o th e tica l v a lu a tio n ” ( H y m a n and

H o d g s o n a n d D ix o n 1 9 9 2 ; R u it e n b e e k 1 9 9 2 ; S a w y e r

S tift e l 1 9 8 8 ), the b a s ic p re m ise is to cre ate a “m a rk e t”

1 9 9 2 ) . A c a s e w a s m a d e b y H o d g s o n an d D ix o n ( 1 9 8 8 )

fo r a s p e c if ic e n v ir o n m e n ta l a ttrib u te b y s im u la tin g

in th e ir e stim a te s o f the e ffe cts o f s e d im e n ta tio n on

d e m a n d a n d s u p p ly c o n d it io n s . S o m e s u r v e y -b a s e d

c o ra l d iv e r s it y a n d u ltim a t e ly on f is h p ro d u c tio n in

te c h n iq u e s su g g e ste d b y H y m a n a n d S tift e l ( 1 9 8 8 )

P a la w a n , P h ilip p in e s . T h e loss o f earn in g s te ch n iq u e

i n c lu d e : d ir e c t q u e s t io n in g , b id d in g g a m e s , u s e

e stim a te s fo re g o n e e a rn in g s a r is in g w h e n a n u m b e r o f

e stim a tio n g a m e s a n d tra d e -o ff a n a ly s is . In the first tw o

p eo p le are affected b y ch a n g e s in e n v iro n m e n ta l q u a lity,

te c h n iq u e s, the re sp o n d e n t is m a d e to a s se ss e ith e r the

e .g ., d e c lin in g c a tc h rates fo r s m a ll-s c a le fis h e rs du e

W T P o r W T A o f a sta te d q u a n t ity o r q u a lit y o f a

to t r a w lin g . D e fe n s iv e e x p e n d itu re s are a p p lie d to

p a r t ic u la r e n v ir o n m e n t a l g o o d . In b id d in g g a m e s ,

14

h o w e v e r, the d e te rm in a tio n o f the v a lu e is m o re o f an

Nonmonetary M easures

ite ra tive p ro c e ss w ith the re se a rch e r p o s in g an in it ia l
b id w ith su b se q u e n t in cre m e n ts. T h e W T P or W T A is

G re g o ry

(19 8 7 )

fo cu se d

on n o n m o n e ta ry

m e a s u re s to v a lu e n o n m a rk e t a ttrib u te s o f e n v ir o n ­

then the m a x im u m (m in im u m ) v a lu e to the user.
T h e v a lid it y o f th e se te ch n iq u e s c a n be e v a lu a te d

m e n ta l re so u rce s b u t d id n ot d is c u s s w h e th e r these

by co m p a riso n w ith results o f elab orate m ark e t research

m e a su re s, w h en m o n e tiz e d , c o u ld be in te g rated into

s u rv e y s fo r c o n s u m e r p ro d u cts. S e v e r a l stu d ie s sh o w

o n e o r a n o th e r o f the c o m p o n e n t s o f T E V . T h e s e

that re sp o n d e n ts d id not a c t u a lly b e h a v e as th e y h ad
c o n s u m e r p ro d u cts m is e r a b ly f a ile d (S p in d le r 1 9 7 5 ;

in c lu d e m e a su re s o f so cia l w ell-being, p sy ch o p h ysica l
m e a s u r e s , a ttitu d e m e a s u r e s a n d m u ltia tt r ib u te
m easures. T h e firs t m e a su re c a n b e s im p ly stated b y

S c h u m a n a n d Jo h n so n 1 9 7 6 ) . It is th u s e x p e cte d that

a s k in g the re sp o n d e n ts i f a s c e n a rio w o u ld a ffe c t th e ir

r e fle c t e d in th e m a r k e t s u r v e y s a n d th a t s e v e r a l

su rv e y s o f e n v iro n m e n ta l go ods, w h ic h are le ss ta n g ib le

h a p p in e s s. S o m e in d ic a to rs c a n be d e v e lo p e d s u c h as

than c o n s u m e r p ro d u cts, w o u ld re su lt in in a c c u r a c y .

e q u ity , p e o p le e m p o w e rm e n t, p a rtic ip a tio n o f w o m en

T h e use o f su ch te c h n iq u e s in L D C c o u n trie s w h ere

a n d the a v a ila b ilit y o f s o c ia l s e r v ic e s .

e d u c a tio n a n d in c o m e s are lo w are lik e w is e c a u tio n e d

In p s y c h o p h y s ic a l e v a lu atio n s, a p articu lar aspect
o f the p h y s ic a l e n v iro n m e n t is used as a stim u lu s to

b y H u f s c h m id t a n d H y m a n ( 1 9 8 2 ) .
C o n tin g e n t v a lu a tio n ( C V ) is so c a lle d b e ca u se

p o t e n t ia l r e s o u r c e u s e r s . T h e s t im u lu s - r e s p o n s e

“ c o n t in g e n t ” c o n d it io n s a re s i m u la t e d a n d th e

relatio n sh ip then ca n be m o d eled statistically, b y m eans

re sp o n d e n ts’ b e h a v io r s u b je c t to th ese c o n d it io n s is

o f ra n k o rd ers, ratin g sc a le s, p aire d c o m p a r is o n s , or

m e a s u r e d . In c o n t in g e n t v a lu a t io n , e s t im a t e s o f

m agnitude estim ates. P s y c h o p h y sic a l m easures h ave been

c o n s u m e r ’s su rp lu s are b ase d on the d ire c t q u e s tio n in g

used to v a lu e so m e la n d sc a p e features ( B u h y o f f and

o f p a rtic ip a n ts. M o s t q u e stio n s are d e s ig n e d to e lic it

W e llm a n 19 8 0 ) but a p p lica tio n s in the fish e ry are rare.

in fo rm a tio n on the m o n e ta ry v a lu e that an in d iv id u a l

M u ltiattrib ute m o d e ls p ro vid e a rig o ro u s m eans o f

p la c e s on p a rtic ip a tio n in a g iv e n a c t iv ity - sp o rtfis h in g

a n a ly zin g preferences and q u a n tifyin g d e cisio n outcom es

for in sta n ce ( G la s s and M u th 19 8 7 ) . B is h o p et a l. ( 1 9 8 7 )

betw een alternatives that v a ry in m u ltip le d im e n sio n s.

a p p lie d C V te c h n iq u e s to e stim a te the p re s e rv a tio n

F o r e x a m p le , K e e n e y ( 1 9 7 7 ) e m p lo y e d m u ltiattrib ute

v a lu e o f strip ed s h in e rs ; N otropis ch ryso cep h a lu s, an

p r o c e d u r e s to s t u d y f is h e r ie s m a n a g e m e n t p o lic y

e n d a n g e re d c y p r in id in L a k e M ic h ig a n . W h it e h e a d

alternatives on a river, and W a lk e r et al. ( 1 9 8 3 ) used the

(19 9 3 )

te ch n iq u e to a n a ly z e trad e -o ffs betw een m a n ag e m en t

u se d C V to e stim a te p re s e rv a tio n v a lu e s o f

p lan s fo r different sto cks o f co h o salm o n .

c o a sta l m a rin e w ild lif e in N o rth C a r o lin a .
as

A m u ltia ttrib u te a p p ro a c h has a lso been a p p lie d ,

in ap p ro p riate fo r m e a su rin g non u se v a lu e s. W h ile b e in g

b oth p a s s iv e ly , in id e n t if y in g ra n g e o f s ta k e h o ld e r

r e lia b le fo r m e a su rin g u s e v a lu e s, i.e ., re sp o n d e n ts had

c o n c e rn s (E d w a r d s 1 9 7 7 ) a n d a c t iv e ly , in b a rg a in in g

CV

m e th o d s

have

co m e

u n d e r a tta ck

a ctu a l e x p e rie n c e a n d c a n th u s id e n tify v a lu e s to th em ,

and n e g o tia tio n ( U l v i l a and S n y d e r 1 9 8 0 ; R a f f ia 1 9 8 2 )

v a lu e s r e s u ltin g fro m C V m eth o d s w ere u n b e lie v a b ly

to a sse ss the v a lu e s that s ta k e h o ld e r g ro u p s (p e o p le

huge. F ir s t a p p lic a tio n s o f C V to n o n u se v a lu e s sh ow ed

w ith r e la tiv e ly co h e re n t v ie w s abo ut a p ro b le m ) attach

that the m eth o d m ig h t not be re lia b le w h e n m e a su rin g

to e n v iro n m e n ta l im p a c ts o f r is k y te c h n o lo g ie s (v o n

u n fa m ilia r c o m m o d itie s . T h is p ro b le m w a s r e a liz e d b y

W in te rfe ld t a n d E d w a r d s 19 8 6 ) .

L a z o et a l. ( 1 9 9 2 ) and b y P e a rc e et a l. ( 1 9 8 9 ) an d had

F o r in terested re ad e rs, B a rto n ( 1 9 9 4 ) p ro v id e s an

prom pted the group to d e v is e su rv e y q u e stio n n aire s that

ind e p th a n a ly s is o f p o p u la r v a lu a tio n te c h n iq u e s w ith

p r o v id e d “ p e r f e c t i n f o r m a t io n ”

a n d “ c o m p le t e

a n n o t a t io n s o n s u p p o r t in g e c o n o m ic t h e o r ie s , a

p s y c h o lo g ic a l c o n t e x t o f th e e c o n o m ic d e c is io n ”

d e s c r ip t io n o f th e m e th o d , a s s u m p t io n s a n d o th e r

( F is c h h o f f a n d F u r b y 19 8 8 ). C o n c e r n re g a rd in g the

lim ita tio n s , a n d a p p lic a tio n s to co a sta l stu d ie s .

m e th o d s w a s e a rlie r s u m m a r iz e d b y

B y w a y o f e x a m p le , a ty p o lo g y o f d iffe re n t use

S c o tt ( 1 9 6 5 ) as “a sk a h yp o th etica l q u estio n a n d you

a n d n o n u s e v a lu e s f o r m a n g r o v e s in th e G u l f o f

g e t a h y p o th e tic a l a n s w e r ”. N e v e rth e le s s , C V re m a in s

G u a y a q u i l , E c u a d o r , a n d a p p l i c a t io n

p o p u la r a n d s t u d ie s f a i l to in d ic a t e e v id e n c e o f

t e c h n iq u e s is s h o w n in F ig . 3 . T h e s e v a lu e s w ere

su b sta n tia l b ia s.

d e riv e d fro m the p ro file an d a p p lic a tio n p a p e rs o f L P

v a lid it y o f C V

v a lu a t i o n

Output/services

Definition

Functional

that can be

Future use

benefits

Value to future

Value from continued

generations

knowledge of

directly consumed

existence
All direct and
indirect uses

Goods

Forest products:
firewood

Habitat for flora

AU direct and

and fauna

indirect uses

alcohol
tannin

- biodiversity
- flora and fauna

Substrate for bivalves

- habitat

timber
Nursery grounds

pulp
forage
fertilizer
fibers
Fishery products:
fmfish

Primary production
from forest litter
Natural barrier against
wind and tides

molluscs
crustaceans

Level of
tangibility
Valuation
techniques

High

Medium

Change in productivity

Property values

Loss of earnings

Wage differentials

Defense expenditure

Low

Low

Low

Travel cost

Replacement cost

Contingent valuation

Contingent valuation

Contingent valuation

Nonmonetary measures

Nonmonetary measures

Nonmonetary measures

Contingent valuation
Nonmonetary measures

Fig. 3. U se and nonuse values o f mangroves in the G ulf o f Guayaquil, Ecuador; associated levels o f tangibility and potentially useful valuation techniques.

16

o n the sa m e site . T h e g o o d s a n d s e r v ic e s lis te d are the
d o m in a n t u s e s o f m a n g r o v e r e s o u r c e s in th e a re a .
O p tio n , b e q u e st a n d e x is te n c e v a lu e s are d is t in c t b u t
are a ll b a se d o n the d e fe rm e n t o f d ir e c t a n d in d ire c t
u s e s fo r v a r y in g re a so n s (a n d th u s v a lu e s ).
A n a rg u m e n t h a s b een m ad e that, to a larg e extent,
w o r ld w id e tre n d s in re so u rce s o v e re x p lo ita tio n is an
e ffe ct o f fla w e d te ch n iq u e s fo r re so u rce s v a lu a tio n . T h e
im p e r f e c t io n s s t e m f r o m r ig id it i e s in t r a d it io n a l
v a lu a t io n t e c h n iq u e s to a c c o u n t f o r th e f o llo w in g
fe atu re s: m a rk e t fa ilu r e s c a u s e d b y e x te rn a litie s a n d
p u b lic g o o d s; n o n m a rk e t g o o d s a n d s e rv ic e s ; in te r- an d
in tr a -g e n e r a tio n a l e q u it y ; a n d d is c o u n tin g to n a m e a
few . H o w e v e r , the stron g lin k a g e s fo stered betw een the
fie ld s o f e c o n o m ic s , the b io lo g ic a l s c ie n c e s , a n d p u b lic
p o lic y h a v e le d to th e d e v e lo p m e n t o f te c h n iq u e s as
d is c u s s e d . T h e w o r k that h a s le d to th ese te c h n iq u e s
im p lie s a n e w c o n s c io u s n e s s . T h e n e x t step is u s in g
t h e s e m e a s u r e s p r o p e r ly , a n d c o m m u n ic a t in g the
im p lic a t io n s o f the r e s u ltin g stu d ie s to p o lic y m a k e r s .

References
Aylward, B. and E.B. Barbier. 1992. Valuing environmental functions in
developing countries. Biodivers. Conserv. 1:34-50.
B arbier, E.B. 1989. T he econom ic value o f ecosystem s: 1 - tropical
wetlands, LEEC Gatekeeper Series No. GK89-02,1IED/UCL London
Environm ental Econom ic Centre, London.
Barton, D.N. 1994. Econom ic factors and valuation o f tropical coastal
resources. SMR Report 14/94. Universitetet I Bergen Senter for MiljoOg Ressursstudier, Norway.
Bell, F. W. 1989. Application o f wetland valuation theory to Florida fisheries.
Florida Sea Grant College and Department o f Economics, Florida
State University, Florida. 95 p.
Bishop, R.C., K.J. Boyle and M.P. Welsh. 1987. Toward total economic
valuation of Great Lakes fishery resources. Trans. Am. Fish. Soc.
116:339-345.
B uhyoff, G. and J. W ellm an. 1980. The specification o f a nonlinear
psychophysical function for usual landscape dimensions. J. Leisure
Res. 12:257-272.
Chua, T.-E. and L. Fallon-Scura, Editors. 1992. Integrative fram ew ork
and m ethods for coastal area m anagem ent. ICLARM Conf. Proc.
37, 169 p.
Costanza, R., S.C. F arberand J. Maxwell. 1989. Valuation and management
o f wetland ecosystem s. Ecol. Econ. 1:335-361.
Dixon, J.A., R.A. Carpenter, L.A. Fallon, P.B. Sherman and S. Manopimoke.
1988. E c o n o m ic a n a ly s is o f th e e n v iro n m e n ta l im p a c ts o f
developm ent projects. Earthscan Publications, London.
Edwards, W. 1977. How to use multiattribute utility measurem ent for social
decision v aluing. IEE E (Institute o f E lectrical and E lectronics
Engineers) Transactions, Systems, M an and Cybernetics 7: 326-340.
Fischhoff, B. andL . Furby. 1988. M easuring values: a conceptual framework
for interpreting transactions with special reference to contingent
valuation o f visibility. J. Risk and Uncertainty 1:147-184.
Folke, C. and T. Karberger, Editors. 1991. Linking the natural environm ent
and the econom y: essays from the Eco-Eco Group. 2nd ed. Kluwer
Academic Publishers, Dordrecht.
Garcia, S.M. and C. Newton. 1995. Current situation, trends and prospects
in world capture fisheries. Conference on Fisheries Management:

Global Trends, 14-16 June 1994. Seattle, USA. 63 p.
Glass, R.J. and R.M. M uth. 1987. Pitfalls and lim itations in the use o f
fishery valuation techniques. Trans. Am. Fish. Soc. 116:381-389.
Gregory, R. 1987. N onm onetary measures o f nonm arket fishery resource
benefits. Trans. Am. Fish. Soc. 116 (3):374-380.
Hodgson, G. and J. Dixon 1988. Measuring economic losses due to sediment
pollution: logging versus tourism and fisheries. Trop. Coast. Area
M anage. 3(l):5-8.
H odgson, G. and J. D ixon. 1992. S edim entation dam age to m arine
resources: environm ental and econom ic analysis, p. 421-446. In J.B.
Marsh (ed.) Resources and environment in A sia’s marine sector. Taylor
and Francis, Washington.
Hufschmidt, M. and E. Hym an, Editors. 1982. Econom ic approaches to
natural resource and environm ental quality analysis. Tycooly Press,
Dublin.
Hundloe, T. 1989. M easuring the value o f the great barrier reef. Australian
Parks and Recreation 3:11-15.
H ym an, E .L . and B. S tifte l. 1988. C o m b in in g facts and v alu e in
environm ental im pact assessment. Westview Press, London.
Keeney, R. 1977. A utility function for exam ining policy affecting the
salmon in the Skeena River. J. Fish. Res. Board Can. 34:49-63.
Krutilla, J.V. 1967. Conservation reconsidered. Am. Econ. Rev. 57:777­
786.
Lazo, J.K., W.D. Schulze, G.H. M cClelland and J.K. Doyle. 1992. Can
contingent valuation m easure nonuse values? Am. J. Agric. Econ.
74:1126-1132.
Munasinghe, M. and E. Lutz. 1992. Environm ental-econom ic valuation
o f projects and policies for sustainable developm ent. Environment
Working Paper 42. World Bank, W ashington, DC.
Panayotou, T. 1993. The environm ent in Southeast Asia: problem s and
policies. Environ. Sci. Technol. 27:2270-2274.
Pearce, D. and D. Moran. 1994. The econom ic value o f biodiversity. IUCN,
The World Conservation Union. Earthscan Publications, London.
Pearce, D.W., D. M arkandya and E.B. Barbier. 1989. Blueprint for a green
economy. Earthscan Publications, London.
Raffia, H. 1982. The art and science o f negotiation. Harvard University
Press, Cambridge, M assachusetts.
Randall, A. 1987. Total econom ic value as a basis for policy. Trans. Am.
Fish. Soc. 116:325-335.
Ruitenbeek, H.J. 1992. M angrove management: an econom ic analysis of
m anagem ent options w ith a focus on B intuni Bay, Irian Jaya.
E nvironm ental M anagem ent D evelopm ent in Indonesia Project
(EMDI). EMDI Environm ental Reports No. 8.
Sawyer, D. A. 1992. Taka bone rate: management, development, and resource
valuation of an Indonesian Atoll. D alhousie University, Canada.
M aster’s thesis.
Schuman, H. and M. Johnson. 1976. Attitudes and behavior. Ann. Rev. Sociol.
2:161-207.
Scott, A. 1965. The valuation of game resources: some theoretical aspects.
Can. Fish. Rep. 4.
Spindler, J. 1975. The accuracy o f consumer surveys in describing markets
for hypothetical goods. Rand Corporation, Santa Cruz, California.
Spurgeon, J.P.G. 1992. The economic valuation of coral reefs. Mar. Pollut.
Bull. 24:529-536.
Ulvila, J. and W. Snyder. 1980. Negotiations on international timber standards:
an application of multiattribute value theory. Operations Res. 28:81­
96.
von Winterfeldt, D. and W. Edwards. 1986. Decision analysis and behavioral
research. Cambridge University Press, Cambridge.
Walker, K„ B. Rettig, and R. Hilbom. 1983. Analysis of multiple objectives
in Oregon coho salmon policy. Can. J. Fish. Aquat. Sci. 40:580-587.
W eisbrod, B.A. 1964. C ollective-consum ptive services o f individualconsumption goods. Q. J. Econ. 78:471-477.
W hitehead, J.C. 1993. Total economic values for coastal and marine wildlife:
specification, validity, and valuation issues. Mar. Res. Econ. 8:119­
132.

Options for Mangrove Management
in the Gulf of Guayaquil, Ecuador*

su rfa c e w ater. T h e s e o c e a n o g ra p h ic c h a ra c te r is tic s are
s e a so n a l in n ature a n d d e p e n d e n t on th e in te n s ity and
p e rm a n e n ce o f the fron t. T h e co a s ta l a re a s o f E c u a d o r

ICLARM -ECLAC Collaborative Project on
the Socioeconom ic Valuation o f Coastal Resources in
Southwest Latin America, Casilla 179-D, Santiago, Chile
F

a b io l a

B e l l 1,

lik e w is e e x p e rie n c e the E l N iñ o p h e n o m e n o n , an e ven t
g e n e ra lly o c c u r r in g e v e ry 3 - 7 y e a rs , c h a ra c te r iz e d b y
h ig h w ate r te m p e ra tu re s fo r p e rio d s r a n g in g fro m 6 to
1 8 m o n th s, a n d h e a v y ra in s.

International Center fo r Living
Aquatic Resources M anagement (ICLARM), MCPO Box
2631, 0718 Makati City, Philippines
A

nnabelle

C

A c c o r d in g to the K o p p e n c la s s if ic a t io n , G u a y a s

r u z - T r in id a d ,

h a s three c lim a te ty p e s w h ic h d is tin g u is h the north fro m
the sou th : s e m i a rid o r step pe c lim a t e , w ith r a in fa ll
lo w e r th an 2 5 0 m m a n n u a lly ; a rid , w ith r a in fa ll lo w e r

B E LL , F. and A. C R U Z -T R IN ID A D . 1996. O ptions for m angrove
m anagem ent in the G ulf of Guayaquil, Ecuador, p. 17-31. In A. Cruz­
T rinidad (ed.) Valuation of tropical coastal resources: theory and
application o f linear program m ing. ICLARM Stud Rev. 25, 108 p.

A b stra ct

th an 5 0 0 m m fro m the m o n th s o f J a n u a ry to A p r il. In
the z o n e o f the G u a y a s R iv e r , the c lim a t e is tro p ic a l
h u m id an d s a v a n n a h .

Characteristics o f the Mangroves
o f Guayas, Ecuador

The econom ic and ecological costs and benefits o f two management
strategies: (1) m angrove conversion and (2) sustainable exploitation are
identified and set up as a linear program m ing problem. The maximization
objective is to increase Total Econom ic Value (TEV) from these strategies
satisfying constraints pertaining to land, labor, availability of penaeid
shrimp fry, rated capacity of processing plants and product demand.
A ggregate benefits resulting from a com bination of both strategies is
US$ 174-106 o f which 60% is contributed by sustainable exploitation of
mangroves (US$ 18.410’ from forestry and US$ 87.610*’ from fishery);
the rem aining am ount is accounted for by conversion to shrimp farms.
These benefits correspond to the sustainable exploitation of 120-106 ha of
mangroves and conversion of 5 .5 1 0 ’ ha.

G eneral D escription o f Study Site

E n v ir o n m e n t a l c o n d it io n s in E c u a d o r , as in m o st
tr o p ic a l c o u n tr ie s , are c o n d u c iv e to the g ro w th and
d e v e lo p m e n t o f m a n g ro v e fo re sts. T o ta l m a n g o v e area
in G u a y a s is 1 1 6 ,0 0 0 h a , re p re se n tin g 6 6 % o f total
m a n g o v e a re a in E c u a d o r ( C L I R S E N 1 9 8 7 ) .
M a n g r o v e s and sa lt fla ts are fo u n d in the in te rtid a l
z o n e ; fu rth e r in w a rd s are the h ig h e r g ro u n d s, w h ic h
are n e v e r flo o d e d . T h e m a n g ro v e s are fo u n d in areas
c lo s e r to the se a and as s u c h are fre q u e n tly in u n d a te d ,
w h e re as the salt fla ts are p e r io d ic a lly in u n d a te d a nd,
in m o st c a s e s , o c c u r b e h in d m a n g ro v e s . In m o st c a se s,

The Coast o f Guayas

c la y e y or m u d d y so ils are rather im p e rm e a b le and e a sily
get flo o d e d d u rin g h ig h tid e s. A r e a s w h ic h d o not h a v e
a n y fo rm o f ve g e ta tio n h a v e h ig h co n c e n tra tio n s o f salt

G u a y a s P r o v in c e is o n e o f fo u r p o lit ic o -a d m in is ­

w h ile those in the h ig h e r a re a s are m o re c o n d u c iv e to

tra tiv e re g io n s o f E c u a d o r an d c o n s ists o f 2 0 ,9 0 0 k m 2

a g ric u ltu re ( F ig . 2 ).

o r 3 4 % o f the n a tio n a l su rfa c e area. T h e p ro v in c e is

T h e m a n g ro v e fo re sts o f G u a y a s are c h a ra c te r iz e d

b o u n d e d b y the G u l f o f G u a y a q u il a n d is the site o f

b y tw o z o n e s: 1 ) the r iv e r frin g e s , w h e re Rhiz.ophora

v a r io u s s o c i a l a n d e c o n o m ic a c t i v i t i e s ( F i g . 1 ) .

spp. (red m a n g ro v e ) o c c u r a n d 2 ) the in n e rm o st to rear

M a n g r o v e s a n d s h r im p fa rm s are fo u n d in the c o a sta l

a re a s, w h ere a m ix o f A vicennia spp. (b la c k m a n g ro v e )

a re a w ith the latter c o m p r is in g 3 0 ,0 0 0 ha.

a n d L a g u n cu la ria spp. o c c u rs (T e rc h u n ia n et a l . 19 8 6 ).

A n im p o rta n t featu re o f the r e g io n ’ s o c e a n o g ra p h y

T h e R h izo p h o ra strip ó c c u r s in th e z o n e in u n d a te d 4 4 5

is the e q u a to ria l front, n o r m a lly lo cated b e tw e e n 0 °

to 7 0 0 tim e s p e r y e a r ( C in t r o n a n d S c h a e f e r 1 9 8 3 )

a n d 3 ° , a n d w h ic h se p arate s the c o ld a n d n u trie n t ric h

w h e re a s the oth e r z o n e is in u n d a te d 1 8 4 to 4 4 5 tim e s

w aters o f the H u m b o ld t cu rre n t a n d the e x te n sio n o f

p e r year. M a n g r o v e fo re sts m a y a ls o c o n ta in z o n e s o f

the E q u a t o r ia l s u b c u rre n t fro m w a rm n u trie n t p o o r

salt d e p o sits (salitrales) a n d m u d d e p o sits (lodo or
pantone) both o f w h ic h are in u n d a te d le ss than 1 84
tim e s p er ye a r. D u e to the h ig h s a lin ity in th is z o n e , the
* ICLARM Contribution No. 1222.
P resent address: Calle Edinburgo 520, Depto. 102, Las Condes,
Santiago, Chile.

m a n g r o v e f o r e s t s a re c o l l e c t i v e l y c a lle d
(T e rc h u n ia n et a l. 19 8 6 ).
17

s a lin a s

18
p r o d u c t s a n d s e r v ic e s d e r iv e d
f r o m it. T h e e c o lo g ic a l fu n c tio n s
o f t h e m a n g r o v e i n c l u d e th e
e x p o r t o f o r g a n ic m a t e r ia l to
e stu a rie s w h ic h se rv e s as fo o d fo r
ju v e n ile s h r im p s a n d f is h a n d /o r
t h e ir p r e y ; th e ro o t s y s t e m o f
m a n g ro ve

tre e s

e n a b le s

th e

reten tio n o f se d im e n ts, p re ve n tin g
e r o s io n a n d a ls o f o r s h o r e lin e
p ro te ctio n ; a n d la s tly , p r o v id in g a
h a b ita t f o r m a n y a q u a tic sp e c ie s
in the m u d fla ts a n d roots.
T h r e e a lte rn a tiv e u s e s o f the
m a n g ro v e s in G u a y a s , E c u a d o r ,
in c lu d e : 1 ) c a p tu r e f is h e r ie s ,

indirect use v ia the p ro te ctio n

and

n o u r is h m e n t p r o v id e d to targ et
Legend:

s p e c ie s a n d

Maritime transport
Catchment of agri 8
industrial waste

Pasture

v i a th e
and

a n d 3 ) a q u a c u lt u r e , c o m p le t e

conversion of
e c o lo g ic a l

[1
^

f is h

direct
exploitation o f m a rk e ta b le g o o d s;

I* Mangrove and shrimp
farm
4

‘ Fishery

of

c r u s t a c e a n s ; 2 ) f o r e s tr y ,

. Town and trade
 centers

Coffee

direct use

e x p lo it a t io n

th e p h y s ic a l a n d

d y n a m ic s

o f th e

e c o s y s te m . T h e three u s e s o c c u r

Cacao

s im u lt a n e o u s ly a n d r e s u lt in a

 , Rice

m e a s u ra b le q u a n tity o f e c o n o m ic

Fig. 1. The coastal zone bordering the Gulf of Guayaquil, Ecuador, as the site of multiple
economic and resource-based activities.

b e n e f it s . H o w e v e r , m a n g r o v e
c o n v e r s io n to s h r im p a q u a c u ltu re
h a s b e e n th e ir m a in u s e in the last

The

Rhizophora, Avicennia an d Laguncularia attain

heights o f  1 5 m , 6 - 1 5 m a n d  5 m , re sp e ctiv e ly. S o m e

tw o d e c a d e s b e c a u s e o f a ttra ctiv e return s in th e exp o rt
m ark e t.

m a n g r o v e tr e e s a r e k n o w n to r e a c h h e ig h t s o f

O f the three a lte rn a tiv e u s e s , m a n g ro v e c o n v e rs io n

3 5 m an d a d e n sity o f 3 6 5 trees per hectare co m p a re d to

re su lts in the g ra v e st d a m a g e to the e n v ir o n m e n t (P a w

an o p tim u m o f 8 0 0 trees p er hectare ( F P V M 1 9 8 7 ) . In

a n d C h u a 1 9 9 1 ) . M a n g r o v e c o n v e r s io n to s h r im p

G u a y a s , stan d in g d e n sity is o n ly 1 8 5 t h a ‘, an in d ica to r

m a ric u ltu re re su lts in a v ic io u s c y c le b e c a u s e o f the

o f o v e re x p lo ita tio n ( T w ille y 1 9 8 9 ) . C h a r a c te r is tic s o f

lo ss o f b re e d in g g ro u n d s fo r la rv a e w h ic h are c r it ic a l

m a n g ro v e s are sh o w n in T a b le 1 . T h e s e sp e c ie s are

in p u ts to the sh rim p in d u stry . O th e r im p a c ts o b se rv e d

u tiliz a b le as tim b e r a n d other w o o d p ro d ucts.

in G u a y a s in c lu d e ch a n g e in w ater q u a lity in th e co a sta l
z o n e d u e to d is c h a rg e s o f s h r im p p o n d s b ro u g h t a b o u t

Alternative Uses for Mangroves: Fishery,
Forestry and Aquaculture

b y w ate r e x c h a n g e w h ic h T w ille y ( 1 9 8 9 ) e stim a te s to
re a c h 2 0 m illio n t d a y .
B o t h a q u a c u lt u r e a n d f o r e s t r y a c t iv it ie s w e re
o b se rv e d to h a v e a d v e rs e e ffe cts o n the e n v ir o n m e n t

V e la s c d ( 1 9 8 7 ) s y n th e s iz e s the ro le o f m a n g ro v e s

in c lu d in g a d e c lin e in the p ro d u ctio n o f m u s s e ls , o ysters

a s : 1 ) e c o n o m ic a n d th e r e fo re e x p lo it a b le a n d 2 )

a n d c o c k le s . T h e f e llin g o f trees c a u s e s th in n in g o f

e c o lo g ic a l a n d th e re fo re c o n s e rv a b le . T h e e c o n o m ic

fo re st c o v e r w h ic h re s u lts in d ir e c t p e n e tra tio n o f so la r

im p o rta n c e o f the m a n g ro v e e co sy ste m a ris e s fro m the

r a y s , in c r e a s in g la n d te m p e ra tu re a n d s a lin it y a n d

19

d e c lin e

in

oxygen

le v e ls

c o n t r ib u t in g

to th e

d isa p p e a ra n c e o f s p e cie s that e x is t in m u d d y substrates.
It lik e w is e c a u s e s a d e cre a s e in n a tu ra l b a rrie rs that
p ro te c t a g a in s t s u rf, a n d w ith w in d a c t io n c a u s in g
Coastal zone

e ro s io n a n d in c r e a s e d s a lin it y o f in te rio r la n d s .

Fishery
C o m m e r c ia lly im p o rta n t s p e c ie s a s s o c ia te d w ith

Penaeus: P.
vannamei, P. stylirostris, P. occidentalis a n d P.
californiensis. T h e s e s p e c i e s h a v e a p a r t i c u l a r
m a n g ro v e in c lu d e s h r im p o f th e g e n u s

m ig ra to ry c y c le a n d a p p e a r s tro n g ly d e p e n d e n t o n the
m a n g r o v e s . O t h e r c r u s t a c e a n s f o u n d in m a n g r o v e s

jaiba) (Ucides sp p., Uca sp p .,
Callinectes toxotes). C o m m e r c ia lly im p o rta n t m o llu s c s
i n c lu d e Anadara tuberculosa, Anadara similis,
Anadara grandis, Mytella guayanensis, Ostrea
columbiensis a n d Chione subrugosa.
in c lu d e c ra b s ( L o c a l:

O n ly o n e f is h s p e c ie s a p p e a rs to b e c o m p le te ly
d e p e n d e n t o n m a n g ro v e s ,

Mugil curema m u lle t (lisa),

a d e tritu s feeder.

THE COM M ERCIAL A N D ARTISANAL SECTOR

T h e c o m m e r c ia lly im p o rta n t s p e c ie s are e x p lo ite d
b y b o th th e a r t is a n a l a n d c o m m e r c ia l f le e t . T h e
c o m m e r c ia l fle e t e x p lo its th e sh r im p f is h e r y w h ic h is
a p ro m in e n t fe atu re in th e G u l f o f G u a y a q u il ( C u n a n d
M a r in 1 9 8 2 ) . S h r im p f is h in g is c o n d u c te d th ro u g h o u t
Fig. 2. Zonation, uses and products/goods derived from coastal
areas in the G ulf o f Guayaquil, Ecuador.

the e n tire co a s t in d e p th s o f 6 0 m . M a in g e a rs u se d are
p a ir traw le rs w ith le n g th s o f 1 0 to 2 5 m a n d 1 9 0 to
5 0 0 h p o r greater.
T h e sh r im p fis h e r y c o n trib u te d 1 0 to 1 2 % o f total
p ro d u c tio n o f s h r im p s in E c u a d o r in re c e n t y e a rs w ith

Table 1. Com m ercially im portant m angrove species in Guayas, Ecuador.

m angle

Rhizophora
harrisonii

Family and species
Avicennia
racemosa
nitida

Laguncularia

Conocarpus
erectus

m. cholo
m. gateado
m. gatucho

m. rojo
caballero

m. de pava
m. iguaner

m. salado

m. blanco
m. hembra
m. bobo

Jell prieto
m. macho

Average height, Ecuador (m)

12

51

30

30

18

13

Average height, general (m)

7-8 ; 10-12

15-35 ; 50-60

8-25

Com m on nam e(s)

Source: H om a (1983); Rollet (1986).

20
the r e m a in in g c o n trib u te d b y cu ltu re . C a t c h o f f u lly -

M o s t m a n g ro v e p ro d u cts are u s e d fo r co n stru ctio n .

g ro w n s h r im p a n d la r v a e a m o u n te d to 1 0 ,8 0 0 t an d

R e d a n d w h ite m a n g ro v e s are v a lu e d f o r th e ir p u lp

6 . 4 - 1 0 9 la rv a e in 19 8 8 , re sp e ctiv e ly. A s fo r la rv a e , a ctu a l

w h ic h is u s e d fo r the m a n u fa c tu re o f b o a rd s , p a n e ls

c a tc h c a n b e a s h ig h as 1 . 3 - 1 0 10 la rv a e (a s s u m in g a 5 0 %

a n d w o o d c h ip s . T h e re d m a n g ro v e is u s e d fo r c h a rc o a l

m o rta lity rate), a n d at a p r ic e o f U S $ 8 .6 p e r th o u sa n d

a n d fro m its b a r k is ta n n in s o u rc e d ; th e latter is m e re ly

la rv a e , a n d c a n b e v a lu e d at U S $ 5 5 - 1 0 9 to 1 1 0 - 1 0 6 p er

a b y -p r o d u c t a n d is e x p lo ite d o n a s m a ll sc a le .

year.
T h e a rtis a n a l f is h e r y u s e s s m a ll v e s s e ls s u c h as

PRODUCTION

rafts, c a n o e s , b o a ts a n d b a rg e s, m a n y o f w h ic h h a v e
b ee n u s e d s in c e th e 16 t h c e n tu ry ( L e n z -V o lla n d a n d

G r o w t h o f m a n g ro v e s is slo w . T h e red m a n g ro v e ,

V o lla n d 1 9 9 2 ) to c a t c h f is h , m o llu s c s a n d c ru s ta c e a n s .

f o r e x a m p le , ta k e s a b o u t 2 5 to 3 0 y e a r s to a tta in

T h e m o st im p o rta n t c r u sta c e a n s are p e n a e id s h rim p s

m a tu rity, w h ile th e oth e r sp e c ie s ta ke 1 5 to 2 0 y e a rs

a n d lo b s t e r s w h ic h a re s o ld fre s h , f r o z e n , c o o k e d ,

(H o m a 19 8 3).

c a n n e d o r sa lte d . L a r v a l a n d ju v e n ile sh r im p are a ls o

Wood:

T h e d e n s ity o f re d m a n g ro v e is 0 .9 to 1 .2

ca p tu re d fo r re a rin g in h a tch e rie s. T h e s e are ca p tu re d

t-m 3. T o e s t im a te y i e ld p e r h e c t a r e , w e c o n s id e r

t h r o u g h o u t th e c o a s t lin e y e a r -r o u n d b u t a re m o s t

b io m a s s p e r h e cta re w ith th e f o llo w in g p e rc e n ta g e

a b u n d a n t d u r in g the r a in y m o n th s fro m N o v e m b e r to

d is trib u tio n p er s p e c ie s :

A p r il (M c P a d d e n 1 9 8 5 ) . T h e a rtisa n a l fle e t a lso ca tch e s

R. mangle

b e rrie d sh r im p fe m a le s u s in g tra m m e l nets.

L. racemosa

C r a b s a re c a p t u r e d in m a r s h e s u s in g m a n u a l

R o o ts

20

—

m e th o d s, tra p s a n d b a its . T h e s e a re s o ld fre s h a n d

T ru n k

65

86

c o n s u m e d lo c a lly a n d e x p o rte d as w e ll. M o llu s c s are

B ra n ch e s

12

10

m a n u a lly e x tra c te d f r o m th e m u d , d u r in g lo w tid e .

Leaves

3

4

T h e s e are s o ld a n d c o n s u m e d as fre sh a n d u n s h e lle d
a n d in so m e c a s e s , c a n n e d o r fro ze n . T h e m a rk e t is

Charcoal: T h e

y ie ld o f w o o d c h a r c o a l is 0 .5 m 3 o f

Anadara tuberculosa

c h a r c o a l p e r m 3 o f w o o d , at a 5 0 % c o n v e r s io n rate.

w h ic h is a ls o e x p o rte d . T h e fis h sp e c ie s ca p tu re d b y

T h u s , g iv e n a d e n s ity o f 6 8 0 k g m 3 o f w o o d c a rb o n ,

the a rtis a n a l se cto r are v a r ie d a n d c o n s u m e d as fresh ,

th is tran slate s to 3 4 0 k g ca rb o n p er m 3 o f w o o d .

d o m e stic e x c e p t in the c a s e o f

co o k e d , salted o r ca n n e d a n d are c o n su m e d b y d o m e stic
an d fo re ig n m a rk e ts.

Tannin: It

is p o s s ib le to o b ta in u p to 9 0 k g o f tree

b a r k f r o m a m a tu r e tre e f r o m w h ic h 3 0 %

can be

e xtra cte d as ta n n in . E x tr a c tio n rates o f ta n n in fro m the

Forestry
T h e e x p lo ita tio n o f m a n g ro v e forests in E c u a d o r

b a rk a n d le a v e s are 1 5 to 4 2 % a n d 2 2 % , r e s p e c tiv e ly .

Aquaculture

is s m a ll s c a le , d o n e m o s tly b y f a m ily g ro u p s, w h ic h
h a v e m a in ta in e d the tra d itio n a l e x p lo ita tio n sy s te m s

T h e g e o g ra p h ic a l c o n d it io n s o f the c o a s ta l zo n e

o v e r the y e a rs . T h e m a in m o d e s o f e x p lo ita tio n are

are c o n d u c iv e to th e g ro w th o f the sh r im p a q u a c u ltu re

p a rtia l a n d s e le c t iv e lo g g in g . P a rtia l lo g g in g in v o lv e s

in d u s t r y w h ic h in 1 9 8 8 b e c a m e th e s e c o n d m o s t

the fe llin g o f alte rn a te strip s o f trees p e r p e n d ic u la r to

im p o rtan t so u rce o f fo re ig n e x c h a n g e n e xt to p e tro le u m

w a te rw a y s e v e r y 1 5 y e a r s ; th is p e r m its the n a tu ra l

(S o lo r z a n o 1 9 8 9 ) . P re se n tly , E c u a d o r a cco u n ts fo r 7 6 %

re g e n e ra tio n o f th e fo re st. S e le c t iv e lo g g in g is the

o f sh rim p p ro d u c tio n in the w este rn h e m is p h e re , is the

f e llin g o f trees w ith d ia m e te r gre ate r th an 5 to 1 2 cm ,

s e co n d la rg e st e x p o rte r o f p o n d -r a is e d s h r im p in the

w h ile the s m a lle r on es are left sta n d in g a lo n g w ith those

w o rld , a n d the fo u rth la rg e st p ro d u c e r (A g ü e r o and

w h ic h b e a r se e d s to a llo w re g e n e ra tio n o f the forest.

G o n z a le z 1 9 9 1 ) . W h ile in itia te d in 1 9 6 8 , th e p e rio d p f

T h e p r in c ip a l u s e o f w o o d in c lu d e s f e llin g o f trees

r o b u s t g ro w th w a s b e tw e e n 1 9 8 0 a n d 1 9 8 7 f r o m

fo r ch a rc o a l an d fire w o o d , an d the m a n u fa ctu re o f w o o d

w h e n c e g ro w th s t a b iliz e d . T h i s d e v e lo p m e n t h a s

p ro d u c ts fo r c o n s tru c tio n . It is p re s u m e d that p re se n t

d ir e c tly ca u s e d the d e stru c tio n o f a ro u n d 3 0 ,0 0 0 h a o f

e x p lo ita tio n s y s te m s h a v e n o t c h a n g e d m u c h f r o m

m a n g ro v e fo re st; the M a n a b i re g io n su ffe re d the m o st

tra d itio n a l fo r m s ( H o m a 1 9 8 0 ) .

a n d at present h a s 5 0 % o f fo re st c o v e r (T a b le 2 ).

21
S h r im p fa rm s w e re in it ia lly co n stru cte d in salt flats

(T a b le 3 ) . T h e c u ltu re s y s te m s u s e d in E c u a d o r a n d

a n d a r e a s o f s p a r s e v e g e t a t io n ; h e re , c o s t s o f

t h e ir c h a r a c t e r is t ic s in c lu d e th e e x t e n s iv e s y s te m ,

c o n s t r u c t io n w e r e m in im a l. L a t e r , m a n g r o v e a n d

a c c o u n tin g f o r 3 5 % o f to ta l p o n d a re a , p ra c t ic e d in E l

in te rtid a l a re a s a n d la n d s f o r m e r ly u s e d fo r a g ric u ltu re

O r o P r o v in c e ; th e s e m i-e x t e n s iv e s y s te m , a c c o u n tin g

w ere a ls o tap p e d (S n e d a k e r et a l. 19 8 8 ). T o date, sh rim p

fo r 5 5 %

fa rm s c o m p r is e 3 5 to 4 8 % o f th e to ta l a re a in h illy

P r o v i n c e ; a n d th e s e m i - i n t e n s i v e s y s t e m , w h ic h

g r o u n d s , 2 7 to 3 4 % in s a lt fla ts a n d 2 5 to 3 0 % in

o p e rate s u n d e r p r o fe s s io n a l, a n d .o f t e n tim e s , fo re ig n

m a n g ro v e s ( M e lt z o f f a n d L iP u m a 1 9 8 6 ) .

m a n a g e m e n t ( M e lt z o f f a n d L i P u m a 1 9 8 6 ) .

In G u a y a s P r o v in c e a lo n e , 9 ,5 0 0 h a o f m a n g ro v e s

o f t o t a l p o n d a r e a , p r e v a le n t in G u a y a s

S h r im p m a ric u ltu re b e g in s w ith th e ca p tu re o f

semilleros

a n d 3 1 ,0 0 0 h a o f sa lt fla ts w e re c o n v e rte d to s h rim p

la rv a e b y

fa rm s fro m 1 9 6 9 to 1 9 8 7 . O v e r a ll, in E c u a d o r , 1 1 7 , 0 0 0

a lth o u g h re c e n tly tra w le rs w e re o b s e r v e d to ca p tu re

(la r v a e c o lle c to rs ) in e stu a rie s,

h a o f sh r im p fa rm s h a v e b e e n c o n stru cte d as o f 1 9 8 7 ,

g r a v id fe m a le s f o r h a tc h e ry p ro d u c tio n ( M e lt z o f f a n d

6 3 % o f w h ic h is c o n ce n tra te d in G u a y a s .

L i P u m a 1 9 8 6 ) . L a r v a e p r o d u c t io n h a s b e e n q u ite
e rra tic w ith p e a k s o c c u r r in g in 1 9 8 2 a n d 1 9 8 3 b e in g
a t t r ib u t a b le to th e “E l N i ñ o ” p h e n o m e n o n . T h e

Table 2. A rea o f m angroves, salt flats and shrimp farms in Ecuador, 1969­
1987, by province.__________________________________________________
Province

Year

M angroves

Esmeraldas

1969
1984
1987
1969
1984
1987
1969
1984
1987
1969
1984
1987
1969
1984
1987

32.0
30.2
29.3
12.4
8.0
6.6
125.5
119.6
116.1
33.6
24.4
23.4
203.6
182.2
175.5

M anabi

Guayas

El Oro

Total

d e v e lo p m e n t c y c le o f sh r im p m a r ic u ltu r e is o b se rv e d
to b e s e lf -d e fe a tin g w ith th e c o n s t r u c tio n o f p o n d s

Shrimp ponds

c a u s in g w id e sp re a d m a n g ro v e d e stru c tio n (T e rc h u n ia n

.

.

et a l. 1 9 8 4 ) a n d the in e v it a b le lo s s o f b re e d in g g ro u n d s

-

1.6
2.6

fo r s h r im p la rv a e . T h u s , w h ile s h r im p p o n d c o v e ra g e

Salt flats

-

845.0
164.0
164.0
40.1
17.3
9.8
9.8
2.5
2.5
51.5
20.0
12.4

-

8.4
10.0
52.6
74.4
-

26.5
29.7
-

89.1
116.8

h a s b e e n in c r e a s in g , th e a v a i l a b i li t y o f la r v a e fo r
s t o c k in g h a s a p p ro a c h e d c r is is le v e ls .

COSTS

T h e c o s ts a s s o c ia te d w ith a q u a c u ltu r e in c lu d e the
co st o f la n d , c o n stru ctio n co sts a n d o p e ratin g e x p en ses.
T h e co st o f la n d v a r ie s a c c o r d in g to its lo c a t io n , so u rce
o f w ate r a n d s o il q u a lity . H ig h la n d s a n d m a n g ro v e s
a re p r ic e d at U S $ 1 , 0 0 0 - h a  1 a n d U S $ 6 , 0 0 0 - h a 1,
r e s p e c tiv e ly . S a ltb e d s are p ric e d in b e tw e e n (H o r n a
1 9 8 3 ) . In G u a y a q u il, a g r ic u ltu r a l la n d c o n v e r t ib le (to

CULTURE SYSTEM S

s h r im p fa rm s ) c o sts a ro u n d U S $ 2 , 0 0 0 - h a 1.

Penaeus

C o s t o f in fra stru c tu re a n d e q u ip m e n t d e p e n d s o n

is m o re a d a p ta b le to e x is tin g c u ltu re

the te c h n o lo g y u s e d . C o n s tr u c tio n a n d e q u ip m e n t co sts

S h r im p fa rm s c u ltu re the w h ite sh rim p ,

vannamei, w h ic h

m e th o d s ; o f s e c o n d a r y im p o r t a n c e is

stylirostris

Penaeus

(A q u a c o p 19 7 9 ).

m a y r a n g e f r o m U S $ 4 , 0 0 0 to 7 , 7 0 0 -h a  1 w ith a n
e c o n o m ic lif e tim e o f 5 to 1 0 y e a rs .

S h r im p c u ltu re re q u ire s the c o n stru c tio n o f ta n k s

T h e m a jo r co m p o n e n ts o f v a r ia b le c o s ts in c lu d e

o r p o n d s w ith h e ig h ts r a n g in g fro m 0 .5 to 1 . 2 m . T h e

c o s t s o f la r v a e , f o o d a n d e n e r g y . P r ic e o f la r v a e

la rv a e are c a p tu re d in e s tu a rie s b y a rtis a n a l fish e rs a n d

d e p en d s o n a v a ila b ility . D e p e n d in g o n the p o in t o f sale,

tra n sp o rte d to s to c k in g ta n k s . T h e la rv a e are e ith e r

so u rc e a n d tim e o f y e a r, the p r ic e o f la r v a e in re ce n t

b ro u g h t to g r o w -o u t fa rm s or to h a tc h e rie s. S u r v iv a l

y e a rs flu c tu a te d fr o m U S $ 1 to 1 3 . 5 -th o u s a n d  1.

rate is lo w th ro u g h th e v a r io u s stages o f p ro d u c tio n
(c a p tu re , tra n sp o rt a n d s to c k in g ) r a n g in g f r o m 1 to 5 %

FIN AL PRODUCT AND PRO D U CTIO N TRENDS

a n d m o rta lity m a y re a c h as h ig h as 5 0 to 1 0 0 % p er
stage.

U p o n h a rv e st, sh rim p s are p ro c e s s e d v i a ste a m in g

P r e v a i l i n g c u lt u r e s y s t e m s a re d if f e r e n t ia t e d

a n d th e ir ta ils re m o v e d . H e a d le s s s h r im p s h a v e fin a l

a c c o r d in g to the le v e l o f te c h n o lo g y , s to c k in g d e n sity ,

w e ig h ts o f a b o u t 6 6 - 6 7 % o f liv e w e ig h t. T h e s e are

fe e d in g r e g im e , f e r t iliz a t io n a n d w a te r m a n a g e m e n t

p a c k e d a n d fro ze n fo r tran sp o rt a n d s e llin g .

22

Linear Programming Application
to the Mangroves of Guayas, Ecuador

Table 3. Main features of shrim p culture systems in Ecuador.
Extensive

Stocking density
( P L l O h a 1)
Yield ( l b h a y e a r 1
)
W eight (g)
Supplem entary
feeding

Sem i-extensive

Sem i-intensive

10-10.5

30-35

80-100

300-800

975-1,300

1,900-3,250

23-35

Parameters

18-21.5

15-18

The Optimization M odel

none

only in final stage
of life cycle

A m o d e l w as co n stru cted w h ic h seeks to

throughout cycle
Feeding ratio: 1.3-2

o p tim ize T o ta l E c o n o m ic V a lu e ( T E V ) d eriv e d
f r o m th e m a n g r o v e e c o s y s t e m in G u a y a s ,
E c u a d o r . O p t im u m T E V

is a r r iv e d a t b y

Fertilizers

none

yes

yes

Breeding tanks

none

yes
(40-45 days)

yes

ranging fro m the extrem e options o f co n servation

pum ped

aeration

p a r tia l r e m o v a l o f m a n g ro v e a n d s u s ta in e d

 100

1,000

55

10

W ater m anagem ent

seawater

c o m b in in g d e ve lo p m en t strategies (see F ig . 3 ),
o r c o n v e rs io n , o r an in te rm e d ia te o p tio n , i.e.,
e xp lo itatio n o f the rem ainder.

Area (ha)
% of use in Ecuador

35

Conservation

does not y ie ld a n y fo rm o f

g o od s b u t generates b e n e fits v ia se rv ic e s and
f u n c t io n s ( d is c u s s e d in p r e v io u s s e c t io n ) .

Source: M cPadden (1985); Espinoza (1989).

Sustainable exploitation in v o lv e s

the extraction

o f forestry and fish e ry go ods in a fa s h io n that assures
future gen e ratio n s o f the sa m e q u a lity o f life (W o rld
C o m m is s io n on E n v iro n m e n t an d D e v e lo p m e n t 1 9 8 7 ) .
T h i s in c lu d e s th e in d ir e c t b e n e f its a s s o c ia t e d w ith
m a n g ro ve s su ch as the se rv ice s an d e c o lo g ic a l fu n ctio n s
C u lt u r e d s h r im p p ro d u c tio n re a c h e d 7 7 ,8 0 0 t in
1 9 8 8 w ith a v a lu e a m o u n tin g to U S $ 3 2 2 m illio n . T o ta l

d e riv e d fro m th em .

Conversion

in v o lv e s a p a rtia l or

co m p lete alteration o f the g e o p h y s ic a l attributes o f the

p r o d u c tio n b y b o th c a p tu re a n d c u lt u r e a m o u n ts to

reso u rce . W e c o n s id e r o n ly the co n v e rs io n to sh rim p

a b o u t U S $ 4 1 6 m illio n /y e a r , w h ic h is a b o u t 4 . 2 % o f

p o n d s b e c a u s e its p re v a le n c e in o u r p ro je c t site has

G N P a n d 2 8 . 3 % o f p r im a r y p ro d u c tio n ( F E D E C A M

e levated it to a m an ag em en t co n ce rn . C o n v e r s io n results

1 9 8 9 ) . T h e e x p o rt m a rk e t, n o ta b ly the U n it e d S tate s,

in a p a rtic u la r c o m m o d ity , s h rim p s , a n d in c u rs co sts

a b so rb s 9 2 % o f total p ro d u c tio n w h ile the re m a in in g

a s s o c ia t e d w ith o p e r a tin g s h r im p f a r m s a n d c o s ts

is a b so rb e d b y th e d o m e s tic m a rk e t.
P r o d u c tio n h a s d e c lin e d in re ce n t y e a rs . In 1 9 8 9

attributed to lo ss o f m a n g ro ve reso u rce , s c a rcity co sts
and co m p e n sa tio n costs.

a n d 1 9 9 0 , o n l y 6 4 , 0 0 0 a n d 6 9 ,0 0 0 t o f s h r im p ,

T h e m o d e l co n sists o f the o b je ctiv e fu n c tio n , the

re s p e c tiv e ly , w e re p ro d u c e d b y the a q u a c u ltu r e se cto r;

constraints and the te ch n ica l co e fficie n ts. T h e m ath e m a­

6 4 % o f to ta l p ro d u c tio n is a c c o u n te d f o r b y the s e m i­

tica l fo rm u latio n o f these co m p o n e n ts are d isc u s se d and

in t e n s iv e f a r m s a n d th e r e m a in d e r is p r o d u c e d b y

su m m a rize d as a representative tab le au (F ig . 4 ).
T h e o b je ctive fu n ctio n co n sists o f d e c is io n v a ria b le s

e x te n s iv e fa rm s .
T o d a te , the m o s t c r it ic a l fa c to r that a ffe c ts the

w h ic h affect the m a x im iz a tio n o b je ctiv e eith er p o sitiv e ly

v i a b i l i t y o f s h r im p c u lt u r e a s a w h o le , a n d th e

or n e g a tiv e ly d e p e n d in g on the v a lu e a n d sig n o f the

h a tc h e rie s, in p a r tic u la r, is the a v a ila b ilit y o f n a tu ra l

co e fficie n t and on the m a g n itu d e o f the d e cis io n va ria b le .

la rv a e fo r s to c k in g in g r o w -o u t p o n d s a n d fo r b re e d in g

T h e d e c is io n v a r ia b le s in o u r o b je c t iv e fu n c t io n are

in h a tc h e rie s. In 1 9 8 8 , fo r e x a m p le , th e a q u a c u ltu re

in flue n ce d b y tw o broad develo pm en t op tions, co n versio n

se cto r u t iliz e d a to ta l o f 9 1 0 9 la rv a e , 7 2 % o f w h ic h

and su stain ab le e xp lo itatio n , an d th e ir re sp e ctiv e costs

w a s p r o v id e d b y th e a r tis a n a l f is h e r y . A r e c o r d o f

and benefits.

o p e r a t io n a l s h r im p f a r m s in
6 1 ,0 0 0

19 8 8 ra n g e d fro m

h a to 1 2 3 ,0 0 0 h a , re sp e ctiv e ly . In G u a y a s , w h ere

A g e n e ra l fo rm u la tio n is :

there are a to ta l o f 8 8 ,0 0 0 h a , r o u g h ly 4 8 ,0 0 0 h a or
5 3 % is o p e ra tio n a l ( M e lt z o f f an d L i P u m a 1 9 8 6 ) .

M axZ = I

N B s+ 1 N B m

23

w h e re N B S is the n e t b e n e fit a s s o c ia te d w ith sh rim p

co e fficie n ts o f th e o b je c tiv e fu n c tio n a n d a s su m e v a lu e s

c u ltu r e a n d N B .M is th e n et b e n e fit a s s o c ia te d w ith
.

p e rta in in g to co sts o r p ric e s .
T h e s u b in d ic e s re p re se n t:

su s ta in a b le d e v e lo p m e n t o f the m a n g ro v e .

1)

a

=

C

T h e m a th e m a tic a l fo rm u la tio n o f the L P m o d e l

=

la n d u s e , a = { C , M } ;
area d e vo te d to co n stru ctio n o f sh rim p
p o n d s ; an d

is :
M =
t

u

v

w

1 XXIIXXX

MaxZ-

a

b

c

a r e a d e v o t e d to c o n s e r v a t i o n o f

b

=

u s e o f re s o u rc e s , b = { G , S , F , F V } ;

G

=

r e s o u rc e s u s e d fo r th e p ro d u c tio n o f

m a n g ro v e , s u s ta in a b le e x p lo ita tio n .

y

■^■abcA j N klmn

^ abc A jN k]nm

2)

A ¡=1 N k = l 1=1 m = l n = l

g o o d s;
S

t

U

V

W

y

S

=

r e s o u r c e s u s e d f o r th e d e liv e r y o f

F

SISEl As= l N s l lsl ms l nsl ^ a b c iA jN kimn * f-a b c iA ¡N
a b c i=
j
k= =
= =

=

re so u rce s u se d fo r the m a in te n a n c e o f

j A klmn
N

s e r v ic e s ;
e c o lo g ic a l f u n c tio n s ; a n d

T h e p r in c ip a l s u b in d ic e s d e f in e th e v a r ia b le

FV=

a c c o r d in g to the o p tio n o f c o n s e rv a tio n o r c o n v e rs io n
to s h r im p fa rm s , the a re a o r z o n e o f e x p lo ita tio n , typ e
o f u se o f the re so u rce a n d e co s y s te m b a se d o n its so u rce
o f v a lu e , the p ro d u c tiv e secto r, le v e l o f c o n v e rs io n ,
te c h n o lo g y a p p lie d , re so u rce s u s e d a n d f in a l p ro d u cts.
T h e n o m e n c la tu r e ad o p ted fo r d e c is io n v a r ia b le s
h a s th e fo rm :

re s o u rc e s d e v o te d fo r fu tu re u se ,
e x iste n c e v a lu e , a n d o th e r v a lu e s not
p r e v io u s ly c o n sid e re d .

3)

c

=

p ro d u c tiv e se cto r; c = { F , P, A } ;

F

=

fo re stry ;

P

=

fis h e ry ; an d

A

=

a q u a c u ltu re .

N o te that the s u b in d e x c , fo r the a q u a c u ltu re sector,
is n o t w r it t e n ; in s t e a d is a s s u m e d i m p l i c i t in a ll

X

abciA .N ,,
j

P

k lm n

abciA N ,,
j

k lm n

*

and

c

abciA N ,
j

k lm n

r e f e r to th e

*The typical variables in the model start with the letter X and refer to
quantities (e.g., hectarage, num ber of postlarvae, liters o f tannin). Cases
where the variable begins w ith a letter other than X represent situations
where such variable is a com ponent o f another or a percentage o f another;
these variables take on a value between 0 and 1.

24

F o r the forestry sector, it w a s a ssu m e d that Avicennia

a c t i v i t i e s c o n c e r n i n g s h r im p f a r m i n g , o r w h e r e

is the o n ly sp e cie s extracted fro m A r e a 1 a n d fro m A re a

s u b in d e x a = c .
4)

i

=

p ro c e s s in g a c t iv ity , i = { 1

2 , the red m an gro ve. T h e fin a l products are fire w o o d fro m

s}

F o r th e p r o d u c t iv e s e c to r, th e n u m b e r in g o f
a c t iv it ie s is b a s e d o n th e c h r o n o lo g y : e x t r a c t io n ,

Avicennia

In th e fis h e ry , the f in a l p ro d u c ts in c lu d e m o llu s c s ,

tran sp o rt, p ro c e s s in g a n d sa le s.
5)

A

=

trees (F ), p ile s fro m red m a n g ro ve trees (P ),

and tan n in fro m red m a n g ro ve trees (T ).
c r a b s , s h r im p f r y , a d u lt s h r im p s a n d f is h . T h e s e

a re a w h e re a c t iv it y i o c c u r s

T h e A . ’ s are the d iffe re n t z o n e s o f th e m a n g ro v e

p r o d u c t s , a s d e f in e d , a s s u m e n o n e e d f o r fu r th e r

a s o u t lin e d b e lo w . T h e d e lin e a t io n s a re b a s e d o n

p ro c e s s in g . W e a s s u m e a c e rta in p e rce n ta g e lo s s fo r

d iffe re n t e c o lo g ic a l fu n c tio n s .

c le a n in g , fo r e x a m p le , in th e c a s e o f h e a d le ss sh rim p s.

Z o n e A : o p e n se a s, w ith h ig h s a lin e c o n ce n tra tio n
Z o n e B : sw a m p s a n d e stu a rie s w h e re s a lin it y is

Constraints

in te rm e d ia te
C o n s tra in ts in c lu d e re so u rce co n stra in ts a n d others

Z o n e C : c o a s t a l f r in g e s , f r e q u e n t ly in u n d a t e d ,

r e la t e d to lin e a r p r o g r a m m in g , in c lu d in g b a la n c e

d o m in a n t s p e c ie s is th e re d m a n g ro v e
Z o n e D : in te rio r z o n e o f th e m a n g ro v e w h ic h is

e q u a t io n s , c o n v e x e q u a t io n s a n d c o u n t e r s . T h e

in u n d a t e d le s s f r e q u e n t ly th a n Z o n e C , d o m in a n t

c o n stra in ts are fo rm u la te d as e q u a litie s o r in e q u a litie s

sp e c ie s are b la c k m a n g ro v e a n d w h ite m a n g ro v e
Z o n e E : sa lt fla ts, ra r e ly in u n d a te d a n d n o e x is tin g

in w h ic h the r ig h t-h a n d sid e ( R H S ) d e te rm in e s the lim it.
T h e c o e f f ic ie n t s a r e r e f e r r e d to a s in p u t -o u t p u t
c o e ffic ie n ts o r t e c h n ic a l c o e ffic ie n ts a n d re p re se n t the

ve g e ta tio n
Z o n e F : h ig h e r /s lo p in g g ro u n d s, n e v e r in u n d a te d ,

v a r ia b le .

g e n e r a lly u s e d b y a g ric u ltu re

6) N

-

a m o u n t o f e a c h re s o u rc e r e q u ire d b y e a c h d e c is io n

le v e l o f c o n v e rs io n o f m a n g ro v e

T h e re le v a n t re so u rce co n s tra in ts are:

a re a , k = { 1 ,..4 } (se e T a b le 4 )

1) Land

l,m

=

le v e l o f te c h n o lo g y (T a b le 5 )

1

=

{ E , I } , m = { 1 . . . 4 ) , m is s to c k in g

E

=

e x te n s iv e c u ltu re s y s te m

I

=

s e m i-in t e n s iv e c u ltu re sy s te m

n

=

n a tu ra l re s o u rc e / f in a l p ro d u ct

d e n s ity

7)

? ? £ n 5 M

( X ^ i A jNMm+x c . , AjNk, J  = A j

fo r a ll typ e s o f la n d a re a j = ( 1 ....4 )

Table 4. A ssum ed conversion levels for m angrove zones C, D, and C and
D, in Guayas, Ecuador, in 105ha.
Conversion
level(k)

Zone
CD
10
20
30
60

10
30
60
120

10

20
30
65

Table 5. A ssum ed levels o f stocking density and effort for forestry and aquaculture corresponding to various
levels o f technology.
Stocking density
(m)

Aquaculture
Extensive
Semi-Intensive
(P L IO ’ ha )

Forestry
Area 1
A rea 2
( T r e e s h a y e a r 1
)

m= 1

30

70

60

28

m=2

40

90

80

40

m= 3

50

110

75

35

25

M angrove conversion

Sustainable exploitation

Costs

M ax T EV
Land

Construction

O perating

H arvesting

B enefits
Sales

Land

Costs
(Forestry)
E xploitation
Processing

Fishing
E ffort

O bjective function
coefficients

XciAj

X ciAjNkL

CiNkl

X CiNkl

XciAjNkN

M iAjNk

XMiAjNkl

X MjN

^MiAjN

Decision
variables

land
area

area converted
to shrim p farms

area converted
to shrim p farms
w ith references
to technology

quantity o f
shrimp
harvested

quantity o f
shrimp
sold

land
area

forest a rea
exploited

quantity o f
trees felled

Fishing effort
per z one and
per species

B enefits
Sales

RHS

^MiN

quantity o f
fishery and
forestry
products
sold

c = A j
=La

=l f
 =L P
 =PP
 =PF
 =PS
=Qf
=Q p

=F
=k l
=KS

 =0
=1
 =0

il

il

I
I

m angrove area from zones 1,...6
labor, aquaculture sector
labor, forestry sector
labor, fishery sector
p lan t capacity, packaging
p lan t capacity, freezing

li

=
=
=
=
=
=

il

Aj
La
Lf
LP
Pp
PF

il

B alance equations
C onvex equations
C ounters
plant c apacity, saw m ill
dem and, forestry products
dem and, fishery products
fish ing effort
capital, sm all-scale
capital, large-scale

Fig. 4. The LP tableau for mangrove utilization in Guayas, Ecuador.
R

2 ) M a x im u m c a r r y in g c a p a c it y o f fo re st, g iv e n

d e n s ity o f r e s o u rc e o r sp e c ie s n,

PAj Nklmn

e x is t in g m a n g r o v e a re a o r le v e l o f c o n v e r s io n a n d

fo r ty p e o f la n d A , c o n v e r s io n

m a x im u m b io m a s s b a se d o n le v e l o f effort

le v e l N k, fo r le v e l o f te c h n o lo g y
1 a n d e ffo rt m

X x (x
11m=A
=

R

M B F , A j N klmn

F A j N kl mn Y .

*A

4 ) P o s tla rv a e

t

R c a .N,

*A:

n , f o r t y p e o f c o n v e r s io n N ,

u

v

w

y

X

X

X

X

X x,

CPL

the m a x im u m b io m a s s o f sp e cie s

=

A j= 1 N k = ll= t m= l„ ? iXcBClAJNkl™  = P L M (A j ’N K) + C PL

g iv e n b y le v e l o f te ch n o lo g y 1 an d
e ffort le v e l m

P L M (A ., N k)

R

FA jNklmn

c a p a c it y o f h a tc h e rie s
a v a ila b ilit y o f se e d s f r o m the w ild

is th e d e n s it y o f r e s o u r c e o r
=

a s a fu n c t io n o f a re a a n d le v e l o f

s p e c ie s n , p e r ty p e o f m a n g ro v e

Y*

c o n v e rs io n

z o n e A , g iv e n c o n v e r s io n le v e l
N k, a n d le v e l o f te c h n o lo g y 1 a n d

5) Labor

e ffort le v e l m
s

3 ) M a x im u m c a rry in g ca p a city o f the fish ery, g iv e n
e x is t in g m a n g r o v e a re a o r le v e l o f c o n v e r s io n a n d

v

w

y

X X X I

X MBC

i=l 1=1 m =l n=l

* R cinY*  = M M O c
J

m a x im u m b io m a ss b ase d o n a p p lie d effort in the fish e ry
MMOc
V

W

X

X

1=1 m = l

X M B P A j N ^ Y *  = R P A :N
jNklm n*A

Rein

=

la b o r a v a ila b le f o r se cto r c

= c o e f f ic ie n t o f p r o d u c t iv it y o f
a c t iv it y I

j

6)

M a x im u m e ffo rt p e r p r o d u c t iv e se cto r, i.e ,
m a c h in e ry , n u m b e r o f n e ts, b o a ts a v a ila b le

R

P A iN klmn*A j

=

m a x im u m b io m a s s o f sp e c ie s n,
fo r le v e l o f c o n v e r s io n N , , a n d
k’

le v e l o f te c h n o lo g y 1 a n d e ffo rt m

v

w

y

X X X
1=1 m=l n=l

X m bq

* R cinY*  = M C E c

26

MCE

m a x im u m effort fo r se cto r c . N u m b e r

a b le to s im u la t e th e r e s o u rc e f lo w to f in a l p ro d u c t,

o f m a c h in e s , n e ts, b oats,

C

p a s s in g a ll stages a n d u n d e rg o in g a n d c a p tu r in g lo sse s

e x t r a c t io n

R c llm n
„

ra te

( p r o b a b ilit y

of

a n d w a stag e to th e e n v iro n m e n t.

ca p tu re ), p e r e ffort a p p lie d , p e r le v e l

T h e e q u a tio n c a n b e e x p re s s e d as:

o f te c h n o lo g y a p p lie d
7)

X aBCiA jN klmn * R aBCilm nY *

M a x im u m p ro c e s s in g c a p a c it y p e r p ro d u c tiv e

•X.

aBCa+lANk*1™

se cto r
R aBClmnY*

=

p e rce n ta g e u sa g e o f re so u rce
b e tw e e n s u c c e s s iv e a c t iv it ie s ,

v

w

y

X

I

I x

MBC2lm n * R c2nY* 

i.e ., i + 1 .

^ c 2n

C o u n te r s h a v e a s im ila r p u rp o se e x c e p t th at these

1=1 m = l n = l

are u s e d w h e n d e c is io n v a r ia b le s are b ro k e n d o w n in to
R

=

C 2 lmn

c o e ff ic ie n t o r rate o f p ro d u c tio n p er

se v e ra l c o m p o n e n ts , e .g ., h e cta ra g e , a n d d o n o t refer
to p r o d u c t t r a n s f o r m a t io n . C o n v e x e q u a t io n s a re

ty p e o f te c h n o lo g y m u t iliz e d

in c lu d e d to a s s u r e c o m p lia n c e w ith s e g m e n ta tio n

CPr

=

m a x im u m c a p a c ity o f p la n t, se cto r
c f o r p ro d u ct lin e n.

d e fin e d b y p ie c e w is e lin e a riz a tio n u s e d in in co rp o ra tin g
n o n lin e a r fu n c tio n s .
L a s t ly , w e a ls o

in c lu d e th e n o n n e g a t iv it y

co n stra in ts w ith re fe re n ce to o u r d e c is io n v a r ia b le s .
8 ) M a x im u m

c a p a c it y o f c o ld

sto ra g e p er

p ro d u c tiv e se cto r
v

w

X

X

X X m bc

Values o f the Constants

y

* R ClnY*cpc,n

T h e c o n s t a n t s in c lu d e th e c o e f f ic ie n t s o f the

1=1 m = l n= l

d e c is io n v a r ia b le s in th e o b je c t iv e f u n c t io n , the
=

xvc 3lm n

v o lu m e o c c u p ie d in tran sp o rt se cto r
m , p e r u n it o f p ro d u c t n tran sp o rte d

=

C P c 3n

m a x im u m c a p a c it y o f w a r e h o u s e ,
fre e z e rs in se cto r c fo r p ro d u c t lin e n

t e c h n ic a l c o e ffic ie n ts , a n d th e r ig h t-h a n d s id e ( R H S )
e le m e n ts. T h e firs t e le m e n t d e fin e s the c o lu m n s o f the
L P ta b le a u w h ic h i s a l 4 1 x l l 5

m a trix w h e re a s the

la s t tw o m a k e u p the ro w s o f the ta b le a u . T h e e le m e n ts
o f th e L P t a b le a u a re d e s c r ib e d in m o re d e t a il in
A p p e n d ix 1 .

9 ) C a p it a l a v a ila b ilit y fo r s m a ll a n d la rg e in v e s to rs
in the a q u a c u ltu r e se cto r

t

I

u

w

y

I

I

I x

COEFFICIENTS O F TH E O BJEC TIV E FUNCTION

CBC jA jN k lnm

*RrA jN k lmnY*
* C

= K C j
^
“ ,

A := lN k =lm=ln=l

T h e c o e ffic ie n ts o f the o b je c tiv e fu n c tio n re fle ct
the c o n trib u tio n o f a p a r tic u la r a c t iv it y to the v a lu e o f
th e o b je c t iv e f u n c t io n ( V O F ) . T h u s , c o s ts te n d to
d e p re ss V O F w h ile re v e n u e s in c r e a s e it.

R ca i

K

ci

= initial investment (infrastructure and
other operating costs) for shrimp farms
located in area A operating under
system 1
=

am ount

of

c r e d it

a v a ila b le

fo r

investments in technology system 1.

T h e c o s t s c o n s i d e r e d i n c l u d e t h o s e o f la n d
c o n v e r s io n ( c o n s t r u c t io n o f s h r im p t a n k s ) , s h r im p
fr y , a n d e x t r a c t io n a n d p r o c e s s in g c o s t f o r fo r e s tr y
a n d f is h in g . T h e p r ic e s r e fe r to th o s e o f f in is h e d
p ro d u cts

w h ic h

in c lu d e

s h r im p s

fro m

th e

a q u a c u lt u r e s e c to r ( w h o le a n d h e a d le s s ) ; f r o m the
fo r e s tr y se cto r, f ir e w o o d , p o s ts a n d t a n n in ; a n d fr o m

Balance Equations, Counters and Convex Sets

th e

f is h e r y

se cto r,

m o llu s c s ,

crab s,

s h r im p

p o s tla r v a e , a d u lt s h r im p s a n d f is h . P r ic e s o f f in is h e d
B a la n c e e q u a t io n s w e re set u p f o r s u c c e s s iv e
a c t iv itie s in the p ro d u c tio n p ro ce ss. W it h th ese w e are

p r o d u c ts a n d th a t o f p r o d u c t io n in p u t s a re b a s e d on
c u r r e n t m a rk e t p r ic e s .

27

C o n s t r u c t io n

co sts ran g e fro m

U S $ 10 0

to

U S $ 1 0 ,4 0 0 -h a 1 d e p e n d in g o n th e m a n g ro v e z o n e a n d

Table 6. Average costs and m arket prices o f products derived from the
m angrove of Guayas, Ecuador.

a re a l c o v e r a g e . D e v e lo p m e n t co sts are h ig h e r in salt
fla ts a n d s lo p in g g ro u n d s th a n in Z o n e s A to D . F o r
e x a m p le , c o n v e rs io n co sts in Z o n e A fo r a 1 0 ,0 0 0 h a
fa rm co sts U S $ 5 0 0 -h a  as c o m p a re d to 6 0 ,0 0 0 h a in

C o n s t r u c t io n

co sts

o f e x t e n s iv e

farm s

whole
headless
clams
crabs
postlarvae
shrimps
fish

1,000
1,000
10,000
5,000
5,000

firewood
posts
tannin

U S $ 8 ,4 9 0 -h a 1 w h ile that o f s e m i-in t e n s iv e fa rm s is
U S $ 3 2 , 4 6 0 - h a  1 w h ic h r e m a in s c o n s t a n t d e s p it e
d iffe re n t s to c k in g r e g im e s . A n im p o rta n t d e te rm in a n t

5
3
5

U S $ t‘

Forestry

o f s to c k in g is the c o s t o f p o s tla rv a e ( P L ) a n d re la te d
o p e ra tio n a l c o s ts a s s o c ia te d w ith fe e d in g a n d a ir a n d
w a te r

m a n a g e m e n t.

Th ese

co sts

ran g e

7,500
6,700

n.a.
n.a.

Fishery

is

M arket price

u s$ t-‘

A quaculture

Z o n e E w h ic h co sts U S $ 9 , 1 5 0 - h a 1. C o s ts are g e n e rally
h ig h e r fo r the sam e le v e l o f areal c o n v e rs io n in Z o n e E .

E xploitation/
processing costs1

Commodities

2,000
4,000
8,600
6,700
2,500
U S $m -’

50
10
150

fro m

U S $ 8 .6 -t h o u s a n d  1 P L ( e x t e n s iv e , 1 0 , 0 0 0 h a ) to

‘For foresty products.
Source: FPVM (1987); FEDECAM (1989).

U S $ 1 6 . 9 - t h o u s a n d  1 P L ( e x t e n s iv e , 1 2 5 , 0 0 0 h a ) .
H a r v e s t in g c o st is U S $ 6 0 0 - t 1 a n d is u n if o r m fo r a ll
ty p e s o f o p e ra tio n s a n d a re a l c o v e ra g e .
S u s t a in a b le e x p lo ita tio n o f the m a n g ro v e fo re st
in v o lv e s c o sts o f e x tra ctio n a n d p ro c e s s in g . E x t ra c t io n
co sts fo r

Avicennia

in Z o n e D w ith a re a o f 1 0 ,0 0 0 h a

ra n g e s f r o m U S $ 3 0 0 - h a 1 to 7 0 0 -h a 1 w h ile f o r re d
m a n g ro v e in Z o n e C , sa m e a re a l co v e ra g e , ran g e s fro m
U S $ 2 2 5 - h a  to 5 2 5 - h a 1.
In the fis h e ry , c o lle c t io n o f c la m s a n d c ra b s o c c u rs
in Z o n e C ; that o f sh r im p fry in Z o n e B ; an d fo r a d u lt
s h r im p s a n d f is h , in Z o n e A , o r op en seas. C o lle c t io n
co sts fo r th e se p ro d u c ts as w e ll as m a rk e t p r ic e s o f
m a n g r o v e -d e r iv e d c o m m o d itie s are sh o w n in T a b le 6.

T o ta l

net

b e n e f it s

th a t

w o u ld

accru e

to

s im u lta n e o u s c o n v e rs io n a n d e x p lo ita tio n o f G u a y a s
m a n g ro v e s a m o u n t to U S $ 1 7 4 - 1 0 6- y e a r 1. O f the total,
U S $ 1 0 6 - 1 0 6 is a cco u n te d fo r b y su sta in a b le e x p lo ita tio n
o f the m a n g ro v e : U S $ 1 8 - 1 0 6 fro m the fo re stry secto r,
U S $ 8 8 - 1 0 6 fr o m the fis h e ry , a n d U S $ 6 8 - 1 0 6 fro m the
a q u a c u ltu re secto r, in w h ic h U S $ 2 . 5 - 1 0 6 re p re se n ts the
co sts o f tr a n sfo rm in g the m a n g ro v e .
T h e a b o v e e stim a te s are b a s e d on th e s u s ta in a b le
e x p lo ita tio n o f 1 1 9 . 5 - 1 0 3 h a o f m a n g ro v e s d istrib u te d
in Z o n e s C ( 4 6 % ) a n d D ( 5 4 % ) a n d th e c o n v e r s io n o f
5 . 5 - 1 0 3 h a p re fe ra b ly site d in Z o n e C b e c a u s e o f the
lo w e r c o s t s ( c o n s t r u c t io n a n d o p p o r t u n it y c o s t s )

TECH N IC A L CO EFFICIENTS AND RHS VALUES

in cu rre d . O p t im a l a re a o f sh r im p fa r m is 4 9 - 1 0 3 h a w ith
a re al d istrib u tio n as fo llo w s : m a n g ro v e s, 1 1 % ; salt flats,

In the c a s e o f a re so u rce co n stra in t, the te c h n ic a l

6 4 % ; a n d the re m a in in g 2 5 % , s lo p in g g ro u n d s. T h e

c o e ffic ie n ts re p re se n t the co n trib u tio n o f a p a rtic u la r

d is t r ib u t io n o f s h r im p fa r m s a c c o r d in g to m o d e o f

re so u rce , i.e ., la b o r, to a p a r tic u la r d e c is io n v a r ia b le

o p e ra tio n is 3 7 - 1 0 3 h a f o r e x t e n s iv e f a r m s , 8 4 % o f

in c lu d e d in the m a x im a n d .

w h ic h are lo c a te d in sa lt fla ts , a n d 1 3 - 1 0 3 h a fo r s e m i­

R ig h t h a n d s id e v a lu e s d e fin e the lim it s o f the

in t e n s iv e f a r m s , a l l lo c a t e d in s lo p in g g r o u n d s .

restrictio n s e n u m era te d a b o v e or, in the ca se o f re so u rce

O p e ra tio n s in m a n g ro v e a re a s are e x te n s iv e . T h o u g h

c o n stra in ts, th e s u p p ly o r a v a ila b ilit y o f the re so u rce .

le s s in a re a , s e m i-in t e n s iv e f a r m s w o u ld p r o v id e
a p p ro x im a te ly 4 5 m illio n t o f s h r im p s (h e a d s -o n ) or

Results and Discussion

6 4 % o f total p ro d u ctio n .
C o m p a r in g the p a ra m e te r e stim a te s w ith a c tu a l

Solutions to the Primal Problem

v a lu e s s h o w s that m a n g ro v e c o n v e r s io n h a s c le a r ly
g o n e b e y o n d s u sta in a b le le v e ls , i.e ., b y a b o u t 2 0 0 % .

T h e so lu tio n s to the p rim a l p ro b le m are p ro v id e d in

T h e estim ate s furth erm o re sh o w the p re fe re n ce o f sitin g

T a b le 7. T h e s e in c lu d e the o p tim a l va lu e o f the o b je ctive

p o n d s in m a n g ro v e s rath e r than in sa lt fla ts a n d s lo p in g

fu n ctio n a n d the v a lu e s o f the d e c is io n variab le s.

g ro u n d s w h ic h are b oth u n d e r u tiliz e d .

28
Table 7. Param eter estim ates o f the primal LP problem for three alternative uses o f mangroves in Guayas, Ecuador.
Parameters
Option: Aquaculture
Extensive shrim p farms
Sem i-intensive shrimp farms
Shrim p farms, m angrove area 1
Shrim p farms, m angrove area 2
Total area o f shrim p farms, mangrove
Extensive shrim p farms, salt flats
S em i-intensive shrimp farms, salt flats
Total area o f shrim p farms, salt flats
Sem i-intensive shrimp farms, sloping ground
Total area o f shrim p farms, sloping ground
Total extensive shrim p farms
Total sem i-intensive shrimp farms
Total shrim p farms
Shrim p fry sourced from the wild
Shrim p fry sourced from labs
Total fry used
Production, extensive systems
Production, sem i-intensive systems
Total shrim p production (heads-on)
Sales o f shrimp, heads-on
Sales o f shrim p, headless
Total costs
G ross incom e
Net income
Option: sustainable exploitation
M angrove area in Zone 1
M angrove area in Z one 2
Total m angrove area
Sector: forestry
Avicennia felled
R hizophora felled
Sale o f firewood
Sale o f posts
Sale o f tannin
Total costs
G ross incom e
Net incom e
Sector: fishery
Sale o f m olluscs
Sale o f crabs
Sale o f fry
Sale o f shrim ps, heads-on
Sale o f fish
Total costs
Gross incom e
Net incom e
Net benefits, service and function
Total cost o f conservation
Net incom e o f conservation
Net benefit
Total net benefit

Unit

ha-103

PL-109

M O3

US$ lO ^ y ear1

M odel

5.5
0
5.5
0
5.5
31.2
0
31.2
12.6
12.6
36.7
12.6
49.3
3.9
1
4.9
16.4
28.9
45.3
11
19.4
144.4
212
67.7

ha-103
“
“

54.5
65
119.5

cu.m 103
“
“

488.6
510.5
390.9
367.6
35.7
10.2
28.6
18.4

1.10s
US$ 103-y ear‘
“
“

Actual*

-

9.4-22
-

13-25
-

17-36
-

48-74.4
4.2
1.5
5.7
15.8
28.2
44.1
-

212
-

-

116.1
-

4.4

1.0-2.4
600
4.3-8.6
7.2

3.4

M O3
bundles 103
PL-103
t-103

-

1.5
2.7
5.6

11

-

99.4
87.6
0

-

22

US$ lO ^ y ear1

-

128
106
173.7

110**

-

-

*Based on 66% o f total figures for Ecuador given that Guayas accounts for same % mangrove.
**Only for capture PL.

Solutions to the Dual Problem

in te rp re tatio n as th e rate o f c h a n g e in th e V O F g iv e n a
c o r r e s p o n d in g c h a n g e in r e s o u r c e a v a i l a b i li t y h a s

T h e d u a l fo r m u la tio n o f the lin e a r p ro g ra m m in g

im m e n s e e c o n o m ic im p lic a t io n s : th e d u a l v a lu e s

p ro b le m r e s u lte d in th e sa m e le v e l o f n et b e n e fits , i.e .,

p ro v id e m e a su re s o f o p p o rtu n ity co sts fo r in te rm e d ia te

v a lu e o f the o b je c tiv e fu n c tio n ( V O F ) . Its m a th e m a tic a l

g o o d s a n d s e r v ic e s su c h as la b o r w h ile in th e c a s e o f

29

f in a l g o o d s , d u a l v a lu e s r e p r e s e n t th e c o n s u m e r ’ s
w illin g n e s s to p a y (T a b le 8).

Table 8. Param eter estim ates o f the dual LP problem for the m angroves of
Guayas, Ecuador.

In the c a s e o f la n d , the d u a l v a lu e is the v a lu e o f

Param eter

Unit

Dual value

fo re g o n e p ro d u c tio n i f the la n d w ere u s e d a lte rn a tiv e ly .
T h u s , the V O F is e stim a te d to in c r e a s e b y U S $ 3 4 4 a n d
U S $ 2 9 4 fo r e v e r y h e cta re co n v e rte d in to s h rim p p o n d s
in Z o n e s C

a n d D , r e s p e c t iv e ly . T h e e c o l o g i c a l

fu n c tio n s p e rfo rm e d in Z o n e C re su lte d in a h ig h e r
s h a d o w p r ic e th a n Z o n e D . R e s u lt s sh o w th at e a ch
a d d itio n a l h e cta re o f s h r im p fa r m in Z o n e E , sa lt fla ts,
w o u ld a d d an a v e ra g e o f U S $ 6 7 7 to total n et b e n e fits
n o tw ith s ta n d in g th e fa c t that it h a s a lre a d y re a ch e d
s u b o p tim u m le v e ls . T h i s is d u e to th e fa c t that m o re
th a n 9 0 % o f s h r im p p ro d u c tio n is d e r iv e d fro m th is
zo n e.
T h e d u a l v a lu e s e stim a te d fo r fo re stry a n d fis h e ry
p ro d u cts a p p ro x im a te th e ir m a rk e t p ric e s . T h e h ig h e r

M angrove area, Zone 3
M angrove area, Zone 4
Shrimps farms, Zone 5
A vicennia
Rhizophora
Firewood
Posts
Tannin
M olluscs
Crab
Shrimp fry
Shrimps
Fish
Fry sourced from wild
Fry destined for hatcheries
Capital, extensive system
Capital, intensive system

344
294
675
35
15
50
6
100
2,000
4,000
9,800
6,700
2,500
1.72
0
2
450

U S S h a y e a r 1

“
“

U S $ m 3

“
“
“
“
uss-r1
“
“
“
“

USS-10-3

“

US$-106-year

sh a d o w p r ic e s a s s ig n e d to fis h e r y p ro d u cts, e s p e c ia lly
that o f sh r im p fry, e m p h a s iz e s the ro le o f the m a n g ro v e
in the su ste n a n c e o f c o a s ta l m a rin e re so u rce s . A n o th e r
p o s s ib le ju s t if ic a t io n is that fo re stry p ro d u cts c a n be
so u rce d

fro m

n o n m an g ro ve

fo re sts

in c lu d in g

d ip t e r o c a r p a n d h a r d w o o d fo r e s ts ; th u s , th e lo w e r
sh a d o w p ric e .
F r y o b ta in e d fro m the w ild h a v e a p o s itiv e sh a d o w
p ric e b u t that o b ta in e d fro m the h a tch e rie s h a v e a ze ro
s h a d o w p r ic e in d ic a t in g that th e re so u rce is n o n s c a rc e ,
i.e ., th e d e m a n d is le s s th a n the in s ta lle d c a p a c ity .
R e s u lts furth e r in d ic a te that p a c k a g in g a n d fre e zin g
c a p a c ity o f the a q u a c u ltu re se cto r as w e ll as s a w m illin g
c a p a c it y in fo r e s t r y a re in e x c e s s o f d e m a n d , i.e .,
sh a d o w p r ic e is z e ro . L ik e w is e , there is a su rp lu s o f
a v a ila b le la b o r in a q u a c u ltu re , fo re stry an d the a rtisa n a l
f is h e r y r e la t iv e to th e e x p lo it a b le r e s o u r c e . T h u s ,
in c r e a s in g la b o r s u p p ly w ill n o t re s u lt in a n y ch a n g e in
the o p tim a l b e n e fits p ro v id e d b y m a n g ro v e c o n v e rs io n
a n d /o r s u s ta in a b le e x p lo ita tio n .

2)

c h a n g e s in th e s u p p ly o f n a t u r a l f r y a s a

fu n c tio n o f E l N iñ o o c c u r r e n c e s ;
3)

a v a ila b ilit y o f c a p it a l f o r in v e s t m e n t in the

a q u a c u ltu re sector. A n in c re a s e in in v e s tm e n t c a n be
in terp reted as a te c h n o lo g ic a l b re a k th ro u g h o r in fu s io n
o f fo re ig n in v e stm e n t.
I n S c e n a r io s 1 a n d 2 , the a re a co n v e rte d to sh rim p
fa r m s in Z o n e C w a s a s s u m e d to in c r e a s e w ith the
a d d itio n a l a re a b e in g re le a s e d fro m Z o n e F (h ig h e r
g r o u n d s ) a n d f r o m the a re a o r ig in a lly in te n d e d fo r
su sta in a b le m a n ag e m e n t. In b oth ca se s, total net b en e fit
is lo w e r t h a n th e b a s e s it u a t io n . I n th e c a s e o f
a q u a c u ltu r e , the d e c lin e in n e t in c o m e is g reate r in
S c e n a r io 2 d u e to the a d d itio n a l a ss u m p tio n o f a d rop
in the su p p ly o f n atural fry. N e t in c o m e fro m the forestry
se cto r d ro p p e d b e ca u se o f a d e cre a s e in e x p lo ita b le
a re a f o r re d m a n g r o v e s , a n d th u s , f ir e w o o d s a le s ,
w h e re a s s a le s o f s h r im p la rv a e a n d o f a d u lt sh rim p
c a u s e d the s lid e in the fis h e r y sector.
In S c e n a r io 3 , the in c re a s e in n a tu r a lly su p p lie d

Sensitivity Analysis

f r y c o m p e n s a te s fo r th e to ta l lo s s o f h a t c h e ry fry,
re s u ltin g in a net in c o m e h ig h e r th an th e b a se situ a tio n .

A s e n s itiv ity a n a ly s is w a s c o n d u c te d to d e te rm in e

N e t in c o m e f r o m th e f is h e r y is lik e w is e im p r o v e d

the e ffe ct o f a lte rin g v ita l p a ra m e te rs o n the n e t b e n e fit

m a in ly th rou gh h ig h e r sa le s o f sh rim p la rv a e . H o w e v e r,

( T a b le 9 ). T h e b a s e s c e n a r io re p re se n ts th e p r im a l

a n in c re a s e in n a tu ra l f r y w a s n ot sh o w n to im p a c t on

p r o b le m

the s u p p ly o f a d u lt sh rim p an d that o f fin f is h , in gen eral.

w h i l e t h e a d d i t i o n a l s e v e n s c e n a r io s

c o n s id e re d are b a s e d o n th e f o llo w in g :
1)

S ce n a rio s 4 and 5 h a ve a strong co n se rv a tio n ist b ias

r e la x a t io n o f th e r e s tric tio n p e r ta in in g to the n evertheless resulted in net in co m e s h ig h e r than the
but

lo c a t io n o f f is h f a r m s , p a r t ic u la r ly , to a s s e s s the

base situation. S ce n a rio s 4 and 5 assu m e ch a n g e s in the

f e a s ib ilit y o f lo c a t in g in oth e r m a n g ro v e z o n e s ;

sitin g o f sh rim p p on d s in Z o n e s E a n d F and w ith no

30
Table 9. Sensitivity analysis o f primal problem param eter for five scenarios and effects on total net benefits.
Scenarios
Base

1

2

3

4

5

Aquaculture sector
Z one E conversion (ha-1O’)
Z one F conversion (ha-10’)
Shrim p farm s in salt flats (ha-103)
Shrim p farm s in hilly grounds (ha-103)
Natural fry (PL-109)
Hatchery fry (PL-109)
Shrim p production head-on (-103)
Net incom e (U S SK P-year1)

5.5
0
31.2
12.6
3.9
1
45.3
67.7

10
0
31.2
7.5
3.9
1
45
62.9

7.6
0
31.2
7.5
2.7
2
44
59.9

5.5
0
31.2
12.6
4.9
0
45.3
69.5

0
0
27.3
0
3.8
2
62.6
103.9

0
0
31.2
6.5
6.1
2
86.6
141.4

54.5
65
390.9
367.6
35.7

50
65
358.4
367.6
35.7

52.4
65
375.5
367.6
35.7

54.5
65
390.9
367.6
35.7

60
65
430.1
367.6
35.7

60
65
430.1
367.6
35.7

18.4

17.3

17.9

18.4

19.7

19.7

1.5
2.7
5.6
4.4
3.4

1.5
2.7
5.6
4.3
3.4
87.2
0
104.4
167.3

4.5
2.7
3.9
4.3
3.4

1.5
2.7

1.5
2.7
5.6
4.5
3.5
88.7
0
107.9
211.7

1.5
2.7

Sustainable exploitation

Zone 3 conservation (ha-103)
Zone 4 conservation (ha-103)
Sales of firewood (m 3-103)
Sales o f posts (mM O3)
Sales o f tannin (m M O3)
Net incom e (U S$106-y earl)

87.6
0
106
173.7

75.1
0
93
152.9

00
oo

F ish ery se cto r
Sales o f m olluscs (t-103)
Sales o f crabs (t-103)
Sales o f larvae (t-103)
Sales o f shrim p, head-off (t-103)
Sales o ffis h (t-103)
Net incom e (U S$10f’-y e a rl)
Net benefit (services, function) (US$106-year)
Net benefit m angrove (US$106-year)
Total net benefit (U S$106-y earl)

4.4
3.4
111.7
0
130.1
199.5

O
O
00

Forestry sector

4.5
3.4
112.2
0
132
273.4

c o n v e rsio n in Z o n e s C an d D w h ic h are m an g ro ve areas.

detrim ent o f the en viro n m e n t w h ich is b e in g v ie w e d as

S c e n a rio 4 resulted in a 2 2 % in cre ase in total net benefit,

being “subservient to im m ediate individual econom ic

the in cre a se b e in g a cco u n te d fo r b y in cre ase d pro d uctio n

objectives”. P o sse s sio n o f sh rim p farm s is, furtherm ore,

o f the a q u acu ltu re sector. S ce n a rio 5 resulted in a 5 7 %

co n sid e re d to b e a status sy m b o l, in the sam e w a y as

in cre a se in total net b e n e fit b e ca u se o f the a d d itio n a l

p o sse ssin g a hacienda. T h e fin a n c ia l sector co m plem ents

a s s u m p tio n o f p e a k p ro d u c tio n o f n a tu ra l fry. B o th

this w ith its p reference for sh ort-term b u sin e sse s (fast

scen a rio s a lso resulted in an in crease in net in co m e from

p a y b a c k p eriod ) w ith lo w start-up as w e ll as operating

the fish e ry sector, fro m sales o f la rv ae and sh rim p s, alb eit

costs (i.e., sh rim p p onds).

to a greater exten t fo r S c e n a r io 5 . T h is co n firm s the

Preference for short-term g ain s, e s p e c ia lly in relation

im p ortant e c o lo g ic a l fu n ctio n s o f m an g ro ve s and their

to co n se rvatio n , can be p e rce ive d as ratio nal g iv e n the

c o m p le x lin k a g e s w ith the entire c y c le o f sh rim p grow th

la ck o f in form atio n , uncertainty and ris k in v o lv e d in lo n g ­

and m aturatio n, w h ic h a lso affects p ro d uctio n both from

term investm ents (in c lu d in g investing in the environm ent).

traw l fish e rie s a n d a q u acu ltu re (M cP a d d e n 1 9 8 5 ; P a u ly

F u r th e rm o re , s u c h b e h a v io r is n o t a d is t in g u is h in g

an d In g le s 19 8 8 ).

characteristic o f sh rim p farm ers in Ecuad o r. W h e n ch o ices

Conclusion

betw een d e ve lo p m en t and co n se rv atio n h a ve to b e m ade,
exp re ssin g the re su ltin g options in n um bers, p referab ly
in cu rre n cy term s, p erm its the d e cisio n m a k e r to assess

In E c u a d o r , th e p h e n o m e n a l g ro w th o f s h r im p

sh o rt-term g a in s vis-à-vis e c o lo g ic a l in te g rity w h ic h

m a ricu ltu re has been ob se rve d b y M e ltz o ff and L iP u m a

m in im iz e s risk , u n certain ty an d a b sen ce o f in form atio n.

( 1 9 8 6 ) to be co n siste n t w ith the n a tio n ’s s o c ia l character

L P is o n e o f s e v e r a l a v a ila b le t e c h n iq u e s that

a n d f in a n c ia l e n v ir o n m e n t . T h e a u th o rs p o in t out a

e n a b le s q u a n tific a tio n o f to ta l b e n e fits a r is in g fro m

te n d e n cy fo r b u sin e ss to v a lu e short-term g ain s to the

sim u ltan e o u s u se o f reso u rce s. T h e L P e x e rcise is u se fu l

in th ree w a y s : 1 ) in d e v e lo p in g th e L P ta b le a u , the
r e s o u rc e s y s te m , its d iffe re n t co m p o n e n ts a n d th e ir
in te rlin k a g e s , is stru ctu re d a n d q u a n tifie d ; 2 ) th ro u g h
th e p r im a l a n d d u a l s o lu t io n , b e n c h m a r k s fo r
d e c is io n m a k e rs are p ro v id e d ; an d 3 ) th rou gh se n s itiv ity
a n a ly s is , a lt e r n a t iv e e n v ir o n m e n t a l a n d e c o n o m ic
sc e n a r io s are sim u la te d . In th is e x e rc is e , w e p ro v e d
the c o m p a t ib ilit y b e tw e e n e c o n o m ic s a n d e c o lo g y b y
s h o w in g that c o n s e rv a tio n is t a p p ro a c h e s to m a n g ro v e
m a n a g e m e n t w o u ld re s u lt in greater n et b e n e fits . M o re
im p o rta n tly , w e h a v e sh o w n h o w the sh o rt-te rm g a in s
o f m a n g ro v e c o n v e r s io n to s h rim p p o n d s c a n b e w ip e d
o u t b y se v e re d e c lin e s in la r v a l p ro d u ctio n , its m o st
c ritic a l input. T h is h as been d one g iv e n the in te rlin kag e s
betw een e c o lo g ic a l param eters sp e cifie d in the o b je c tiv e
fu n c tio n .
O u r a p p ro a c h is a fo rm o f ‘ a d a p tiv e m a n a g e m e n t’
( H o llin g 1 9 7 8 ) , w h ic h e m p h a s iz e s v a r ia b ilit y in tim e
a n d s p a c e b o u n d a rie s as w e ll as u n c e rta in tie s . T h u s ,
w h a t o th ers p e r c e iv e to b e r a tio n a l ap p e ars to b e a c a s e
o f m is in f o r m e d d e c is io n m a k in g . W e h a v e s h o w n
th ro u g h th is e x e r c is e h o w it is p o s s ib le to d e p ic t an
a rra y o f o p tio n s that sp an lo n g -te r m as w e ll as sh o rt­
te r m p la n n in g h o r iz o n s a n d t h u s , m a k e r a t io n a l
d e c is io n s on the b a s is o f p e rfe ct in fo rm a tio n .

R e fe re n ce s
Agüero. M. and E. González. 1991. Una industria millonaria. Ecuador: el
boom cam aronero de Am érica Latina, cultivo, divisas y empleo. [A
m illionaire industry. Ecuador: Latin America shrimp farm ing boom,
c u ltu re , fo re ig n e x c h a n g e and e m p lo y m e n t], A q u a n o tic ia s
Internacional 3( 10 ):3 1-43.
A quacop. 1979. Penaeid reared brood stock: closing the cycle o f P
monodon, P. stylirostris and P. vannamei. Proc. World Maricult. Soc.
10:445-452.
Cintrón, G. and Y. Schaefer. 1983. Introducción a la ecología del manglar.
O ficina R egional de C iencia y Tecnología de la UN ESCO para
A m érica Latina y el Caribe. M ontevideo, Uruguay.
CLIRSEN. 1987. Estudio multitem poral de los manglares, camaroneras y
areas salinas de la costa ecuatoriana mediante información de sensores
remotos. M em oria Técnica. Quito, Ecuador. 35 p.
Cun, M. and C. Marín. 1982. Estudio de los desembarques del camarón
(gen. P enaeus) en el G olfo de G uayaquil (1965-1979). Boletín
Científico y Técnico 5(3). Instituto Nacional de Pesca, Guayaquil,
Ecuador.
Espinoza, F. 1989. Situación actual de la maricultura del camarón en el
Ecuador y estrategias para su desarollo sostenido. M em orias del
S e m in a rio y D o cu m en to T é c n ic o . In stitu to de E stra te g ia s
Agropecuarias. Doc. Tec. No. 21, 213 p.
FEDECAM . 1989. Serie: análisis sectorial. Doc. No. 10. La producción
cam aronera en Ecuador. Octubre, 1989. Eduardo Egas Pena.

FPVM (Fundación Pedro Vicente M aldonado). 1987. Ecuador. Perfil de
sus recursos costeros. PM RC. Guayaquil, Ecuador. 269 p.
FPVM (Fundación Pedro Vicente M aldonado). 1989. Ecuador. Vision
global del desarrollo de la costa. PM RC. G uayaquil, Ecuador. 241 p.
H olling, C.S., Editor. 1978. A daptive environm ental assessm ent and
management. Wiley Interscience, New York.
Homa, R. 1980. Relación suelo m angle, p. 195-214. En Estudio Científico
e Impacto Humano en el E cosistem a de M anglares. M em orias Del
Seminario Organizado Por Unesco, Con el A uspicio Del G obierno
de Colom bia (Cali, 27 de Noviem bre al 10 de D iciem bre de 1978),
Oficina Regional de Ciencia y Tecnología Para A m erica Latina y el
Caribe, M ontevideo, Uruguay.
Horna, R. 1983. Diagnostico del ecosistem a de M anglares Ecuador, p.
321-328. En Trabajos Presentados a la C onferencia Internacional
Sobre Recursos Marinos Del Pacifico, 16-20 M ayo 1983, Vina Del
Mar, Chile.
Lenz-V olland, B. and M . V olland. 1992. D istrib u ció n g eo g ráfic a y
técnicas de la pesca en la C osta E cu ato rian a d u ran te el p eríodo
colonial [G eographic distrib u tio n and gears o f the E cu ad o rian
fisheries during the colonial period], p. 92-113. In M. A güero
(ed.) C ontribuciones para el estu d io de la pesca artesan a l en
A m erica L atina. IC L A R M C onf. Proc. 35, 113 p.
McPadden, C.A. 1985. A brief review o f the Ecuadorian shrim p fishery.
Tec. Inst. Nac. Pesca Ecuador 8(1): 1-68.
Meltzoff, S.K. and E. LiPum a. 1986. The social and political econom y of
coastal zone m anagement: shrim p m ariculture in Ecuador. Coastal
Zone Manage. J. 14(4):349-380.
Pauly, D. and J. Ingles. 1988. The relationship betw een shrim p yields and
in te rtid a l v e g e ta tio n (m a n g ro v e ) a re a s , p. 2 7 7 -2 8 3 . In A.
Yáñez-Arancibia and D. Pauly (eds.) Proceedings o f the IREP/OSLR
W orkshop on the Recruitm ent o f Coastal D em ersal Com m unities,
2 1 -2 5 A p ril 1 986, C a m p e c h e , M e x ic o . IO C (U N E S C O )
Supplementary Papers Workshop Rep. No. 44.
Paw, J.N and T.-E. Chua. 1991. An assessm ent o f the ecological and
economic impact o f m angrove conversion in Southeast Asia, p. 201­
212. In L.M. Chou, T.-E. Chua, H.W. Khoo, P E . Lim , J.N. Paw, G.T.
Silvestre, M.J. Valencia, A.T. W hite and P.K. W ong (eds.) Towards
an integrated management o f tropical coastal resources. ICLARM
Conf. Proc. 22, 455 p.
Rollet, B. 1986. Ordenación integrada de m anglares. Síntesis de Siete
Seminarios Nacionales en A m erica Latina. FO: M ISC/86/4. FAO,
Roma, Italia. 100 p.
Snedaker, S.C. et al. 1988. Ubicación de piscinas cam aroneras y alternativas
de manejo en ecosistemas de manglares en el Ecuador. Proyecto de
Manejo de Recursos Costeros. Serie de Estudios No. 2. Fundación
Pedro Vicente Maldonado. Guayaquil, Ecuador. 86 p.
Solorzano, C. 1989. La industria del cam arón en E cuador. Instituto
Centroamericano de Adm inistración de Empresas INCAE.
Terchunian, A., V. Klemas and A. Segovia. 1986. M angrove m apping in
Ecuador: the impact o f shrimp pond construction. Environ. Manage.
10(3): 345-350.
T w illey, R. 1989. Im pacts o f shrim ps m aricu ltu re p ractices on the
ecology o f coastal ecosystem s in E cuador, p. 91-120. In O lsen
et al. (ed.) A sustainable shrim p m ariculture industry fo r Ecuador.
T e c h n ic a l R e p o rt S e rie s T R -E -6 . I n te r n a tio n a l R e s o u rc e s
M anagem ent P roject, USA.
Velasco, A. 1987. Socioeconomic aspect of mangrove m anagement, p. 67­
73. In State o f the art: mangrove research. Philippine Council for
A g ric u ltu re , F o re stry , and N a tu ra l R e so u rc e s R e se a rc h and
Development, Los Baños, Laguna, Philippines.

Optimization of Economic Benefits
from Fishery and Forestry in Bio-Bio, Chile*

Description o f Study Site
Physical Attributes

IC L A R M -E C L A C C ollaborative
P ro ject on the S o c io eco n o m ic V aluation o f C oastal
Resources in Southw est Latin America, Casilla 179-D,
Santiago, Chile
E d g ard o

A r a n e d a 1,

LOCATION AND TOPOGRAPHY

B i o - B i o is o n e o f C h i l e ’ s th irteen p o lit ic a l and

International Center fo r Living
Aquatic Resources M anagement (ICLARM), MCPO Box
2631, 0718 Makati City, Philippines

a d m in is tra tiv e d istric ts . T h is re g io n co v e rs a total area

A n n a b e lle C ru z-T rin id ad ,

o f 3 6 ,8 2 0 k m 2 a n d c o n s is t s o f 4 9 m u n ic ip a lit ie s
in c lu d in g N u b le , B io - B i o , A r a u c o , T a lc a h u a n o and
C o n c e p c io n , the c a p ita l. A ls o in c lu d e d are the islan d s

IC LARM -EC LAC C ollaborative
P ro ject on the Socio eco n o m ic Valuation o f C oastal
Resources in Southw est Latin America, Casilla 179-D,
Santiago, Chile

F r a n c i s c o M o r a l e s 2,

o f Q u ir iq u in a , M o c h a an d S a n ta M a r ia ( F ig . 1).
T h e m a jo r to p o g r a p h ic a l featu res o f the re gion
in c lu d e :
1 ) A n d e a n m o u n ta in ran g e : h e ig h ts re a ch o v e r
2 ,0 0 0 m , dotted w ith n u m e ro u s vo lcan o e s and the snow ­

A n g e l i c a A r e l l a n o 3, IC LARM -EC LAC Collaborative
P ro ject on the S o cioeconom ic Valuation o f C oastal
Resources in Southw est Latin America, Casilla 179-D,
Santiago, Chile

ca p p e d M t. C h ilia n ( 3 , 1 2 2 m ), A n tu c o (2 ,9 8 5 m ) and
C a lla q u i ( 3 ,0 8 0 m );
2 ) m o u n ta in s situ ate d betw een the in term ediate
d e p re ssio n an d the A n d e a n m o u n ta in ran ge;
3 ) an in te rm e d ia te d e p re ssio n in the northern part

ARANEDA, E., A. CRUZ-TRINIDAD, F. MORALES and A. ARELLANO.
1996. O ptim ization o f econom ic benefits from fishery and forestry
in Bio-Bio, Chile, p. 32-62. In A. Cruz-Trinidad (ed.) Valuation of
tro p ic a l c o a s ta l re so u rc e s : theory and a p p lic a tio n s o f lin e a r

o f th e re g io n , a p p ro x im a t e ly 1 0 0 k m la titu d e from
C h ilia n a n d r o llin g p la in s south o f the B io -B i o R iv e r ;
4 ) a c o a s t a l r a n g e n o rth o f th e r e g io n w h ic h

program m ing. ICLARM Stud. Rev. 25, 108 p.

w e a k e n s to a s e r ie s o f r id g e s w ith in t e r m e d ia te
ca tch m e n t a re a s; to the south o f the B io -B i o R iv e r , the

Abstract

c o a sta l ran ge sh a rp ly in cre a se s to a h e ig h t o f 1 ,0 0 0 m
and a cq u ire s a w a ll-lik e feature, the N a h u e lb u ta R a n g e ;

The net econom ic value o f fishery and forestry in Bio-Bio, Chile was
estim ated with the environm ent as a third sector accounting for positive
and negative externalities.
The main produce of the pelagic fishery is jack m ackerel (Trachurus
m urphyi) and is caught m ostly by sm all boats and barges w hile hake
(M erluccius gayi) is targetted by purse seines. An average o f 95% o f fishery
production is converted into fishm eal 50% of which is sold to foreign
markets. From the forestry sector, the pine (Pinus radiata) is transformed
into logs for saw m illing and pulp.
Optim um net econom ic value is estimated at US$1.37 b illion-year1
87% o f which is accounted for by the forestry sector. Exports of wood
chips from eucalyptus trees as w ell as logs and other wood products from
pine contribute the bulk o f earnings o f this sector. The fishery sector
contributed US$171 m illion m ainly through the exports o f fishm eal.
How ever, w ater pollution caused by fishm eal plants dim inished total
econom ic value by at least US$20 m illion-year1
.

5 ) r o c k y co a st to the north o f the B io -B i o R iv e r
w ith m in o r co a sta l p la in s ; in co n trast, south o f the riv e r
is the sm o o th A r a u c o -C a n e t e p la in w ith an average
w id th o f 2 5 k m ;
6 ) c o n tin e n ta l sh e lf: co n tig u o u s and p a ra lle l to the
co a st e x te n d in g 7 0 k m tow ard s the T u m b e s p e n in su la
a n d fro m C o n c e p c io n , d e cre a s in g to 4 0 k m tow ards
A r a u c o ; and
7 ) c o n tin e n ta l slo p e : the z o n e a ris in g fro m the
c o n tin e n ta l tre n ch up to the co n tin e n ta l sh elf.
T h e co a s ta l zo n e in c lu d e s the 4 9 m u n ic ip a litie s in
F ig . 1 , the co a sta l C o rd ille ra s, the littoral p la in s, the B io ­
B io e s tu a rin e s y s te m a n d the co a s ta l sy s te m o f the
A r a u c o G u l f an d the B a y o f S a n V ic e n te . T h e B io -B io
e s tu a ry is a b r a c k is h in te rp h a se b e tw e e n the r iv e r

♦ICLARM Contribution No. 1219.
Present address: José Manuel Infante N 2802, Nuñoa, Santiago,

sy s te m a n d the A r a u c o G u lf . P a ra lle l to the B io -B io
e stu arin e syste m is the B a y o f S a n V ic e n te /A r a u c o G u lf

Chile.
2Present address: Calle Edipo Rey 5751, Las Condes, Santiago, Chile.
’Present address: Stationary Sources Em issions Central Program
(PROCEFF), O livares 1229, 6o Piso, Santiago, Chile.

syste m , c h a ra c te rize d b y the in flu x o f eq uato rial waters
d u rin g sp rin g a n d su m m er.

32

33
CLIM ATE A ND O CEA N IC CURRENTS

R e g io n a l c lim a te ra n g e s fr o m w in try
r a in s to p ro lo n g e d d r y s e a s o n s , the la tter
r a n g in g fro m s e v e n to e ig h t m o n th s . T h e
c o a s ta l c o r d ille r a a c ts a s a c lim a t ic
b a r r ie r

a f f e c t in g

te m p e ra tu re

and

d is t r ib u t io n o f r a in f a ll. O f f s h o r e , th e
H u m b o ld t C u r r e n t ( F i g . 2 ) tr a n s p o r ts
c o ld a n d lo w s a lin it y w a te rs la d e n w ith
n u trie n ts f r o m th e s u b a n ta rc tic r e g io n .
A ls o , w a te r is u p w e lle d fro m the d e ep e st
z o n e s r e p la c in g w a r m e r a n d n u t r ie n t d e f ic ie n t s h a llo w

w a t e r s . N u t r ie n t

e n ric h m e n t p ro ce sse s co n trib u te to a h ig h
p r im a r y (p h y to p la n k to n ) p ro d u c tio n a n d
th u s, to la rg e s to c k s o f f is h .

Social and Econom ic Attributes

POPULATION CHARACTERISTICS

Fig. 1. The Chilean coastline and location o f R egion VIII, B io-B io (left), and the
coastal m unicipalities bordering Arauco G ulf and B ay o f San Vicente (right).

R e g i o n V I I I i s th e s e c o n d m o s t

p o p u la te d r e g io n o f th e c o u n t r y w ith e s tim a te s fo r
1 9 9 0 at 1 . 7 m i l l i o n , a b o u t 1 3 %

o f C h i l e ’ s to ta l

p o p u l a t i o n . D e n s e l y p o p u la t e d c i t i e s
C o n c e p c io n
HY DROGRAPHY

( 4 8 % ) , Ñ u b le ( 2 5 % )

in c lu d e

and B io -B io

( 1 9 % ) . P o p u la t io n d e n s it y is 4 5 p e r s o n s k m 2 at th e
r e g io n a l le v e l w ith v a r ia t io n b e tw e e n t o w n s , i.e .,

T h e r e g io n ’s h y d r o g r a p h ic n e tw o rk is sh a p e d b y
b oth the A n d e a n ra n g e a n d r iv e r s y s te m s. T h e A n d e a n
r iv e rs , n a m e ly , the B io - B i o , N u b le , a n d L a ja , o rig in a te
fro m the in te rn a l a re a s o f the A n d e a n m o u n ta in ran g e ,

C o n c e p c i o n ( 2 3 1 p e r s o n s k m 2) a n d B i o - B i o ( 2 0
p e r s o n s k m 2). R e g io n a l p o p u la t io n g r o w th is 1 . 1 % ,
le s s th a n th e n a t io n a l a v e r a g e o f 1 . 6 % . A lm o s t 8 0 %
o f th e r e g io n ’ s p o p u la t io n li v e in u r b a n a re a s .

i.e , fro m the m e ltin g o f sn o w w h ic h re su lts in a la rg e r
v o lu m e d u rin g the e n d o f sp rin g . T h e n o n A n d e a n riv e rs,

INCOM E AND EM PLOY M ENT

the C h i li a n , D ig u illin , C h o lg u a n , Itata , D u q u e c o a n d
T h e r e g io n a l c o n t r ib u t io n to G D P w a s 9 % to

M u lc h e n , o r ig in a te f r o m th e w e ste rn se cto rs o f the
m o u n ta in ra n g e ; w a te r s u p p ly c o m e s fro m b o th ra in

10 %

an d snow . T h u s , th e flo w o f w a te r is as h ig h in s u m m e r

fo r a n a v e r a g e o f 3 3 % o f r e g io n a l G D P ( 1 9 8 5 - 8 9 ) ,

in th e la s t d e c a d e . M a n u f a c t u r in g a c c o u n t e d

as in sp rin g .

w h ile th e f o r e s t r y s e c t o r r a n k e d s e c o n d , at 1 3 % .

T h e B i o - B i o R iv e r is o n e o f th e la rg e st in C h ile

T h e la b o r f o r c e in R e g io n V I I I r e a c h e d 6 0 0 ,0 0 0

d r a in in g a n a re a o f 2 4 ,0 0 0 k m 2 at a flo w rate o f 9 0 0

p e r s o n s in 1 9 9 0 o r 1 2 . 8 % o f th e n a t io n a l la b o r fo r c e .

m 3 s e c o n d I t s p r in c ip a l trib u ta rie s are th e V e rg a ra ,

O f th e to ta l, 5 6 8 ,0 0 0 p e o p le w e re f u l ly e m p lo y e d .

L a ja , M a lle c o , R a h u e , R a n q u il, Q u e c o , D u q u e c o an d

A m o n g th e p r o d u c t iv e s e c to r s , a g r ic u lt u r e , f is h e r ie s

B u r e o r iv e r s . T h e Ita ta R iv e r d r a in s an a re a o f 1 1 , 5 0 0

a n d f o r e s t r y c o n t r ib u t e d 2 3 % ;

k m 2 w ith a flo w rate o f 1 4 0 n F - s e c o n d 1. Its m a jo r

in d u s t r y , 1 7 . 8 % ; a n d c o m m e r c e , 1 6 % . T h e g ro w th

s e r v ic e s , 2 3 % ;

t r ib u t a r ie s a re th e N u b l e , C a t o , C h i l i a n , P a l p a l ,

in e m p lo y m e n t in th e r e g io n , w h ic h is 5 . 8 % is g reate r

D ig u illin a n d L a r q u i riv e rs .

th a n th e n a t io n a l a v e r a g e o f 4 . 7 % .

34

P a n a m e r ic a n a w h ic h ru n s f r o m n o rth to sou th
a n d cu ts th ro u g h th e c itie s o f C h i li a n a n d L o s
A n g e le s . T h e c o a s ta l ro a d n e tw o rk c o v e r s a
le n g th o f 3 1 3 k m a n d cu ts th ro u g h th e c itie s o f
Q u ir ih u e a n d T ir u a . R o a d n e tw o rk s b ra n c h out
fro m the m a in h ig h w a y , c o n n e c tin g th e to w n s
o f B u ln e s a n d C h a im a v id a , a n d C a b r e r o an d
C h a im a v id a .
T h e r a ilw a y s y s te m c o v e r s 7 9 5 k m , 2 0 0
k m o f w h ic h b e lo n g to th e ce n tra l r a ilw a y s an d
th e r e m a in in g , the m in o r lin e s . M o s t o f the
r a ilw a y tra ffic is d ire c te d to w a rd s C o n c e p c io n .
In 1 9 9 0 , 3 m illio n t o f c a rg o w ere tran sp o rte d
v i a th e r a i l w a y s y s t e m

w it h 6 0 %

b e in g

a cco u n te d fo r b y w o o d a n d w o o d p ro d u cts. T h e
o th e r c o m m o d it ie s in c lu d e s a lt a n d s u g a r ,
im p o r t e d w h e a t , f e r t i l i z e r s , c e m e n t a n d
p e tro c h e m ic a ls .
T h e m a jo r p o r t s in th e p r o v i n c e a re
lik e w is e co n ce n tra te d in C o n c e p c io n . A m o n g
the m o re im p o r ta n t o n e s a re P u e r to d e S a n
V ic e n t e , w h ic h h a n d le s a b o u t 1 . 0 4 m illio n
t -y e a r 1 o f w o o d p ro d u c ts; L ir q u e n , w h ic h is a
p r iv a t e p o rt; a n d M u e lle C A P w h ic h h a s a
c o m b in e d c a p a c ity o f 2 .5 m illio n t -y e a r 1. T h e
la tte r ’s n o rth e rn se cto r c a te rs to b u lk c a rg o
h a n d lin g w h ile the sou th e rn se cto r is p re se n tly
L o n g itu d e (°W)

p la g u e d w ith id le c a p a c it y b e c a u s e o f th e w e a k
steel m arket.

Fig. 2. O ceanic currents influencing C hile’s coast.

T h e re g io n h a s th ree im p o rta n t a irp o rts:
C a r r i e l S u r in C o n c e p c io n ; M a r a D o lo r e s in L o s
A n g e le s ; a n d B e rn a rd o O ’ H ig g in s in C h ilia n . T h e r e

T h e f is h e r y se cto r e m p lo y s o v e r 2 5 ,0 0 0 p e rso n s
w ith the a rtis a n a l se cto r a c c o u n tin g fo r a b o u t 1 5 ,0 0 0

are a ls o 2 0 s m a ll a ir f ie ld s scattered in the co a st a n d in
the C o rd ille ra s.

fish e rs . O f m a jo r s ig n if ic a n c e is the in d u s t ria l fish e ry ,
w h ic h e m p lo y s 1 0 ,0 0 0 p e rs o n s , 6 0 % o f w h o m are

S O C IA L ISSU ES

e m p lo y e d at f is h m e a l p la n ts. T h e re g io n co n trib u te s
5 0 % o f e m p lo y m e n t in the fo re stry se cto r w ith the
fo llo w in g b re a k d o w n : 5 7 % , p lan tatio n a n d s ilv ic u lt u r e ;
3 9 % , in d u s t ria l fo re s try ; an d 6 2 % , fo re stry s e rv ic e s .

R e g i o n V I I I e x p e r ie n c e s m o r e a c u t e s o c i a l
p ro b le m s than the oth e r re g io n s o f C h ile . A c c o r d in g to
C E P A L ( 1 9 9 0 ) , 4 6 % o f the re g io n a l p o p u la tio n earn
in c o m e s in s u f f ic ie n t to m e e t b a s ic n e e d s, 1 8 %

INFRASTRUCTURE

in d ig e n ts , a n d 2 5 %

are

are b e lo w p o v e r ty le v e ls . T h e

la rg e st p ro p o rtio n o f the p o o r p o p u la tio n is fo u n d in
T h e tran sp o rt s y s te m o f R e g io n V I I I c o n s is ts o f

u rb a n a re a s . A b o u t 4 7 % o f th e p o p u la t io n liv e in

r o a d n e t w o r k s , r a i lw a y s , p o rts a n d a ir p o r t s . T h e

p o v e rty in the c itie s but in d ig e n c e is r e la t iv e ly greater

r e g io n a l r o a d n e t w o r k is c o n s t r u c t e d a lo n g th e

in the ru ra l areas. T h is is m a n ife ste d in lo w in c o m e

lo n g itu d e o f the C e n tr a l D e p re s s io n w ith c o n n e c tio n s

le v e ls w h ile in d ig e n c e , in a d d itio n to the fo rm e r, is

to the co a st, p a r tic u la r ly in the c ity o f C o n c e p c io n , an d

c h a ra c te riz e d b y a d e arth in in fra stru ctu re a n d b a sic

the A n d e a n ran g e . T h e m a in h ig h w a y is the C a rre te ra

s e rv ic e s .

Natural Resources Endowment, Usage
and Impacts in the Coastal Zone

___________________________________________ 35
___________________________________
c JT)
m
l9
°

T h r e e d e c a d e s p rio r to 1 9 7 5 , e c o n o m ic g ro w th o f
the re g io n w a s o rie n te d to w a rd s im p o rt su b stitu tio n .
T h e e m p h a s is w a s o n the p ro d u c tio n o f b a s ic m e ta ls,
c h e m ic a ls a n d fo o d . In the 1 9 8 0 s , there w a s a sh ift
to w a rd s th e e x p lo ita tio n o f n a tu ra l re so u rce s s u c h as
f is h

s t o c k s a n d f o r e s ts . T h is ste e re d e c o n o m ic

d e v e lo p m e n t to w a rd s the e x p o rt m a rk e t, p a r tic u la r ly
that o f w o o d p ro d u cts a n d fis h m e a l. T h e trend in n atural
r e so u rc e d e p e n d e n c y , p a r t ic u la r ly in the c o a s ta l z o n e ,
is d e p ic te d in F ig . 3 . N o te that th e e c o n o m ic a c tiv itie s
u se c o a s ta l a n d m a rin e re so u rce s as ra w m a te ria ls fo r
fu rth e r p r o c e s s in g o r f o r w a ste d e p o s itio n fro m the
in t e r io r a re a s w h e r e h u m a n s e ttle m e n ts a n d o th e r
e c o n o m ic a c t iv it ie s a b o u n d .
T h e e n v ir o n s o f th e B a y o f S a n V ic e n t e p ro v id e
e x c e lle n t e x a m p le s o f m u ltip u rp o se re so u rce s. T h e B a y
is the site o f a m a jo r p o rt are a , ca te rin g to b oth the
in d u s tria l fis h in g in d u stry as w e ll as to c o m m e r c ia l an d

Legend:

p a sse n g e r ca rg o , f is h m e a l p la n ts , iro n a n d steel p la n ts

( Q Thermoelectric plants

a n d c h e m ic a l p la n t s . T o u r is t b e a c h e s are f o u n d in
L e n g a , R a m u n t c h o a n d R e c o t o w h ile s m a ll f is h in g
c o m m u n itie s are in the co a s ta l to w n s o f S a n V ic e n te

Artisanal fishers

Forestry

i t

i l L

M ining

Other activities
Processing plants
Ports

Beaches

a n d L e n g a . T h e oth e r e c o n o m ic a c t iv itie s in the area
in c lu d e : a rtisa n a l a n d in d u stria l f is h in g , in d u stria l w o o d
p la n t s ( C i a . C h i l e n a d e A s t i l l a s in S c h w a g e r a n d
A STEX

Fig. 3. The coastal area o f Region VIII, B io-B io, Chile and the
various resource-dependent econom ic activities situated here.

in C o l c u r a ) , m in e s ( C i a . C a r b o n if e r a in

S c h w a g e r a n d E N A C A R in P u e rto L o t a ) , b e a c h e s in
P la y a B la n c a , C o lc u r a , C h iv il in g o a n d L a r a q u e te , and
s a w m ills a n d th e rm o e le c tric p la n ts in P u e rto C o r o n e l.
A r t is a n a l f is h in g c o m m u n itie s a n d to u ris t b e a c h e s
are scattered o v e r th e A r a u c o c o a s tlin e in the to w n s o f
A r a u c o , L l i c o , T u b u l a n d P u n ta L a v a p ie . T h e tow n o f
A r a u c o is th e site o f fo re st p la n ta tio n s a n d re la te d
in d u strie s, i.e ., F o re s ta l A r a u c o , F o re s ta l C a r a m p a n g u e
a n d C e lu lo s a A r a u c o y C o n s titu c ió n .

T h e m a r in e s p e c ie s o f c o m m e r c ia l im p o r ta n c e
num ber about 1 2 5 (IF O P

1 9 8 8 ) , 6 4 o f w h ic h are

ca p tu re d in R e g io n V I I I an d w h ic h in c lu d e fis h (3 4 ),
m o llu s c s ( 1 2 ) , c r u s t a c e a n s

( 9 ) , a lg a e

(7 ) and

e c h in o d e rm s ( 1 ) (se e A n n e x 1 fo r a c o m p le te list). T h e
b u lk o f re g io n a l la n d in g s c o n s is ts o f f is h sp e c ie s w h ic h
in c lu d e Trachurus m u rp h yii ( C h ile a n j a c k m a c k e re l;
lo c a l n a m e , ju rel), Sardinops sa g a x (S o u th A m e r ic a n
p ilc h a r d ; lo c a l n am e, sardina española), a n d E n g raulis

ringens ( P e r u v ia n a n c h o v y ; lo c a l n a m e , a nchoveta).
Fisheries

F i g . 4 d e p ic t s th e h is t o r ic a l tre n d in th e to ta l
la n d in g s o f im p o rtan t p e la g ic sp e cie s in the T a lc a h u a n o

F is h e r y resource distribution in C h ile is heterogenous

area. N o te the sh a rp in c re a s e in ja c k m a c k e re l la n d in g s

du e to the w id e ra n g e o f e n v iro n m e n ta l c o n d itio n s that

b e g in n in g in the 1 9 7 0 s a g a in s t the d ro p in s a rd in e s and

d e te rm in e p r o d u c t iv ity . T h e w aters o f R e g io n V I I I ,

a n c h o v e t a . P r e s e n t ly , th e f is h e r ie s d e e m e d f u l l y

e s p e c ia lly in the G u l f o f A r a u c o , su p p o rt the h ig h e st

e x p lo ite d in c lu d e j a c k m a c k e re l a m o n g the p e la g ic s ,

c a tc h e s ; the total la n d in g s o f m a rin e re so u rce s re ach e d

a n d h a k e a n d lo b sters a m o n g the d e m e rsa ls.

3 .2 m illio n t in 1 9 9 1 re p re se n tin g 5 3 % o f the n a tio n a l
la n d in g s .

O n ave ra g e , 9 5 %

o f th e t o t a l f i s h c a t c h a re

p r o c e s s e d in t o f is h m e a l w h ile th e r e s t is p r o c e s s e d

36

in to c a n n e d a n d f r o z e n f is h ; m o llu s c s a re m o s t ly

j a c k m a c k e r e l, th e S o u t h A m e r ic a n p ilc h a r d , and

c a n n e d w h ile c r u s t a c e a n s a re m a r k e te d in f r o z e n

Clupea bentincki A r a u c a n ia n h e r rin g ( lo c a l n a m e ,
sardina común); th e se s to ck s are m a in ly e x p lo ite d b y

f o r m ( T a b le 1 ) .

the p u rse se in e fle e t; 2 ) the d e m e r s a l f is h e r y w h ic h

Merluccius gayi h a k e
(merluza común), Genypterus maculatus b la c k c u s k ee l (congrio negro) a n d Dissostichus eleginoides
P a ta g o n ia n to o th fish (bacalao de profundidad); these
in c lu d e s the f o llo w in g s p e c ie s :

TYPES O F FISHERIES

F o u r ty p e s o f fis h e rie s op erate in th e re g io n : 1 ) the
p e la g ic f is h e r y fo r w h ic h the m a jo r s p e c ie s in c lu d e the

s to ck s are m a in ly e x p lo ite d b y the tra w le r fle e t; 3 ) the
c ru sta ce a n s w h ic h are lik e w is e e x p lo ite d b y the traw ler
f le e t w it h m a jo r s p e c ie s i n c l u d i n g t h e lo b s t e r s ,

Pleuroncodes monodon red sq u a t lo b ste r ( langostino
colorado) an d Cervimunida johni y e ll o w lo b s t e r
(langostino amarillo) a n d s h r im p s , Heterocarpus reedi
C h ile a n n y lo n s h r im p (Camarón nailon); a n d 4 ) the
b e n th ic fis h e ry w h ic h is an a rtis a n a l o n e a n d w h ic h

Gari solida (culengue), Ensis
macha ( huepo) a n d Tagelus dombeii ( navajuela).

e x p lo its the m o llu s c s

F ig . 5 s h o w s the lo c a t io n a n d d is tr ib u tio n o f three
im p o r ta n t p e la g ic s p e c ie s : th e P e r u v ia n a n c h o v y ;
S p a n is h sa rd in e s ; a n d j a c k m a c k e re l. T h e d istrib u tio n
o f m a c k e r e l e x te n d s fro m the G a lá p a g o s Is la n d s in
E c u a d o r to the S tra its o f M a g a lla n e s ( I F O P 1 9 8 8 ) . It
e xte n d s le n g th w ise to a ro u n d 1 5 0 0 m ile s in th e C h ile a n
co a st a n d co rre sp o n d s to a to ta l a re a o f 1 m illio n sq uare
m ile s ( I F O P 1 9 8 8 ) . T h e d e p th d is tr ib u tio n is to 3 0 0 m
in the south, b u t c lo s e r to the sh ore, w h ere the u p w e llin g
is m o re p ro n o u n c e d , th e d e p th is b e tw e e n 2 0 a n d 6 0 m .
T h e d is t r ib u t io n o f th e c o m m o n s a r d in e is f r o m
C o q u im b o u p to I s la M o c h a a n d p o s s ib ly e x te n d in g to
C h ilo é to a d ep th o f 5 0 m .
T h e fis h e ry in R e g io n V I I I c a n be c la s s if ie d into
a rtis a n a l a n d in d u s t ria l su b se c to rs. A r t is a n a l f is h in g is
d e fin e d b y the G e n e r a l L a w o f F is h e r y a n d A q u a c u ltu re
a s c o n d u c te d w ith in 5 m ile s fro m the c o a s tlin e w h ile
Fig. 4. Landings o f major pelagic species in the Talcahuano area,
1963-1984.

the in d u s tria l fis h e r y g o e s b e y o n d th is lim it , e x te n d in g
to the te rrito rial seas a n d the E E Z . T h e in d u s tria l fish e ry
a ls o i n c l u d e s th e h a r v e s t in g o f f i s h a n d /o r th e

Table 1. Utilization o f catch in Region VIII, Chile, 1991, in tonnes.

p ro c e s s in g o f s u c h in to f in is h e d p ro d u cts.
R e g io n V I I I c o n trib u te s, o n the a v e ra g e , h a lf o f

Type o f resource
Crustaceans

the ca tch e s o f the a rtisa n a l a n d in d u s tria l se cto rs (T a b le

Product type

Fish

Molluscs

Others

Fresh
Frozen
Salted/dried
Smoked
Canned
Fish meal
Dehydrated
Total

1,027
57,694
3,582
34
119,791
3.010,812

19
830

1,112

-

-

534
65

-

-

-

3,439

-

-

-

-

-

-

-

-

3,192,940

4,288

1,112

413
1,012

_

2 ). A n c h o v e ta an d j a c k m a ck e re l are the m o st im p o rtan t
sp e c ie s c a u g h t b y th e a rtis a n a l a n d in d u s t ria l fish e ry ,
r e s p e c tiv e ly . T h e h ig h v o lu m e o f f is h la n d in g s in the
a rtis a n a l secto r, r o u g h ly 6 4 % o f n a tio n a l f is h c a tch
le v e ls , a n d the p ro life r a tio n o f f is h in g c o m m u n itie s
a lo n g th e c o a s t , p r o v e th e e n o r m o u s s o c i a l a n d
e c o n o m ic im p a c t o f fis h e rie s in the re g io n . D u r in g the
e x p lo s iv e g ro w th p e rio d o f 1 9 8 0 -9 0 , a v e ra g e la n d in g s

37
Table 2. National and regional landings of the artisanal and industrial fishery (in
tonnes) by major species, and production of the industrial fishery, by product type,
1989.
Artisanal
Species

Industrial

National

Regional

National

Regional

183,315
53,171
16,879
10,909
2,744

152,840
46,899
10,235
3,276
2,676

1,504,039
106,479
2,372,982

84,226
106,454
1,751,486

Fish
Peruvian anchovy
Araucanian herring
Chilean jack mackerel
Hake
Patagonian grenadier
South American pilchard
Others
M olluscs
Snails
Cockle
Clam
Mussels
Others
Crustaceans
Shrimps
Crab
Conch
Prawns
Algae
Other species
Product type
Fishmeal
Oil
Canned
Frozen

jack mackerel (C) along the Chilean coast, and location
of the main fisheries.

o f the artisanal sector increased from 33 t to 151 t but
this is nevertheless a minor percentage relative to the
growth in the industrial sector.
Artisanal. Artisanal fishing com m unities are
distributed along the coast of the Bay of San Vicente
but most especially along the Gulf o f Arauco due to
the diversity o f marine resources landed here. The
major fishing towns are Concepcion, San Vicente and
Colium o, G ulf o f Arauco, Santa Maria Island and
between Lebu and Isla Mocha (Fig. 6). Boats usually
fish w ithin 5 km from the coastlin e reaching a
maximum o f 100 km depending on the kind of boat
and on the species targetted.
The artisanal fleet is comprised o f two types of
fishing vessels: boats and barges. Boats are generally
made of wood with a length of 10 m or less and without

Total

-

-

207,209
1,564,674
99,950

207,157
28,437
33,544

-

_

-

-

86,838

12,371

1,298
1,557
33,367
8,763
65,489

629
466
373
284
573

-

-

-

-

-

-

-

-

-

-

5,575

1,196

3,288
1,193

453
328

-

.

-

-

-

-

573

573

178,480
28,887

24,036
1,110

-

-

4,541

1,769

-

-

-

-

-

-

-

-

1,377,796
260,078
53,970
57,236

515,066
117,147
25,949
12,472

676,178

256,501

7,615,102 2,883,707

crew cabins. The mode o f propulsion may either be
inboard motor, outboard motor or oar. Crew size is
usually 2 to 4 people. The gears often used include gill
nets, trammel nets, longlines, compressed air diving
and traps.
Barges are longer than 10 m, and generally have
crew cabins and wheelhouses, with an inboard motor
and a crew o f 4 to 10 people. Barges use mechanized
equipment such as sonar and radar. The gears usually
used are longlines, gill nets and trammel nets. The fish
targetted by artisanal vessels are shown in Table 3.
Barges account for 89% of the catches o f large pelagics
and offshore demersals while the smaller boats (both
m ech anized and n onm ech an ized ) target coastal
demersals such as hake and grouper. A characterization
o f the artisanal capture fishery according to target

38

Fig. 6. Location o f the artisanal fishing com m unities in the Bay of
San Vicente and G ulf o f Arauco area, Chile.
Table 3. Type and num ber of artisanal fishing crafts and target species
in the Bay o f San Vicente, Concepcion, Chile.
Target species
Large pelagics and offshore
dem ersals (albacore,
deepsea cod, golden eel)

2

5

1

8

3

Medium pelagics (grunt,
chub m ackerel, bonito.
eel. bream)

Sail boat

39

Small pelagics (Spanish
sardine, com m on sardine,
anchovy. Chilean jack
mackerel)

M otor boat

17

Barge

Benthic invertebrates
(squids, snails, mussels,
crabs)
Coastal dem ersals (hake,
grouper)

-

43

19

Other coastal resources
(algae, redfish. silversides)

-

4

7

species, vessel, engine, equipment and gear as well as
average fishing distance is presented in Table 4.
Artisanal vessels (boats and barges) operate along
the entire coastline o f the Gulf o f Arauco (Table 5).

The communities o f San Vicente and Lo Rojas have
the largest number o f vessels, with barges and sailpow ered boats accounting for the largest share.
Medium-size vessels (boats with inboard and outboard
motors) are more prevalent in the communities o f Tubul
and Laraquete.
Fish landed at the ports o f San Vicente and Lota
are consumed fresh by the adjacent communities while
those landed at the port o f Coronel are used as inputs
for fishmeal factories in the area. A small percentage
o f the fishery catch is processed, i.e., smoked, dried/
salted or salted.
Industrial. The industrial fishery consists o f two
major components: capture fishery and processing. The
capture fishery is conducted in various fishing grounds
depending on the fleet and on the target species. On
the average, the trawler fleet reaches a distance o f 20
to 25 km from the coast while the purse seine fleet
operates from Isla Mocha up to San Antonio and further
up to a distance o f 130 km.
Target species include the hake, black cusk-eel and
Patagonian toothfish. Jack mackerel landings o f the
industrial sector account for 94 to 96% o f the total
volume of landings at the national level with the region
contributing 38% to the total.
The industrial fishery uses fishing vessels of weight
greater than 50 GT and includes purse seiners and
trawlers. Gears used and operational regimes vary
according to targetted resources (Table 6).
Industrial processing consists of the reduction of
fish into meal and/or oil, canned and frozen fish. In
1989, the country produced 1.8 m illion t o f fish
products, 77% o f which was fishmeal. Region VIII
accounts for an average o f 38% o f total fishm eal
production (Table 2). Major species processed as
fishmeal include Chilean jack mackerel, sardines and
anchovies. These species are also canned in addition
to molluscs.
M ost o f the fishmeal factories are found in the
landing centers of the industrial fleet including the ports
o f Talcahuano (27), San Vicente (6), Coronel (8) and
Tomé (I), where most of the fishmeal factories are
found (Table 7). Table 8 shows pertinent characteristics
o f fish processing activities in the region.
Forestry

Due to favorable environmental conditions, Region
VIII is basically a forestal region with over 41 % o f its

39
Table 4. Characteristics o f the artisanal capture fishery by type o f species and utilization o f capital and technology.

Species

Fishing vessel
Engine
Type
Useful
HP
Useful
Length
life
life
(meters) (years)
(years)

E quipm ent
Type
Useful
life
(years)

Fishing gear
Type
Useful
life
(years)

Fishing
distance
(miles)

1.

A nchoveta,
sardine

Barge with
inboard
engine:
wooden hull

12-18

20

120

15

Echosounder,
w inch

5

Encircling
net

5

5-6

2.

D eepsea cod

Barge with
inboard
engine:
wooden hull

12-18

20

140-200

15

Echosounder

5

“Espinel”

5

25-30

3.

Sw ordfish

Barge with
inboard
engine:
wooden hull

12-18

20

200-250

15

Echosounder,
sonar

5

Albacore
net

5

40-70

4.

M erluza

Barge with
inboard
engine

7-12

15-30

50-80

10

Little
equipm ent

“Espinel”

5

2-7

5.

Shellfish

Sailboat

7

8-10

25-40

5

-

-

-

1

6.

Algae

Boats with
outboard
motors

7

10-15

25-40

5

Compressor,
diving
equipm ent

10/5

-

1

Table 5. Vessels used by the artisanal fishing fleet, per locality, 1990.
Locality

Barges
Inboard
m otor

San Vicente
Lenga
B oca Sur
M aule
Lo Rojas
Pueblo H.
El Morro
L a Conchilla
El Blanco
Lota
Colcura
Laraquete
Arauco
Tubul1
Llico
Punta Lavapie

86

53

14
26

1
4

47
49

20

14
3
1
2
1
7
4

2
10

25
9
26
19
70

48

1

25

Boats
Outboard
m otor

Sail

Total

59
75
16
14
77
17
10
4
18
49
15
25
11
49
8
34

206

‘Twenty-one vessels land in Lo Rojas; the rem aining vessels, in
Coronel.
2Also includes Las Peñas.

16
181
18
13
5
25
98
15
50
20
75
30
118

40
Table 6. C haracteristics o f the industrial capture fishery, by target species.

Resources

1. M ackerel, with
hake, Spanish sardines.
anchoveta, com m on
sardine

Gear type

Fishing vessel
Useful
Length
life
(m)
(years)

Hold
capacity
(m 1)

Operation

Product type

Engine
Days

(bp)

H o u rsd ay 1

350

30-40

30

1,200

Purse seine

2-5

16

Fishmeal;
canned;
frozen

600

41-60

30

1,800

Purse seine

2-5

16

Fresh

1,200

61-70

30

2,800

Purse seine

2-5

16

150

20-30

30

375

Trawler

2-4

12

Frozen

350

30-40

30

1,200

Trawler

2-5

16

Fresh

100

20-30

30

375

Trawler

2-3

-

Frozen

2. Hake, with
black and gold
conger, breams,
elephant fishes

3. Shrim p

a re a c o m p r is in g n a tiv e (4 0 0 ,0 0 0 h a ) a n d p la n ta tio n
Table 7. N um ber and location o f fish processing plants in Region VIII,
Concepcion, Chile, per product line.

fo re sts (6 0 0 ,0 0 0 h a ). T a b le 9 s h o w s the c o n trib u tio n
o f p rim a ry a n d p la n ta tio n fo re sts to total fo re st area
a n d the a re a l c o v e r a g e o f R e g io n V I I I . A lis t in g o f

Fishmeal

Frozen

Canned

Dried/salted

Tomé

1

1

1

-

-

Talcahuano

8

14

16

3

1

San Vicente

6

2

2

1

-

Coronel

5

3

2

-

-

20

20

11

4

1

Location

Total

Smoked

n a tiv e fo re st s p e c ie s in C h ile a n d that o f R e g io n V I I I
is p r o v id e d in A n n e x 2 .
T h e e x p a n s io n o f fo re s t p la n ta t io n s h a v e b e en
tre m e n d o u s b e tw e e n 1 9 6 5 a n d 1 9 8 6 ( F ig s . 7 a n d 8)
w ith th e in c r e a s e in a re a a lo n g th e c o a s t lin e . T h e
fo re stry se cto r p o ste d a ro b u st e c o n o m ic g ro w th in the
la s t d e ca d e w ith co n trib u tio n to G D P a v e ra g in g 3 %
a n d to e x p o rts, 9 . 4 % .
F o r e s t re so u rce s are u s e d fo r tw o p u rp o se s: 1 ) the
e x p o rt o f lo g s a n d 2 ) the u se o f th e se p rim a ry m a te ria ls
a s in p u ts f o r fu rth e r p ro c e s s in g .
W o o d p r o c e s s in g , o n th e o th e r

Table 8. Important characteristics o f industrial fish processing.
Product

1. Fishmeal
and oil
(Type A)
2. Fishmeal (B and C)
Oil (Type B)

Production
rate (t h o u r 1
)
50

Reduction
rate (%)
20
4.5

Equipm ent

h a n d , is c la s s if ie d in to tw o w a y s:
M arket (%)

1)

p ro ce sse s w h ic h d o n o t a lte r the

b a s ic structure o f the raw m a te ria l,
Boilers, press,
mill drier

Domestic (20)
Export (80)

i.e ., lo g s , c h ip s , lu m b e r, b o a rd s ;
an d 2 ) those that un d e rg o c h e m ic a l
p r o c e s s e s , i.e ., c e llu lo s e a n d its

100

23
6

Boilers, press,
mill drier

D om estic (20)
Export (80)

d e r iv a tiv e s .
T h e fo r e s tr y se c to r e m p lo y s
a p p r o x im a t e ly 8 3 ,0 0 0 w o r k e r s ,

3. Fishmeal (C)
Oil (C)

100

23
6

Boilers, press

Domestic (10)
Export (90)

5 0 % o f w h ic h c o m e fro m R e g io n

4. Canned (jars)

6,000

30

Boiler
Pressure cooker

Domestic (25)
Export (75)

e m p lo y m e n t, 4 8 % is in v o lv e d in

5

30

Freezing chamber

Export (100)

V III.

Of

th e

s ilv ic u lt u r e
5. Frozen

Notes: Types o f fishm eal and oil vary according to quality with Type A having the lowest quality,
etc.

a c t iv it ie s ,

to ta l
and

43%

r e g io n a l

h a r v e s t in g
in

in d u s t r ia l

f o r e s t r y a n d th e re st in r e la te d
fo re stry s e r v ic e s .

41
Table 9. Forestry resources o f C hile and R egion VIII, area covered and production.

National
Area
Volume
(mMO6)
(ha)

Resource

7,616,500
1,386,444
1,192,287
81,773
112,384
10,389,388

Primary forest
Plantation
P. radiata
Eucalyptus
Others
Total

915.1
177.6
144.1
33.5
1,270.3

Region VIII
Area
(ha)
401,700
592,355
560,448
31,840
67
1,586,410

Volume
(mM O6)
24.1
78.1

102.2

Regional
contribution
to total (%)
5.3
42.7
47.0
38.9
0.1
-

v o lu m e

a re

th o se

of

th e

genus

Nothofagus, i.e ., Nothofagus obliqua, N.
dombeyi an d N. alpina. C h a r a c t e r is t ic s
o f im p o rtan t fo rest sp e c ie s are p ro v id e d
in T a b le 1 0 .

PRODUCTION DYNAM ICS

F o r e s try a c t iv it ie s in c lu d e a ll w o rk
r e la tin g to the u s e o f fo re s t re so u rc e s .
T w o p h ase s are c o n s id e re d in th is p a p e r: 1 ) the in it ia l
p h a se in c lu d in g s u b a c t iv it ie s

su ch as n u rse ry,

p la n ta tio n s (fo re statio n a n d re fo re s ta tio n ), s ilv ic u lt u r e ,
a n d h a rv e s tin g ; a n d 2 ) the p ro c e s s in g p h a s e o r w h a t is
refe rre d to h ere as in d u s t ria l fo re stry.
F o r e s t n u rse rie s o r fo re st r e se rv e s a re la n d areas
a llo te d to the g ro w in g o f p la n t s e e d lin g s , w h ic h , o n c e
a d e q u ate g row th h a s b e e n a tta in e d , are tra n sp o rte d to
d e sig n a te d p la c e s o f p la n tin g . T h e r e w e re 1 2 0 n u rse rie s
id e n t if ie d in 1 9 8 9 c o n t r ib u t in g 5 0 . 6 % to n a t io n a l
s e e d lin g p ro d u ctio n w ith sh a re s o f p in e a n d e u c a ly p tu s
re a c h in g 4 7 . 9 % a n d 6 0 % , r e s p e c tiv e ly .
T w o m a in p ro ce sse s are o f in te re st in the h a rv e stin g
stage: fe llin g an d h a u lin g . F e llin g in v o lv e s the p ro cesse s
o f ro ta tin g , c u ttin g , c h o p p in g , th in n in g a n d tr im m in g .
T h e m o st c o m m o n to o ls are the m o to r-s a w , a rc h -s a w ,
b e n t-s a w an d a x . H a u lin g is the p ro c e s s o f tra n sp o rtin g
fe lle d trees to a sto ra g e a re a s u c h a s a la k e o r to a

FOREST RESOURCES: NATIVE AND PLANTATION SPECIES

T w o ty p e s o f p la n ta tio n sp e c ie s are c u ltiv a te d in

Pinus radiata (pino radiata) a n d
e u c a ly p tu s Eucalyptus globulus, E. camaldulensis a n d
E. viminalis. T h e p in e is o f m a jo r im p o rta n c e in term s
the re g io n : the p in e

o f a re a p la n te d a n d v o lu m e e x p lo ite d . It repre se n ts
8 5 % o f to ta l fo re st p la n ta tio n in C h i le a n d 9 0 % in
R e g io n V I I I .
A l l e u c a ly p tu s p la n ta tio n s in C h i le u s e the sp e cie s

E. globulus

w h ile the oth e r tw o sp e c ie s are u s e d in

m a rg in a l a re a s as w in d b re a k e rs . R e g io n a l c o v e ra g e o f
e u c a ly p tu s is a b o u t 6 4 ,0 0 0 h a, 4 . 5 % o f the p la n ta tio n
a re a in C h ile .
A m o n g the n a tiv e fo re st sp e c ie s in R e g io n V I I I ,
the m o re s ig n if ic a n t o n e s in te rm s o f a re a p la n te d and

8. Forest plantation in Bio-Bio region, Chile, 1986

42
Table 10. Characteristics o f important forest species in R egion VIII, Chile.

English
com mon name

Scientific
name

Spanish
com mon name

M aximum
height/width

Origin

Plantation species
Pine
Eucalyptus

Pinus radiata
Eucalyptus globulus

Pino
Eucalypto

40 m / 90 cm
40 m / 1 m

California
Australia

Native species
Rauli beech
Coigue

Nothofagus alpina
Nothofagus dombeyi

Rauli
Coihue

40 m / 2 m
40 m / 2.5 m

Endem ic
Endem ic

processing line. The simplest form o f hauling is done
using oxen while the mechanized forms include forest
tractors and logging turrets.
The regional contribution of the industrial forestry
sector is the most important in the country with
cellulose and paper production contributing 77% to
national production; lumber, 55%; and fiberboard, 100%.
Industrial forestry can be d ivid ed into tw o
categories: 1) that which manufactures wood without
altering its structure (chips, pulpwood, logs, sawable
wood, serrated wood, etc.); and 2) that which applies
chemical processes in the wood for the extraction of
cellulose and its derivatives. Regional production for
both categories is shown in Table 11 and general
descriptions follow.
Sawmilling. The pine Pinus radiata is the main
species used in sawmilling. The sawmilling industry
in Chile is highly heterogenous in terms of scale of

Table 11. Production of forestry sector in Region VIII.
Product
Category 1
Wood pulp
Logs
Wood chips
Lumber
Sawdust
Others
g o ry 2
Cellulose
Newsprint
Others

1989 (m 1-1O’)

2,465.3
2,172.3
3,766.6
1,230.2
1,040.9
771.5

435.9
155.9
80.1

Occurrence
in Chile

All regions
Coastal areas and
central plains

Regions VII to X
Regions VI to XI;
very common; found
around lakes and
rivers

operations, technology, products and yield. Sawmills
can be classified as either mechanized, nonmechanized,
and/or temporary. M echanized saw m ills attain an
average production o f 50,000 m3-year3 and utilize
sophisticated technology. Temporary sawmills use old
machineries which are manually operated; average
annual production is 10,000 m3. In the intermediate
are the traditional nonm echanized saw m ills with
average production ranging from 10,000 to 50,000
n f-y ea r1.
The yield of sawmills depend on a host o f factors
such as: the state o f mechanization, i.e., (type o f saws,
chipping machines, etc.); the system of felling; and the
state of raw material. Sawdust is a by-product of sawed
timber and commands the lowest price in the market;
thus, the efficiency of sawmilling is gauged by the
production o f sawdust which should be kept at a
minimum.
Boards and plywood industry. The particleboard
industry is formed by four factories, two o f which are
located in Region VIII. Both belong to the Wood and
Synthethic Enterprises S.A. (M ASISA). These are:
Wood and Panel Plant S.A. (MAPAL), in Concepcion,
and the M ASISA plant in Chiguayante. MAPAL is
known to be a very efficient producer, even on the
national level, with an average input of 2.45 m3/board
ton. M ASISA Chiguayante ranks next with average
input of 3.03 m3/board ton.
Only one fiberboard factory exists in the whole
country: Pressed Woods CHOLGUAN S.A., which is
located in the Yungay commune. The products of
CHOLGUAN factory fall under the distinctly hard
fiberboard classification, with a density o f 1 t-nr3.

43
Table 12. N am es and important characteristics o f w ood chip centers in R egion VIII, B io-B io, C hile.

Establishm ent
Asseradero San Lorenzo

Technology
Drum

in d u s try is c o m p o s e d o f s ix en ter­

Annual
production
(m 3)
10,000-50,000

T h e veneer and nonveneer
p r is e s , o f w h ic h o n e is fo u n d in

Species
Pine

M arket

R e g io n V I I I , the A g r ic u lt u r a l a n d

Export

F o r e s t a l S o c ie t y C O L C U R A

in

L o t a . T h e v e n e e r in d u s t ry u t iliz e s ,
Aserradero Copihue

Disc

10,000-50,000

Pine

Export

Astillas Exportaciones

Disc

 100,000

Pine, eucalyptus
native species

Export

e x c e p t fo r th e e u c a ly p t u s sp e c ie s

Eucalyptus

Astillas J.C.E. Ltda.

Blade

10,000-50,000

Native species

-

Bosques Arauco S.A.

Disc

10,000-50,000

Pine

Cia. Chilena Astillas

Disc

Disc

 100,000

 100,000

Eucalyptus and
native species

o n ly

c a p a c it y o f th e C O L C U R A p la n t

Domestic

Cia. Astillas Concepcion

globulus,

in d ig e n o u s s p e c ie s . T h e in s ta lle d
is 4 5 0 ,0 0 0 r r F -y e a r 1 o f ve n e er.

Wood chips.

N in e

f ir m s

p ro d u c e w o o d c h ip s in the re g io n .
Export

A ll

f a c t o r ie s

use

s t a t io n a r y

e q u ip m e n t b u t d iffe re n t te c h n o lo ­

Eucalyptus and
native species

Export

g ie s , le v e l o f p ro d u c tio n , sp e cie s
u s e d a n d m a rk e t (T a b le 1 2 ) .

Forestal Coronel S.A.

Disc

50,000-100,000

Native species

Export

Gonzalez Huepe M aria E.

Blade

 10,000

Eucalyptus and
native species

Export

Cellulose and paper.

The

in d u s try c o n s is ts o f s ix e n te rp rise s
w h ic h o p erate s e v e n p la n ts in the
r e g io n .

T a b le

13

lis t s

th e se

enterprises, th e ir a n n u a l p ro d uctio n ,
s p e c ie s u s e d a n d f in a l p ro d u ct.

Tourist Resources
Table 13. Paper and cellulose plants in Region VIII, Bio-Bio, Chile and selected characteristics.

Firm
Celulosa Arauco y
Constitución
Planta Arauco I
Planta Arauco II

Species
used

Annual
production
(t)

R e g io n V I I I o ffe rs a d iv e r s e
ra n g e o f to u rist a ttra ctio n s : u rb a n

M arket
orientation

Final
product

c e n t e r s , r iv e r s ,

s n o w -c a p p e d

m o u n ta in s , h ot s p rin g s , in d u s t ria l
p a r k s , b e a c h e s a n d p o rts, a n d sites
o f h is t o r ic a l a n d c u lt u r a l im p o r ­

Pino radiata
Pino radiata

150,000-200,000
 300,000

Export
Export

Kraft cellulose
Kraft cellulose

ta n c e . T h e b e n e fits p ro d u c e d b y
the t o u r is m se cto r in c lu d e fo re ig n

Celulosa del Pacifico
Planta Mininco
Compañía M anufacturer
de Papeles y Cartones
Planta Laja

Forestal e Industrial
Sta. Fe S.A.
Planta Nacimiento

e x c h a n g e g e n e ra tio n , s a v in g s ( v ia
Pim radiata

 300,000

Export

Kraft cellulose

Pino radiata
Eucalipto

 300,000

Export

Kraft cellulose,
printing paper,
packing paper

“ in v is ib le

e x p o rt”

p ro d u cts)

and

of

n a t iv e

e m p lo y m e n t

g e n e ra tio n , a ll o f w h ic h co n trib u te
s ig n if ic a n t ly

to r e g i o n a l a n d

n a tio n a l d e v e lo p m e n t. T h e to u rism
in d u s t r y , h o w e v e r , c o n t r ib u t e s

Eucalipto

200,000-250,000

m in im a lly to r e g io n a l in c o m e a n d

Dom estic and
export

Kraft cellulose,
white paper

M echanical pulp, is th r e a te n e d b y p o llu t io n f r o m
newsprint
in d u s t r y , m a in ly f r o m f is h m e a l

e m p lo y m e n t, th e la tte r a v e ra g in g
n o m o re th a n 0 . 5 % . T h i s p o te n tia l

Industrias Forestales
Planta Nacimiento

Pino radiata

100.000-150,000

Export

Papeles Bío-Bío S.A.
Planta San Pedro

Pino radiata

100.000-150,000

Dom estic and
export

p la n t s a n d c e ll u lo s e a n d p a p e r
fa c to rie s .

44

The tou rist attractions
geographically as:

can

be

cla ssified

1) Andean zone
The principal resources include hot springs,
volcanoes, snow slopes and fishing but there is no largescale development except those with foreign tourist
appeal. The main tourist attractions are the ski center
and hot springs o f Chilian. The ski center is complete
with skiing equipment, a hotel, as well as five open-air
and naturally heated pools. O f secondary importance
is the Antuco tourist com plex which is situated at the
foot o f the Antuco volcano which is inside the Laja
Lake National Park. Site facilities include cablecars,
restaurants, bars and ski equipment.

metropolis which is considered a historical, cultural,
folkloric and gastronomic center and boasts o f major
infrastructure including hotels and transportation
facilities.
3) Araucanian route
The most important tourist attraction in the region
based on the number o f visitors are its beaches, notably
the Playa Blanca, and the beaches at Chivilingo and
Laraquete. Tourism services such as hotels, inns and
camping sites, are most prevalent in Concepcion and
Nuble. Tourism activities peak during spring (January
and February) and winter (July and August). Domestic
tourists come mainly from the Santiago area whereas
foreign tourists come from the United States, Germany
and several Asian countries.

2) Coastal range
Externalities

The most prominent attractions are the beaches to
the north o f Penco and to the south o f the Bay o f San
Vicente. Am ong the beaches identified, less than half
can be reached by public transport while most beaches
do not have facilities such as hotels and restaurants
(Table 14). A lso o f major importance is the Concepcion

The environmental problems o f the region are
reflective of the diverse economic activities and natural
resource use in the area (Tables 15 and 16). The Bay
of San Vicente is the site o f petrochemical plants,
fishmeal plants, cement plants, iron and steel mills,

Table 14. Location and characteristics o f beaches in the coastal zone of Region VIII.
Beach

Town

Transport

Facilities

Activities

Lenga

Talcahuano

Private

None

Recreation/swim m ing

Ram untcho and Recoto

Talcahuano

Private

None

Recreation/fishing

D esem bocadura

Talcahuano

Private

None

Recreation/fishing

Las Escaleras

Talcahuano

Private

None

Recreation/fishing

Escuadrón

Coronel

Private

None

Recreation/fishing

Playa Blanca

Coronel

Public

Restaurants

Recreation/swim m ing

C olcura

Lota

Public

None

Recreation/swim m ing

Chivilingo

Lota

Public

None

Recreation/swim m ing/fishing

L araquete

Arauco

Public

Hotels and restaurants

Recreation/swim m ing/fishing

Arauco

Arauco

Public

Hotels

Recreation/swim m ing/fishing

Llico

Arauco

Private

None

Recreation/sw im m ing/fishing

Tubul

Arauco

Private

None

Recreation/swim m ing/fishing

Punta Lavapie

Arauco

Private

None

Recreation/fishing

Table 15. Principal contaminants originating from liquid effluents in Concepcion Bay.

Pollutant
source

Production
system

Product

Tomé

Slaughterhouse
Textile industry

Cut meat
Spun cotton

None
None

Fishing industry

Flour, oil and
frozen fish
Porcelain, sanitary
wares
Flour, frozen oil and
canned fish and
shellfish.
Flour, canned
fish in oil
Glasses and crystals

Glue water
concentration
-

Treatment

Penco

Porcelain factory

El M orro

Fishing industry

Isla Rocuant

Fishing industry

Lirquen
Talcahuano

Glass industry
Dockyards

San Pedro

M ercantile ships,
petroleum retailers
fishers and launches.
Paper factory

Laja

Paper factory

Chiguallante

Textile factory

Brewery

Principal
contaminants
W ater with blood, grease, excrem ents
Solids (fibers), maltose, glucose,
solvents, caustic soda, colorings,
auxiliary chem ical substances.
Organic m atter (Glue water,
oils, blood water)
Clays, colorings, anilines

G lue and blood
w ater concentration

Organic matter

None

Organic matter

-

Fine sand, china clay
Heat, Calcium hydroxide,
Sodium hydroxide, Sodium carbonate,
Sulphuric acid, Hydrocarbons.
Spilled petroleum, oils, food residues.

-

-

-

“

Organic m atter (fibers, bark), talc,
china clay, aluminum sulfate, fungicides.
Cellulose fibers (organic matter),
Sodium lignite, Chlorine lignine, Mercury.
Sodium sulfide, hypochlorite sulfite,
sulfuric acid, formic acid, starch,
glucose, wax, pectins, alcohols, fixatives,
acetic acid, detergents, soaps, organic tints.
Liquid presser and aquarelle tint,
yeast, starch, alcohol, chrom ium salts.

Beer

Table 16. Principal contam inants originating from liquid effluents dum ped into the Bay of San Vicente.
Pollutant
source

Production
system

Product

Talcahuano

Iron and steel
mill

Iron ingots,
lam inated steel

Sedim entation
and neutralization

Petrochemical

Polychloride
vinyl (Pvc),
chloride vinyl
Dychlorotene
hydrochloric acid
polyethylene
Chlorine, caustic
soda and other
by-products
Flour, canned
fish in oil
Chips
Wire

Sedim entation
Neutralization

Cement

-

Petrochemical

San Vicente

Fishing industry
Wood chips
W ire factory

San Vicente
and Talcahuano

Cem ent factory
M ercantile ships
Petroleum retailers
and launches
Sewage and waste
disposal

Treatment

Principal
contam inants
Iron sheet, ammonia, phenols,
ferrous salts, cyanid oils;
lubricants.
Hydrochloric acid, chloride,
salts, oils, lubricants,
hydrocarbon chlorates

Sedim entation
N eutralization

Chlorine compounds, m ercury

Glue water
concentration
-

Organic matter
Chips
Small iron sheets, sulphuric
acid, hydrochloric acid, soap
Heat, sediments
Spilled petroleum, oils,
food residues
Detergents, soaps,
coliform s, excrem ents, grease
oils, food residues, urea

46
m e rc h a n t v e s s e ls a n d o il ta n k e rs;
it a ls o se rv e s a s a re p o s it o r y o f

D isch a rge of
raw m aterial

P um ping w ater

th e p u b lic w a s te s y s t e m in the
t o w n s o f T a lc a h u a n o a n d S a n

P um ping w a te r
-

R ecovery

are ab a tto irs a n d te x tile m ills in

t
Separa tion of

R eco ve ry of

of solids

V ic e n te . In the B a y o f C o n c e p c io n ,

pum pinç station

blood w a te r

T o m é , fis h m e a l p lan ts in T o m p é ,
El

M o rro

and

Is la

S torage

R o cu a n t,

s a w m ills in T a lc a h u a n o , a n d a

C oagulation
1

p ap e r fa cto ry in L a ja .

Firing

T h e e n v ir o n m e n ta l p ro b le m s
?

o f the r e g io n a re a ttrib u ta b le to

P ressing

tw o im p o rta n t e c o n o m ic se cto rs,

C oagulated
blood w a te r

Trap liquids

C lam p (vise)

n a m e ly : f is h e r y a n d fo re stry.
In d u s t r ia l e f f lu e n t s fr o m

R ecovering so lid s

r e d u c t io n p la n t s c o n s t it u t e th e

R eco ve ry of
inso lu ble solids

m a in s o u r c e o f c o n t a m in a t io n in
Evaporation

the re g io n in th e f o r m o f liq u id
d is c h a r g e s , s p e c i f i c a l l y in the
Bays

O il trap

E m ission of
o d o r and m aterial ^ “ _ D ry in g _
to th e a tm o sp he re

of

San

V ic e n t e

and

Purification

C o n c e p c io n , g a s e o u s e m is s io n s
M illing

a n d p a r t ic u la t e m a tte rs . F ig . 9
sh o w s th e p r o c e s s in g stru ctu re o f

P reservative

a t y p ic a l re d u c tio n p la n t a n d the

S torage

addition

re su ltin g e fflu e n ts p e r stage in the
p ro d u c tio n c y c le .

D eodorized w a te r

T h e e n v iro n m e n ta l im p a cts o f

v

Final
product

the a rtisa n al fis h e ry e m an ate fro m
inadequate so lid an d w aste disp o sal

W ash w a te r o f e q u ip m e n t
a n d p lants

Dry
flo ur

syste m s. T h is h a s p ro v e n h a rm fu l
to the m a rin e e n v iro n m e n t a n d has

S torage

c a u se d attendant h ealth r is k s in a ll
o f the co a sta l fis h in g c o m m u n itie s
(T a b le 1 7 ) . A n o th e r en viro n m e n ta l

Fig. 9. Typical operation of a fish reduction plant and resulting effluents.

c o n ce rn is the c o lle c tio n o f fire w o o d fo r c o o k in g w h ic h

A n o t h e r e n v ir o n m e n t a l irr ita n t a s s o c ia t e d w ith

ca u se s not ju s t the d eterio ration o f m a n g ro ve an d u p la n d

fo re sta l e x p lo ita tio n a n d the s a w m illin g in d u s try is the

forests b u t a lso e ro sio n a n d seaw ater seepage.

d isch a rg e o f sa w d u st o r c h ip s in to w a te rw a y s or d ire c tly

T h e in d u s t r ia l f o r e s t r y se c to r, m a in ly th r o u g h

to the se a r e s u ltin g in the s u ffo c a tio n o f m a rin e flo ra

c e llu lo s e a n d p a p e r p la n t s , is th e s o u r c e o f liq u id

a n d fa u n a . T h is is p re v a le n t in D ic h a t o a n d in th e P o rts

e fflu e n ts a n d g a s e o u s e m is s io n s . T h e s e are d u m p e d in

o f S a n V ic e n t e a n d L ir q u e n w h e re s a w m ills a b o u n d .

h ig h c o n c e n tra tio n s in th e B i o - B i o R iv e r o r d ir e c tly

E r o s i o n i s a n o t h e r s e r io u s p r o b le m d u e to b a d

in to the A r a u c o G u l f f r o m th e se v e n p la n ts o p e ratin g

m a n a g e m e n t a n d in a p p ro p ria te u s e o f the s o il.

in the r e g io n . T h e p r in c ip a l co n ta m in a n ts are lig n in ,
c h lo r in e , m e r c u r y a n d d iffe re n t k in d s o f sa lts d e riv e d

Model Formulation and Implementation

fro m the w h ite n in g o f c e llu lo s e ( C O R E M A 1 9 9 2 ) . T h e
m o st n o x io u s is m e r c u r y w h ic h c a u s e s h a rm fu l effe cts

T h e v a rie d a n d c o n flic tin g u se s o f c o a sta l re so u rces

o n the n e r v o u s s y s te m a n d e v e n d e ath w h e n a b so rb e d

a n d r e s u lt in g e n v ir o n m e n t a l e x t e r n a lit ie s se t th e

in h ig h d o s a g e .

f ra m e w o rk fo r th e d e v e lo p m e n t o f the lin e a r m o d e l.

47
Table 17. Environm ental im pact o f the artisanal fishery in comm unities located in the coastal zone o f the Bio-Bio region,
Chile.
’
Com m unity
Lenga
Boca Sur
M aule
Lo Rojas
Pueblo Hundido
El Morro
La Conchilla
El Blanco
Lota
Colcura
Laraquete
Arauco
Las Penas
Tubul
Llico
Punta Lavapie
A

A1
A2
A3
A4
B

B1
C

Cl
C2
C3
D
Dl
E
El
F
FI

A1

A2

A3
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X

X
X
X
X
X
X
X
X
X
X
X

X
X
X
X

A4
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X

B1

Cl

X

X
X
X

C2

D
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X

X

X
X
X
X

X
X
X
X
X
X
X

X

X

E

F
X

X

X

deficiency of dom estic waste disposal systems and sources o f potable water.
contam ination of ground aquifers.
visual and foul odor.
contamination o f marine environment.
health risks.
deficiency o f solid waste collection systems,
contam ination by nonbiodegradable waste matter,
use o f firewood for cooking,
deterioration of flora and fauna,
erosion.
seaw ater seepage,
presence of dom estic animals,
anim al excreta.
use o f mechanized fishing crafts,
w ater contam ination from hydrocarbons,
algae cultivation.
contam ination caused by use o f nonbiodegradable elements.

T h e b a s ic stru c tu re c o n s is t s o f th re e e le m e n ts : the

W e firs t e la b o ra te th e n o m e n c la t u r e to p r o v id e

o b je c tiv e fu n c tio n , the co n stra in ts, a n d the c o e ffic ie n ts

c la r it y in the d e s ig n a n d to a id u s in th e id e n tific a tio n

o f the m a trix .

o f the v a r ia b le s u se d .

The

objective function

is th e m a x im iz a t io n o f net

b en efits a c c r u in g fro m fo re stry a n d fish e ry. T h e to u ris m
se cto r w a s not co n sid e re d in m o d e l fo rm u la tio n b e ca u se

Nomenclature

o f its in s ig n if ic a n t co n trib u tio n to total re v e n u e s. T h e

constraints m a y

th e o r e tic a lly in c lu d e b io lo g ic a l lim its

s u c h as b io m a s s fo r fis h e r y a n d m a x im u m a llo w a b le

O b je c t iv e fu n c tio n v a r ia b le s c a n e ith e r b e c o st o r
re v e n u e v a r ia b le s w ith the r e s p e c tiv e s p e c if ic a tio n s :

c u t f o r f o r e s tr y o r t e c h n o lo g ic a l lim it s a s in p la n t

C o st: X

p ro c e s s in g c a p a c ity . H o w e v e r , o u r m o d e l d o e s n ot d e a l

R e v e n u e :X emp

w ith re a l re so u rce co n stra in ts b u t rath e r w ith b a la n c e

estgra

C o s t v a r ia b le s are fu rth e r c h a ra c t e r iz e d as e ith e r a

an d c o n v e x ity e q u a tio n s w h ic h m a k e s the interpretation

f in a n c ia l co st,’ X

o f m a trix c o e ffic ie n ts q u ite d iffe re n t. T h is is d is c u s s e d

co st v a r ia b le ran g e s are as fo llo w s :

in gre ate r d e ta il in the re le v a n t se ctio n .
L a s t ly , the

matrix coefficients

A

=

f, o r a s an e n v ir o n m e n ta l co st. T h e

a c tiv itie s o r sta g e s o f p ro d u c tio n r e q u ire d
to re a ch the f in a l p ro d u c t sta g e ( F ig . 1 0 a n d

a re in p u t-o u t p u t

se ctio n b e lo w );

ra tio s, i.e ., the a m o u n t o f re so u rce i that is n e e d e d b y
p ro ce ss x. T h e v a lu a tio n o f e n v iro n m e n ta l e x te rn a litie s

R

a n d its in c o rp o ra tio n in m o d e l-b u ild in g is d is c u s s e d

G

se p arate ly.

,

estgra ’

=

re so u rce s ;
g e a r o r m eth o d u s e d , w h ic h m a y be s p e c if ic
to the typ e o f re so u rce b e in g e x p lo ite d ;

48
TH E O BJEC TIV E FUNCTION

Fishery

Forestry

T h e o b je c tiv e f u n c tio n c o n s is ts o f e le m e n ts that
e ith e r a d d (re v e n u e ) o r d im in is h (c o st) th e b e n e fits
d e riv e d fro m v a r io u s e c o n o m ic se cto rs o f th e c o a sta l
zone.

E n v ir o n m e n t a l e x t e r n a lit ie s

a re

a ls o

c o n s id e re d as c o st ite m s in th e o b je c t iv e f u n c tio n .
T h e g e n e ra l fo rm o f th e o b je c tiv e fu n c tio n is :

N B = (R fC .)

...1)

w h ere
R .1 =

total re v e n u e a s s o c ia te d w ith e c o n o m ic

C .1 =

co sts

a c t iv itie s r a n g in g f r o m i to E ; a n d

Fig. 10. Activity stages for fishery and forestry. Note that capture fishery
is equivalent to harvesting in the forestry sector; otherwise all other
activities are the same.
T

=

S

=
=

e c o n o m ic

T h e c o m p u ta tio n a l fo r m is g iv e n as:

E
C ! =

S

T

G

R

A

£ Z X £ L Z [ ( C

s c a le o f o p e ra tio n , h e re d e f in e d as la rg e

- fc
v

s c a le o r s m a ll s c a le ; an d
E

w it h

a c t iv itie s p r e v io u s ly d e fin e d .

te c h n o lo g y , h e re d e fin e d as b e in g c a p ita l
in te n s iv e o r la b o r in te n s iv e ;

a s s o c ia t e d

csigra

csigra f

x *o
^

* Q cstira  1

cslgra

x1


...2)

e c o n o m ic se cto rs, here d e fin e d as fis h e ry
w h ere

a n d fo re stry.
T h e re v e n u e v a r ia b le ran g e s are:
P

=

M =

C

f in a l p ro d u c t;
m a r k e t s , in c lu d i n g 1 ) d o m e s t ic , m a jo r
m a rk e ts ; 2 ) d o m e s tic , m in o r m a rk e ts ; 3 )

,

estgra

f

= a s s o c ia t e d f i n a n c ia l c o s t pre r a c t i v it y ;

Q
estgra^

= q u a n t it y o f th e p r o d u c t /g o o d fo r a

C

= v a lu e

g iv e n a c t iv it y le v e l;

in te rn a tio n a l m a rk e ts; a n d
E

=

e c o n o m ic se cto rs as p r e v io u s ly d e fin e d .

x
estgra

pr l a c e d

on

e n v ir o n m e n t a l

e x te rn a litie s ; a n d
Q estgrax

Elaboration o f Variables

= q u a n t it y a s s ig n e d to a p a r t i c u l a r
e n v ir o n m e n ta l e x te rn a lity .

T h e a c t iv it ie s in th e f is h e r y a n d fo re s try se cto r
re se m b le th o se o f a m a n u fa c tu r in g c o n c e rn , i.e ., in it ia l

PM E

JN =yyy
-l
r ,

*o
^emp

1

—
3)

stage is a ctu a l p ro d u ctio n w h ile fin a l stage is m a rk e tin g .
In fis h e rie s , the in it ia l stage is ca p tu re o r h a rv e s tin g .
T h is is lik e w is e th e c a s e fo r fo re stry b u t o n ly fo r the

where

n a tiv e sp e c ie s w h ic h are n ot p la n te d . In th e c a s e o f
p la n ta tio n sp e c ie s c o n s id e re d h ere, i.e ., the p in e

radiata

Pinus

P


=

p ric e o f p ro d u c t P at m a rk e t M u t iliz in g

Qemp

=

q u a n tity o f p ro d u ct P p ro d u c e d , d e stin e d

a n d e u c a ly p t u s , the in it ia l stages b e g in w ith

p la n tin g a n d s ilv ic u ltu re . H e n c e fo rth , the re so u rce s take
on a s i m i la r p a th . A n e la b o r a t io n o f th e se s ta g e s

re s o u rc e E ; an d
fo r m a rk e t M , u t iliz in g re s o u rc e E .

a c c o r d in g to s c a le o f o p e ra tio n , g e a r o r m e th o d u s e d ,
re so u rc e s , a n d f in a l p ro d u c ts is p re se n te d in T a b le s
1 8 ,1 9 and 2 0 .

T h e c o m p u t a t io n a l f o r m s h o w s th a t w h ile a ll
le v e ls o f co sts are c o n s id e re d p e r a c tiv ity , o n ly the fin a l
:

49
Table 18. A ssum ed sequence o f production activities in the fishery sector, characterization and resources used.
Activity

Scale

Capture

Small

Technology

G ear

Resources

Labor
intensive

Handline

Crabs
Com m on hake
Mackerel
Com m on hake
Mackerel
Spanish sardine
Anchoveta
Cod
Albacore

Capital
intensive

Large

“Espinel”
Encircling
net

Capital
intensive

“Espinel”
Albacore
net
Encircling
net

Trawler

Processing

Small

Labor
intensive

Slaughter
Salting
Sm oking
Table and knife

Capital
intensive

Canning lines

Freezing lines

Fishm eal
plants

Large

Capital
intensive

Canning lines

Freezing lines

Fishmeal
plants

Storage

Large

Labor
intensive

Bulk
Sacks/crates

Capital
intensive

Small

Fish tank
Cold storage

Capital
intensive

Cold storage

Anchoveta
Com m on sardine
Mackerel
Spanish sardine
“M erluza de cola”
“M erluza com ún”
Black crab
Shrim p
A nchoveta
M ackerel
Com m on hake
Mackerel
Com m on hake
Mackerel
Com m on hake
Black crab
Mackerel
Spanish sardine
Sardine
Cod
Albacore
Com m on hake
Black crab
Mackerel
Spanish sardine
Sardine
A nchoveta
Mackerel
Spanish sardine
Sardine
Cod
Albacore
Com m on hake
Black crab
Shrim p
M erluza de cola
Mackerel
Spanish sardine
Sardine
Anchoveta
Shellfish
Crab
Com m on hake
Shellfish
Cod
Albacore
Comm on hake
Black crab
Cod
Albacore
Com m on hake
Black crab
Shrim p
continued

50
Tablel8. continued

Activity

Scale

Technology

G ear
W arehouse

Resources

Mackerel
Sardine
Spanish sardine
C ontainer
“M erluza de cola”
W arehouse
Mackerel
Sardine
_______________________________ Spanish sardine
Anchoveta
Fishmeal
“M erluza de cola”
Sacks/warehouse
M ackerel
Sardine
Spanish sardine
_______________________________ Anchoveta_______
________________________________________________________________________ Bottles________________ Fish oil__________
Transport
Small
Labor
Human hauling
Black crab
intensive
M ackerel
_______________________________ Com m on hake
Animals
Black crab
Mackerel
Com m on hake
Truck/van
Capital
Mackerel
intensive
Anchoveta
Sardine
Barges
Black crab
Mackerel
Com m on hake
Albacore
Capital
Refrigerated
Black crab
intensive
trucks
M ackerel
Com m on hake
Albacore
Shrimp
Trucks
Mackerel
Shellfish
Anchoveta
Sardine
Tankers
Bulk oil
Fishmeal sacks
Ship
Bulk meal
Cans
Frozen items

51
Table 19. A ssum ed sequence o f production activities in the forestry sector, characterization, resources used and final products.

Activity
Planting

Scale
Small

Large
Silviculture

Small

Large
H arvesting

Small

Technology
level
Labor
intensive
Capital
intensive
Capital
intensive
Labor
intensive
Capital
intensive
Capital
intensive
Labor
intensive
Capital
intensive

Large

Processing

Capital
intensive

Small

Labor
intensive
Capital
intensive
Labor
intensive
Capital
intensive

Large

Gear
Seeding by
hand
Plough
Anim al cart
Tractor
Ax/hatchet
Hacksaw
n.a.
M echanical saw
L um berjacks
Animal carts
L um berjacks
Tractors
M echanical saw
Lum ber jacks/mechanical
saws
Tractors
Oven
H atchet
n.a.
M akeshift sawmills
Chipm akers
Pulp and paper industry

Woodboard industry

Mechanized sawmills
Storage

Small

Large

Labor
intensive
Capital
intensive
Capital
intensive

Sacks
Bulk storage
W arehouse
Timberyard
Shed, storehouse

Stacking yard
Tanks
Transport

Small

Large

Labor
intensive
Capital
intensive
Capital
intensive

Anim al and human
Haulage
Light trucks
Tanks
Trucks

Train

PR
EG
EN

: P inus radiata.
: E ucalyptus globulus.
: Endem ic species.

Final products
(Resource used)

Ships

Charcoal/(PR, EG)
Firewood/(PR, EG)
n.a.
Lumber/(PR, EG, EN)
Wood products/(PR, EG, EN)
Chips/(PR, EG)
Chem ical pulp/(PR, EG)
M echanical pulp/(PR, EG)
Paper and carton/(PR, EG)
Particleboard/(PR)
Fiberboard/(PR)
Plywood/(PR, EG, EN)
Panel/veneer/(EN)
Lumber/(PR, EG, EN)
Wood oroducts/(PR. EG. EN)
Charcoal
Lum ber
Wood products
Paper and carton
Particleboards
Fiberboard
Plywood
Chips
Chemical pulp
M echanical pulp
Charcoal and firewood
Lum ber and wood products
Chemical pulp
M echanical pulp
Lum ber
Wood products
Chips
Logs for export
Lum ber
Wood products
Chips
Chemical pulp
M echanical pulp
Lum ber
Wood products
Logs_________

52
Table 20. U pper lim its o f catch levels (MO3), based on Schaefer yield functions segm ented into 6 groups, Y. (i = 1,2....6).

c o m m a n d in g the
h ig h e s t p r ic e s .

Species
Eels
H ake
Jack mackerel
Molluscs
Spanish sardine
Anchovy
Patagonian toothfish
Sw ordfish
Patagonian grenadier
Shrim p
Algae
Com m on sardine

Y,

Y,
1.3
12.0
550.0
2.0
20.0
50.0
22.0
0.8
72.0
0.04
5.5
130.0

1.9
22.0
1,000.0
2.5
25.0
75.0
0.35
1.30
84.0
0.065
9.50
180.0

Y,
2.4
30.0
1,430.0
3.2
32.0
95.0
0.45
1.90
94.0
0.095
13.0
220.0

y4

y

.2.7
34.0
1,720.0
3.6
36.0
108.0
0.53
2.4
100.0
0.12
15.0
250.0

5

2.9
36.0
1,850.0
3.9
39.0
115.0
0.58
2.7
104.0
0.13
16.0
270.0

Y*
3.0
37.0
1,900.0
4.0
40.0
117.0
0.60
2.9
106.0
0.135
16.5
280.0

H a k e an d ja c k
m a c k e r e l, w h ic h
a re m o r e a b u n ­
d a n t, c o m m a n d
lo w e r p ric e s .
A v e r a g e co st
o f p la n t in g p in e
v a r ie s

p ro p o r­

tion ally

w it h

s t o c k in g d e n s ity
( T a b le 2 6 ) . T h e
ra n g e s g iv e n fo r
s i lv i c u lt u r e a n d

p r o d u c t s t a g e , i . e . , t h a t w h ic h r e a c h e s f i n a l a n d

h a r v e s t in g c o r r e s p o n d to d if f e r e n t p r u n in g a n d

in te rm e d ia te c o n s u m e r , is in co rp o ra te d a s re v e n u e .

h a rv e s tin g rates. P r o c e s s in g , sto rage a n d tran sp o rt co sts
f o r p in e as w e ll a s d o m e s t ic a n d m a rk e t p r ic e s are

CO EFFIC IEN TS O F TH E O BJEC TIV E FUNCTION

sh o w n in T a b le 2 7 . N o t e th e h ig h m a rg in s b e tw e e n
ex p o rt a n d d o m e s tic p ric e f o r a ll b u t o n e p ro d u c t, w o o d

T h e c o e ffic ie n ts o f the o b je c tiv e fu n c tio n are p rice s
o f in p u ts a n d o u tp u ts. T a b le 2 1 s h o w s th e y ie ld le v e ls
a sso cia te d w ith e a c h o f the s ix se g m e n ts o f the S c h a e fe r
c u r v e ; h a rv e s tin g co s ts are p re se n te d in T a b le 2 2 . T h e
in c r e a s in g c o s t fu n c tio n c a n b e e x p la in e d b y F ig . 1 1
w h ic h d e p ic ts lin e a r ly d e c r e a s in g y ie ld p e r effo rt as
effo rt in c r e a s e s . C o s t p e r u n it o f effo rt w a s a s s u m e d
co n sta n t a n d th u s b e c o m e s an in c r e a s in g fu n c tio n o f
o u tp u t ( A g u e r o 1 9 8 7 ) .

c h ip s .
N o p la n t a t io n a c t iv it ie s w e re a s s u m e d fo r
e u c a ly p t u s . H o w e v e r , p r u n in g a n d h a r v e s t in g c o sts
w ere a ls o sh o w n to v a r y w ith le v e l o f e x p lo ita tio n , i.e .,
U S $ 3 3 . 3 3 - 1 5 6 h a . O t h e r co s ts as w e ll a s p r ic e s are
p ro v id e d in T a b le 2 8 . L o g s , p u lp a n d w o o d c h ip s are
m a rk e te d e n tire ly in fo re ig n m a rk e ts w h ile p ly w o o d ,
v e n e e r a n d f ir e w o o d a re s o ld e n t ir e ly in th e lo c a l
m a rk e ts.

T a b le 2 3 s h o w s th e p ro c e s s in g c o s ts p e r p ro d u ct
lin e a n d the sp e cie s that un d erg o s u c h p ro c e s s in g . C o s t s

THE CONSTRAINTS

w e re a s s u m e d to b e co n sta n t o v e r a ra n g e o f d iffe re n t
s p e c ie s . P r o c e s s in g o f fre s h a n d d r ie d f is h p ro d u cts
in c u r the le a s t c o s t w h ile c a n n in g in c u r s the greatest

T h e typ e o f co n stra in ts u s e d in th is e x e r c is e in
a d d itio n to the n o n n e g a tiv it y co n s tra in ts are :

co st. A m o n g the s p e c ie s , ja c k m a c k e re l a n d the sa rd in e
sp e c ie s are su b je c te d to m o st typ e s o f p ro c e s s in g ; a lg a e

1 ) C o n v e x it y

is o n ly p r o c e s s e d in t o it s d r ie d f o r m a n d b a c a la o ,
a lb a c o re , a n d e e ls as fre s h a n d fro ze n .
S t o r a g e , tr a n s p o r t a n d m a r k e t in g c o s t s a re

- X ( b i+ 1 * l) + b 1 = 0

...4)

p re se n te d in T a b le 2 4 . T ra n s p o rt o f fre sh a n d fro ze n
f is h is m o re e x p e n s iv e d u e to its h ig h p e r is h a b ilit y .

w h ere

S to ra g e c o sts f o r fre s h a n d fro z e n a n d w e ll a s d rie d
f is h are r e la tiv e ly c h e a p e r d u e to the s im p le r te ch n o lo g y

b‘

re s o u rc e b io m a s s in se c tio n i ; a n d

re q u ire d , i.e ., c ra te s a n d ic e ch e sts.

n

n u m b e r o f se ctio n s c o n s id e re d (s ix , in th is

A v e r a g e w e ig h te d p r ic e o f p ro c e s se d fis h p ro d u cts

a p p lic a t io n ).

a n d m a rk e t d e stin a tio n v a r ie s a c c o r d in g to sp e c ie s u s e d
( T a b le 2 5 ) . T h e p r ic e o f f is h m e a l a n d o i l is n o t

2 ) B a la n c e

d e p e n d e n t o n th e f is h s p e c ie s ; c o n tra r ily , fro z e n f is h is
h ig h ly s e n s itiv e w ith s h r im p s , b a c a la o a n d a lb a c o re

pr * b‘- Qrp = 0

...5)

53
Table 21. Assumed harvesting costs (in US$ t ‘) for various fish species and yield levels.
Harvesting costs
Resources

Y,
413
150
4,014
334
148
604
231
61
536
55
1,086
1,593

Eels
Hake
Jack m ackerel
Molluscs
Spanish sardine
Anchovy
Patagonian toothfish
Swordfish
Patagonian grenadier
Shrimp
Algae
C om m on sardine

Y,
603
275
7,299
418
185
906
375
98
626
90
1,754
2,206

y

3

6

y4

762
374
10,437
534
237
1,148
549
126
700
132
2,338
2,697

Y,

y

857
424
12,554
601
267
1,305
396
148
745
166
2,672
3,064

921
449
13,503
651
289
1,390
780
162
775
180
2,839
3,310

953
462
13,868
668
297
1,414
837
168
790
187
2,923
3,432

Note: Harvesting costs correspond to each yield segm ent (Table 20).

Table 22. Assum ed processing costs (in US$ t1 by product.
)
Product

Fresh
Frozen
Meal A
M eal B
Dried
Canned

Processing
cost
55.55
416.62
97.61
97.61
40
686.92

Eels

Hake

X
X

Jack
mackerel

X

X
X
X

Spanish
sardine

Comm on
sardine

X
X
X
X

X
X
X

X
X

X

M ollusc

X

X

X
X

Anchovy Toothfish Sw ordfish Grenadier
X
X

X
X

Shrim p

X
X
X

X

X
X

X

Table 23. A ssum ed storage, transport and marketing costs (in U S $ 4 1 per
)
type o f processed fish product.

Yield (Y)

Costs
Product
Fresh
Frozen
Fishmeal A
Fishm eal B
Dried
Canned

Algae

Storage

Transport

M arketing

1.5
1.5
12.0
12.0
1.5
6.0

43
43
30
30
30
30

20
22
26
20
10
25

C

D

Y /f

Fig. 11. Fundamental relationships between biological characteristics
of fish resources and technology of capture and various cost factors.
A) Relationships between yield and the underlying fish biomass
(note that B,  B2  B3). B) Relationships between yield, effort and
the quotients cost per unit of yield and yield per unit of effort. C)
Relationships between yield per effort, effort and cost per unit of
yield.

E ffo rt

Cost per unit of yield

54
Table 24. Average weighted price (export and domestic) (in U S S t 1 o f processed fish products.
)
Price
Species
Fresh

M eal B

400

450

400
400

450
450

138
138

150
150

450

138

150

591

400

450

138

150

5
95

5,500

M eal A

400

Eel
Hake
Jack m ackerel
M ollusc
Spanish sardine
Anchovy
Toothfish
Sw ordfish
G renadier
Shrim p
Algae
Com m on sardine
M arket distribution
Dom estic
Export

Frozen

45
55

62
38

5,000
5,000

2,143
1,779
1,435
4,500
682

5,000
7,567

Oil A

Oil B

Dried

Canned

6,150
6,939

867
8,000
1,000

8,596
532

0
100%

1,000

Table 25. Plantation, culture and harvesting cost (in U S S h a 1 o f pine at various stocking densities.
)
Stocking
density 1
769 s h a 1

Plantation
Silviculture
Harvest

Stocking
density 3
2,190 s ha-1

Stocking
density 4
3,280 s h a1

440
6.7-21.8
36.6-115.8

Pine

Stocking
density 2
1,845 s h a1
460
6.2-21.9
34.4-109

462
6.2-17.5
31.3-99.5

480
5.5-17.5
31.2-97.8

Table 26. Processing, transport and storage costs (in US$-m3) for wood products derived from pine and
corresponding market prices.
Price
Product type

Processing

Logs
Lumber
Wood products
Chips

6.0
5.7
5.5
3.1

Transport (pine)

Storage

International

Domestic

1.1
1.2
2.0
1.7

3.0
2.5
2.5
2.0

40
51
125
166

25
28
63
183

55
Table 27. Processing, transport and storage costs (in US$ m 3) for wood products derived from eucalyptus and
corresponding m arket prices.
Price
Product type

Processing

Logs
Pulp
C hips
Plywood
Veneer
Firewood

5.1
4.5
3.1
4
5.5
1

Transport (pine)
3
2.7
2.5
3.2
2.5
1.5

1.1
1.7
1.5
1.2
2
0

International
48
418
60
n.a.
n.a.
n.a.

Domestic
n.a.
n.a.
n.a.
265
296
0

5 ) L a n d a v a ila b ilit y

Table 28. Estimates o f net benefit per sector from LP
exercise.

Economic sector

Storage

Net benefit
(US$.103-year)

A_ + A

 = T o tal A re a

...9 )

T h e o n ly re a l re so u rce c o n stra in t u s e d in the m o d e l
Fishery
Mackerel
Common hake
Others
Forestry
Pine
Eucalyptus
Total

171,358
120,177
21,551
29,630
1,186,410
105,552
1,080,858

is the a v a ila b ilit y o f la n d f o r fo re st p la n ta tio n . T h e a re a
p la n te d to p in e a n d e u c a ly p tu s m u st b e le s s than or
e q u a l to total p la n ta tio n area.

T HE MATRIX COEFFICIENTS

1,357,768

Environment

C o e f f ic ie n t s p e rta in to the y ie ld p e r se g m e n t, as in
fo restry, or c a tc h a b ility , as in the fish e ry . In m o st ca se s,

(20,000)

Total

c o e ffic ie n ts are e x o g e n o u s ly d e te rm in e d p erce n ta g e s
s u c h as th e d is a g g r e g a tio n o f h a rv e s ts b y s c a le o f

1,137,768

o p e r a t io n , ty p e o f g e a r, p r o d u c t ty p e a n d m a rk e t
T h e e q u a tio n in d ic a t e s th e c o n v e r s io n rate (p r)

d e s t in a t io n . In lik e m a n n e r, c o e f f ic ie n t s re p re se n t

re p re se n ta tiv e o f a p a r tic u la r p ro d u c tio n p ro c e s s , sa y

d is a g g re g a tio n o f f in is h e d w o o d a n d fis h p ro d u cts into

fro ze n f is h o r f is h m e a l in the c a s e o f fis h p ro c e ss in g ,

its d iffe re n t fo rm s.

at w h ic h th e b io m a s s is c o n v e r t e d in to a f in is h e d

T h e m a trix co e fficie n ts, constants o f the o b je ctive
fu n ctio n an d co n strain t elem en ts are in co rp o rated into a

p ro d u c t (Q r p ).

fin a l L P tableau that is a 7 8 2 x 5 3 0 m a trix (A p p e n d ix 1 ).
3 ) B a la n c e
R rp * Q rp - Q ra = 0

...6)

Environmental Externalities
A m o n g th e n u m e r o u s e n v ir o n m e n t a l e f f e c t s

T h e o u tp u t o f a c t iv it y A
the n e x t a c t iv it y A

b e c o m e s the in p u t fo r

re s u ltin g f r o m a c t iv it ie s in the f is h e r y a n d fo re stry

, i.e ., n o w a stag e is in v o lv e d .

secto r, o n ly w ate r c o n ta m in a tio n as a c o n s e q u e n c e o f
the f is h p ro c e s s in g a c tiv itie s w a s q u a n tifie d here. A n

4)

C o n v e x it y o f d e m a n d

in d e x o f w ater p o llu tio n is the d e cre ase o f o x y g e n le v e ls
as m e a su re d b y d is s o lv e d o x y g e n ( D O ) le v e ls . O x y g e n

( 1 / Q r a ‘) * Q r a  = 1

...7 )

c o e f ( Q r a 1) * Q r a  = 1

...8)

or

is re m o v e d fr o m the w ate r as the o r g a n ic m atter in it
d e c a y s . A c c o r d in g to I F O P ( 1 9 8 8 ) , liq u id e fflu e n ts o f
fis h m e a l p la n ts re a c h B D 0 7 le v e ls e q u a l to 0 .5 7 k g t 1
o f f is h p ro ce sse d . In o rd e r to m a in ta in an a cce p ta b le

T h is e q u a tio n in d ic a te s that e a c h a c tiv ity c a n b e

sta n d ard ( B D 0 7 1 0 m g I 1, as in S p a in ) , it is n e c e ssa ry

ta ke n as a se g m e n t o f the total d e m a n d c u rv e , th u s, the

to d ilu te the a ffe cte d a re a b y 5 7 ,0 0 0 1 fo r e v e r y tonne

re stric tio n  = 1 .

o f f is h p ro ce sse d .

56

To implement this, a constant in the objective
function was added, i.e., imputing the cost o f freshwater,
here assumed to be US$ 1 -t1. The constraint row merely
summed up total fish processed and is similar in form to
the balance equations enumerated above.

Results and Discussion
Results

The solution to the linear programming problem
is the estimate o f total net benefit generated by fishery
and forestry. In the process, the solution identifies the
optimum values o f the variables which vary from one
sector to another. In the fishery, the variable is the
amount o f fish “handled” at each activity level while
in the forestry sector, the quantity of wood and/or wood
products. The algorithm used in linear programming
essentially estimates dual values as well as right-hand
side and objective function coefficient ranges, but due
to the absence o f real resource constraints the dual
values as w ell as the right-hand side ranges are not
analyzed.
Total net benefit amounts to U S$1.36 billion-year1,
87% o f which is accounted for by forestry; the fishery
contributes US$171 million (Table 29). The Chilean
jack mackerel, which is sold at international and
national markets as frozen, fishmeal and oil, contributed
70% o f sectoral revenue while hake, marketed only as
frozen, ranked second (Table 30). The optimum annual
harvesting levels for jack mackerel and hake are 1.9
million t and 37,000 t, respectively. These levels are
contingent on several factors including final market
demand, transport, processing and storage capacity, as
well as current levels o f effort in the industrial capture
fishery.
The large-scale sector contributes a major portion
o f catch for hake, jack mackerel, Spanish sardine,
anchoveta and Patagonian grenadier whereas the smallscale sector dominates the capture o f eels, molluscs,
bacalao, albacore and algae.
In the forestry sector, the optimum areas planted
to pine and eucalyptus are 50,000 and 30,000 ha,
respectively. All areas planted to pine are based on a
stocking density of 3,280 seedlings h a 1. No planting
is involved in the case o f eucalyptus.
Total quantity o f timber is based on the amount
harvested and/or thinned, as part o f silvicultural

practices. Logs constitute a major use o f pines and the
optimum level o f export was estimated at 1,384 m3
(Table 31). In addition to wood products and wood
chips, eucalyptus is also used for veneer and firewood.
Wood chips constitute the major export and is valued
at an average price o f US$60-t ‘. N o pulpwood is
extracted from both species.
The optimum net benefits are diminished by a total
o f U S $20 m illion considering the environm ental
externalities attributed to pollutants from fishmeal
plants. This represents the co st o f p um ping in
freshwater to improve the DO levels. The estimate of
optimum net benefits should be lower due to a larger
number o f externalities which could not be quantified.
W hile real resource constraints were missing and
that many variables were exogenously determined, the
emphasis o f this application is the linkage between
different activities within each sector to arrive at an
optim um quantity. Thus, the optim um quantity
harvested is not based on biomass constraints or effort
constraints alone but also by demand conditions for
the final product.
The relevance o f coastal zone m anagem ent and
the “system s approach” espoused in A giiero et al.
(this vol.) is highlighted by the interconnectedness
o f econom ic activities in the fishery and forestry^
A succinct exam ple is the determination o f optimal
catch levels in the capture fishery which was shown
to be an indirect function o f final market demand
and constrained by p revailing cap acities in the
transport, storage and processing sectors. W ithout
such fram ework, optim al catch lev els w ould be
based, for exam ple, on either M SY or MEY, which
are purely biological parameters. Even the latter,
which at best considers appropriate measures of
opportunity costs o f the factors o f production,
thereby incorporating m acroeconom ic factors, is
relatively m yopic and still quite lim ited to the
capture fishery sector.
This framework has the potential of estimating the
impact of factors outside the capture fishery sector on
itself, e.g., changes in storage fees or in increased demand
for substitute products. Unfortunately, this particular
application, though not of linear programming in general,
did not deal with real resource constraints. A useful
sensitivity analysis would have emerged if hypothetical
cases of increased or decreased resource endowments
could be measured against potential economic benefits
and on the values of the variables.

Table 29. Optimum levels of production (in t-103y e a r) resulting from LP exercise, by product type, activity and m ajor species.

Activity
Capture
Large scale
Small scale
Processing
Fresh
Before processing
After processing
Frozen
Before processing
A fter processing
Fishmeal and oil
Before processing
Fishmeal A
Fishm eal B
After processing
Fishmeal A
Fish Oil A
Fishm eal B
Fish O il B
Dried
Before processing
A fter processing
Canned
Before processing
A fter processing
Storage
Fresh
Frozen
Fishmeal A
Fishmeal B
Dried
Canned fish
Transport
Fresh
Frozen
Fishmeal A
Fishmeal B
Dried
Canned fish
M arketing
Fresh
Frozen
Fishmeal A
Fishmeal B
Dried
Canned fish

Hake

3.00
0.90
2.10

37.00
35.52
1.48

Jack
mackerel

S panish
sardine

Anchovy

4.00

40.00
39.60
0.40

115.04
78.20
36.90

0.40
0.36

Crabs

Toothfish

Swordfish

2.90
2.90

0.60
0.00
0.60

0.03
0.02

0.01
0.01

0.04
0.04

1.10
0.22

2.12
1.42

2.89
1.53

0.56
0.36

1,773.43
620.70
1,152.12

37.85
13.25
24.60

114.62
40.12
74.51

103.56
36.25
67.32

136.55
27.93
253.60
69.16

3.05
0.60
5.66
1.48

8.83
1.81
16.39
4.47

7.25
1.63
13.46
4.04

1,898.96
1,898.96

0.01
0.01
2.99
1.59

37.00
17.76

13.48
5.53

M olluscs
4.00

Grenadier

Shrim p

103.98
102.94
1.04

0.14
0.14

0.42
0.13

Algae

0.14
0.14

16.00
0 .00
16.00

16.00
15.20

42.36
0.01
1.59

108.62
0.58

17.76
136.55
253.60

5.53

42.36

0.03
0.01

0.36
0.22
3.05
5.66

0.58

17.76
136.55
253.60

2.89

5.53

0.02
1.42
8.83
16.39

0.04
0.36
7.25
13.46

0.13

0.03

15.20

0.01
1.59

0.01

3.05
5.66

0.02
1.42
8.83
16.39

0.04
0.36
7.25
13.46

0.13

0.03

15.20
42.36
0.01
1.59

0.01
0.36

17.76
136.55
253.60

5.53
3.05
5.66

0.02
1.42
8.83
16.39

0.04
0.36
7.25
13.46

0.13

0.03

15.20
42.36

0.01
continued

in

oo

Table 29. continued
Activity
Sales
Fresh
International
Domestic
Frozen
International
Domestic
Fishmeal A
International
Domestic
Fishmeal B
International
Domestic
Fish oil A
International
Domestic
Fish oil B
International
Domestic
Dried
International
Domestic
Canned
International
Domestic
Net benefit (U S $103)

Crabs

Jack
mackerel

M olluscs

Spanish
sardine

0.36

Hake

Anchovy

Toothfish

Sw ordfish

0.02

0.01

0.04

0.21
0.01

1.35
0.07

1.46
0.08

0.34
0.02

1.68
0.02

4.85
3.97

3.99
3.26

1.35
2.15

6.23
10.16

5.12
8.35

27.93

0.60

1.81

1.63

69.16

1.48

4.47

4.04

0.01

1.51
0.08

5.28
16.87
0.89
136.55
75.10
61.45
253.60
96.37
157.23

5.22
0.06

G renadier

0.13
0.01

Shrim p

Algae

0.03
0.00

0.46
14.74
0.43
0.14
1,600.8

21,550.81

120,176.84

0.01
0.00
5,065.87

2,286.37

5,207.66

7,459.51

2,299.04

4,658.38

21.39

1,030.73

59
Table 30. O ptim um estim ates (in m ’ 10’) o f LP exercise for forestry sector, by product type, activity and species.
Activity levels

Pine

Plantation and
silviculture
Q uantity thinned
Q uantity o f tim ber extracted
H arvesting
Q uantity harvested
Q uantity o f tim ber extracted
Total quantity of tim ber
Processing
Raw material inputs
Logs
Lumber
Wood products
Wood chips
Veneer
Firewood
O utput
Logs
Lumber
Wood products
Wood chips
Veneer
Firewood
Storage
Logs
Lum ber
Wood products
Wood chips
Veneer
Firewood

Eucalyptus

800.00
800.00

1,546.39
17,647.06

9,090.90
9,090.90
9,890.90

17,647.06
17,647.06
19,193.45

3,659.63
1,681.45
2,868.36
1,681.45
n.a.
n.a.

n.a.
n.a.
1,919.30
14,395.00
1,919.30
959.67

2,308.13
907.98
1,548.92
1,218.72
n.a.
n.a.

n.a.
n.a.
1,036.45
10,433.56
1,036.45
191.93

2,308.13
907.98
1,548.92
1,218.72
n.a.
n.a.

n.a.
n.a.
1,036.45
10,433.56
1,036.45
191.93

References
A gü ero , M. 1987. A b io eco n o m ic m odel o f the P eruvian pelagic
fishery, p. 307-324. In D. Pauly and I. T sukayam a (eds.) The
P eru v ian an ch o v eta and its upw elling ecosystem : three decades
o f change. 1CLARM Stud. Rev. 15, 351 p.
C E P A L . 1990. U n a e s tim a c ió n de la m a g n itu d de la p o b re z a en

Activity levels
Transport
Logs
Lumber
Wood products
Wood chips
Veneer
Firewood
Sales
Logs
International
Domestic
Lumber
International
Domestic
Wood products
International
Domestic
Wood chips
International
Domestic
Veneer
International
Domestic
Firewood
International
Domestic

N et revenue (US$)

Pine

2,308.13
907.98
1,548.92
1,218.72
n.a.
n.a.

Eucalyptus

n.a.
n.a.
1,036.45
10,433.56
1,036.45
191.93

1,384.80
923.20
635.59
272.40
1,239.13
309.78

0.00
1,036.45

1,218.71

10,433.56
0.00
0
1,036.45
0
191.93

105,552.47

1,080,858.35

C h ile . E c o n ó m ic a p a ra A m é ric a L a tin a y e l C a rib e , S a n tia g o ,
C h ile .
COREM A. 1992. Aspectos generales sobre recursos y contam inación en
la V III R e g ió n . C o m is ió n R e g io n a l d e M e d io A m b ie n te ,
C oncepción, Chile.
IFOP. 1988. A nálisis de la activ id ad p e s q u e ra e x tra c tiv a n acio n al.
C aracterización Flota Pesquera Industrial. F lota C erquera. IFOP,
Santiago, Chile.

A nnex 1. H ydrobiological resources o f C hile exploited at the national and regional (B io -B io ) level (*).
Local name

S cientific name

Presence o f species
in B io -B io , Chile

Fish
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
38.
39.
40.
41.
42.
43.
44.
45.
46.
47.
48.
49.
50.
51.
52.
53.
54.
55.
56.
57.
58.
59.
60.

A cha
A gujilla
A lbacora
A nchoveta
A nguila
A pañado
A tún aleta amarilla
A tún aleta larga
A tún de ojo grande
A yanque
A zulejo
Bacalao de profundidad
Bacalao o mero
B lanquillo
B onito
Breca
B rótula
Caballa
Cabinza
Cabrilla
Cabrilla común
Cachurreta
Caz.ón
Chancharro
Cojinoba del norte
Cojinoba moteada
Cojinoba del Sur
Congrio colorado
Congrio dorado
Congrio negro
Corvina
D orado
Jurel
Lenguado de ojos chicos
Lenguado de ojos grandes
Lisa
M achuelo
M arrajo
M erluza del sur
M erluza de cola
M erluza de tres aletas
M erluza común
M ulata
Nanue
Palom eta
Pam panito
P ejegallo
Pejeperro
Pejerrata
Pejerrey de mar
Pejesapo
Pejezorro
Peto
Raya
Reineta
Róbalo
Rollizo
R oncacho
Salmón del Pacifico
Salmón del Atlántico

 In d ic a te s p r e s e n c e o f s p e c ie s .

Kyhosus analogus
Scomberesox saurus
Xiphias gladius
Engraulis ringens
Ophictus spp.
H emilutjanus macrophthalmos
Thunnus albacares
Thunnus alalunga
Thunnus obesus
Cynoscion analis
Prionace glauca
Dissostichus eleginoides
Polyprion spp.
Prolatilus jugularis
Sarda chiliensis
Acantholatris gayi
Salilota australis
Scom ber japónicas
Isacia conceptionis
Sebastes oculatus
Paralabrax humeralis
Katsuwonus pelam is
Galeorhinus ziopterus
H elicolenus lengerichi
Seriolella violácea
Seriolella porosa
Seriolella caerulea
Genypterus chilensis
Genypterus blacodes
G enypterus maculatus
Cilus montti
Coryphaena hippurus
Trachurus murphyi
Paralichthys microps
Hippoglossina macrops
M ugil spp.
Ethmidium maculatum
Isurus glaucus
M erluccius australis
Macruronus magellanicus
Micromesistius australis
M erluccius gayi
Graus nigra
Girellops nebulosas
Parona signata
Stromateus stellatus
Callorhinchus callorhinchus
Pimelometopon maculatus
Coelorhynchus spp.
Odonteshes spp.
Sicyases sanguineus
Alopias vulpinus
Acanthocybium solandri
Raja spp.
Lepidotus australis
Eleginops maclovinus
M ugiloides chilensis
Sciaena spp.
Oncorhynchus spp.
Salmo salar

*
*

*
*

*
*
*
*

*
*
*
*
*
*
*
*

*
*
*
¡«
1
*
*
*

*
*
*
*

*

*

c o n tin u e d .

A nnex 1. continued

Local ñame

61.
62.
63.
64.
65.
66.
67.
68.
69.
70.

Sardina
Sardina común
Sargo
Sierra
Tollo
Tomoyo
Trucha arco iris
Trucha café
Trucha de arroyo
Vidriola

Molluscs
1. Alm eja (taca)
2.

3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.

3.
4.
5.
6.
7.
8.
9.
10.
II.
12.
13.
14.
15.
16.
17.
Algae
1.
2.
3.

Presence of species
in Bio-Bio, Chile

Sardinops sagax
Clupea bentincki
Anisotremus scapularis
Thyrsites atun
M ustelus mentu
Labrisomus philipii
Salmo gairdneri
Salmo trutta
Salvelinus fontinalis
Seriola mazatlana

*
X

X
X


X

Venus antiqua
Protothaca thaca
Loligo gahi
Thais chocolata
Chorus giganteus
Tegula atra
Calyptraea trochiformes
Aulacom ya ater
M ytilus chilensis
Choromytilus chorus
Gari solida
Dosidicus tunicata
Fissurella spp.
Concholepas concholepas
M esoderma donacium
Solen gaudichaudi
Ensis macha
Tagelus dombeii
Chlamys purpurata
Chlamys patagonica
Ostrea chilensis
Crassostrea gigas
Odontocymbiola magellanica
Octopus vulgaris

X

Rhynchocinetes typus
Heterocarpus reedi
Lithodes antarticus
Paralomis granulosa
Haliporoides diomedeae
Cancer edwardsii
Cancer porteli
Homalaspis plana
Cancer setosus
Cancer coronatus
Euphausia superba
Jasus frontalis
Panulirus pascuensis
Cervimunida johni
Pleuroncodes monodon
Municla subrugosa
M egabalanus psittacus

X

Camarón nailon
C entolla
Centollón
Gamba
Jaiba
Jaiba limón
Jaiba mora
Jaiba peluda
Jaiba reina
Krill
Langosta de Juan Fernández
Langosta de Isla de Pascua
Langostino am arillo
Langostino colorado
Langostino de los canales
Picoroco

Chasca
Chasca gruesa
Chascón

Gelidium rex
Gymnogongrus furcellatus
Lessonia nigrescens

Alm eja
Calamar
Caracol lócate
Caracol trumulco
Caracol tegula
Chocha
Cholga
Chorito
Choro zapato
Culengue
Jibia
Lapas
Loco
Macha
Navaja de mar
Navaja de mar
Navajuela
Ostión del norte
Ostión del sur
Ostra
Ostra del Pacifico
Piquihue
Pulpo

Crustaceans
1. Camarón de roca
2.

Scientific name

X

*
==
1
X

X
X
X

X
X
X
X

X

.
X

X
X
X
X

X

X

X

X

continued.

A nnex 1. continued
Local ñame

S cientific ñame

Presence o f species
in B io -B io , Chile

4.
5.
6.
7.
8.
9.
10.
11.
12.

Chicorea de mar
Cochayuyo
Huiro
Lechuha de mar
Liquen gomoso
Luche
Luga-luga
P elillo
A nhfeltia

M astocarpus papillatus
D urvilaea antárctica
M acrocystis pyrifera
Ulva lactuca
Chondrus canaliculatus
Phorphyra columbina
Iridaea ciliata
Glacilaria spp.
Anhfeltia plicata

*
%

*
*
*

Echinoderm s

Eriz.o

Loxechinus albus

H em ichordate

Piure

Pyura chilensis

*

Annex 2. P rincipal native forest species o f C hile and Region V I I I (*).
Local ñame

S cientific ñame

Presence o f species
in B io -B io , Chile

1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.

A raucaria
Ciprés de Cordillera
Alerce
Ciprés de Guaitecas
M anió de Hojas Largas
M anió de Hojas Punzantes
Lleuque
M anió de Hojas Cortas
Espino
Palma Chilena
Algarrobo
Tamarugo
Pim iento
Pelu
Tineo
Avellano
Trevo
Naranjillo
O livillo
Lingue
Litre
Canelo
Notro
Quillay
M aitén
Sauce Chileno

“
indicate presence o f species.

Araucaria araucana
Austrocedrus chilensis
Fitz.roya cupressoídes
Pilgerodendron uriferum
Podocarpus salignus
Podocarpus nubigemas
Podocarpus andinus
Saxegothaea conspicua
A cacia caven
Jubaea chilensis
Prosopis chilensis
Prosopis tamarugo
Schinus molle
Sophora microphylla
Weinmannia trichosperma
Gevuina avellana
Dasyphyllum diacanthoides
Villarez.ia mucronata
Aextoxicom punctatum
Persea lingue
Lithraea caustica
Drimys winteri
Embothrium coccineum
Quillaja saponaria
M aytenus boaria
Salix chilensis

*
*

*
*

*
*
*
*

*
*
*
*

*
*
*

continued.

A nnex 2. continued

Local ñame

S cientific ñame

Presence o f species
in B io -B io , Chile

27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
38.
39.
40.
41.
42.
43.
44.
45.
46.
47.
48.
49.
50.
51.
52.

Coigue de Chiloé
Coigue
Coigue de M agallanes
Roble
Ñirre
Rauli
Ruil
Bollan
M olle
Radal
Lenga
Hualo
Baldo
Peumo
Bellota del Sur
Bellota del Norte
Qeule
Arrayán
Pitra
Luma
M eli
Patagua
Laurel
Tepa
Tiaca
Ulmo

Nothofagus nítida
Nothofagus dombeyi
Nothofagus betuloides
Nothofagus obliqua
Nothofagus antárctica
Nothofagus alpina
Nothofagus alessandri
Kageneckia oblonga
Schinus latifolius
Lomatia hirsuta
Nothofagus pum ilio
Nothofagus glauca
Peumus boldus
Cryptocarya alba
Beilschmiedia berteorana
Beilschmiedia miersii
Gamortega keule
Luma apiculata
Myrceugenia exsucca
Am om yrtus luma
Am om yrtus meli
Crinodendron patagua
Laurelia sempervirens
Laurelia philippiana
Caldcluvia paniculata
Eucryphia cordifolia

*

*
*
*

*

*
*
*
*
*

*
*
*
*
*

*
*
*

Options for Land Use Management
in Lingayen Gulf, Philippines*

A

nnabelle

C

ruz

-T

r in id a d

and

Z

o r a id a

A

lo ja d o

,

In te r n a tio n a l C e n te r f o r L iv in g A q u a tic R eso u rces
M a n a g em en t, M C P O B o x 2631, 0 7 1 8 M a ka ti City,
Philippines
A g n e s G r a c e G . C a r g a m e n t o , National Economic and
Development Authority (NEDA) Region I, San Fernando,
La Union, Philippines

CRU Z-TRINIDAD , A., Z. ALOJADO and A.G.C. CARGAMENTO. 1996.
Options for land use m anagem ent in Lingayen Gulf, Philippines, p.
64-77. In A, C ru z-T rin id ad (ed.) Valuation o f tropical coastal
resources: theory and application o f linear programming. ICLARM
Stud. Rev. 25, 108 p.

Abstract
In view o f the fast-changing pace of land use in the Lingayen G ulf
area, P hilippines, this study estim ates optim al land use com binations,
particularly with respect to aquaculture. A direct cost and revenue approach
would result in total net revenues o f P7.4 billion or US$0.29 billion and
total conversion o f rem aining m angrove areas to milkfish ponds. However,
the Total Econom ic Value (TEV) approach resulted in a net revenue o f P35
billion with the follow ing land use scenarios: i) no mangrove conversion;
ii) conversion o f salinized ricelands to milkfish ponds; and iii) conversion
of grasslands to shrim p ponds. The results em phasize the im portance of
valuation as this greatly influences the results o f linear program m ing
solutions.

research components which independently determined
suitable areas for human settlements (Cargamento and
Rillon 1994), tourism (Cargam ento et al. 1994),
mangrove reforestation (Alojado et al. 1994) and
brackishwater development (Paw et al. 1994).
Paw et al. (1 9 9 4 ) determ ined su itab ility for
brackishwater pond siting using several physical criteria
including soil type, elevation, physiography, access to
road networks, and access to water and land use. This
study prioritized marginal lands (grasslands, swamps),
coconut plantations, and unproductive agricultural
lands as well as degraded mangroves as having the
greatest potential for conversion.
As a complement to the study by Paw et al. (1994),
this study focuses on net economic returns o f particular
land use options to determ ine the fea sib ility o f
converting to aquaculture (both shrimp and milkfish)
or to retain the use o f land. Four land types are
considered: 1) productive ricelands, 2) salinized
ricelands, 3) grasslands, and 4) m angroves. The
fram ew ork used is a constrained m axim ization
approach where optimal land use results in the greatest
level o f net revenue for society. Net revenues are valued
using a direct cost and revenues approach, future value
approach and foregone earnings approach. The last two
were used to account for indirect and nonuse values in
accordance with the Total Econom ic Value (TEV)
concept.

Lingayen Gulf Profile
Introduction
Lingayen G ulf was the Philippine pilot site o f the
A S E A N -U S A ID Coastal R esources M anagem ent
Project which was executed by the International Center
for Living Aquatic Resources Management (ICLARM)
from 1986 to 1992. The study produced several
technical reports including the Lingayen Gulf Profile
(McManus and Chua 1990) and the Lingayen Gulf
Coastal Area M anagem ent Plan (N ED A Region I
1992). The area was subsequently studied using an
approach based on Geographic Information Systems
(GIS) with the major objective of a zonation scheme
for both land use and water space utilization (Paw et
al. 1994). This latter project was comprised o f several

♦ICLARM Contribution No. 1220.

Resource-based Activities and Issues:
Fisheries, Aquaculture and Tourism
Lingayen Gulf, located in northwestern Luzon,
Philippines, has a surface area o f 2,100 km2 and is
bounded by the provinces of La Union and Pangasinan.
Seventeen municipalities border the Gulf; ten are from
Pangasinan, namely: Alaminos, Anda, Bani, Bolinao,
Sual, Labrador, Lingayen, Binmaley, San Fabian and
Dagupan, while seven are from La Union, namely:
Agoo, Aringay, Bauang, Caba, Rosario, San Fernando
and Sto. Tomas (Fig. 1).
Previous studies have delineated the Gulf into three
sectors (Mines 1986). Sector I includes the munici­
palities of Sual towards the northernmost tip of Bolinao,
characterized by hard-bottom coralline substrates. Most
brackishw ater ponds and traw ling a ctiv ities are
64

65

lo c a liz e d in S e c to r I I , c h a ra c te r iz e d b y soft a n d m u d d y

re la te d a c t iv it ie s a c c o u n t f o r 8 3 % o f to ta l e m p lo y m e n t

su b strate s a n d in S e c to r I I I , w ith s a n d y sub strate s.

in S e c to r I I I b u t o n ly 4 6 % in S e c to r I w h e re f a r m in g is

T h e p o p u la t io n o f P a n g a s in a n a n d L a U n io n

a m o re im p o rta n t o c c u p a tio n .

p r o v in c e s w a s e stim a te d at 1 . 1 5 m illio n in 1 9 8 9 b y the
P h ilip p in e N a t io n a l C e n s u s a n d S t a tis tic s O f f ic e w ith

FISHERIES

an a v e ra g e o f 4 0 % liv in g n e a r the co ast. D e n s it y is

T h e f is h e r ie s o f L in g a y e n G u l f c o n s is t s o f the

h ig h e st in S e c t o r I I at the m u n ic ip a l a n d v illa g e le v e ls .

c o m m e r c ia l a n d m u n ic ip a l se cto r. T h e c o m m e r c ia l

E s t im a t e d p o p u la t io n g r o w t h ra te is 3 . 2 %

at th e

se cto r is re p re se n te d b y at le a s t t h ir t y -e ig h t tra w le rs

m u n ic ip a l le v e l b u t is e stim a te d to r e a c h 1 2 % in the

w h ic h in c re a s e d tw o fo ld b y the 1 9 9 0 s o w in g to the

c o a s ta l v illa g e s ( M c M a n u s a n d R iv e r a 1 9 9 0 ) .

tr a w lin g b a n in M a n ila B a y . T h e in c r e a s e in n u m b e rs

F e r r e r et a l. ( 1 9 8 8 ) note that the G u l f p ro v id e s m o re

m a y w e ll in c lu d e d a n is h se in e s

(hulbot hulbot) w h ic h

th an h a lf o f the e m p lo y m e n t in the a re a e ith e r th ro u g h

a re a c t u a lly re fitte d tra w le rs . A v e r a g e c a t c h o f the

d ir e c t f is h in g o r its a n c illa r y a c tiv it ie s . F is h in g a n d

c o m m e r c ia l se cto r a m o u n te d to 3 8 ,0 0 0 t y e a r 1 fro m

Longitude ( ° W )
Fig. 1 . Lingayen Gulf coastal area.

Estuarine grasslands in Dagupan City, Pangasinan with potential for aquaculture conversion. Photo by A. Cruz-Trinidad.

67

MB

- V

líM

Photos by A. Cruz-Trinidad

í í

T S V * * .;

A*

É § ! ¿ :  4  :!

.

M angrove area in Lingayen G ulf dominated by
Nipa species (Nipa fruticans).

.* ■ 1
I.’

r
~


68

1989 to 1993 whereas the municipal sector landed an
average o f 21,000 t-year1during the same period. The
m unicipal sector has 28 different types o f gears
(Silvestre and Palma 1990), the most important o f
w hich are g ill nets and ex p lo siv es. The sectoral
contributions to gross revenues are P 631 million* and
PI 30 million for the municipal and commercial sectors,
respectively.
Several studies point to the overexploitation o f the
Lingayen Gulf fisheries. Fox (1986) used fisher density,
Silvestre (1986) analyzed biologically optimum mesh
sizes and species composition, while Signey (1987) and
Cruz and Silvestre (1988) compared profitability
parameters o f various types of fishing gears. Further­
more, intense com petition between municipal and
commercial fishers is prevalent due to the intrusion of
trawlers into municipal inshore waters. The situation
is aggravated by the increase in number o f municipal
fishers who feel forced to deploy destructive fishing
techniques such as blast fishing (Pauly 1990).
AQ U AC U LTU R E

The importance o f aquaculture, especially the
brackishwater culture o f milkfish Chanos chanos, and
much later, shrimp, cannot be overemphasized. The
region is the country’s third largest producer o f milkfish
and tiger shrimps (in volume and value terms) next to
Western Vi say as and Central Luzon. From 1990 to
1993, an annual average o f 17,000 t o f milkfish was
produced y ield in g P 585 m illio n -y e a r 1. Shrim p
production, while yielding an average o f 2 ,1 0 0 1 during
the same period, resulted in annual average receipts of
P343 million (Table 1).
T here are 1 6 ,0 0 0 hectares o f fish pon d s in
Pangasinan and La Union provinces, 13,000 ha o f
which are privately owned (Table 2). Fishpond density
is highest in the municipalities o f Dagupan, Binmaley
and Lingayen with an average pond size o f 1.9 ha.
Fishponds are managed extensively with an average
production not exceeding 1,000 kg-ha year1 (Paw et
al. 1994). Monoculture o f milkfish predominates, but
some farmers especially in the Binmaley area have
experimented with polyculture o f milkfish-siganid,
shrimp-milkfish, and shrimp-siganid-milkfish. Oyster
farms with an average area o f 100 m2are concentrated

Ì!U S $I = P25.4 (July 1992 to June 1993).

Table 1. Production o f milkfish and shrimp from brackishw ater ponds in
the Ilocos Region: volum e and value of production, 1990-93.
1990
Volume (t)
M ilkfish
Shrim p

1991

1992

17,804
4,189

23,561
4,556

17,017
875

662,076
534,186

719,820
119,611

Value (in thousand pesos)1
Milkfish
363,208
Shrim p
518,442

1993

11,195
1,619

593,990
199,600

US$1 = P25.4, July 1992-June 1993

Table 2. Num ber and total area of privately-owned brackishw ater fishponds
in the coastal municipalities o f Pangasinan Province, 1984.

M unicipality
San Fabian
M angaldan
Dagupan
Binmaley
Lingayen
Labrador
Sual
Alaminos
Bani
Anda
Bolinao
Total

No. o f
fishponds

Total area
(ha)

324
71
2,693
3,721
2,337
138
61
305
205
137
50

279
157
3,830
3,728
1,729
153
112
1,200
1,328
881
55

10,042

13,452

in the Dagupan-Binmaley area. Hanging culture or bitin
is the most common method. Cage culture o f groupers,
snappers and siganids is a nascent but highly promising
industry. Groupers, in particular, fetch attractive prices
in the domestic markets, more so in the export market,
especially when sold live (Agiiero and Cruz 1991).
Water pollution from domestic and industrial waste
affects growth and survival o f cultured species. Serious
contamination o f the Dagupan-Binmaley River with
domestic wastes resulting in high coliform counts affect
the oyster farms in the area. Industrial pollution from
the Bayawas River and mine tailings from the Benguet
uplands is detrimental to the fishponds. Another issue
faced by the industry is the low productivity o f milkfish
ponds w hich has vast im p lication s on land use
alternatives.
T O U R IS M

The Lingayen G ulf area is endowed with long
stretches of sandy beaches running from Bauang to
Agoo in La Union, natural scenic areas such as the
Hundred Islands in Alaminos, and a rich culture and

69

h isto ry . A c o m p le te lis t o f to u rist site s, to g e th er w ith

E x is t in g la n d u se o f the 1 7 c o a s ta l m u n ic ip a lit ie s

re so rts a n d f a c ilit ie s , is p ro v id e d b y C a r g a m e n to et a l.

is sh o w n in T a b le 3 . R ic e la n d s a n d g r a s s la n d s o c c u p y

(19 9 4 ).

a s ig n if ic a n t a re a in the r e g io n . M a n g r o v e s , th o u g h

T o u r is m d e v e lo p m e n t is h ig h ly d e p e n d e n t o n

p re se n tly o c c u p y in g o n ly 2 2 7 h a , h a v e b e e n d o m in a n t

e n v ir o n m e n t a l q u a lit y , so th e is s u e s th a t c o n f r o n t

in the G u l f a re a a n d are p rim e a re a s fo r f is h p o n d site s,

f is h e r ie s a n d a q u a c u ltu re a ls o affe ct th is secto r, a lb e it

e s p e c ia lly in th e e a ste rn a n d ce n tra l p o rtio n s . Irrig a te d

no t d ir e c tly . W a te r p o llu t io n a n d silta tio n are p ro b le m s

r ic e la n d s o c c u p y 4 6 % o f the to ta l la n d a re a a n d are

that d ir e c t ly a ffe c t to u ris m . S it in g o f p o n d s a n d ca g e s

m o s t ly situ a te d in A la m in o s a n d B a n i. T h e a re a o f

a re a ls o p o t e n t ia l d e te rre n ts to t o u r is m a c t iv it ie s .

s a lin iz e d r ic e la n d s w a s e stim a te d b a s e d o n a d is ta n c e

O v e r f is h in g a n d its atten d an t e v ils , e .g . c o ra l m in in g

o f 1 . 5 k m fr o m the sh o re o r 1 5 , 6 1 2 h a . G r a s s la n d s

a n d b la s tfis h in g , in d ir e c t ly a ffe ct to u ris m b e c a u se it

d o m in a te the la n d s c a p e s o f S u a l, B a n i a n d L a b r a d o r

re n d e rs the re s o u rc e a e s th e tic a lly u n a p p e a lin g , n o t to

w h ile the r e m a in in g m a n g ro v e s are lo c a liz e d in B o lin a o

m e n tio n the d a n g e rs p o se d b y ille g a l f is h in g m e th o d s.

a n d L in g a y e n .
L a n d u se co n v e rs io n patterns are d e riv e d fro m 1 9 8 6
a n d 1 9 9 0 m a p s p ro d u c e d b y the B u r e a u o f S o ils a n d

Changing Land Use Patterns

W a te r M a n a g e m e n t ( B S W M ) (T a b le s 4 a n d 5 ) . O f the
1 , 1 6 3 h a o f m a n g ro v e s , 7 3 % h a v e b een re tain e d as su ch

T h e M e d iu m T e r m R e g io n a l D e v e lo p m e n t P la n o f

w h ile 2 4 3 h a h a v e b e e n c o n v e rte d to r ic e f ie ld s . W h ile

R e g io n I e m p h a s iz e s the s ig n if ic a n c e o f the p ro v in c e s

the B S W M m a p s sh o w e d n o m a n g ro v e c o n v e r s io n to

o f P a n g a s in a n a n d L a U n io n as p rim a ry g ro w th h u b s

fis h p o n d s d u rin g the p e rio d , the a b o v e m e n tio n e d G I S

(C a rg a m e n to an d R illo n 1 9 9 4 ) . U n d e r the N o rth w e ste rn

stu d y n oted th e c o n v e rs io n o f at le a st 2 1 h a in B o lin a o

L u z o n G r o w t h Q u a d r a n g le P ro g ra m , th is a re a w ill be

( A lo ja d o et a l. 1 9 9 4 ; P a w et a l. 1 9 9 4 ) .

the site fo r three o f the in d u stria l centers to be d e ve lo p e d

Ir r ig a t e d r ic e f ie l d s h a v e b e e n c o n v e r t e d in to

in a d d it io n to its t r a d it io n a l a c t iv it ie s in f i s h i n g ,

g ra ss la n d s , fis h p o n d s , m a n g ro v e s a n d b u ilt -u p areas.

a q u a c u ltu re a n d to u rism . T h e s e d e v e lo p m e n t trends are

C o n v e r s io n o f ir r ig a t e d r ic e la n d s to a q u a c u lt u r e is

e x p e cte d to e x e rt fu rth e r p re ssu re on c o a s ta l re so u rce s

s ig n ifica n t in the m u n ic ip a litie s o f B a n i a n d L in g a y e n

m a in ly d u e to a n in c r e a s e in p o p u la t io n a n d i n ­

(T a b le 5 ). O u t o f the total fish p o n d h ectarage, o n ly 5 8 %

m ig ra tio n . T h e f o llo w in g se ctio n d e scrib e s the fast p ace

h a ve been m a in tain e d as su ch , w ith 3 0 % o f the area being

o f la n d u se c h a n g e a n d m a p s o u t d e v e lo p m e n t tren d s.

converted to rice lan d s and a sm a lle r percentage to co co n u t

Table 3. Change in land use from 1986 to present (area in hectares).
M unicipalities

Grassland

M angrove/
nipa

Alaminos
Anda
Bani
Bolinao
Sual
Labrador
Lingayen
Binmaley
San Fabian
Dagupan
Agoo
Aringay
Bauang
C aba
Rosario
San Fernando
Sto. Tomas

5,259
620
6,151
1,502
9,012
5,488
0
0
3,169
0
464
2,335
2,250
2,227
2,945
3,253
1,547

0
0
0
183
0
0
285
0
0
0
0
0
0
0
0
0
0

9,283
3,756
8,531
2,868
4,132
1,391
2,867
1,769
2,516
1,141
1,724
1,831
1,854
1,023
3,055
1,988
2,311

734
502
2,202
123
69
305
1,855
2,822
55
2,541
27
608
131
0
0
254
375

0
0
0
0
0
0
357
12
11
19
10
42
99
60
0
0
48

46,222

468*

52,040

12,603

658

Total

Ricefield,
irrigated

Total m angrove/nipa area as updated by areal photo is 227 ha.

Fishponds

Beach
sand

Riverwash

Total

Freshwater
swamp

Salt
beds

0
0
0
0
0
0
13
0
578
0
0
21
245
19
0
0
0

0
0
0
0
0
0
157
0
0
0
0
0
0
0
0
0
0

0
124
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0

15,276
5,002
16,884
4,676
13,213
7,184
5,534
4,603
6,329
3.701
2.225
4.837
4.579
3,329
6,000
5,495
4,281

876

157

124

113,148

Table 4. Change in land use in Lingayen G ulf from 1986 to 1990, from existing to potential land use.

Legends

Forest
Grassland
M angrove/
nipa
Paddyrice
irrigated
Shrubs
Coconut
Built-up
Fruits
Cassava
Sugarcane
Corn
Fishpond
Saltbed
Beachsand
Ipil-ipil
Riverwash
Grapes
Mango
Maguey
Swamp
Total

Legends

Forest
Grassland
Mangrove/
nipa
Paddyrice
irrigated
Shrubs
Coconut
Built-up
Fruits
Cassava
Sugarcane
Corn
Fishpond
Saltbed
Beachsand
Ipil-ipil
Riverwash
Grapes
Mango
Maguey
Swamp
Total

Primary
forest

Secondary
forest

Grassland

33,372
15,010

M angrove/
nipa

9,297
140,644

465
10,521

302
21,620

1,337
16,059

249

54

1,698
48
78
111

18,444
17,117
233
1,021

Shrubs

848

2,445
559

Paddyrice
irrigated

183,043
8,149
5,118
17,379
33
61
1,289
277
3,842
124
1,398

9,244
57,252
2,404
460

753
32
266
9
18
1,586

40

2,352
18

3,004

Bamboo

60,954

103
190,307

Upland
rice

Salt­
bed

155

10
2,833

Beachsand

Ipil-ipil

13

246

5,378
22
43
15
841
249,183

River
wash
118
651

Coconut

Built-up

Coffee

Cassava

Sugarcane

Corn

Fishpond
-j
o

437

1,159

287

1,219

12
3,082
944
6,311
808

293

946
131

3,073
453
205
713

1,552

14,660
747
863
12,509
24

533

57

899
94
883

166

1,113
15

16
45

75

384
152
527

93

503
182
149
64
85
45
708
91
30
87
88,251

Rice
terrace

566
7
369

73

1,368

15
7,923
134
338

423

149

1,834

1

9

569

509

94

228

445
2,447

36
46
6,392

1,736

1,217
14,458

10
21
13,237

Grapes

33
100

70
33,711

M ango

M aguey

Swam ps

Kaingin

Vegetable
low terrace

A irport

Total

46,904
152

10

100

198,771
1,163

13
49

296
246

236
61

10

48
31
34
18

75
43

3,328
245

324
151

233

19

3
338

75

1,370
33
10

34

79
266

10

43

22
24

9
19

24
10

194
93

15

48

13
230
771

105

33

7,949

42

523

39
49

82

721

773

948

131

12,599

608

92

509

351

61
1,523

46

1,164

25

243,396
97,348
15,498
34,075
102
1,317
4,654
676
13,765
568
3,507
45
21,270
152
150
138
2,814
686,313

Table 5. C hange in land use in Lingayen G ujf area from 1986 to 1990, by municipality.

Change Alaminos

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Total

131.50
377.90
101.60

Anda

Bani

Bolinao

891.80
98.60

20.90
68.70
135.90
38.80

Labrador

Lingayen

Binm aley

San
Fabian

Dagupan

Agoo

10.50

210.60

611.00

470.60

7.50

331.60

7.5 0

Bauang

San
Fernando

Sto.
Tomas

28.40
1,807.50
130.00

23.90
70.20

1.50

86.60

52.30

9.00
92.60
1,384.80

64.20
2,216.80

7.50
23.90

115.00
207.60
2,207.90

14.90

230.00

16.40

135.90

4.50

88.10
113.50

431.70

89.60
248.00

127.00

216.60

50.80
23.90

68.70

68.70
434.70

Aringay

213.70

372.00
383.90
256.90
85.10
1.50
131.50

Sual

52.30
4.50

607.90

131.50

31.40

448.10

9.00
7.50
3.00
13.40
1,114.40

1,239.90

2,956.30

279.20

224.20

304.70

2,414.10

3,429.70

65.80

2,998.00

26.90

253.90

375.00

Total

717.20
20.90
3,637.50
643.80
271.80
582.50
9,055.50
130.00
539.20
94.10
696.10
9.00
7.50
3.00
13.40
16,421.50

72
and b u ilt-u p areas. G r a s s la n d s h a ve been co n ve rted to

i.e ., m ilk f is h p o n d s, s h r im p p o n d s a n d m a in te n a n c e o f

ric e p ad d ies, e sp e c ia lly in the m u n ic ip a litie s o f A n d a and

e x i s t i n g u s e . “ M a i n t e n a n c e ” u s e i n c l u d e s b o th

S u a l, and into sh ru b la n d s and se co n d ary forests. T a b le 5

p ro d u c tiv e a n d n o n p ro d u c tiv e u s e o f la n d .

a ls o in d ic a t e s th a t s u it a b le a r e a s f o r a q u a c u lt u r e

P ro d u c tiv e a n d s a lin iz e d ric e la n d s c a n b e co n ve rted

c o n v e rsio n are m in im a l: so m e 7 .5 h a o f ric e la n d , 3 h a o f

to p o n d s at a d e v e lo p m e n t c o s t o f P 1 0 0 , 0 0 0 - h a 1.

g ra ssla n d in S a n F a b ia n a n d 1 3 .4 h a o f sh ru b la n d in

C o n v e r s io n co sts o f g r a s s la n d s is P 2 0 0 ,0 0 0 h a 1, tw ic e

B o lin a o .

th e c o s t o f r ic e la n d s d u e to th e a b s e n c e o f p a d d y

S u b s ta n tia l m a n g ro v e a n d n ip a s w a m p s in c lu d in g

stru ctu re s. M a n g r o v e c o n v e rs io n co st is e stim a te d at

r ic e la n d s w e re c o n v e rte d to a q u a c u ltu r e fa r m s w ith

P 5 0 0 , 0 0 0 - h a 1 ( A . C a r g a m e n t o , p e r s . c o m m .) a n d

m a n g ro v e c o n v e r s io n h a v in g b e g u n d u rin g th e 1 9 5 0 s

in c lu d e s the co n s tru c tio n o f d ik e s a n d th e c le a r in g o f

(D a n n h a e u s e r 1 9 8 6 ; P a w a n d P a lm a 1 9 9 1 ) . P re s e n t

f o r e s t s . O p e r a t in g c o s t s f o r a l l t y p e s o f p o n d s

aggreg ate a re a o f b ra c k is h w ater p o n d s is 1 4 ,5 8 9 h a w ith

ir r e s p e c t iv e o f in it ia l la n d ty p e is h e ld c o n s ta n t at

a b o u t 1 ,5 6 6 h a lo c a te d in L a U n io n , th e rest b e in g

P 1 0 0 , 0 0 0 - h a 1 (P r im a v e r a 1 9 9 3 ) .

d is tr ib u te d a m o n g th e m u n ic ip a lit ie s o f B in m a le y ,

A v e r a g e m ilk f is h p r o d u c t io n is a s s u m e d to be

D a g u p a n , B a n i, a n d L in g a y e n in P a n g a s in a n . P a w et

h ig h e r th a n the cu rre n t a v e ra g e to r e fle c t th e th ru st

al. ( 1 9 9 4 ) sh o w e d the c o n v e rs io n rate o f d iffe re n t la n d

to w a r d s s e m i-in t e n s iv e p o n d o p e r a t io n . M in im u m

u se ty p e s to b ra c k is h w a te r p o n d s fro m 1 9 8 6 to 1 9 9 0 to

p ro d u c tio n le v e l fo r m ilk f is h is 5 ,0 0 0 k g - h a  - y e a r 1 fo r

total 6 ,5 3 4 h a o r an a v e ra g e o f 1 ,3 0 0 h a -y e a r 1.

p ro d u c tiv e r ic e la n d s a n d g r a s s la n d s b u t is a s s u m e d to
b e h igh er, i.e ., 7 ,5 0 0 k g h a -1 y e a r 1 fo r s a lin iz e d ric e la n d s

Costs and Benefits of Altering Land Use

as an e ffe ct o f sa ltw a te r in tru s io n . T h e p ro d u c tio n le v e l
fo r sh rim p is b a se d o n e stim a te s u s e d b y P r im a v e r a
( 1 9 9 3 ) f o r s e m i-in t e n s iv e f a r m s . A s in th e c a s e o f

Monetary

m ilk f is h , p ro d u c tio n le v e ls fo r s h rim p s fro m s a lin iz e d
fa rm s are in c re a s e d to 5 ,0 0 0 k g - h a 1- y e a r ‘ .P r o d u c tio n

T a b le 6 lis t s f o u r ty p e s o f la n d u s e ty p e s a n d

le v e ls fo r b oth s h rim p s a n d m ilk f is h are c o n s id e r a b ly

c o rr e s p o n d in g p aram e te rs r e fle c tin g a lte rn a tiv e u s e s,

in c re a s e d in the c a s e o f c o n v e r s io n fr o m m a n g ro v e s

Table 6. Cost and revenue parameters o f different land use types in Lingayen
G ulf area.

d u e to its f a v o r a b le p h y s i c a l a n d e c o l o g i c a l
attrib utes.
R ic e la n d s y ie ld net re v e n u e s i f m a in ta in e d as

Existing land use
and param eters
Productive ricelands
Conversion cost ( P h a 1
)
Operating cost (P ha  y e a r 1
)
Production (k g -y ea r1
)
Average net revenue
Salinized ricelands
Conversion cost (P h a 1)
Operating cost (P ha -y ear)
Production (k g -y ear1
)
Average net revenue
Grasslands
Conversion cost (P h a 1
)
Operating cost (P ha -y e a r)
Production (k g -y ear1
)
Average net revenue
Mangroves
Conversion cost (P h a 1
)
Operating cost (P ha -year )
Production (k g -y ear1
)
Average net revenue

M ilkfish
ponds

Alternative use
Shrimp
ponds

No
conversion

s u c h . P r o d u c t io n f o r a tw o c r o p p in g p e r io d is
9 ,2 0 0 k g -y e a r 1 ( C . R . d e la C r u z , p ers. c o m m .) a n d
o p e ra tin g c o s t is P 1 0 , 0 0 0 - y e a r 1. O p e r a t in g c o st

100,000
100,000
5,000
265,000

100,000
100,000
4,000
420,000

100,000
100,000
7,500
452,500

100,000
100,000
5,000
490,000

200,000
100,000
5,000
255,000

200,000
100,000
4,000
360,000

in c lu d e s c o s t o f se e d s, fe rt iliz e r s , a n d la b o r a n d is
10,000
9,200
55,200

a ss u m e d s im ila r fo r s a lin iz e d r ic e la n d s . A v e r a g e
p ro d u c tio n fo r the latter, h o w e v e r, w a s a s s u m e d to
be 7 ,0 0 0 k g -y e a r 1 d u e to the e ffe ct o f sa ltw a te r

500,000
100,000
10,000
600,000

500,000
100,000
6,000
570,000

in tru s io n .
12,000
7,000
42,000

G ra s sla n d s w o u ld y ie ld no reven ue i f m a in ta in e d
in t h e ir e x i s t i n g f o r m b e c a u s e n o d i r e c t l y
m a rk e ta b le g o o d s a n d s e r v ic e s a rise fro m th e ir use .

75,000
0
-75,000

S o c ie t y w o u ld , in fact, in c u r a c o st e q u iv a le n t to
th e ir cu rre n t a sse sse d v a lu e .
T h e v a lu e o f m a n g ro v e s w a s b a s e d o n P I D S
( 1 9 9 4 ) , w h ic h d id v a lu a tio n w o rk fo r tw o m a n g ro v e

0
8,695
8,6953

e c o s y s te m s , i.e ., P a g b ila o B a y in Q u e z o n P r o v in c e
a n d U lu g a n B a y in P a la w a n . T h e v a lu e u s e d fo r
L in g a y e n G u l f w a s b a se d on the fo rm e r b e c a u s e o f

B ased on farm gate price of P120 kg for shrimps, P75 k g ‘ for milkfish and
P6-kg 1 for rice.
Based on assessed value and represents foregone earnings.
Based on m angrove valuation in Pagbilao, Quezon.

s im ila r a re a s, i.e ., 3 5 0 h a fo r P a g b ila o a n d 2 2 7 h a
fo r L in g a y e n as o p p o se d to 1 ,8 0 0 h a fo r U lu g a n
B a y , as w e ll as status o f e x p lo ita tio n . T h e v a lu e

73

was based on sum m ation o f direct (fish, invertebrates
and juveniles) and indirect goods (litterfall).
T h e c o n v e rsio n option re su lts in av erage n et
revenue based on a 10-year cash flow where conversion
costs are reflected only for the first year. Thus, net
revenue resulting from m angrove conversion are the
highest am ong all alternatives despite high conversion
costs. N et revenue resulting from the conversion of
grasslands is the lowest. The status quo results in net
revenue for productive and salinized ricelands, albeit
lower for the latter. N et revenue accruing to m angroves
is m inim al but positive because no costs are incurred,
w h ile g ra ssla n d s re su lt in a net loss b ec au se no
m arketable goods and services result from its nonuse.
A straightforw ard com parison o f the net revenue
resulting from three land use options shows that, based
on econom ic efficiency objectives and in the absence
o f fixed (e.g., land availability) as well as exogenous
lim its (conversion lim its), all m angroves w ould be
converted to ponds and none o f the existing land types
w ould be re tain ed . T he L P ex ercise allow s us to
determine the optimal land use mix without compromising
these limits.

ricelands and grasslands also have a role in flood
prevention.
M angrove is a very critical resource found in the
coastal area. Aside from the directly m arketable goods
and serv ic es such as fo re s t re so u rc e s (c h a rc o a l,
firewood, tannin), wildlife, fisheries, forage and w ater
supply, mangroves have im portant ecological functions.
Zam ora (1989) points out that once a m angrove area is
converted into a fishpond, it no longer functions as a
n a tu ra l s y ste m a n d c e a s e s to c o n trib u te to th e
p ro d u c tiv ity o f the n earb y n e a rsh o re ec o sy ste m .
Furtherm ore, m angrove conversion results in the loss
o f all standing biom ass as well as the total disruption
of soil, preventing natural regeneration.
A dverse effects o f m angrove conversion include
decreases in catches of m ature and juvenile fish and
shrimp (M artosubroto and N aam in 1977; C am acho and
B agarinao 1986). The loss o f nursery grounds and
eventual scarcity o f shrim p fry also affect aquaculture
operations as docum ented in B ell and C ruz-T rinidad
(this vol.).

L in e a r P r o g ra m m in g A p p lic a tio n

Objective Function

Environmental
Use o f the TEV approach necessitates the identifi­
catio n o f u se and n o nuse values o f land types as
presented in Table 7. R icelands and grasslands found
in th e L in g ay e n G u lf area have tw o d irec t uses:
agriculture and human settlements. Moreover, ricelands
and grasslands play an im portant role o f providing
veg etativ e co v er thus preventing soil erosion and
decreasing the am ount o f sedim ents reaching the Gulf.
G ranting that the Lingayen G ulf area is flood prone,

The objective function is the m axim ization o f net
revenue arising from the use o f four types o f land for
three possible options. N et rev en u e p er o p tio n is
dependent on tw o com ponents: 1) area o f land devoted
for a particular purpose; and 2) net revenue resulting
from the production of m arketable products including
rice, shrimps, ponds. C om ponent 2 is com puted based
on prices and estim ated production levels.
The solution to the objective function includes
optimal land use mix and the resulting level o f total

Table 7. Use and nonuse values o f land types in coastal areas o f Lingayen Gulf, Philippines.
Land type

Direct use

Indirect use

Ricelands

Agriculture
Human settlements

Nutrient retention

Grasslands

Agriculture
Human settlements

Sedim ent retention
W ildlife habitat

Mangroves

Forest resources
W ildlife
Fisheries
Forage
Agriculture
W ater supply

Groundwater recharge/discharge
Flood and flow control
Shoreline/bank stabilization
Sediment retention
Nutrient retention
Biological diversity

Nonuse

External support
Recreation/tourism
Water transport
Uniqueness to culture/heritage

74

profits. The representation o f the objective function is
as follows:

M ax1
!

H.2

1=NR„ * H ;

ij

...1)

u

’

Nr

= the net revenue resulting from land type i
and option j; and
H..
= th e a re a d e v o te d to lan d ty p e i and
potential and use j.
The subscripts i and j refer to existing land type
and potential land use, respectively:
i
= I ,...4
1
= productive ricefield;
2
= salinized riceland;
3
= grasslands; and
4
= m angroves,
j
= I ,...3
1
= no change;
2
= m ilkfish ponds; and
3
= shrim p ponds.
Nr
.1
where
Tr
Cc
Oc..
where
k
1
2
3

= T R - CC -O C

J

U

J

...2)

= Total revenue, product o f price, P k and
quantity o f production, Q k;
= C onversion cost of land type i into option
j’
= O perating cost o f land type i used for
option j ;
= 1....3
= rice;
= m ilkfish; and
= shrim p

Constraints
1)

Land use constraints

H

=
=
=
=

H’j
h 

36,428
15,612
46,222
227

...3)
...4)
...5)
...6)

The above constraints are the existing area o f the
fo u r ty p es o f land use, w hich is th eo retically the
m axim um allow able level o f conversion.

= 10,000

...7)

R 3 = 10,000

w here f is profit and is equal to

J
L

2) Conversion constraints

...8)

A n additional constraint im posed on the system is
the m axim um conversion rate to pond aquaculture. The
limit im posed is 10,000 ha each for m ilkfish and shrimp
ponds and is binding for a period o f 10 years. This
translates to an annual conversion rate o f 1,000 ha
which was observed to be the average conversion rate
for the region (Paw et al. 1994).
3) N onnegativity constraints

Hu

= 0

R e s u lts

Optimal Land Conversion Rates
Using a direct cost and revenues approach, the areal
distribution for different land types across three land
use options is sum m arized in Table 8. P rod u ctiv e
ricelands are m aintained but all salinized ricelands are
converted to ponds. M ilkfish ponds account for 63%
o f the to tal a rea o f salin ized rice lan d s w h ile the
rem aining am ount is devoted to shrim p ponds. Due to
the lim its im posed on area o f shrim p and m ilkfish
ponds, only 4,161 ha o f grasslands resu lted from
optim al conversion rates, w hile the rem aining area
would be retained despite the low returns. This scenario
supports the total conversion o f the rem aining 227 ha
o f m angroves to m ilkfish ponds. P otential benefits
re su ltin g from this land use m ix am o u n t to P7.4
billion-year1which is about 50% of the estim ated Gross
Value Added in agriculture and forestry o f P15.3 billion
in current prices (NSCB 1995).
The optimal distribution changes w hen the TEV
approach is used. This approach involves the estimation
o f F u tu re V alue (F V )* and th e in c o rp o ra tio n o f
foregone benefits. The latter is estim ated by subtracting
from potential net revenues the corresponding am ount
foregone by m aintaining the land in its existing form.

*An analog o f the Present Value (PV) criterion, the use o f FV emphasizes
the importance of future rather than present benefits.

75
Table 8. Optim al land u se allocation (ha) u sing a direct costs and revenues
approach (C ase 1) and a Total E conom ie Value (T E V ) approach (C ase 2).
C ase 1

Alternatives
M ilkfish
ponds

Productive ricelands
Salinized ricelands
Grasslands
M angroves

0
9 ,7 7 3
0
227

N et benefits

-

Shrimp
ponds
0
5 ,8 3 9
4,161
0
7 .4 -10s

E xisting
use
3 6 ,4 2 8
0
42,061
0
-

Sensitivity Analysis

C ase 2
Productive ricelands
Salinized ricelands
Grasslands

based on a 10-year planning scenario and a discount
rate o f 3%. The optim al land use mix resulting from
said approach is as follows: 1) productive ricelands are
m aintained as such w hile m ore than 60% o f salinized
ricelands are better off being converted to m ilkfish
ponds; 2) o f the total grasslands area, 10,000 ha are
proposed for conversion to shrim p ponds; and 3) no
m angroves are to be converted to ponds. This optimal
land use mix results in a net benefit o f P35 billion.

0
1 0 ,0 0 0
0

0
0
1 0 ,0 0 0

3 6 ,4 2 8
5 ,6 1 2
3 6 ,2 2 2

0

0
3 5 -1 0 9

2 27

M angroves
N et benefits

-

-

For exam ple, the conversion o f productive ricelands
to m ilk fis h p o n d s w o u ld n e c e s s a rily e lim in a te
possibilities o f using said land for rice production.
Potential net revenue is then m inim ized by the am ount
o f revenue foregone by m aintaining land in its existing
fo rm (T a b le 9). T h is p ro c e d u re is b ase d on the
assum ption that land conversion results in adverse and
oftentim es irreversible environm ental im pacts. On the
other hand, land that is m aintained in its existing form
has im plicit potentials fo r conversion. The resulting
net revenue is thus estim ated as the existing revenue
plus average potential revenue arising from conversion.
This procedure has an inherent conservationist bias
since it has a m inim ization effect on the conversion
option and an enhancem ent effect on the nonconversion
option.
Future Values (FV) w ere estim ated for m angroves
because o f indirect as well as nonuse values which
w ere n o t ad e q u ately assessed . F u rth erm o re, it is
assum ed that the value o f critical ecosystem s increase
exponentially in relation to the rem aining area mainly
b e c a u se o f th e ir b eq u e st v alu e. F u tu re v alu e o f
m angroves was estim ated to reach P6.1 m illion-year1

This exercise determ ines the effect o f changing the
constraints and that o f the coefficients in the objective
function on the estim ate o f net revenue and optimal
land use distribution, assuming a direct cost and revenue
approach (Case 1). Changes in the constraints assumed
a downscaling o f the limits to pond conversion, i.e., from
10,000 ha-year1to 5,000 ha-year1for a period o f 10 years.
The result is a corresponding decrease in total revenue
by m ore than half and a shift in the allocation o f land.
The 5,000 ha conversion lim it for m ilkfish ponds was
allocated am ong salinized ricelands, 4,773 ha and
m a n g ro v e s, 227 h a. S h rim p p o n d s w e re w h o lly
allocated to salinized ricelands. Productive ricelands
and grasslands w ere m aintained in their existing form,
the fo rm er because o f rev en u e resulting from rice
production. G rasslands w ere retained because o f the
relatively low returns after conversion (Table 10).
Changes in objective function coefficients would
be brought about by changes in one or m ore o f the
com ponents, e.g., production levels, price, or costs.
A ssum ed increases in production levels o f m ilkfish
w ould result in an increase in total revenues to P9.8
billion. M ilkfish pond conversion was totally allocated
to grasslands with the rem aining area being retained.
The allocation for shrimp ponds was distributed am ong
salinized ricelands, 9,773 ha and m angroves, 227 ha.
Productive ricelands are retained.

C o n c lu sio n
Table 9. E stim ation o f net revenue based on a Total E conom ic Value (T E V )
approach, in pesos.
Land type

M ilkfish

Productive ricelands
Salinized ricelands
Grasslands

2 1 9 ,8 0 0
4 2 2 ,5 0 0
2 5 5 ,0 0 0

M angroves

6 0 0 ,0 0 0

Shrim p

E xisting use

3 2 4 ,8 0 0
4 6 0 ,0 0 0
3 6 0 ,0 0 0
5 7 0 ,0 0 0

3 1 7 ,5 0 0
4 7 1 ,2 5 0
3 0 7 ,5 0 0
6 ,1 2 0 ,3 9 4

The LP was used to determ ine optim al land use
based on tw o conflicting scenarios. The first uses a
direct cost and revenue approach and results in an
optim al m ix which m axim izes net revenue but has an
inherent bias tow ards short-term gains. Thus, C ase 1
results in a total conversion o f m angroves. T he second

76
Table 10. Sensitivity analysis o f optimal land allocation applied to two
cases and resulting benefits: Case I, pond conversion cut by half; Case 2,
increase in m ilkfish production1 (land use in ha, total benefit in pesos).

Land type
Case 1
Productive riceland
Salinized riceland
Grassland
Mangroves
Total benefit
Case 2
Productive riceland
Salinized riceland
Grassland
Mangrove
Total benefit

M ilkfish

Local distribution
Shrimp

Existing use

0
4,773
0
227
-

0
5,000
0
0
3.1■10

36,428
5,839
46,222
0
-

0
0
10,000
0

0
9,773
0
227
9 .8 1 0 9

36,428
5,839
36,222
0

-

-

Productive riceland, salinized riceland and grassland to 10,000 kg-ha
m angroves to 15,000 kg h a .
U S$I=P25.40 (July 1992 to June 1993)

ca se is an a d a p ta tio n o f the T E V ap p ro ach and
in co rp o rates all po ssib le sources o f value. C ase 2
em phasizes the future earnings o f a particular land use
and accounts for all foregone earnings as well. The
distribution o f land use based on Case 2 shows a bias
towards m aintaining land in its present state, especially
for land with large foregone earnings as in the case of
productive ricelands, or as in the case o f mangroves,
large indirect and nonuse values. The resulting net
revenue is higher in Case 2 despite the fact that large
earnings from shrim p and milkfish culture are foregone
in the short-run.
The exercise results in recommendations that are only
as good as the values used. The value assigned to a
particular resource is dependent first on the knowledge
and appreciation of its natural function and next on the
valuation procedure used. The critical role of valuation is
em phasized in A guero et al. (this vol.) as being the
essential inputs o f the L inear Program (LP). M ore
theoretical and applied work in natural resources valuation
is obviously required in order to establish guidelines for
applicability, especially pertaining to issues of double­
c o u n tin g a n d a p p ro p ria te u se o f d is c o u n t rates.
Furtherm ore, a m ore effective interface between the
biological sciences and resource economics should be
fostered to determ ine the linkages of ecological functions
to marketable goods and services.
The procedure used, however, has proven to be
useful in policy setting in this fast-growth region where
excessive pressures on coastal land use may com pro­
m ise sustainability objectives.

References
Agüero, M. and A.V. Cruz. 1991. The econom ic im pact of alternative
investm ent and m arketing decisions under varying conditions: a case
of fish culture in the Philippines, p. 26-276. In L.M. Chou. T.-E.
Chua, H.W. Khoo, P.E. Lim, J.N. Paw, G.T. Silvestre, M.J. Valencia,
A.T. W hite and P.K. Wong (eds.) Towards an integrated m anagement
of tropical coastal resources. ICLARM Conf. Proc. 22, 455 p.
A lojado, Z.N ., J.N . Paw and K.Q. C asuga. 1994. Id en tificatio n for
reforestation in Lingayen G ulf area, Philippines. GISCA M P Tech.
Rep. Part II.
BSW M (Bureau o f Soils and W ater M anagem ent). 1986. Physical land
resources o f the province o f La Union. Land Resources Evaluation
Project. Bureau o f Soils and W ater M anagem ent, D epartm ent of
Agriculture, Manila, Philippines.
Camacho, A.S. and T. Bagarinao. 1986. Impact o f fishpond developm ent
on the m angrove ecosystem in the P hilippines, p. 383-405. In
Mangroves o f Asia and the Pacific: status and management. Tech.
Rep. UNDP/UNESCO Research and Training Pilot Program m e on
M angrove Ecosystem s in A sia and the Pacific. Natural Resources
M anagem ent Center, Philippines.
C argam ento, A.G. and N. Rillon. 1994. Im pact o f hum an settlem ent
developm ent and expansion in the coastal area. GISCA M P Tech.
Rep. Part II.
Cargamento, A.G., E. Cacanindin and K.Q. Casuga. 1994. Identification
and assessment of coastal tourism areas in Lingayen Gulf. GISCAM P
Tech. Rep. Part II.
Cruz, A.V. and G. Silvestre. 1988. Econom ic analysis o f m edium trawlers
in the Lingayen Gulf. Fish. Res. J. Phil. 13(1 2): 1-14.
D annhaeuser, N. 1986. A quaculture and land reform : inco n g ru o u s
conditions in the Philippines. Hum. Organ. 45(3):254-260.
Ferrer, E.M., C. Anonuevo, G. Castillo, R. Catelo, H. Chan, R. Rivera and
S. Rodriguez. 1988. M arketing studies of selected com m unities in
Lingayen Gulf. Terminal report submitted to the International Center
for Living A quatic R esources M anagem ent for the A SEA N/US
Coastal Resources Management Project.
Fox, P. 1986. A manual o f rapid appraisal techniques for Philippine coastal
fisheries. B ureau o f Fisheries and A quatic R esources Research
Division, Manila.
M artosubroto, P. and N. Naamin. 1977. Relationship between tidal forests
(mangroves) and com mercial shrimp production in Indonesia. Mar.
Res. Indones. 18:81-86.
M cManus, L.T. and T.E. Chua, Editors. 1990. The coastal environm ental
profile of Lingayen Gulf, Philippines. ICLARM Tech. Rep. 22, 69 p.
M cManus, L.T. and R.A. Rivera. 1990. Population and socioeconom ics,
p. 38-43. In L.T. M cM anus and T.E. C hua (eds.) T he coastal
environmental profile of Lingayen Gulf, Philippines. ICLARM Tech.
Rep. 22, 69 p.
Mines, A.N. 1986. Assessm ent of the fisheries o f Lingayen Gulf. Final
Report. Philippine Council for Agriculture and Resources Research
and D evelopm ent, and C ollege o f F isheries, U niversity o f the
Philippines, Quezon City, Philippines. 55 p.
NSCB (National Statistical Coordination Board). 1995. 1995 Philippine
statistical yearbook. National Statistical Coordination Board, Manila,
Philippines.
NEDA, Region I (National Economic Developm ent Authority, Region 1,
Philippines). 1992. The Lingayen G ulf coastal area m anagem ent plan.
ICLARM Tech. Rep. 32, 87 p.
Pauly, D. 1990. On Malthusian overfishing. Naga, ICLARM Q 13(1 ):3-4.
Paw, J. and A. P alm a, E ditors. 1991. A ction plan for aq u acu ltu re
m anagement. ASEAN/US Coastal Resources M anagem ent Project,
M anila, Philippines.
Paw, J.N., F. Domingo, Z.N. Alojado and J.C. Guiang. 1994. Land resource
assessm ent for brackishwater aquaculture developm ent in Lingayen

G u lf area, Philippines. G ISC A M P Tech. Rep. Part 11.
PIDS (P hilip pine Institute for D evelop m ent Studies). 1994. Philippine

F o o d and A g r ic u ltu r e O r g a n iz a tio n o f th e U n ite d N a tio n s ,
B angkok.

m a n g ro v e reso u rce v alu ation project. A c co m p lish m e n t Report,

Silvestre, G.T. 1986. A ssessm ent o f the m u ltispecies dem ersal stock o f the

Septem ber 1994. PID S, Makati City, Philippines.
Primavera, J.H. 1993. A critical review o f shrimp pond culture in the
Philippines. Rev. Fish. Sci. 1(2): 151 -201.
S ig n e y , L .O . 1 9 8 7 . C o n s e q u e n c e s o f e x c e s s iv e fis h in g e ffo r t in
L in g a y en G u lf, P h ilip p in es, p. 2 0 8 -2 1 7 . In IPFC S y m p o siu m on
the E x p lo ita tio n and M an agem en t o f M arine Fishery R esou rces
in S o u th e a st A sia , 1 6 -1 9 February 1 9 8 7 , D a r w in , A u stra lia .
R A PA R ep.: 1 9 8 7 /1 0 . R e g io n a l O ffic e for A sia and the P a c ific,

Samar Sea, Philippines. Dept. Mar. Fish. Tech. Rep. 7 ,6 5 p. U niversity
o f the Philippines in the V isayas, Iloilo, Philippines.
Silvestre, G.T. and A .L . Palma. 1990. E con om ic sector, p. 15-31. In L.T.
M cM anus and T.E. Chua (eds.) The coastal environm ental profile o f
Lingayen G ulf, Philippines. ICLARM Tech. Rep. 22 , 6 9 p.
Zamora, P.M. 1989. Philippine mangroves: their depletion, conversion and
decreasing productivity. W allaceana 58:1-5

follow ed (e.g., W arfel and M anacop 1950; Legasto et
al. 1975; Sim pson 1978) which were wholly or partly
on the B ay ’s fisheries. Detailed assessm ent conducted
by the Institute o f Fisheries D evelopm ent and Research
(IFDR) o f the University of the Philippines, College
of Fisheries and the International C enter for Living
Aquatic Resources M anagem ent (ICLARM ) in the area
in 1979-81 sum m arized these works (Bailey 1982a,
1982b; Pauly and M ines 1982; Smith and M ines 1982;
Smith et al. 1983), presented a diagnosis o f the status
o f th e f is h e r ie s , w h ic h w e re c h a r a c te r iz e d by
o v e re x p lo ita tio n and d istrib u tio n a l in eq u ity , and
provided appropriate m anagem ent options. The area
was revisited by IC LA R M in 1992-93 via a R esource
and Ecological A ssessm ent (R EA ) study under the
auspices of the Philippine D epartm ent o f A griculture’s
(D A ) F isheries S ecto r P rogram (FSP). D a ta w ere
collected in the San M iguel Bay area during July 1992
- June 1993 based on three data generation activities:
1) inventory of fishing gears, from January to June
1993; 2) m onitoring o f com m ercial and m unicipal
fish e rie s, fro m Ju ly 1992 to Ju n e 1993; an d 3)
monitoring of fishing operations from July 1992 to June
1993 (Silvestre et al. 1995).
Thus far, the REA study is the most comprehensive,
dealing with physical and biological oceanography,
fisheries stock assessm ent and threatened ecosystem s.
The socioeconom ic com ponents included cost and
returns of different types o f gears, fishing dynam ics,

O p tim a l F le e t C o n fig u ra tio n in S a n M ig u e l
B ay, P h ilip p in e s : A S im p le L in e a r
P r o g ra m m in g A p p ro a c h *
A

n n a b e l l e

C

r u z

- T

r in id a d

and

L

en

R .

(Í

a r c e s

,

I n te rn a tio n a l C e n te r f o r L ivin g A q u a tic R eso u rces
M anagem ent (ICLARM), M CPO Box 2631, 0718 Makati
City, Philippines
C R U Z -T R IN T D A D , A. and L .R . G A R C E S . 1996. O p tim al fleet
configuration in San M iguel Bay, Philippines: a sim ple linear
p ro g ram m in g approach, p. 78-86. In A. C ruz-T rinidad (ed.)
Valuation o f tropical coastal resources: theory and application of
linear program m ing. ICLARM Stud. Rev. 25, 108 p.

A b s tra c t
T hree altern ative scenarios w ere used to estim ate fishery net
re v e n u e s in San M iguel B ay, P h ilip p in e s, u sin g a c o n s tra in e d
maxim ization approach. The constraints included total allowable catch,
catch d istrib u tio n and crew w ages. T he sc en ario w hich clo sely
approxim ated the existing effort levels in the fishery resulted in net
revenues am ounting to P6.3-1(T-year1or U S$248T03 y e a r. A scenario
which accom m odated an increased num ber of fish corrals but diminished
“baby” trawlers by alm ost 30%, resulted in a net revenue increase to
P19.4-I06 year f The latter scenario’s bias tow ards sm all-scale gears
resulted in the h ig h est level o f net revenues, thus m aintaining a
congruence between efficiency and equity objectives. Wages, which were
observed to be greater than prevailing opportunity costs, were deemed
unsustainable if catch constraints were to be met.

I n tr o d u c tio n
San M iguel Bay (Fig. 1), located in
the Bicol region in the Pacific coast of
the Philippines, is a shallow, estuarine
body o f w ater with an area o f about 1,115
km 2. The bay is bounded by seven coastal
m unicipalities, M ercedes and Basud, in
C am arines N orte, and Sipocot, Cabusao,
C alab an g a, T inam bac and Sirum a, in
C am arines S ur province. The National
S ta tis tic s O ffic e (N S O 1990a, N S O
1990b) estim ates population in the 74
coastal villages to have reached 93,000
in 1990. Agriculture, fishery and forestry
are the m ajor sources o f income.
Since the first investigation of the
San M ig u el B ay fish eries in the late
1930s (Um ali 1937), a series of works
♦ICLARM Contribution No. 1161

Fig. 1. San Miguel Bay, Philippines.

78

79

as traw lers, gill nets, push nets and stationary gears
including fish corrals, lift nets, and filter nets.

m a rk e t p e r fo rm a n c e , liv e lih o o d o p tio n s a n d
institutional arrangem ents.
This paper estim ates fishery net revenues from data
collected by the D A -FSP San M iguel Bay project, using
a co n strain ed m axim ization approach. F ishery net
revenue is the aggregate revenue earned by individual
fishing units and is thus affected by fleet structure.
S everal strategies can be adapted to m axim ize net
revenues: for exam ple, concentrate on a choice group
o f h ig h ly e f fic ie n t v e s se ls ; o r fu lly e x p lo it the
resource to increase catch levels. The first proposal is
invalidated by equity considerations while the latter is
not sustainable. A possibility exam ined here is the
m a x im iz a tio n o f n et re v e n u e s th a t in c o rp o ra te s
c o n s tr a in ts su c h as a llo w a b le c a tc h e s , e q u ity
im plications and m inim um wages.

Gears Operating in San Miguel Bay
TRAW LERS

San M iguel B ay is one o f the m ost im portant
traw ling grounds in the Philippines. It is relatively
shallow, with 89% less than 7 fathom s, and 95% o f its
bottom is com posed o f sand, m ud and sandy-m uddy
substrate. The fishing fleet is dom inated by trawlers
and their “derivatives” the latter including mini and
baby traw lers, both classified, by tonnage less than 3
gross tons (GT), as m unicipal gears.
Sm all or ‘baby’ traw lers use boats that are 1.6-3.0
G T with 68-160 hp diesel engines. Crew size is five to
six fishers. Each trip lasts 2-3 days. M ini traw lers (itikitik or kuto-kuto) use bancas with outriggers and are
pow ered by 10-16 hp gasoline engines. C rew size is
tw o to three fishers and fishing lasts from 5 :00 a.m. to
3:00 p.m. M ini traw ls are used in shallow waters o f 4 ­
10 m depth and target sergestid shrimps.
T here w ere 35 large traw lers and 38 m edium
trawlers registered in the area but only one large trawler
was observed to operate interm ittently during the
sam pling period. There are 260 mini traw lers and 50
baby traw lers p resen tly o p eratin g ; th ese w ere all
included in the sample.

T h e S a n M ig u e l B a y F is h e ry
San M iguel Bay is characterized by a m ultigear
and m ultispecies fishery. A bout 5,300 fishers reside
in the seven coastal m unicipalities bordering the bay
(Sunderlin 1995a, 1995b) and em ploy over 50 distinct
types o f fishing m ethods/gear and over 4,700 units of
v a rio u s ty p e s o f fis h in g gear. T he m a jo r gears
considered in this paper contributed roughly 75% of
the total catch in 1993 and are listed together with the
num ber o f boats per class in Table 1. They are classified

Table 1. Com parison o f fishin g effort and catch per gear type in San M iguel B ay from 1980-81 to 1992-93.
Gear type

1980-81

1992-93

N o. o f
units

Trips per
year

C atch (t)

(%)

30
17
72
188

103

2,385»

12.5»

9,291°

48.6°

1,345
171
60
834

156
53
225
150

N o. o f
units

Trips per
year

35
38
50
260

125»

2 ,6 7 0
60
260
2 45

C atch (t)

(%
)

202

25
308
3 ,9 0 5
1,901

0 .1 4
1.7
22
10.7

171
115
2 40
168

7 ,5 5 0
1,021
9 67
823

42
6
5
5

Trawlers
Large
M edium
Sm all
M ini

191

Other gears
G ill nets
L ift net
Filter net
S cisso r net

All others
»Large and m edium
Sm all or (baby) and mini

4 ,8 5 4
624
2 95
4 76

25
3
1.5
2.5

80
GILL NETS

The study identified 24 types o f gill nets totalling
to 2,670 units. Gill nets are nam ed according to mode
o f operation (e.g., drift gill net, bottom set gill net) or
target species (e.g., shrim p gill net, lait; crab gill net,
pangasag) but the m ost com m on is the ordinary gill
net, panke. C h aracteristics o f gill nets in Table 1
actually refer to an index based on panke units.

later; the process is repeated for harvest the follow ing
m orning. Target species include sergestid and penaeid
shrim ps and anchovies.

Catch and Species Composition

Silvestre et al. (1995) described push nets or scissor
nets (hud-hud) as consisting of collapsible, triangularlyframed netting material m ounted over two criss-crossed
bam boo poles. O perations usually involve a single
fisher pushing the gear along the bottom within wading
depth but they have been recently observed to be
m ounted in front o f bancas pow ered by 10-16 hp
gasoline engines.

Total landings w ere estim ated to be about 1 7 ,7 5 0 1
from July 1992 to June 1993 (Silvestre et al. 1995).
A bout 35% w ere landed by traw ls, 42% by gill nets
and the rem aining 23% by the other gears.
A total of 175 species distributed am ong 110 genera
and 70 fam ilies were observed to occur in the catch
(C in co eta l. 1995). Croakers (Sciaenidae), slipmouths
(L e io g n a th id a e ), p e n a e id sh rim p s (P e n a e id a e ),
sergestid shrimps (Sergestidae), crabs (Portunidae) and
a n c h o v ie s (E n g ra u lid a e ) d o m in a te th e la n d in g s,
collectively accounting for 58.5% o f the total landings
during the period. A detailed breakdow n o f species
com position per gear type is provided in Silvestre et
al. (1995).

STATIONARY GEARS

Status o f Exploitation

PUSH NETS

Stationary gears include fish corrals, lift nets and
filter nets. The descriptions provided below are based
on Silvestre et al. (1995).
Fish corrals, sagkad, are sem i-perm anent gears
used for guiding and trapping fish. The gear consists
o f a guiding barrier, tw o to three playground areas, and
a bunt or catching area. The bunt is usually set in the
e v e n in g ; h a rv e stin g u sin g scoop n ets occu rs the
follow ing m orning. Operations involve two to three
fishers who are transported by a nonm otorized banca.
Target species are pelagics but usually include small
dem ersals and shrimps.
L ift nets, bukatot, are square-shaped nets attached
by pull ropes to four bases m ade o f bam boo or coconut
trunks planted on the seabed. Lift nets are operated in
w aters o f about 10-20 m depth usually near the mouth
of the Bay and were observed in the towns o f M ercedes,
Sirum a and Basud. They are only used during the dark
phases o f the m oon and have kerosene lam ps to attract
fishes. Operations involve about four to five fishers
w ho raise the net via the pullropes. Target fishes are
slipm ouths and clupeids.
Filter nets, biakus, are conical bags o f netting set
against the tidal currents near the mouth o f rivers. The
net is usually low ered at dusk and retrieved 4 hours

A com parison o f key physical indicators by major
gear types between the 1980-81 and 1992-93 studies is
presented in Table 1. Except for the small/baby trawlers,
all gears increased in num bers. M oreover, there is also
a m arked increase in the frequency of trips per gear
type.
In addition to increased fishing effort are other
param eters that point to a w orsening o f the status of
exploitation in the Bay including: excessive fishing
pressure, changes in species composition, and changing
econom ic perform ance.
EXCESSIVE FISHING PRESSU RE

E xcessive fishing p ressu re continues to be an
overriding issue confronting the fisheries of San M iguel
Bay despite the reallocation o f effort (Silvestre et al.
1995). A com parison o f relative indices o f total catch,
aggregate traw l horsepow er, num ber o f fishers and
traw lable biom ass shows that traw lable biom ass has
declined by about 80% from its 1940 levels (Fig. 2).
The decline in catch rates is m ost abrupt for traw lers,
i.e., 11,700 t in 1980 to about 6,100 t in 1992-93, in
view o f the strict enforcem ent of the 7 km, 7 fathom
ban, the decline in num ber o f small traw l units, and
reduced catch rates o f m ini trawls.

81
CHA NGE IN ECONOM IC PERFORM ANCE
Trawable biomass
Number of municipal fisheries
Aggregate hp of trawlers

O O

Total catch

I

0
)

4
0

D
C

Fig. 2. Relative indices o f trawlable biomass, total catch, number of
fishers and aggregate horsepower o f trawlers in San Miguel Bay from
the 1940s to the early 1990s.

C inco et al. (1995) also noted that m ean
exploitation ratio for the m ore abundant species
is 0.65. T hese observations are indicators o f
overfishing and are supported by conventional
fisheries theory and likew ise reflects that a stock
is overfished when biom ass is reduced below 30
to 50% o f virgin stock levels or if the exploitation
ratio is way above the “optim um ” values ranging
from 0.3 to 0.5 (Silvestre et al. 1995).

The im pacts o f these variables on econom ic
param eters are shown in Table 3a. M onthly catch
value for all but one gear, push nets, has declined
severely. Baby trawls were the largest casualties with
m onthly catch value depreciating by alm ost 90%
from 1980-81 levels.
D eclines in the rate o f return on investm ent
(ROI) were experienced by fish corrals and mini and
bab y traw le rs alth o u g h re m a in in g p o sitiv e . In
c o n tra s t, f ilte r n e ts , p u sh n e ts a n d g ill n e ts
experienced robust growth. Changes in ROIs can be
partially attributed to changes in capital requirements
(Padilla et al. 1995). The 1980-81 study showed that
it was m ore expensive to engage in gill net fishing
than other artisanal fishing m ethods such as fish
corrals and lift nets (Supanga 1982; Supanga and
Sm ith 1982; Tulay and Sm ith 1982; Yater 1982). At
that time, investm ent cost for mini traw lers was only
half of that required by gill nets. By 1993, capital

Table 2. Changes in relative abundance of various fam ilies/groups in the catch
during surveys in San M iguel Bay in the late 1940s, early 1980s and early 1990s
(Cinco et al. 1995).

Family/group

Observed change in
relative abundance

Probable cause

Sharks and rays

Massive decrease

Recruitm ent overfishing

Cephalopods

Relative increase

Reduced predation

Penaeid shrimps

Relative increase

Reduced predation

Pristidae

D isappearance

Recruitm ent overfishing

Relative increase

Species replacem ent
reduced predation
Growth overfishing

CHA NG E IN SPECIES COM POSITION

Table 2 gives a sum m ary of trends in species
c o m p o s itio n c h a n g e s re fle c tiv e o f g ro w th ,
recruitm ent and ecosystem overfishing (Cinco et
al. 1995). This trend is also m anifested in species
com position changes by gear type. In 1980-81,
croakers (abo and pagotpot) constituted 82% of
the catch of gillnets; this figure was down to 20%
in 1992-93 with other species such as shrimp,
m anta rays, and hairtails occurring. Liftnets still
catch anchovies (dilis) but none o f the m inor
catches such as herrings, crevalles and squids are
known to presently occur in the catch; instead,
there has been replacem ent by other species
in clu d in g croakers, slipm ouths and sergestid
shrimps.

“Trash” fish
a) low-value species
(e.g., Gobiidae)
b) juveniles of high-value
species

Relative increase

Leiognathidae

M assive decrease

No straightforward
explanation

Tetraodontidae
Apogonidae

Relative increase

Species replacement

Sphyraenidae
D repanidae
Synodontidae

Relative decrease

Recruitment overfishing

Engraulidae
Trichiuridae

Relative increase

Technological
im provement (higher
trawl opening and
speed)

Carangidae
Scombridae

82
Table 3a. C om parison o f k ey eco n o m ic indicators betw een 1980-81and 1992-93 San M iguel B ay studies.

M onthly
catch value
(Peso)
G ear type
F ixed gears
Fish corral
Filter net
Lift net
Trawlers
Mini
Sm all/baby
Large
O ther gears
Gill nets
Push nets

Derived wage rates*
Peso d a y 1

ROIs
1993

1981

1981

Pure profit for all units
(thousand P)
1981

1993

1993

10,622
2,669
15,947

190.8
35.2
(1.8)

8,257
2,301
7,391

101.1
190.2
(1.7)

36.1
53.0
23.3

80.7
60.7
31.0

1,295
308
(3,074)

5,700
1,793
(648)

15,236
25,908

83.6
63.6
-

8,357
8,781

78.4
12.9
0.2

92.0
114.7
-

93.4
54.7
66.2

6,115
8,635
-

4,397
(30)
-

25.6
14.8

5,974
247

46.6
145.8

47.7

61.8

-

-

899
(108)

1,934
764

12,524
148

♦Unskilled crew.
Source: Padilla et al. (1995).

cost requirements had tilted in favor of gill nets with
initial outlay amounting to 51%, 60% and 70% that of
lift nets, fish corrals and mini trawls, respectively.
Wage rates were derived by Padilla et al. (1995)
based on total payments to labor (cash and in-kind).
Only master fishers of trawlers and the unskilled crew
offish corrals and mini trawlers were observed to earn
wages that are higher than the agricultural (nonplantation)
rate. However, all fishers earned wages that were above
the region’s opportunity wage rate o f P35 day _
1
(US$1=P25.4 July 1992-June 1993). Table 3b shows
that wage rates increased between 1980-81 and 1992­
93 for fixed gears and gillnets but declined by almost
50% for baby trawls.

Pure profit, the economic benefit from fishing, net
of the opportunity costs of the factors of production,
was taken to represent economic rent. Fish corrals,
filte r nets and g ill nets ex p e r ie n c e d a large
improvement in pure profits while mini trawlers
suffered a 28% decline. Baby trawlers, which had
the largest level of pure profits in 1980-81 reflected
losses in 1993.
Despite indications o f overexploitation, total
pure profit for the San Miguel Bay fishery for 1992­
93 was positive and greater than 1980-81 levels. This
can be explained by the evolution of the fleet into
its present configuration thereby minimizing losses.
Another hypothesis is the worsening quality of life

Table 3b. Com parison of key econom ic indicators between 1980-81and 1992-93 San M iguel Bay studies.
Catch rate
per year1
G ear type

(t)

Fish corral
Filter net
Lift net

1.8
3.7
17.02

M ini trawl
Baby trawl
Large trawl
Gill net
Push net

Catch value
per year2
(Peso)

Costs per
year2
(Peso)

W td price
(P e so k g )

Labor
requirem ents
per trip2

Labor
per year
(person-trip)

34,180
28,920
40,864

i,1 1 4
9,635
31,555

20.6
9.6
11.6

1.6
1.2
4.6

170
288
529

7.3
78.1
24.7

74,670
88,940
171,368

53,539
77,122
110,143

14.6
31.2
14.9

1.5
1.8
9

303
239
72

2.8
3.4

50,322
9,914

39,334
2,598

31.2
39.6

2
1.4

328
235

Silvestre et al. (1995).
Padilla et al. (1995).
US$1=P25.4 (July 1992-June 1993).

83

in the region which drives down the alternative uses
and returns to labor and capital.

X.

= number of boats per gear class; and

W.

= wage rate.

L in e a r P r o g ra m m in g A p p lic a tio n
Linear programm ing was used to estim ate
potential benefits accruing to the San Miguel Bay
fishery under varying constraints. The elements of
the linear program are as follows: 1 ) an objective
function, the m axim ization of net revenues; 2 )
co n stra in ts, in clu d in g total a llo w a b le catch,
minimum and/or maximum number of units per gear
type; and 3) the input-output coefficients, including
catch rates per gear type. The variables optimized
by the linear program in the primal formulation, i.e.,
the primal solution, are the number of units per gear
type. The dual solution, being the converse of the
primal, has as its variables the constraints used in
the primal solution. The dual solution provides a
measure of the opportunity cost of the particular
resource (Agiiero et al., this vol.) and as such
in d icates changes in net revenue if a certain
constraint is relaxed.
Objective Function

The coefficients of the objective function are catch
value per year and operating costs. Catch value is
estimated by multiplying catch rate per year (Silvestre et
al. 1995) by average weighted prices per gear type (Padilla
et al. 1995). All cost items were derived from the work of
Padilla et al. (1995). The eight types of gears considered
include three fixed gears, i.e., fish corral, filter net and
lift net; three types of trawlers, i.e., mini, baby (small)
and large; and gill nets and push nets.
Constraints
a) Total allowable catch
L C Vl * X l = 14,000
’

...2)
/

where CV = volume of catch per gear type.
Given the level of overexploitation, total annual
catch for all gear types must be less than or equal to
1993 levels.
b) Distribution of catch

Maximize profit, n , such that:

X CV* X. = 5,880

TR - TC

8

n= I

[{(R, - OC.) * X,} - {LC * W.}]

... 1 )

i—
1
where the coefficients include:

...3)

X C V * X  = 4,900

FI =

...4)

X CV* X. = 3,220

...5)

The present distribution of total catch should be
maintained with gill nets, stationary gears and trawlers
contributing 42%, 35% and 23%, respectively. This is
to ensure that in the search of maximum revenues,
equity objectives are not compromised.

TR

=

total revenue;

TC

=

total costs;

Rl

=

catch value of fish per gear type;

c) Effort limits

°C.

=

material and fixed expenses per gear
type; and

X1  = X E
B

LC i

=

labor costs per gear type

and the variables are:

...6)
7

In consonance with effort reduction in the trawl
fleet, the number of units for all types of trawlers should
be less than or equal to existing levels; the other types
of gears were allowed to expand.

84

d) Minimum wage rates
W. = 35

...7)

Wage rates must be at least equal to the prevailing
opportunity cost of labor in the region.
e) Non-negativity constraints

X.=0

...8)

W.  = 0

...9)

Input-Output Coefficients
Volume of catch per gear type, C V , is provided in
constraint (a), the summation of which should be less
than or equal to total allowable catch. The same
coefficien t is used to satisfy constraint (b), the
distribution of catch. Otherwise, the other coefficients
would take on a value of 1 or 0 depending on whether
they are affected by particular constraints.
R e su lts
The primal values correspond to the optimal
number of gears and wage levels (Table 4). The dual
value of wages represents the opportunity cost of labor;
that of gears represent the increase (decrease) in the
value of the objective function if constraints on the
number of units were relaxed, i.e., specific gears were
increased by one unit.
Scenario A is a current representation of the San
Miguel Bay fishery with the following constraints: total
allowable catch of 14,000 ty e a r 1 a catch distribution
,
ratio as specified in constraint b), and minimum wage
rates of P 35day. Scenario B examines the effect of a
different fleet configuration on net revenues, i.e, current
level of effort for the trawler fleet is maintained while
gill nets and other stationary gears are allowed to
expand. Scenario B likewise considers constraints (a)
and (b). Scenario C is similar to Scenario B except
that catch distribution ratio is modified as follows: 50%,
gill nets, 30%, stationary gears, and 20%, trawlers.
Scenario D is a situation wherein wage rates were
pegged at the levels derived by Padilla et al. (1995)

which were, in most cases, higher than the opportunity
costs of P35-day‘.
Scenario A yielded net revenues of P6.3 million
with lift nets, gill nets and push nets, sustaining losses.
Optimal number of units matches existing levels except
for baby trawls which were reduced by 24%. Dual
values show that fishery net revenues would diminish
by P9,206, P492 and P909, for every lift net, gill net
and push net added to the existing fleet, respectively.
In the same manner, fishery revenues would increase
if the number of profitable gears were expanded, for
example, each large trawl has the potential of increasing
net revenue by P57,613.
The constraints introduced by Scenarios B and C
via limitations on “perceived” destructive gears such
as trawlers and on catch distribution resulted in higher
levels of net revenue (Table 4). The number of baby
trawls diminished by 24% for Scenario B and 88 % for
Scenario C whereas optimal number of fish corrals
increased by 82% and 520%, respectively. The optimal
number of other stationary gears however remained
unchanged. Scenario C resulted in the highest level of
benefits, P19.4 million, despite having the lowest
number of baby trawlers ( 88 % less than existing levels)
and the highest number of fish corrals. Lift nets had
the highest opportunity costs despite having a minimal
fleet size, i.e., 60 units. This is because of its huge labor
requirement per year and the relatively large costs
incurred relative to catch value (Table 3b). Scenario D
resulted in a net loss of P14 million and the total
eradication of mini and baby trawlers; otherwise, the
number of all other gear types are maintained at its
present levels.
The primal value of wages is P35-day for all
scenarios. Because wage is a cost factor in the
estimation of net revenue, the dual values are negative,
with the magnitude depending on the labor
requirements per gear type and the wage rate. For
example, increasing wages by one peso would result
in a P74 reduction in net revenue for large trawlers; on
the other hand, gill nets would suffer a greater decline
amounting to P509,712.
C o n c lu sio n
The LP sim ulation proved to be a useful
management tool in its predictive and analytic capacity.
This exercise helped predict changes in fishery net

85
Table 4. O ptim al num ber of units per gear type and optimal wage levels (primal) com pared with opportunity costs (dual) o f linear program m ing
variables used to model San M iguel Bay fisheries.

Current
levels

Gear

Scenario A
Optimal
O ppor­
num ber
tunity costs
o f units
per gear
type/
optimal
wage
rates

Optim al
num ber
o f units
per gear
type/
optimal
wage
rates

Scenario B
Oppor­
tunity costs

Optimal
num ber
o f units
per gear
type/
optimal
wage
rates

Scenario C
Oppor­
tunity costs

Scenario D
Optimal
O ppor­
num ber of
tunity costs
units per
gear type/
optimal
wage
rates

Num ber o f units
Fish corral
Filter nets
Lift nets
Mini trawls
Baby trawls
Large trawls
Gill nets
Push nets

123
260
60
260
50
1
1,554
245

123
260
60
260
38
1
1,554
245

20,456
9,205
(9,206)
10,203
. 0
57,613
(492)
(909)

224
260
60
260
38
1
1,554
245

0
(32,843)
(202,629)
10,203
0
57,613
(492)
(39,548)

767
260
60
260
11
1
1,554
245

0
(32,843)
(202,629)
10,203
0
57,613
(492)
(39,548)

123
260
60
0
0
1
1,554
245

20,456
9,205
(9,206)
10,203
0
57,613
(492)
(909)

Wage rates (Peso)
Fish corral
Filter nets
Lift nets
Mini trawls
Baby trawls
Large trawls
Gill nets
Push nets

80.7
60.7
31.0
93.4
54.7
66.2
61.8
-

35
35
35
35
35
35
35
35

0
0
0
0
(31,740)
0
(509,712)
(57,575)

35
35
35
35
35
35
35
35

(38,137)
(74,880)
(31,740)
(78,780)
(9,111)
(72)
(509,712)
(57,575)

35
35
35
35
35
35
35
35

(130,692)
(74,880)
(31,740)
(78,780)
(2,685)
(72)
(509,712)
(57,575)

80.7
60.7
31.0
93.4
54.7
66.2
61.8
-

(20,910)
(74,880)
(31,740)
(78,780)
(9,111)
(72)
(509,712)
-

Net revenues (Peso)

P6.3 million

P8.4 million

P19.4 million

(P I4 m illion)

US$1 = P25.4, July 1992-June 1993.

revenues given alternative fleet configuration and wage
structures. Scenario A is the closest approximation to
the existing situation in San Miguel Bay minus the
constraints. The exercise shows that had these
constraints been in force, the fishery would gain P6.3
million per year or 6 % of operating and labor costs. It
seems rational to assume that existing net revenues are
larger given that no catch limits are in force; this is
corroborated by the work of Padilla et al. (1995) who
estimated positive pure profits amounting to PI 3
million.
Linear programming is another economic technique
that uses economic efficiency as its sole numeraire,
i.e., equity considerations are not considered. In fact,
in situations where catch distribution limits were not
applied, the resulting fleet structure consisted solely
of large trawlers. Likewise, the institution of catch
distribution limits as well as limits on the number of
trawlers caused the phenomenal increase in the number
of fish corrals simply because it had, relative to the
other stationary gears, the largest average profit. Both

configurations w ould increase net revenues
substantially but would provide reason to eradicate the
small-scale, mostly unprofitable, gears.
This situation was resolved by incorporating catch
distribution ratios as constraints. In this exercise, there
seems to be a congruence between economic efficiency
and equity objectives given that Scenario C, which has
an inherent bias towards small gears resulted in a fishery
revenue that was also the highest. This observation
seems to augur well for future management initiatives
especially in effort reduction because this will tend to
minimize potential conflicts.
Simulating alternative wage levels indicates the
increasing volatility of the labor market in the region.
Current wage payments coupled with catch constraints
resulted in a nonfeasible solution as in Scenario D, i.e.,
net revenues were negative. Clearly, wages cannot be
maintained by specific gear types if catch or effort limits
were sim ultaneously enforced. Thus, resource
overexploitation can be viewed as an indirect result of
maintaining current wage rates because if labor were

86
paid rates higher than prevailing opportunity costs, then
due to open access, more fugitive labor is attracted to
the fishery. The fishery resource would be subsidizing
labor that is being used inefficiently. Thus, it is often
the case that in overexploited fisheries, e.g., Lingayen
Gulf (Cruz and Silvestie 1988) and Philippine small
pelagics fishery (Trinidad et al. 1993), labor earns pure
profit even if entrepreneurs sustain economic losses.
On the other hand, if access were limited by any of the
constraints incorporated in the linear program, current
wage rates could not possibly be maintained.
This theoretical exercise provides a useful tool for
policy setting and while the estimates may never attain
point accuracy, the method certainly contributes
appropriate benchmarks for decisionmaking.
A c k n o w le d g e m e n ts
Many thanks to Ms. Madz Dalusung, Mr. Gerry T.
Silvestre, Dr. John McManus, Dr. Hal McArthur and
Dr. Madan Dey, who shared with us some o f their views
and materials for this paper.

R e fe re n c e s
Bailey, C ., E ditor. 1982a. S m all-scale fisheries o f San M iguel Bay,
Philippines: social aspects o f production and marketing. ICLARM
Tech. Rep. 9, 57 p.
B ailey, C „ E ditor. 1982b. S m all-scale fisheries o f San M iguel Bay,
Philippines: occupational and geographic mobility. ICLARM Tech.
Rep. 10, 57 p.
Cinco, E.A., J.C. Diaz, Q.P. S ia III and G.T. Silvestre. 1995. A checklist of
fishes caught in San M iguel Bay. In G. Silvestre, C. Luna and I.
Padilla (eds.) M ultidisciplinary assessm ent o f the fisheries in San
Miguel Bay, Philippines (1992-93). ICLARM Tech. Rep. 47. C D ­
ROM. ICLARM , Manila.
Cruz, A. V. and G.T. Silvestre. 1988. Economic analysis o f medium trawlers
in the Lingayen Gulf. Fish. Res. J. Philipp. 13( 1-2): 1-14.
Legasto, R.M ., C.M . del M undo and K.E. Carpenter. 1975. On the hydrobiological and socioeconom ic surveys o f San Miguel Bay for the
proposed fish nurseries/reservations. Philipp. J. Fish. 13(2):205-246.
NSO. 1990a. 1990 Census o f population and housing. Report No. 2-22E
Cam arines Norte, National Statistics Office. Manila. Philippines.
NSO. 1990b. 1990 Census o f population and housing. Report No. 2-23E.
Cam arines Norte, National Statistics Office. Manila, Philippines.

Padilla, J.E., M.L. D alusung and G.B. Calica. 1995. Econom ics o f capture
fisheries in San M iguel Bay. In G. Silvestre, C. Luna, and J. Padilla
(eds.) M ultidisciplinary assessm ent o f the fisheries in San Miguel
Bay, Philippines (1992-1993). ICLARM Tech. Rep. 47. CD-ROM.
ICLARM , Manila.
Pauly, D. and A.N. M ines, Editors. 1982. Sm all-scale fisheries o f San
Miguel Bay, Philippines: biology and stock assessm ent. ICLARM
Tech. Rep. 7, 124 p.
Silvestre, G., E. Cinco, R. G atchalian and J. Diaz. 1995. Catch and effort
in the San M iguel Bay fisheries. In G. Silvestre, C. L una and J. Padilla
(eds.) M ultidisciplinary assessm ent o f the fisheries in San Miguel
Bay, Philippines (1992-93). ICLA RM Tech. Rep. 47. CD-RO M .
ICLARM , Manila.
Sim pson, A. 1978. R eport o f the BFAR/SCS w orkshop on the fishery
resources o f the Pacific coast o f the Philippines. South C hina Sea
D evelopm ent and Coordination Program me, Manila. SCS/GEN/78,
48 p.
Smith, I.R. and A.N. Mines, Editors. 1982. Sm all-scale fisheries o f San
M iguel Bay, Philippines: econom ics o f production and marketing.
ICLARM Tech. Rep. 8, 143 p.
Smith, I.R., D. Pauly and A.N. Mines. 1983. Sm all-scale fisheries o f San
M iguel Bay, P hilippines: options for m anagem ent and research.
ICLARM Tech. Rep. 11, 80 p.
Sunderlin, W.D. 1995a. Livelihood options for fishing fam ilies in San
M ig u e l Bay. In G . S ilv e s tre , C. L una, an d J. P a d illa (e d s.)
M ultidisciplinary assessm ent o f the fisheries in San M iguel Bay,
P hilippines (1992 -1 9 9 3 ). IC L A R M Tech. R ep. 47. C D -R O M .
ICLARM , Manila.
Sunderlin, W.D. 1995b. Socioeconom ic characteristics o f com m unities and
fishing households bordering San M iguel Bay. In G. Silvestre, C.
Luna and J. Padilla (eds.) Multidisciplinary assessment o f the fisheries
in San M iguel Bay, Philippines (1992-93). ICLARM Tech. Rep. 47.
CD-ROM . ICLARM , Manila.
Supanga, N.C. 1982. Costs and earnings o f Cabusao pushnets, p. 61-63.
In I.R. Smith and A.N. Mines (eds.) Sm all-scale fisheries o f San
M iguel Bay, Philippines: econom ics o f production and marketing.
ICLARM Tech. Rep. 8, 143 p.
Supanga, N.C. and I.R. S m ith. 1982. C osts and returns o f C abusao
stationary gears, p. 45-60. In I.R. Smith and A.N. M ines (eds.) Smallsc ale fish eries o f San M iguel Bay, P h ilippines: econo m ics o f
production and marketing. ICLARM Tech. Rep. 8, 143 p.
T rin id ad , A .C ., R .S . P om eroy, P.V. C o rp u z and M .A giiero . 1993.
Bioeconomics o f the Philippine small pelagics fishery. ICLARM Tech.
Rep. 38, 73 p.
Tulay, E. and I.R. Smith. 1982. Costs and earnings o f mini trawlers, p. 6 4 ­
77. In I.R. Smith and A.N. Mines (eds.) Sm all-scale fisheries o f San
Miguel Bay, Philippines: econom ics o f production and marketing.
ICLARM Tech. Rep. 8, 143 p.
Umali, A.F. 1937. The fishery industries o f San Miguel Bay. Philipp. J.
Sci. 63(2): 227-258.
Warfel, H.E. and P.R. Manacop. 1950. O tter trawl explorations in Philippine
waters. U.S. Fish and W ildlife Serv. Dept. Int. Res. Rep. 25, 49 p.
Yater, F. 1982. Gill-netters: costs, returns, and sharing system s, p. 27-44.
In I.R. Smith and A.N. Mines (eds.) Small scale fisheries o f San
M ig u el B ay, P h ilip p in e s : e c o n o m ic s o f p ro d u c tio n and
m arketing.(ICLARM Tech. Rep. 8, 143 p.)

87

O P U S : In te r a c tiv e S o ftw a re f o r S olving
L in e a r P r o g ra m m in g M o d e ls U sin g th e
S im p le x A lg o rith m *
M a x A g ü e r o 1 and S t a f f o f t h e IC LA R M /EC LA C 2
P roject on Socioeconom ic Valuation o f Coastal Resources
o f Southwestern Latin Am erica

AGÜERO, M. and staff o f the ICLARM /ECLAC Project on Socioeconomic
Valuation o f Coastal Resources o f Southwestern Latin America. 1996.
O P U S : an interactive software for solving linear program m ing model
using the sim plex algorithm , p. 87-99. In A. Cruz-Trinidad (ed.)
Valuation of tropical coastal resources: theory and application o f linear
program m ing. 1CLARM Stud. Rev. 25, 108 p.

A b s tra c t
This docum ent introduces the OPUS software conceptualized and
developed under the ICLARM/ECLAC Project on Socioeconomic Valuation
of Coastal Resources o f Southwestern Latin A m erica from 1990 to 1992.
T he softw are is designed and developed for use with IBM PC or its
com patibles. The routines in the software are structured to assist scientists
working on coastal resources valuation through linear programming models.

OPUS’ menus serve as a guide to the different
procedures and functions o f the program. These
facilities, as an example, allow you to:
• manage and maintain the data files efficiently;
• select data entry (tableau in a matrix format);
• select the working language (English or
Spanish; English is the default); and
• sort the data based on geographic areas.
The program was developed using the “Revised
Simplex” algorithm, for solving large models.

OPUS Structure
OPUS has two main modules, Data Manager and
Solution A lgorithm . Data M anager enables
management of the data and controls the execution of
the model. It also generates the interface between the
users and the Solution Algorithm.
The secon d m odule, S o lu tio n A lgorithm ,
solves the m odel using the “R evised Sim plex”
algorithm.

In tr o d u c tio n
This section gives a general description of the
program and defines the symbols and conventions
followed or used in the OPUS software and this manual.

Symbols and Conventions
The following symbols and conventions are used
or followed throughout this manual:

What Is OPUS?

•I
OPUS is an interactive and user-friendly linear
programming software. Its design philosophy is
intended for users with little experience in micro­
computers. Depending on the need of the user, OPUS
offers a set of facilities for file management and for
configuring the program’s working environment. The
other contributions in this volume should be consulted
for the theory behind this approach and examples of
practical applications.
TCLARM Contribution No. 1221.
In tern atio n a l C enter for S u stain ab le E cological D evelopm ent
(ICSED), Casilla 27004, Santiago, Chile.
2United Nations Economic Com m ission for Latin A m erica and the
Caribbean (ECLA C), Casilla 179-D, Santiago, Chile.


1

This box emphasizes important messages of
command or set of instructions.
• BOLD WORDS
This is used to highlight terms in this manual.

S o ftw a re In s ta lla tio n
This section lists the hardware and software
required to install OPUS. It describes the contents of
the diskettes including configuration parameters and
installation procedure.

88

System Requirements
P A T H = C :\ in stallation directory

OPUS was designed to run on the IBM PC (DOS
ver. 3.0 or later) and its compatibles. The following is
the minimum system configuration:
• 640 K-bytes of RAM memory;
• 1 Floppy Disk drive (only for installation);
• 1 Hard Disk drive;
• Color or Monochromatic monitor; and
• 1 Printer.

S E T O P L S = C :\ in stallation d irectory

Finally, you must reboot the system to record the
new commands.

Installation Test
OPUS cannot run from floppy disks. It is essential
to install the program in a hard disk.

Once you have completed the installation, the
following steps can be used to test that installation
was successfully completed.
1st. Run OPUS from DOS prompt.

Installation Procedure
An installation routine is included in the
distribution disk to install properly the software to a
hard disk. Installation involves a set of procedures
described below.
Insert the Disk in a floppy drive and enter the
following command:
INSTALL d e stin a tio n drive:

To complete the installation, the AUTOEXEC.BAT
file will have to be edited to include the following
command lines:

0

C:\OPHS01 enter
OPUS will display its identification screen
(Fig. 1).
Press any key to exit from this logotype screen
and get into the Main Menu.
2nd. Once you are inside the OPUS Main Menu,
select the test file M ANGLAR.
3rd. From the Parameters screen, press F4
to activate the data entry/edit procedure (tableau).
4th. Once you are in the data tableau, run the
program with F3 and then see the outputs.

P U S / P

c

Linear Programming Systcn
Uersion 1.0

^

■

E conom ic C o n n is s io n f o r L a t in A m erica and t h e C a r ib b e a n
I n t e r n a t i o n a l C e n te r f u r L i v in g A q u a tic R e s o u r c e s M anagem ent
P .O . Box 1 7 9 -D S a n t i a g o . CHILE
P h o n e: 5G 2 2 0 8 5 0 5 1
C a b le : UNATIONS
T e l e x : 4 4 1 0 5 4 ITT

Fig. I. OPUS introductory screen.

89

5 th . Press  F 10 several times to go to the
preceding level screens, to com plete a run o f all
o f the routines in OPUS.
If the system does not respond correctly,
proceed as follow s:
1)
Make sure that the AUTOEXEC.BAT
file has the correct path given in the
installation.
2)
Make sure that you have enough memory
(640K ).
3)
Reduce the parameter definitions in the
P A T H and S E T com m an d s in the
C O N F IG .S Y S file.
4)
M ake sure that in the in s ta lla tio n
directory o f O PUS, all the fo llo w in g
files exist:
OPUS.EXE
LPNEW 006.EXE
SWAPCTRL.EXE
LSORT.EXE
PL_M ESSA.ENG
PL_M ESSA .SPN
PL_HELPR.ENG
PL_HELPR.SPN
M ANGLAR.*

(System manager)
(SIMPLEX algorithm)
(Swap routine)
(Sort procedure)
(English m essages)
(Spanish m essages)
(Help in English)
(Help in Spanish)
(Data files to test instal­
lation)

o ru s /p c

Using the Software
File Organization
In order to facilitate file management, it is advisable
to create the directories to store data at DOS level
(please refer to the DOS manual for details on how to
create subdirectories). Moreover, it is recommended
that you update the information contained in the
working directories used by OPUS as often as possible.
It is important to delete all files that are not used and
backup all the standing files. If you want to delete files,
you may do it automatically from the program’s M ain
M enu but if you want to make backup files, use the
DOS CO PY or BA CK U P commands.

Screens and Messages
One of the main characteristics of OPUS is the
common screen format used throughout for the user
interface so as not to distract and to avoid confusion in
using the program.
OPUS has two kinds of messages, help messages
and e r r o r m essages. The former is activated by
pressing F1 and provides information and guidance
on the use of the different commands and functions of
the program (Fig. 2). The Help feature can be invoked
while using the following routines: file management,

LINEAH PROGRAMMING SYSTEM
R iilcr.l o r C a t. h Ne w F i 1e

DATE:« i z 31/1V 9S
j
OPUS/-PC

E:\OPUS0i
U sin g a rro w k e y s ,
s e l e c t an
f i l e and p r e s s ENTER.

e x is tii

P r e s s F4 and e n t e r t h e b a s i c in f o r n i
t i o n a b o u t t h i s new f i l e .
O p tio n a l!
you ca n c r e a t e a co p y o f an e x i s t i i
f ile .
U s in g a rro w k e y s ,
e r a s e and p r e s s 
P r e s s FS and e n t e r t h e f u l l p a th nai

Fig. 2. Sample help window.

90

parametrization, data entry and editing. The error
messages are automatically activated every time an
invalid operation is encountered or invalid data are
entered.
Both kinds of messages are shown in the same
screen where it was activated or where the error
appeared. The help messages are displayed in a window
while the error messages appear on the 23r line of the
d
screen (on top of the Options Menu). To deactivate a
message, press ESC.

Main Menu
The M ain m enu con tain s a set o f file
management functions and utilities to configure the
program ’s w orking environm ent. In the upper
portion o f the window, the names of the existing
data files in the selected directory are shown, while
file creation/identification is done in the lower
window (see Fig. 3).
File management includes creation, copying and
deleting. The program configuation allows the user to
select the working language (English or Spanish) and
define data directories.
•

•

•

•

Once you have entered everything, press F2 to
proceed and record the data or press Esc to Cancel.
These comments are displayed in the lower part of the
window.

To create a new data file (NewFile). Press
F4, and the following data/information
requirements appear:
New file (nam e): Use a combination of up to
eight alphanumeric characters based on the

OPUS/PC

•

•

•

To select any existing data file, look for its
name in the list of Existing Files, set the cursor
on top of it using the arrow keys, and then
press  E nter to complete the selection and
the screen for S03 - parameters is displayed
(see section PARAMETERS for further
information).
To delete a data file (Erase), set the cursor on
top of the name using the arrow keys and then
press F3. Once you have done this, OPUS
will ask you to confirm the operation.
If you want to access your files from a
particular directory (Dir), press F5 and then
enter the pathname of the directory (refer to
DOS manual for more information about
directories and pathnames).

LINEAR PROGRAMMING SYSTEM
S e l e c t o r C r e a te New F i l e

F l- H e l p F 3 -E r a s e F 4 -N e w F lle F S -D lr F8—
Lang
Fig. 3. File selection screen.

format conditions of the file names managed
by the MS-DOS Operating System.
Base file (copy from ): To create a copy of an
existing file, enter the name of this file then
press F2.
Com m ents: To make your file identification
easier, provide some kind o f comments
referring to the model/application you want
to make with the data.

F 1 0 -E x it

91
OPUS/PC

L1NI.DK FKOCKnnniNC SYSTEM
S e l e c t o r C r e a te New F i l e

D fiT E :0 5 /3 i/1 9 9 5
OPUS/PC

C r e a te f i l e
Name
: __________
Comments :

Copy from :

Fig. 4. Language selection screen.

•

•

OPUS can operate in two languages, English
or Spanish. To select the language interface,
press F 8 and then choose the language using
the arrow keys (see Fig. 4). Press  E nter
once you have selected or Esc if you want
to keep the language selected before.
To terminate OPUS and exit to DOS, press
 F10 . To temporarily exit to the DOS
environment, press F9. On a temporary exit
to DOS, once you have finished working in
DOS, enter ‘E X IT ’ from the DOS prompt to
return to the OPUS environment.

Parameter Setting
This routine allows you to:
• select the kind of optimization that will be carried
out with the data;
• fix the control points to ran the program; and
• define data ranges for calibration.
The required data for this screen are as follows
(see Fig. 5):
• To begin the maximization process, type MAX,
otherwise type M IN. Press  E nter to go to the next
field, or move with the arrow keys.
• To select the number of restrictive equations
(rows) that your model will have, press E nter to go
to the next field and replace with new inputs or move
with the arrow keys.

• To select the number of variables of the model,
less the slack and artificial variables, press  E nter to
replace new inputs or move with the arrow keys.

Data Entry/Edit
The data entry/edit routine allows the configuration
of the tableau in a matrix form. The screen format used
for this purpose is shown in Fig. 6 and the main
components are as follows:
1. Heading: On the first two lines of the screen,
OPUS shows the file identification and the objective,
i.e., minimize or maximize. The data that may be
entered/edited here are:
• Data filename
• Kind of process (maximize or minimize)
• Number of constraints in the tableau
• Number of variables (without considering slack
and artificial variables)
• Active edition sector in the tableau (objective
function, constraints coefficients and the right-hand side
of the constraints)
• Cursor position in the tableau
2. D ata tableau: OPUS uses its own coordinate
system. It utilizes the columns identified through a
sequence of alphabetic characters that are located
immediately under the screen heading. The constraints
are enumerated at the left side of the tableau.

92

Fig. 5. Variable number entry screen.

Wane: MANGLAR

P r o c e s s : MAXinize
¡ O b j e c t iv e F u n c t io n C o e f f i c i e n t s
1
■ ! O1

x i 1 A
z ■
!
.\ £ 1 ú 1 
M
C
►
..........m u *
Fx m m w m Ê Ê Ê Ê m - . 1
-1 .7 5 2

■ I

1

m
m
m
m

01
f [IB
IB
 01
m
*j j
1jjÊ

-3

i
1
i

i
i

m

D

1:
-6 .1 7 8
1

i

1

i

C o n s t r a in t s : 108
P o s itio n :

N o n S la c k U a r s : 126

:

. ;
s

R el

=
=
=
=
=
=
=
=
=
=
=
=
=

RIIS

1
1

60
6S
2 4 .5
10
27

100
0
1

0
1
0

1

0
m : 0
= 1
=
0
= 1
sa
0

o clici.fvie wip do V
f
T a b -C u rso r F 2 - S a v e F3-R un F 4-U iew F 5/F 6-N am es A ltM -M o d ify A lt P - P r i n t F I 0-E x i t 1

Fig. 6. Data entry screen.

• OPUS gives default names for the objective
function variables (X I, X2, X3 ... etc.), however, these
labels can be altered. To edit the names of these
variables, press F5 (see Fig. 7). A window is
displayed and you can enter the new names. If you have
more than eighteen variables, you can use the PgUp,
PgDn keys to go forwards or backwards in the
window. To exit this window, press Esc.
• OPUS gives default names for constraints (Y 1,
Y2, ... etc), which can be edited and changed by
pressing F 6 . The screen used for this purpose has
the same format as the one shown in Fig. 7.

The edit feature in the tableau is done by sector.
• The first sector consists of the coefficients of
the objective function, which are edited on the first
row of the tableau, and is denominated as row “Fx” .
• The second sector consists of the constraints
coefficients and are edited in the matrix located
immediately under the objective function.
• The third sector consists of the right-hand side
(RHS) values of each constraint, together with the
relation that conditions them (Rel), which are edited
in the columns located at the right side of the screen.

93
P1™ -

i
V
1
2
3
4
5
6
7
8
9
1
1
1
1
1
*
1
1
1
■

MANGLAR
P r o c e s s : M AXinize
U.tr i .ili It: n,trmv;
f
=
XI
C
= XC1A2
X2
- XC1A3N1E
X3
= XC1A3N2E
X4
= XC1A3N1I
X5
= XC1A3N21
X6
- XC1A4N1I
XV
- XC1A4N2I
X8
= C1A12N1
X9
- C1A12N2
X10
= C1A12N3
X li
= C1A12N4
X12
= C1A1N1
X13
= C1A1N2
X14
= C1A1N3
X15
- C1A1N4
X16
= C1A2N1
X17
= C1A2N2
X18

C o n s t r a in t s : 108
P o s itio n :
D
-3

E
- 6 .1 7 8
1

1

S c r o l l E s c - E x it

t

N o n S la c k U a r s: 126
■C . N1.
.,1
Re 1
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
—

1

RHS
60
65
2 4 .5
10
2?
100
0
1
0
1
0
1
0
0
1
0
1
0

Fig. 7. Variable name entry screen.

• To see the results of a previous execution (View),
To move within the tableau, use the Tab key
press F4. This operation displays the outputs of a
and arrow keys.
process, if any.
3.
Functions menu: The functions menu provides
4.
Multiplying data: To change the values of the
alternatives and facilities to execute the process.
objective function and/or the constraint’s coefficients,
• To save your data in the data directory, press
F2. While the data are being saved, a message and/or the right-hand side in a proportional way, i.e.,
appears at the right corner of the screen which indicates m ultiplying each group by a constant, press
Alt+M and a window will be displayed for you
this.
to enter the options (see Fig. 9). If you enter an option,
• To execute the process, press F3. Processing
time depends on the size of data and speed of computer. the program prompts for the ranges and for the
Hence, it is advisable to first save the data (see below) multiplicative factor. Press F2 to proceed or Esc
to Exit.
before pressing F3 (see Fig. 8).

arne : MANGLAR
P r o c e s s : M AXinize
b j e c t i o e F u n c tio n C o e f f i c i e n t s

C o n s t r a in t s : 108
P o s itio n :

N o n S la c k U a r s : 126
P r o c e s s in
=
=
==
=
=
=
=
=
=
=
=
=
=
=
=
=

Fig. 8. Process status window.

60
65
2 4 .5
10
27
100
0
1
0
1
0
1
0
0
1
0
1
0

94

5.
Exiting: To exit the data tableau and go to the • Reports
previous screen, press F10.
Before you enter the tableau and run the process,
you can select the listings with the results. To do
P rin tin g
that, press F7 and a window with a different set
of options is displayed.
• Data
The screen that displays the final results has the
To print the information contained in a data tableau
(Print), press Alt+P. This function will activate following options:

ante : MANGLAR
P r o c e s s : M AXinize
O b je c t iv e F u n c tio n C o e f f i c i e n t s

C o n s tr a in ts : 108
P osition:

NonSlack U a rs : 126

:
Re I

RHS

Fig. 9. Multiply data menu.

the menu that will allow you to use one of print options
(see Fig. 10):
1. Print the variables and coefficients of the objective
function. For that, you have to enter the range you want
to print, or use the range given by default if you want
to print the objective function completely.
2. Print the constraint coefficients and, optionally,
print the objective function coefficients and the right
side of the tableau.
To print part of the coefficients matrix, enter the
coordinates of the upper left corner and the lower right
corner.
3. Print only the values of the right-hand side of
the tableau and its relational operators. In case the
printer is not enabled, an error message is displayed.
Press F2 to proceed or Esc to Exit

Selecting the options : To select the results of the
process, the following may be followed:
1st. Set the cursor on top of the kind of result you
want to obtain.
2nd. Mark this result pressing Space
3rd. Repeat steps one and two to select the results
of interest.
To complete the selection procedure, press F2.
Exit results menu: To exit the results selection
screen, press Esc.
Outputs
OPUS can generate a set of reports from the final
results of the process. As an option, OPUS generates
a report with the partial results in each iteration that
you specify.

95

• Final results
The report with the final results that you selected is
shown in a special screen which provides a set of options
that, among other things, allows you to print selected
results (Fig. 11).

• OPUS allows you to print results selectively. To
do that, a special menu is displayed that is activated by
pressing theF7key. This function allows you to select
from a menu (see Fig. 13), the kinds of results you want
and the variable range to print, menu.

Fig. 10. Data printing menu.

• To move from one place to another in the

• To activate the results printing process, press

results report (Fig. 12), use the PgUp, PgDn,

^  ’
...
.
» T o exit this screen and go back to the previous
one, press F10, otherwise press Esc.

and arrow keys.

OPUS/PC
MANGLAR

LINEAR PROGRAMMING SVSTEM
G e n e r a l P a r a m e te r s

DATE:0 6 / 0 1 /1 9 9 5
OPUS/PC

E:\OPUS0i
Output Menu
PRIMAL UALUES
DUAL UALUES
RMS RANGES
COST RANGES

Fig. 11. Output menu.

The solution to the
The s o l u t i o n to the
Ranges for e l e m e n t s
Ranges for elements


l i n e a r program
dual
:
of the RHS column ;i
of the o b j e c t i v e row

96
N ane: MANGLAR

P r o c e s s : MAXimize

C o n s t r a i n t s : 108

_ ^ ^ _ ^ ^ ^ _ O u t j £ U t P r o b I e i r i _ J  o l u t i o n _ _ _ i_

5 4 3 .4 0 3 8 7 0
O p t in iz e d U a lu e :
PRIMAL PROBLEM SOLUTION

MANGLAR
U a r ia b le

S o lu tio n

i s MAXIMU
5 / 31/ 199 $

L evel

S ta tu s

XC1A1
XC1A2
XC1A3N1E
XC1A3N2E
XC1A3N1I
XC1A3N2I
XC1A4N1I
XC1A4N2I
C1A12N1
C1A12N2
C1A12N3
C1A12N4
C1A1N1
C1A1N2

N o n S la c k U a r s : 126

B a s is
B a s is
N o n b a s is
N o n b a sis
B a s is
N o n b a sis
B a s is
N o n b a s is
B a s is
N onbas i s
B a s is
B a s is
B a s is
N o n b a s is

10.0000
0.0000
0.0000
0.0000
2 4 .5 0 0 0

0.0000

2 7 .0 0 0 0

-

0.1000
0.1000

- 1 .7 5 2 0
- 3 .0 0 0 0
- 6 .1 7 8 0
- 10.0000
- 6 .4 7 8 0

10.0000

0.0000

-

0.0000
0.0000
0.0000
1.0000
0.0000

- 0 .0 8 0 0
-0 .7 2 0 0
- 2 .8 8 0 0
- 1 1 .5 2 0 0
- 0 .5 0 0 0
- 1 .2 5 0 0

1 .0000

t-I« --» -S cro ll PgUp/PgDn-ScrM ou F 7 ~ S e t0 u t F 8 ~ P r in t

F I 0 - E x it I

Fig. 12. S o lu tio n o u tp u t sc ree n .

Name: MANGLAR

P r o c e s s : MAXimize
C o n s t r a i n t s : 108
O u tp u t P rob lem S o l u t i o n

N o n S la c k U a r s: 126

Fig. 13. O u tp u t sta tu s m en u .

A c k n o w le d g e m e n ts
™

■

r t / - t

Ann*

R e fe re n c e
T -i-

1 he assistance ot 1CLARM programmers, bn

Garnace and Felimon C. Gayanilo, Jr. as well as the
supervision from Daniel Pauly are acknowledged
gratefully.

Pauly, D. 1993. D ata-rich books. B ioS cience 43(3): 167-168.

97

Appendix 1. Documentation of LP tableaus.
In the tradition of data-rich books (Pauly 1993),
this appendix is written for users who may want to
test, verify and update the data used in the linear
programming tableaus (Araneda et al., this vol.; Bell
and Cruz-Trinidad, this vol.; Cruz-Trinidad et al., this
vol.; and Cruz-Trinidad and Garces, this vol.).
The files used in these application papers are
available in spreadsheet format. Files Bio.wbl and
Fabio.w bl. having been validated using LP88 , are
available in LP format. F iles L in ga.w b l and
Sanmig.wbl have been validated using the LP routine
of a commercial spreadsheet package.
All files can be accessed and processed in OPUS
software or any other LP program that is available.
File Name File Size (KB)
1. Fabio.wbl
31,200
2. Bio.wbl
115,652
3. Linga.wbl
6,736
4. Sanmig.wbl
34,264

Appendix 2. Glossary of technical terms.
a r tif ic ia l m a rk e t - a market that could be
constructed for experimental purposes, to determine
consumer willingness to pay for a good or service. For
example, a home water purifier kit might be marketed
at various price levels or access to a game reserve might
be offered on the basis of different admission fees,
thereby facilitating the estimation of the value placed
by individuals on water purity or on the use of
recreational facility, respectively.
backup - security copy for effective recovery in
the event of loss of service from some other resource.
balance equations - constraint equations used in
the stepwise linearization process.
b a sic s o lu tio n - augm ented corner-point
(infeasible) solution.
bequest value - value that people derive from
knowing that others (perhaps their own offspring) will
be able to benefit from the resource in the future (also
heritage or preservation value).
coefficient - constant value for variables in the
various equations and/or objective function.
collusion - agreement between firms to cooperate
to avoid mutually damaging rivalry which may involve
informal or tacit agreement, arising, for instance, from

the pooling of information, to formal arrangement
within cartel organizations where sanctions are
imposed on defectors.
c o n s tr a in e d m a x im iza tio n a p p ro a c h - the
maximization of an objective function where the choice
variables are subject to some constraints.
constraints - restrictions to which the objective
function is subjected; usually a m athem atical
relationship between the choice variables o f an
optimization problem, in which some function of the
variable (e.g., a linear function) is not equal to a
constant. An example is a budget constraint on the
maximization of utility.
contingent valuation - a nonmarket valuation
technique which tries to obtain information on
consumers’ preferences by posing direct questions
about willingness to pay. What is sought are personal
valuations of the respondent for increases or decreases
in the quantity o f some good, contingent upon a
hypothetical market.
data files - set of stored data, containing the inputs
given by the users, grouped together under a unique
file name.
defensive expenditure - one approach in eliciting
willingness to pay based on direct effects valued on
conventional markets. Individuals, firm s, and
governments undertake a variety o f “defensive
expenditures” in order to avoid or reduce unwanted
environmental effects. Environmental damages are
often difficult to assess, but information on defensive
expenditures may be available or can be obtained at
lesser cost than direct valuations of the environmental
good in question. Such actual expenditures can then
be interpreted as a minimum valuation of benefits.
dual - the minimization associated with each linear
programming problem in standard form , i.e.,
mathematically,
given LP1: Max cx
such that Ax  b
x 0
then the LP given by
LP2: Min by
such that A‘y  c
y 0
is called the dual of LP1 and LP1 is called the
primal.
elasticity - a measure of the percentage change in
one variable with respect to a percentage change in
another variable. Measures of elasticity tend to be

98

carried out for very small changes in the variable
causing the response (e.g., a percentage change in
quantity due to a very small change in price).
existen ce value - the perceived value o f an
environmental asset unrelated either to current or
optional use; that is, simply because the resource exists.
externality - externalities are variously known as
external effects, external economies and diseconomies,
spillovers and neighborhood effects. Externalities exist
when the production or consumption of a good or
service by one economic unit has a direct effort on the
welfare of producers or consumers from another unit.
future value - the value in the future of an amount
to be received or paid in the current period. This is
determined by multiplying the present value of income
by the discount factor 1 -* (1 + i)n.
■
game theory models - models using a theory of
individual rational decisions under conditions of less
than full information concerning the outcomes of those
decisions. The theory examines the interaction of
individual d ecisions given certain assumptions
concerning decisions made under risk, the general
environment, and the cooperative or uncooperative
behavior of other individuals.
indirect use value - value of an ecosystem in the
provision of a number of biological life support
functions that are generally public goods (e.g., coral
reefs provide biological support in the form of nutrients
and habitat for coral fisheries, and coastline protection
functions).
input-output models - models utilizing a method
of analysis in which the economy is represented by a
set of linear production functions, describing the
interrelationships between all sectors.
lin e a r p r o g ra m m in g - a technique for the
formalization and analysis of constrained optimization
problems in which the objective function is a linear
function, and is to be maximized or minimized subject
to a number of linear inequality constraints.
market failure - the inability of a system of private
markets to provide certain goods at the most desirable or
‘optimal’ levels. In general, market failures arise because
of 1 ) nonexcludability; and/or 2 ) nonrival consumption
of a good. Nonexcludability means that individuals who
have not paid for a good cannot be prevented from
enjoying its benefits. A good is nonrival if its
consumption by one person does not preclude its

enjoyment by anyone else.
monopoly - in the strictest sense of the term, a
firm is a monopoly if it is the only supplier of a
hom ogeneous product for which there are no
substitutes and many buyers.
multiperiod linear programming - activities are
repeated in a number of periods and constraints are
progressively modified over time so that the optimal
solution within periods varies.
nonlinear programm ing - in contrast to linear
programming, this involves an optimization framework
that can handle nonlinear objective functions as well
as nonlinear inequality constraints.
nonuse value - value attributed to a resource for
its use by future generations (bequest value), its future
direct and indirect use by present generations (option
and quasi-option value), and its present utility because
of the knowledge of its existence (existence value).
objective fu n c tio n - a function relating the
objective (the variable to be optimized) to the choice
variable in an optimization problem.
option value - the value of a resource based on
how much individuals are willing to pay today for the
option of preserving the asset for future (personal)
direct and indirect use.
perfect competition - a market structure is perfectly
competitive if the following conditions hold: 1 ) a large
number of buyers and sellers; 2 ) homogenous products;
3) availability of perfect information; and 4) free entry.
pivot element - coefficient located in the intersection
of the entering basic variable and the leaving basic
variable.
prim al - (see dual).
property value - also referred to as a “hedonic
price” technique, the property value method is based
on the general land value approach. The objective is
to determ ine the im p licit prices o f certain
characteristics of properties. In the environmental area,
for instance, the aim of the method is to place a value
on the benefits of environmental quality improvements,
or to estimate the costs of a deterioration (for example,
the effects of air pollution in certain areas).
pure profit - a residual sum left over when we have
subtracted from the revenue generated by some activity
all of the opportunity costs of production, the normal
profit required to keep the producer in business.

99

reduced cost/return - feasible range given to the
cost/return variables in the optimization process.
replacement cost - under this approach, the costs
that would have to be incurred in order to replace a
damaged asset are estimated. The estimate is not a
measure of benefit of avoiding the damage in the first
place, since the damage costs may be higher or lower
than the replacement cost. However, it is an appropriate
technique if there is some compelling reason as to why
the damage should be restored, or certainty that this
will occur.
right-hand side (RHS) - constant value located
at the right-hand side of the equation (constraint).
se n sitiv ity an a lysis - involves changing the
parameters of a decision problem and studying how
this affects the outcome. It is particularly associated
with cost-benefit analysis, where the most common
form is the use of alternative discount rates. The
purpose of the analysis is to identify the important
assumptions upon which the analysis is based - those
to which the outcome is sensitive.
sh adow p ric e - an imputed valuation o f a
commodity or service which has no market price.
Shadow prices are used in cost-benefit analysis and in
the application of mathematical programming to a
planned economy. They represent the opportunity cost
of producing or consuming a commodity which is
generally not traded in the economy. Even in a market
economy certain outputs such as health, education, and
environmental quality do not attract a market price. A
set of shadow prices representing consumers’ marginal
rates of substitution or producers’ marginal rates of
transformation between such commodities may be
calculated reflecting the marginal costs of production
or the marginal value of their use as inputs. To the
extent that market prices do not reflect opportunity
costs, cost-benefit analysis may substitute shadow
prices.
shadow price vector - represents the (maximum)
change in value that the objective function can take if
an additional unit of a constraining factor is available.
sim p lex algorith m - a sim plex is a sort of
n-dimensional analog of a triangle, with corners that
represent extreme points, and the simplex method
provides a systematic procedure whereby we can move
from one extreme point of the feasible region to

another, till the optimal one is reached.
slack variables - variables that are introduced to
convert the functional inequality constraints into
equivalent equality constraints.
swap - computational techniques that involve
transferring data to another storage media while it is
not being used to maximize RAM memory.
tableau - a tabular form to record the essential
information in a linear programming problem, namely,
the coefficients of the variables, the constants on the
right-hand side of the equations, and the basic variables
for each equation.
Total Economic Value (TEV) - sum of total use
value and nonuse values of the environment when
viewed as an asset.
travel cost - the travel cost method measures the
benefits produced by recreation sites (parks, lakes,
forests, wilderness). A related method can also be used
to value “travel time” in projects dealing with fuelwood
and water collection.
use value - associated with both direct extractive
uses (e.g., of fish, coral) and nonextractive direct uses
(e.g., recreation) of the environment as an asset.
virtual disk - a store management system in which
a user is able to use the storage resources of a computer
without regard to constraints imposed by a limited main
store, and the requirements of other applications which
may be using the system.
wage difference - this method is based on the
theory that in a competitive market the demand for
labor equals the value of the marginal product and that
the supply of labor varies with working and living
conditions in an area. A higher wage is therefore
necessary to attract workers to locate in polluted areas
or to undertake more risky occupations. Again, as in
the case of property value, the wage differential can
only be used if the labor market is very competitive.
w illin g n e ss to p a y ( WTP) - a m easure of
consumer’s surplus, it is the amount a consumer is
willing to pay over and above current consumption of
a particular good or service.
working directory - directory configured by the user
to save swap files, communication files between the data
manager module and the solution algorithm module, and
output files. The default working directory, if the user
does not configure one, is the data directory.

100

Author/Name Index
Agüero, M. vi, viii, 1, 4, 6-7, 9, 20, 31, 52, 56, 59, 68, 76, 83,
86-87

Dom ingo, F. 64, 68-69, 72, 74, 76
Dourojeanni, A. v

Ahm ed, M. viii, 4, 7

Dow, J.P., Jr. 4, 8

Alojado, Z. 1-2, 64, 68-69, 72, 74, 76, 97

Doyle, J.K. 14, 16

Alterm an, R. 5, 8

Edwards, W. 14, 16

Añonuevo, C. 65, 76
Aquacop 2 1 ,3 1

Espinoza, F. 22, 31

Araneda, E. viii, 1-2, 13, 32, 97

Fallon, L.A. 12, 16

Fabunan, A. viii

Arellano, A. viii, 1-2, 13, 32, 97

Fallon-Scura, L. vi, 9, 16

ASEAN/US CR M P 7

Färber, S.C. 13, 16

Aylward, B. 10-11,16

FEDECAM 27,31

Bagarinao, T. 73, 76
Bailey, C. 78, 86

Ferrer, E.M. 65, 76

Balsiger, J.W. 4, 8

Flores, X. 7, 9

Fischhoff, B. 14, 16

Barbier, E.B. 1 0 -1 1 ,1 4 ,1 6

Folke, C. 13,15

Barton, D.N. 14, 16

Fox, P. 6 8 ,7 6

Bell, F.W. vi, viii, 1-2, 6, 16-17, 56, 83, 97

FPVM 2 7,31

Binudin, C. viii

Furby, L. 14, 16

Bishop, R.C. 14, 16

Garces, L. 1 ,3 - 4 ,7 8 ,9 7

Bower, B.T. 4, 8

Garcia, S.M. 9, 16

Boyle, K.J. 14, 16

Gam ace, E. viii, 96

Brekke, K. 4, 8

Garrod, D.J. 4, 8

BSWM 6 9 ,7 6

Gatchalian, R. 78, 80-83, 86

Buhyoff, G. 14,16
Bunpapong, S. 7-8

Gayanilo, F.C., Jr. viii, 96

Cacanindin, E. 64, 69, 76

Gonzalez, E. vi, viii, 1, 6, 20, 31, 56, 76, 83

Calica, G.B. 83-86

Gregory, R. 11, 14, 16

Camacho, A S. 73, 76

Guiang, J.C. 64, 68-69, 72, 74, 76

Glass, R.J. 14, 16

Cargam ento, A.G.C. 1-2, 64, 69, 72, 76, 97

Haywood, K. 2

Carpenter, K.E. 78, 86

Hazell, B.R. 3, 8

Carpenter, R.A. 12, 16

Hilbom , B. 14, 16

Castillo, G. 6 5 ,7 6

Hill, M. 5, 8

Casuga, K.Q. 64. 69, 76

Hodgson, G. 13, 16

Catalan, A. viii

Holling, C. 7-8,31

Cátelo, R. 65. 76

Homa, R. 19-21,31

CEPAL 59

Hufschmidt, M. 4, 8, 14, 16

Chan. H. 65, 76

Hundloe, T. 1 1 ,1 3 ,1 6

Chou, L.M. 6 - 7 ,3 1 ,7 6

Hupert, D.D. 4, 8

Chua, T.-E. 1, 6-9, 16, 18, 31, 64, 76-77

Hyman, E.I. 5, 8, 11, 13-14, 16

Cinco, E. 78, 80-83, 86

IFOP 3 6 ,5 9

Cintrón, G. 17,31

Ignizio, J.P. 3, 8
Ingles, J. 30-31

C U R S E N 17,31
COREM A 46, 59

James, D.E. 4, 8

Corptiz. P.V. 86

Johnson, M. 14, 16

Costanza, R. 13, 16

Karberger, T. 13,16

Cruz, A.V. 68, 76, 86
Cruz-Trinidad. A.V. vi, vii, viii, 1-4, 6, 9, 13, 17, 19, 31-32, 56,
64. 73, 76, 78, 83, 87, 97

Keeney, R. 5, 8, 14, 16
Kennedy, J.O.S. 4, 8
Khoo, H.W. 3 1 ,7 6

Cun, M. 19,31

Klemas, V. 17 ,2 1 ,3 1

Dalusung, M.L. 81-86

Krutilla, J.V. 10,16

Dannhaeuser. N. 72, 76

Laszio, E. 2, 8

de la Cruz, C.R. 72

Lazo, J.K. 14,16

del Mundo, C M. 78, 86

Legasto, R.M. 78, 86

Dey. M. 86

Lenz-Volland, B. 20,31

Diaz, J.C. 78. 80-83. 86

Leontief, W.W. 4, 8

Dixon, J.A. 2, 4, 7-8, 12-13, 16

Lim, P.E. 3 1 ,7 6

LiPuma, E. 21-22, 30-31

Sawyer, D.A. 13, 16

Luna, C. 86

Schaefer, Y. 17,31

Lutz, E. 12, 16

Schulze, W.D. 1 4 ,1 6

Manacop, P.R. 78, 86

Schuman, H. 14-15

Manopimoke, S. 12, 16

Scott, A. 14, 16

Marín, C. 19,31

Scura, L.F. 1, 8 see also Fallon-Scura, L.

Markandya, D. 14, 16

Segovia, A. 17, 21, 31

Marsh, J.B. 16

Shepherd, J.G. 4, 8

M artosuboro, P. 7-8, 73, 76

Sherman, P.B. 12, 16

Matessich, R. 2, 8

Sia, Q .P .III 80-81,86

Maxwell, J. 13, 16

Siegel, R.A. 4, 8

McArthur, H. 86

Signey, L.O. 68, 77

McCarl, B.A. 4, 8

Silvestre, G.T. 31, 68, 76-78, 80-83, 86

McClelland, G.H. 14,16

Simpson, A. 78, 86

McManus, J. 86

Smith, LR. 78, 81, 86

McM anus, L.T. 7-8, 64-65, 76-77

Snedaker, S.C. 21,31

M cPadden. C.A. 22,30-31

Snyder, W. 14, 16

Medina. M. viii

Solorzano, C. 20, 31

Meister, A.D. 4, 8

Sorenson, J. 5, 8

Meltzoff, S.K. 21-22,30-31

Spindler, J. 14, 16

Mines, A.N. 64, 76, 78, 86

Spreen, T.H. 4, 8

Morales, F. 1-2, 13, 32, 97

Spurgeon, J.P G . 11, 16

Moran, D. 9, 16

Squires, D. 4, 8

Mueller, J.J. 4, 8

Stiftei, B. 5, 8, 11, 13, 16

M unasinghe, M. 12, 16
Muth. R.M. 14, 16

Sunderlin, W. viii, 79, 86

Naamin, N. 73, 76

Terchunian, A. 17 ,2 1 ,3 1

NEDA 6 4 .7 6

Torres, F.S.B., Jr. viii

Newton. C. 9, 16

Trinidad, A.C. 86 see also Cruz-Trinidad, A

Norton. R.D. 3, 8

Tsukayama, 1. 7, 59

NSCB 7 4 .7 6

Tulay, E. 81, 86

NSO 78, 86

Twilley, R. 18,31

Padilla, J .E. 4 ,8 ,8 1 ,8 3 - 8 6

Ulvila, J. 14,16

Palma, A. 68. 72, 76-77

Umali, A.F. 78, 86

Supanga, N.C. 8 1 ,8 6

Panayotou, T. 9 ,1 6

United States Fish and W ildlife Service 5, 8

Pauly, D. vii, viii, 7, 30-31, 59, 68, 77-78, 86, 96-97

Valencia, M.J. 3 1 ,7 6

Paw, J.N. 1.7-8, 1 8 ,3 1 ,6 4 ,6 8 - 6 9 ,7 2 ,7 4 ,7 6

Velasco, A. 18,31

Pearce, D.W. 9. 14, 16
P1DS 72, 77

Volland, M. 20,31
Walker. K.B. 14, 16
Wallace, S.W. 4, 8

Pomeroy. R. viii, 86

Warfel, H.E. 78, 86

Primavera. J.H. 72, 77

Watkins, J.W. 4, 8

Raffia, H. 5, 8. 14, 16

Weisbrod, B.A. 10, 16

Randall, A. 5, 8, 13, 16

Wellman, J. 14, 16

Rettig, B. 14, 16

Welsh, M.P. 14, 16

Pido. M.D. 1,8

Rillon, N. 64-65, 69, 76

White, A.T. 7-8, 86

Rivera. R.A. 65, 76
Robilliard, G. 5, 8

W hitehead, J.C. 14, 16
Williams, M.J. viii, v

Rodriguez, S. 65, 76

W interfeldt, D. von 14, 16

Rollet. B. 19,31

Wong, P.K. 31, 76

Rothschild, B.J. 4, 8

Yanez-Arancibia, A. 31

Ruitenbeek, H.J. 13, 16

Yater, F. 81, 86

Sadorra. M.S.M. 6-8

Zamora, P.M. 73, 77

»

102

Geographic Index
Africa, subSaharan vi
Agoo 6 4 ,6 8 -6 9 .7 1

Concepcion 32-34, 37-38, 42, 44
Bay 45-46

Alam inos 64, 68-69, 7 1

Coquim bo 36

América Latina 3 1 ,5 9

Coronel 38-40, 44

America, Latin v. 1, 31

Dagupan 6 4 ,6 6 ,6 8 -6 9 ,7 1 -7 2

South vi. vii. viii

Desem bocadura 44

Anda 6 4 .6 8 -6 9 .7 1 -7 2

Dichato 46

Andean m ountain range 32-34

Diguillín 33

Antuco 32, 44

D uqueco 33

Arauco 32, 39, 44, 47

Ecuador vi, vii, viii, 1, 9, 14-15, 17-22, 24-25, 27-31, 36

-Cañete 32

El Blanco 3 9 ,4 7

G ulf 32, 33, 36-38, 46

El Morro 39,45-47

Aringay 64, 69, 7 I

El Oro Province 21

Asia vi, 76

England, New 4

Southeast vii. 7, 31, 77

Escuadrón 44

Australia 42

Esmeraldas 21

Ban Don Bay 7-8

Europe 11

Bangladesh vi, 4, 7

Florida 13

Bani 6 4 ,6 8 -6 9 ,7 1 -7 2

Galápagos Islands 36

Barents Sea 4

Germany 44

Basud 78, 80

Great Barrier R eef 11,13

Bauang 64, 68-69, 71

Guayaquil 21,31

Bayawas River 68
Benguet 68
Bicol region 78

Golfo de 31
G ulf of viii, 1, 9, 14-15, 17-19
Guayas 1 7 -1 9 ,2 2 ,2 4 -2 5 ,2 7 -2 9

Binmaley 64, 68-69, 71-72

Province 17, 21

Bintuni Bay 16

River 17

Bio-Bio viii, 1, 32-34, 41, 46-47, 60-63

Guimaras Strait 4

Boca Sur 39, 47

Indonesia 7-8, 16, 76

Bolinao 6 4 .6 8 -6 9 ,7 1 -7 2

Irian Jaya 16

Bristol Bay 4

Isla M ocha 36-38

Brunei D arussalam 6-7

Isla Rocuant 45-46

Bulnes 34

Israel 8

Bureo 33

Itata 33

Caba 64, 69

Johore, South 6-7

Cabrero 34

La Conchilla 39, 47

Cabusao 78, 86

La Union 64-65, 68-69, 72, 76

Calabanga 78

Labrador 6 4 ,6 8 -6 9 ,7 1

California 42

Laja 3 3,45-46

Callaqui 32
Camarines Norte 78, 86

Lake National Park 44
Laraquete 35, 38-39, 44, 47

Camarines Sur 78

Larqui 33

Caribbean 1

Las Escaleras 44

Carolina, North 14

Las Peñas 39, 47

Carretera Panam ericana 34

Lebu 37

Cato 33
Chaim ávida 34

Lenga 35, 39, 44, 47

Chiguallante 45

Lingayen 68-69
G ulf vii, 1, 7-8, 64-65, 67-68, 70-73, 76-77, 86

Chiguayante 42

Lirquen 45-46

Chile vi, vii. viii. 1, 11, 32-33. 34-36, 38, 40-43, 47, 59-63

Llico 35, 39, 44, 47

Chillan, Mt. 32-34, 44

Lo Rojas 38-39, 47

Chiloé 36

Los Angeles 34

Chivilingo 35, 44

Lota 3 8 -3 9 ,4 4 ,4 7

Cholguán 33

Luzon 64

Colcura 35, 39, 44. 47

Central 68

Coliumo 37

Northwestern 69

M agallanes, Straits of 36

Rahue 33

M alaysia 6-7

Ramuntcho 35, 44

M alleco 33

Ranquil 33

M anabi 20-21

Recoto 35, 44

M angaldan 68

Rosario 64, 69

M anila vi, 86

Sam ar Sea 77
San Antonio 38

Bay 65
M aule 39, 47

San Fabian 64, 68-69, 71-72

M ercedes 78, 80

San Fernando 64, 69, 71

M ichigan, Lake 14

San M iguel Bay vii, 1, 3-4, 78-86

Mocha 32

San Pedro 45

M ontevideo 31

San Vicente 38-40, 46

M ulchén 33

San Vicente, Bay o f 32-33, 35, 37-38, 44-46

N ahuelbuta Range 32

Santa M aria Island 32, 37

Nuble 3 2 -3 3 ,4 4

Santiago vi, 59

Oregon 16

Segara A nakan-Cilacap 7-8

Pacific 76

Sipocot 78

coast 4, 78, 86

Sirum a 78, 80

Pagbilao Bay 72
Palawan 13, 72

South Java 8

Palpal 33

Sto. Tomas 64, 69, 71

Spain 55

Pangasinan 64-66, 68-69, 72

Sual 6 4 ,6 8 -6 9 ,7 1 -7 2

Penco 44-45

Talcahuano 32, 38, 40, 44-46

Peru vi

Thailand 7-8

Phangnga Bay 7-8

Tinambac 78

Philippines v, vi, vii, 1, 4, 7-8, 13, 64-65, 73, 76-79, 86

Tirua 34

Playa Blanca 35, 44

Tomé 3 8 ,4 0 ,4 5 -4 6
Tompé 46

Pueblo Hundido 39, 47
Puerto Coronel 35
Puerto de San Vicente 34
Punta Lavapie 35, 39, 44, 47

Tubul 35, 38-39, 44, 47
Tumbes peninsula 32
Ulugan Bay 72

Queco 33

United States 11, 22, 44

Quezon Province 72

Uruguay 31
Vergara 33
Visayas, Western 4, 68

Quirihue 34
Quiriquina 32

104

Species Index
abo 8 1 see cro a k er(s); pagotpot

Bonito 38, 60

A cacia caven 62

b ream (s) 38, 40

A canthocybium solandri 6 0

Breca 60

Acantholatris gayi 60

Brótula 60

A cha 60

Caballa 60

Aextoxicom punctatum 62

caballero 19

Agujilla 60

Cabinza 60

Albacora 6 0

Cabrilla 60

alb aco re 38, 4 9 -5 0 , 52, 56

Alerce 62

común 60
Cachurreta 60

a lg ae 3 5 ,3 7 - 3 9 ,5 2 - 5 4 ,5 6 - 5 8 ,6 1

Calamar 61

Algarrobo 62

Caldcluvia paniculaía 63

Alm eja (taca) 61

Callinectes toxotes 19 see m olluscs

Alopias vulpinus 6 0

Callorhinchus callorhinchus 60

A m om yrm s luma 63
Am om yrtus m eli 63

Calyptraea trochiformes 6 1
Camarón de roca 6 1

A nadara granáis 19 see m o llu sc(s)

Camarón nailon 36, 61 see also Heterocarpus reedi; shrim p,

Anadara similis 19 see m o llu sc(s)
Anadara tuberculosa

19-20 see m ollusc(s)

a n ch o v e ta 3 5 -3 7 , 39-40, 49 -5 0 , 56, 6 0 see also Engraulis

ringens; an ch o v y , P eru v ian
P eru v ian 7, 59

C hilean nylon

Cancer coronatus 6 1
Cancer edwardsii 61
Cancer porteri 61
Cancer setosus 6 1

a n ch o v ies 80-81 see also dilis

Canelo 62

an ch o v y 38. 52

Caracol locate 61

P eru v ian 36 -3 7 , 53 -5 4 , 5 7 -5 8 see also Engraulis ringens;

anchoveta

Caracol tegula 6 1
Caracol trumulco 6 1

Anguila 60

C aran g id ae 81

Anhfeltia 62

carp 4

Anhfeltia plicata 62

c atfish 4

Anisotremus scapularis 61
Apañado 60

Cazón 60

A p o g o n id ae 81

Centollón

Araucaria 62

c ep h alo p o d (s) 81

araucana 62

Cervimunida johni 36, 61 see lobster, yellow ; langostino amarillo

Arrayán 63

Chancharro 60

Centolla 6 1
61

A tún aleta am arilla 60

Chanos díanos 68 see m ilkfish

Atún aleta larga 60

Chasca 61

Atún de ojo grande 60

gruesa 61

Aulacomya ater 61

Chascón 6 1

Austrocedrus chilensis 62

Chicorea de m ar 62

Avellano 62

Chione subrugosa

Avicennia 18, 24, 2 7 -2 9
nítida 19 see also m an g ro v e

Chlamys patagónica 6 1

spp.

17 see also m an g ro v e, b lack

19

Chlamys purpurata 61
Chocha 6 1

Ayanque 6 0

Cholga 6 1

Azulejo 60

Chonclrus canaliculatus 62

Bacalao 52, 56

Chorito 6 1

de profundidad 36, 6 0 see D issostichus eleginoides;
to o th fish . P atag o n ian

Choro zapato 6 1
Choromytilus chorus 61

Beilschmiedia berteorana 63

Chorus giganteus 61

Beilschmiedia m iersii 63

Cihts montti 60

B ellota d e l N o rte 63

Ciprés de Cordillera 62

B ellota d e l S u r 63

Ciprés de Guaitecas 62

Blanquillo 60

clam (s) 27, 37

Baldo 63

Clupea bentincki 36, 61 see herring, A raucanian

Bollán 63

clu p eid (s) 80

Cochayuyo 62

eucalyptus 3 2 ,4 1 ,4 3 ,4 8 ,5 5 - 5 6 , 59

cockle(s) 18, 37

Eucalyptus camaldulensis 41

cod 38-39.49
Coelorhynchus spp. 60

Eucalyptus viminalis 41

Coigue 42. 63
de Chiloe 63
de M agalkmes 63

Eucalyptus globulus 41-43, 51
Eucryphia cordifolia 63
Euphausia superba 61
Fissurella spp. 61

Coihe 42

Fitzroya cupressoides 62

Cojinoba del none 60
Cojinoba del Sur 60

Galeorhinus ziopterus 60
Gamba 61

Cojinoba moteada 60

Gamortega keule 63

conch 37
Concholepas concholepas 61

Gelidium rex 61

condor 11

Genypterus blacodes 60

conger, black and gold 40

Genypterus chilensis 60

(ongno Colorado 60

Genypterus maculatus 36, 60 see eel, black cusk-; congrio negro

Gari solida 36, 61 see culenge

Congrio dorado 60

G em ina avellana 62

Comzrio negro 36, 60 see eel, black cusk-; Genypterus maculatus

Girellops nebulosas 60

Conocarpus erectus 19 see mangrove

Glacilaria spp. 62

Corvina 60
Corxphaena hippurus 60
crab(s) 19-20. 24, 26-27. 29-30, 37-38, 49, 57-58, 80 see also

Gobiidae 81
Graus nigra. 60
grenadier 54, 57-58
Patagonian 37, 52-53, 56

jaiba; Callinectes wxotes; Portunidae; Ucides spp,
black 49-50

groundfish 4

Crassostrea gigas 61

grouper(s) 38, 68

crevalles 81

grunt 38

Crinodendron paragua 63
croaker(s) 80-81 s e e also abo; pagotpot

Gymnogongrus furcellatus 61

crustacean(s) 2. 15. 19,35-37 see also crab(s)

hake 32, 35-38; 40, 52-54, 56-58 see also M erluccius gayi; merluza,

hairtail(s) 81
común

C npiocaiya alba 63
Culengue 36,61 see also Gari solida
Cvnoscion analis 60
cvprinid 14 see also Notropis chrysocephalus

com mon 49-50, 55
Haliporoides diomedeae 61

Dasyphyllum diacanthoides 62

Helicolenus lengerichi 60
Hemichordate 62

demersals 80

H emilutjanus macrophthalmos 60

dibs 81 see anchovies
Dissostichus eleginoides 36 see bacalao de profundidad;

herring 81

toothfish, Patagonian

Araucanian 36-37 see also Clupea bentincki; sardina común
Heterocarpus reedi 36, 61 see Camarón nailon; shrimp, Chilean
nylon

Dissostichus eleginoides 60
Dorado 60

hilsa 4

Dosidicus tunicata 61

Hippoglossina macrops 60

Drepanidae.81

Homalaspis plana 61

Drimys winteri 62

Hualo 63

Dunilaea antarctica 62

huepo 36 see also Ensis macha

eagle, bald 11

Huiro 62

Echinoderms 35, 62

Iridaea ciliata 62

eel(s) 3 8 .5 3 -5 4 .5 6

Isacia conceptionis 60

black cusk- 36. 38 see also Genypterus maculatus
Eleginops niaclovinus 60

Isurus glaucas 60
Jaiba 19, 61 see crab

elephant fishes,40

limón 61

Einbotliriuin coccineum 62

mora 61

Engraulidae 80-81 see anchovies

peluda 61

Engraulis ringens 35, 60 see anchovy, Peruvian; anchoveta
Ensis inacha 36, 61 see huepo
Eri:o 62

reina

61

Jasus frontalis 61
Jeli prieto 19

Espino 62

Jibia

Ethnndium maculatum 60

Jubaea chilensis 62

Eucalipto 43

jurel 35, 60 see mackerel, jack

Eucalypto 42

Kageneckia oblonga 63

61

106
Katsuwonus pelam is 60

embra 19

Krill 61

guaner 19

Kyhosus analogus 60

acho 19

Labrisomus philipii 61

ojo 19

Laguncularia 18-19 see mangrove
racemosa 20
spp. 17
Langosta de Isla de Pascua 61
Langosta de Juan Fernández 61
langostino am arillo 36, 61 see also Cervimunida johni; lobster,
yellow
Langostino colorado 36, 61 lobster, red squat; Pleuroncodes
m onodon

salado 19
mangrove 20
black 17, 24
red 17, 20, 24, 27 see also Rhizophora spp.
white 20, 24
M anió de H ojas Cortas 62
M anió de H ojas Largas 62
M anió de Hojas Punzantes 62
M arrajo 60

Langostino de los canales 61

Mastocarpus papillatus 62

Lapas 61

M aytenus boaria 62

Laurel 63

M egabalanus psittacus 61

Laurelia philippiana 63

Meli 63

Laurelia sempervirens 63

M erluccius australis 60

Lechuha de m ar 62

M erluccius gayi 32, 36, 60 see hake

Leiognathidae 80-81 see slipm ouths

M erluza 39

Lenga 63

común 36, 49, 60 see hake; M erluccius gayi

Lenguado de ojos chicos 60

de cola 49-50, 60

Lenguado de ojos grandes 60

de tres aletas 60

Lepidotus australis 60

del sur 60

Lessonia nigrescens 61

M esodesma donacium 61

Lingue 62

M icromesistius australis. 60

Liquen gom oso 62

milkfish 3, 64, 68, 72, 74-76 see also Chanos chonos

Lisa 1 9 ,6 0 see mullet

Molle 63

Lithodes antarticas 61

mollusc(s) 15, 19, 24, 26, 29, 36-37, 52-54, 56-58, 61, see also

Lithraea caustica 62

Anadara granáis; Anadara similis; Anadara

Litre 62

tuberculosa; Callinectes toxotes; Mytella guayanensis.
Ostrea columbiensis

Lleuque 62
lobster(s) 20, 35-36
red squat 36 Pleuroncodes monodon; langostino colorado
yellow 36 see also Cervimunida johni
Loco 6 I

M ugil spp. 60
curema 19 see mullet
M ugiloides chilensis 60
M ulata 60

Loligo gahi 6 1

mullet 19 see also liza; M ugil curema

Lomatia hirsuta 63

Munida subrugosa 61

Loxechinus albus 62

mussel(s) 18, 37-38

Luche 62

Mustelus mentu 61

Luga-luga 62

M yrceugenia exsucca 63
Mytella guayanensis 19 see molluscs

Luma 63
apiculata 63

M ytilus chilensis 61

Macha. 61

Nanue 60

M achuelo 60

Naranjilla 62

mackerel 40, 55, 49-50

Navaja de m ar 61

Chilean jack 35, 37-38 see also Trachurus murphyi

Navajuela 36, 61 see Tagelus dombeii

chub 38
jack 32, 35-37, 52-54, 56-58 see also Trachurus murphyi

ñipa 67, 69, 72 see also Ñipa fruticans

M acrocystis pyrifera 62

Ñipa fruticans 67
Nothqfagus 41

M acruronus m agellanicus 60

alessandri 63

Maitén 62

alpina 41-42, 63
antárctica 63

mangle 19
blanco

19

betuloides 63

bobo 19

dombeyi 41-42, 63

cholo 19

glauca 63

de pava

19

nitida 63

ateado

19

obliqua 41, 63

atucho

19

pumilio 63

Notro 62

Piquihue 61

N otm pis chrysocephalm 14 see also cyprinid

Pitra 63

Ñirre 63

Piure 62

Octopus vulgaris 61

Pleuroncodes monodon 36, 61 see lobster, red squat; langostino

Odonteshes spp. 60

colorado

Odontocym biola magellanica 61
Olivillo 62

Podocarpus andinas 62
Podocarpus nubigemus 62

O ncorhynchus spp. 60

Podocarpus salignus 62

Ophictus spp. 60

Poly prion spp. 60

Ostión del norte 61

Portunidae 80 see crab(s)

Ostión del sur 61

prawn(s) 4, 37

Ostra 61

Prionace glauca 60
Pristidae 81

del Pacifico 61

Prolatilus jugularis 60

Ostrea chilensis 61
Ostrea colum biensis 19 see molluscs

Prosopis chilensis 62

otter 4

Prosopis tamarugo 62

oyster(s) 1 8 ,6 8

Protothaca thaca 61

pagotpot 81 see croaker(s); abo

Pulpo 61

Palm a Chilena 62

Pyura chilensis 62

Palom eta 60

Qeule 63

Pampanito 60

Quillaja saponaria 62

Panulirus pascuensis 61

Quillay 62

P aralabrax humeralis 60

R odal 63

Paralichthys microps 60

R aja spp. 60

Paralomis granulosa

Rauli 63

61

Parana signata 60

Rauli beech 42

Patagua 63

ray, manta 81

Pejegallo 60

Raya 60

Pejeperro 60

redfish 38

Pejerrata 60

Reineta 60

Pejerrey de m ar 60

Rhizophora spp. 17-18, 28-29 see also mangrove, red

Pejesapo 60

harrisonii 19 see also mangrove

Pejezorro 60

mangle 19-20 see also mangrove
racemosa 19 see also mangrove

pelagic(s) 80
Pelillo 62

Rhynchocinetes typus 61

Pelu 62

Róbalo 60
Roble 63

penaeid 31

Rollizo 60

shrim p 17
Penaeidae 80 see shrimp(s), penaeid
Penaeus 19 see shrimp
Penaeus californiensis

19

Penaeus m onodon 31
Penaeus occidentalis

Roncaeho 60
Rui! 63
Salilota australis 60
Salix chilensis 62

19

Salmo gairdneri 61

Penaeus stylirostris 19, 21, 31

Salmo salar 60

Penaeus vannam ei 19, 21, 31

Salmo trutta 61

Persea lingue 62

Salmón del Atlántico 60

Peto 60

Salmón del Pacifico 60

Peumo 63

salmon, coho 14, 16

Peumus boldus 63

salmonid stocks 5

Pliorphyra colum bina 62

Salvelinus jontinalis 6 1

Picoroco 61

Sarda chiliensis 60

pilchard. South A merican 35-37 see also Sardinops sagax

Sardina 61

Pilgerodendron uriferum 62
Pim elometopon m aculatus 60
Pimiento 62

pine 32.41-43,48,52,54-56,59
Pino 42
radiata 41, 43
Pinus radiata 32, 41-42, 48

común 36, 61 see also Clupea bentincki; herring,
A raucanian
española 35 see pilchard, South American; Sardinops
sagax

sardine(s) 36-38, 39, 49-50
common 38, 40, 49, 52-54
Spanish 36, 38, 40, 49-50, 52-54, 56-58

Valuation o f tropical co a sta l reso u rces: theory and
application o f linear programming. A. Cruz-Trinidad, Editor.
1996. ICLARM S tud. Rev. 25, 108 p.

TITLES OF RELATED INTEREST
A model to determ ine benefits obtainable from the m an ag e­
ment of riverine fisheries of Bangladesh. M. Ahmed. 1991. ICLARM
Tech. Rep. 28, 133 p.
Bioeconomics of the Philippine small pelagics fishery. A. Cruz­
Trinidad, R.S. Pomeroy, P.V. Corpuz and M. Agüero. 1993. ICLARM Tech.
Rep. 38, 74 p.
The economics and m anagem ent of Thai marine fisheries.
T Panayotou and S Jetanavanich. 1987. ICLARM Stud. Rev. 14, 82 p.
.
.
Small-scale fisheries of San Miguel Bay, Philippines: economics
of production and marketing. I.R. Smith and A.N. Mines, Editors. 1982.
ICLARM Tech. Rep. 8, 143 p.
Integrative framework and methods for coastal area
management. T.E. Chua and L.F. Scura, Editors. 1992. ICLARM Conf.
Proc. 37, 169 p.

HOW TO ORDER
For book prices and more publication information, please contact:
The Editor
ICLARM
MCPO Box 2631,0718 Makati City, Philippines
Tel. nos. (63-2) 812-8641, 818-0466 ext. 110
Fax no. (63-2) 816-3183
E-mail: ICLARM@cgnet.com
Payment should be in U dollars by bankdraft or check (payable to ICLARM)
S
from a US-based bank. We also accept payment through the American
Express card.
Visit our home page: h ttp ://w w w .c g ia r.o rg /ic la rm /

Notro 62

Piquihue 61

Notropis chrysocephalus 14 see also cyprinid

Pitra 63

Ñirre 63

Piure 62

Octopus vulgaris 61

Pleuroncodes monodon 36, 61 see lobster, red squat; langostino

Odonteshes spp. 60

colorado

Odontocym biola magellcmica 61

Podocarpus andinus 62

Olivillo 62

Podocarpus nubigemus 62

Oncorhynchus spp. 60

Podocarpus salignus 62

Ophictus spp. 60

Polyprion spp. 60

Ostión del norte 61

Portunidae 80 see crab(s)

Ostión del sur 61

prawn(s) 4, 37

Ostra 61

Prionace glauca 60

del Pacifico 61

Pristidae 81

Ostrea chilensis 61

Prolatilus jugularis 60

Ostrea colum biensis 19 see molluscs

Prosopis chilensis 62

otter 4

Prosopis tamarugo 62

oyster(s) 18, 68

Protothaca thaca 61

pagotpot 81 see croaker(s); abo

Pulpo 61

Palm a Chilena 62

Pyura chilensis 62

Palom eta 60

Qeule 63

Pam panito 60
Panulirus pascuensis 61

Quillaja saponaria 62

Paralabrax humeralis 60

Rodal 63

P aralichthys microps 60

Raja spp. 60

Paralom is granulosa

Rauli 63

61

Quillay 62

Parona signata 60

Rauli beech 42

P atagua 63

ray, m anta 81

Pejegallo 60

Raya 60

Pejeperro 60

redfish 38

Pejerrata 60

Reineta 60

Pejerrey de m ar 60

Rhizophora spp. 17-18, 28-29 see also mangrove, red

Pejesapo 60
Pejezorro 60

harrisonii 19 see also mangrove


mangle 19-20 see also mangrove

pelagic(s) 80

racemosa 19 see also mangrove

Pelillo 62

Rhynchocinetes typus 61

Pelu 62

Róbalo 60

penaeid 31

Roble 63

shrim p 17

Rollizo 60

Penaeidae 80 see shrim p(s), penaeid
Penaeus 19 see shrimp
P enaeus californiensis

19

P enaeus monodon 31
Penaeus occidentalis

R oncacho 60
R uil 63
Salilota australis 60
Salix chilensis 62

19

Salmo gairdneri 61

P enaeus stylirostris 19, 21, 31

Salmo salar 60

P enaeus vannam ei 19, 21, 31

Salmo trutta 61

Persea tingue 62

Salmón del Atlántico 60

Peto 60

Salmón del Pacifico 60

Peumo 63

salmon, coho 14, 16

Peumus boldus 63

salmonid stocks 5

Phorphyra columbina 62

Salve linus fontinalis 61

Picoroco 61

Sarda chiliensis 60

pilchard, South American 35-37 see also Sardinops sagax

Sardina 61

Pilgerodendron uriferum 62
Pim elometopon maculatus 60
Pimiento 62
pine 32, 41-43, 48, 52, 54-56, 59
Pino 42
radiata 41, 43
Funis radiata 32, 41-42, 48

común 36, 61 see also Clupea bentincki; herring,
Araucanian
española 35 see pilchard, South American; Sardinops
sagax
sardine(s) 36-38, 39, 49-50
com mon 38, 40, 49, 52-54
Spanish 36, 38, 40, 49-50, 52-54, 56-58

108
Sardinops sagax 35, 61 see pilchard. South American; sardina
española

squid(s) 38, 81
Stromateus stellatus 60

Sargo 61

swordfish 39, 52-54, 57-58

Sauce Chileno 62

Synodontidae 81

Saxegothaea conspicua 62

Tagelus dombeii 36, 61 see navajuela

Schinus latifolius 63

Tamarugo 62

Schinus molle 62

Tegula atra 61

Sciaena spp. 60
Sciaenidae 80

Tetraodontidae 81

Scom ber ja p onicus 60

Thais chocolata 61

Tepa 63

Scom beresox saurus 60

Thunnus alalunga 60

Scom bridae 81

Thunnus albacares 60

Sebustes oculatus 60

Thunnus obesus 60

Sergestidae 80 see shrimp(s), sergestid

Thyrsites atun 61

Serióla mazatlana . 61

Tiaca 63

Serioleha caerulea 60

Tinea 62

Seriolella porosa 60

Tollo 61

Seriolella violácea 60

Tomoyo

shark(s) 81

toothfish 54, 57-58

shellfish 39. 49-50
shrim p(s) v, 2-3, 9, 11-12, 17-18, 19-24, 26-31, 36-37, 40, 49-50,

Trachurus murphyi(i) 3 2 ,3 5 ,6 0 .sec m ackerel, jack;

Patagonian 36, 38, 52-53 see also Dissostichus eleginoides

52-54, 57-58, 64, 68, 72-76, 80-81 see also Penaeus
californiensis; Penaeus occidentalis; Penaeus
stylirostris; Penaeus vannamei
Chilean nylon 36 see also Camarón nailon; Heterocarpus
reedi
white 21
penaeid 20, 80-81
sergestid 79-81 see also Penaeidae
tiger 68
Sicyases sanguineus 60
Sierra 61
siganid 68
silverside(s) 38
slipmouth(s) 80-81 see also Leiognathidae
snail(s) 37-38
snapper(s) 68

61

mackerel, Chilean jack
Trevo 62
Trichiuridae 81
Trucha arco iris 61
Trucha café 6 1
Trucha de arroyo 61
tuna, bluefin 8
tuna, southern bluefin 4
Uca spp. 19 see crab(s)
Ucides spp. 19 see crab(s)
Ulmo 63
Ulva lactuca 62
Venus antiqua 61
Vidriola 61
Villarezia mucronata 62

Solen gaudichaudi 61

Weinmannia trichosperma 62

Sophoru microphylla 62

whale(s), bowhead 4, 8

Sphyraenidae 81

Xiphias gladius 60

Valuation o f tropical co asta l reso u rces: theory and
application of linear programming. A. Cruz-Trinidad, Editor.
1996. ICLARM S tud. Rev. 25, 108 p.

TITLES OF RELATED INTEREST
A model to determ ine benefits obtainable from the m an age­
ment of riverine fisheries of Bangladesh. M. Ahmed. 1991. ICLARM
Tech. Rep. 28, 133 p.
Bioeconomics of the Philippine small pelagics fishery. A. Cruz­
Trinidad, R.S. Pomeroy, P.V. Corpuz and M. Agüero. 1993. ICLARM Tech.
Rep. 38, 74 p.
The economics and m anagem ent of Thai marine fisheries.
T Panayotou and S. Jetanavanich. 1987. ICLARM Stud. Rev. 14, 82 p.
.
Small-scale fisheries of San Miguel Bay, Philippines: economics
of production and marketing. I.R. Smith and A.N. Mines, Editors. 1982.
ICLARM Tech. Rep. 8, 143 p.
Integrative framework and methods for coastal area
management. T.E. Chua and L.F. Scura, Editors. 1992. ICLARM Conf.
Proc. 37, 169 p.

HOW TO ORDER
For book prices and more publication information, please contact:
The Editor
ICLARM
MCPO Box 2631,0718 Makati City, Philippines
Tel. nos. (63-2) 812-8641, 818-0466 ext. 110
Fax no. (63-2) 816-3183
E-mail: ICLARM@cgnet.com
Payment should be in USdollars by bankdraft or check (payable to ICLARM)
from a US-based bank. We also accept payment through the American
Express card.
Visit our home page: h ttp ://w w w .cg iar.o rg /iclarm /


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