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Competition and information among British Columbia salmon purse seiners Ledbetter, Max 1986

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COMPETITION AND B R I T I S H COLUMBIA  INFORMATION SALMON  AMONG  PURSE S E I N E R S  By  MAX L E D B E T T E R .Sc.,  The U n i v e r s i t y  A THESIS  of British  Columbia,  SUBMITTED I N P A R T I A L F U L F I L L M E N T  THE  REQUIREMENTS  FOR THE DEGREE OF  DOCTOR OF PHILOSOPHY  in  THE  F A C U L T Y OF GRADUATE S T U D I E S  (Department  We  accept this to  THE  o f Zoology)  thesis  the required  as c o n f o r m i n g standard  UNIVE£S-I-TY OF B R I T I S H April ©  COLUMBIA  1986  Max L e d b e t t e r ,  1986  1977  OF  In p r e s e n t i n g  t h i s t h e s i s i n p a r t i a l f u l f i l m e n t of  requirements f o r an advanced degree a t the  the  University  o f B r i t i s h Columbia, I agree t h a t the L i b r a r y s h a l l make it  f r e e l y a v a i l a b l e f o r reference  and  study.  I further  agree t h a t p e r m i s s i o n f o r e x t e n s i v e copying o f t h i s t h e s i s f o r s c h o l a r l y purposes may  be  department or by h i s or her  granted by  the head o f  representatives.  my  It i s  understood t h a t copying or p u b l i c a t i o n o f t h i s t h e s i s f o r f i n a n c i a l gain  s h a l l not be allowed without my  permission.  Department of  pOllQft  The U n i v e r s i t y of B r i t i s h 1956 Main Mall Vancouver, Canada V6T 1Y3 Date  DE-6  (3/81)  Columbia  written  Abstract T r a d i t i o n a l f i s h e r i e s models are based upon s i m p l i s t i c assumptions concerning f l e e t behavior. o p e r a t e i n d e p e n d e n t l y o f one random f a s h i o n .  Poisson  F i s h i n g v e s s e l s a r e assumed to  a n o t h e r and t o sample the f i s h p o p u l a t i o n i n a  T h i s d i s s e r t a t i o n p r o v i d e s a r e v i e w o f the m a j o r component  p r o c e s s e s c o n t r i b u t i n g t o the o p e r a t i o n o f f i s h i n g f l e e t s and u s e s d a t a on s a l m o n p u r s e s e i n e r s t o p r e s e n t t e s t s o f the h y p o t h e s e s  field  contained  i n the h i s t o r i c a l assumptions.  Data p e r t a i n i n g to i n t e r f e r e n c e competition  and i n f o r m a t i o n were a n a l y z e d .  S i n c e f i s h e r i e s management u s u a l l y  assumptions c o n c e r n i n g the form o f e x p l o i t a t i o n r a t e responses  to  entails effort,  t h e consequences o f non-random f i s h e r m a n b e h a v i o r were e x p l o r e d . A l t e r n a t i v e models o f the f i s h i n g p r o c e s s were p r o p o s e d  and  examined.  I n B r i t i s h C o l u m b i a , s a l m o n p u r s e s e i n e r s l i n e up a t f i s h i n g points,  f o r m i n g w e l l d e f i n e d queues.  i n Johnstone The and  S t r a i t u s i n g a one  These queues were measured o v e r  time  dimensional recording scale.  d i s t r i b u t i o n o f e f f o r t was  fit  to t h e o r e t i c a l truncated Poisson  truncated negative binomial distributions.  b i n o m i a l r a t h e r than the Poisson. c a t c h e s were a l s o non-random.  access  Most d a t a f i t  the  negative  Movement p a t t e r n s a n d t i m e s e r i e s  of  A n a l y s i s o f v a r i a n c e methods i n d i c a t e d t h a t  line-up lengths r e f l e c t e d set catch rates. W a i t i n g times were q u a n t i f i e d u s i n g f u n c t i o n a l and s t a t i s t i c a l U s i n g t h e w a i t i n g t i m e s , t h e f l e e t s e t e f f o r t a n d number o f s e t s p e r were c a l c u l a t e d .  Although  o f t h e number o f b o a t s i n i t i a l decrease Two queuing  t h e f l e e t s e t e f f o r t was  a near  vessel.  models were p r e s e n t e d f o r e x p l o i t a t i o n r a t e s i n r e l a t i o n patterns.  T h e o v e r f l i g h t m o d e l was  boat  linear function  i n the area, i n t e r f e r e n c e c o m p e t i t i o n produced  i n sets per  models.  to  based upon the l i n e - u p  an  d i s t r i b u t i o n s and and  a s s u m e d t h a t i n f o r m a t i o n was  the parameter e s t i m a t e s r e f l e c t e d a n e c d o t a l  about f i s h behavior. o f 100  The  was  model f i t w e l l  statistical  information level  vessels. binomial  d i s t r i b u t i o n was  used  e s t i m a t e e x p l o i t a t i o n r a t e s from c a t c h per v e s s e l d i s t r i b u t i o n s . assumed t h a t salmon abundance does n o t a f f e c t the shape o f  distributions. was  and  The  e x p l o i t a t i o n r a t e s s a t u r a t e d a t an e f f o r t  As an a l t e r n a t i v e m o d e l , t h e n e g a t i v e to  good.  As e f f o r t i n c r e a s e d ,  d e s c r i b i n g t h e s h a p e o f t h e d i s t r i b u t i o n , k, f i s h i n g power o f the f l e e t  the  the d i s t r i b u t i o n o f c a t c h per  p r e d i c t e d t o b e c o m e more s k e w e d t o t h e o r i g i n .  (decreasing  The  It  vessel  parameter  should have t r a c k e d  the  as t h e d i s t r i b u t i o n became more  skewed). A f t e r f i t t i n g t h e w e e k l y d i s t r i b u t i o n s , i t was e x p l o i t a t i o n r a t e s from the s a l e s s l i p model d i d n o t parameters o f the o v e r f l i g h t model.  An  found t h a t the  relative  saturate  the  like  alternative derivation indicated  t h a t the shape o f c a t c h per u n i t e f f o r t d i s t r i b u t i o n s responds to the and As  aggregative  p r o p e r t i e s o f the f l e e t and  to the magnitude o f the  t h e mean c a t c h p e r s e t i n c r e a s e s , k w i l l i n c r e a s e .  size  catch.  Salmon abundance,  f l e e t n u m e r i c a l r e s p o n s e s and v e s s e l a g g r e g a t i o n s a f f e c t the skewness o f the c a t c h per u n i t e f f o r t d i s t r i b u t i o n s . In general,  t r a d i t i o n a l model a s s u m p t i o n s were r e j e c t e d .  not operate independently. The  B o a t s were n o t d i s t r i b u t e d i n a random  o v e r f l i g h t model p r o v i d e d  predicted exploitation rates.  e x p l o i t a t i o n r e s p o n s e t o e f f o r t was incorporated  Vessels  i i i  fashion.  The  q u a l i t a t i v e l y d i s t i n c t from the  i n t r a d i t i o n a l models.  did  forms  T A B L E OF  CONTENTS  ABSTRACT  i i  LIST  OF T A B L E S  v i  LIST  OF FIGURES  v i i  ACKNOWLEDGEMENTS CHAPTER  I.  ix  Introduction  Responses  1  o f the Fishing  Components  System  of the Fishing  3  Process  6  Competition  6  Information  8  Saturation Fishing Skill,  and S e l e c t i v i t y  . . . . .  Power  9 10  Strategy,  and M o t i v a t i o n  11  Search  13  Mobility  14  The  Models  CHAPTER I I .  16 Salmon S e i n e Johnstone  Vessel The CHAPTER  Boats  Strait  andthe  Salmon F i s h e r y  Operation  Johnstone III.  Data  Strait  . Fishery  Collection  IV.  Line-up  Independence  21 27  and V e r i f i c a t i o n  Verification CHAPTER  20  33 35  and D i s t r i b u t i o n  Distributions  of Effort  44 44  Movement a n d A c t i v i t y  51  Discussion  57  iv  CHAPTER V.  Competition  and S e t S t r a t e g i e s  Line-up  and E f f o r t  Levels  Effects  of Set Strategies  60 on C a t c h p e r S e t  Discussion CHAPTER V I .  60  72 79  Models  o f the Fishing  Process  84  The  Overflight  Model  88  The  Sales Slip  Model  109  Discussion CHAPTER V I I . Literature  126 General  Discussion  131  Cited  138  v  L I S T OF T A B L E S  Table  I  Parameter binomial  estimates  f o rthe truncated  and t r u n c a t e d Poisson  frequency  fits  negative  t o queue  length  data  48  Table  II  Access  point-flight  ANOVA  Table  III  Short  Table  IV  S e t time  Table  V  One-way ANOVA  Table  VI  S e t t y p e - l i n e - u p - w e e k ANOVA  Table  VII  Average  50  t e r m v e s s e l movements  55  components  69  f o rv e s s e l e f f e c t s  weighted  ratios  76  f o r 28 v e s s e l s  f o r s e t type  77  and l i n e - u p  catches Table  VIII  Monte c a r l o overflight  Table  IX  80 simulation of error model  The parameter v a l u e s sizes  i n the 110  (k), standard  f o r the negative  binomial  vi  errors  and sample  f i t t o CPUE d a t a  . . .  118  L I S T OF  FIGURES  Figure  1  A conceptual  model o f f l e e t  dynamics  Figure  2  Fishing innovations  Figure  3  Set strategies  Figure  4  The J o h n s t o n e  Figure  5  A beach  Figure  6  Coding  Figure  7  Observation  Figure  8  Reported  Figure  9  Aerial  Figure  10  Queue  length  Figure  11  Beach  set line-ups:  Figure  12  Beach  s e t l i n e - u p s : medium  Figure  13  Beach  set line-ups: high  Figure  14  Within  Figure  15  Queue r e s p o n s e  Figure  16  Average  line-up  length vs. e f f o r t  63  Figure  17  Maximum  line-up  length vs. e f f o r t  64  Figure  18  Average beach  Figure  19  Average  Figure  20  Operation  Figure  21  Waiting  times  Figure  22  Average  number  Figure  23  Total  Figure  24  Proportion  Figure  25  The s e l e c t i o n  Figure  26  Exploitation rates  i n the salmon  4  seine  fishery  . . . .  22 25  Strait  study  area  29  s e t queue  36  error  38 error  39  and observed  vessel  effort  41  counts  42  frequency  opening  distributions  45  low e f f o r t  fleet  52  effort  53  effort  54  movements  56  hypotheses  61  set line-up  open s e t l i n e - u p  length vs. effort length vs. effort  o f a queue  set effort  66 .  as a f u n c t i o n o f queue of sets  65  length  70  per boat vs. e f f o r t  73  vs. effort  o f open s e t e f f o r t rule  f o r entry  74 vs. effort and e x i t  of effort  as a f u n c t i o n o f e f f o r t vii  68  82 . . . .  91 101  Figure  27  Catch  and  Figure  28  The  Figure  29  Total  fleet  Figure  30  k vs.  effort  time  CPUE v s .  catch  s e r i e s o f the k vs.  per  fish  set  104  skewness parameter  stationary fleet  k  c  . . .  106 119 120  viii  Acknowledgements I would l i k e to thank the B r i t i s h Columbia S c i e n c e C a n a d i a n Sportsman's Fund f o r t h e i r R.  H i l b o r n , Dr.  C. J . W a l t e r s ,  I. V e r t i n s k y and Dr. My  D.  Dr.  support.  S. H o l l i n g , D r . N.  Ludwig p r o v i d e d  r e s e a r c h a s s i s t a n t , Mia Davis,  boats.  C.  financial  scholarships.  The  Dr.  the  P. L a r k i n ,  Dr.  J . Wilimovsky,  Dr.  academic commentary and  d i d an a d m i r a b l e j o b on the  I would a l s o l i k e to thank the N a t i o n a l Science  R e s e a r c h C o u n c i l and  C o u n c i l and  and  assistance.  fishing  Engineering  the U n i v e r s i t y o f B r i t i s h Columbia f o r p r o v i d i n g  B r i t i s h C o l u m b i a p u r s e s e i n e r f i s h e r m e n made t h e  possible.  ix  thesis  CHAPTER  I  INTRODUCTION  Fisheries  m a n a g e m e n t e n c o m p a s s e s many o f  technological  and  Fishermen  s c i e n t i s t s are  fishes with  and  i n the  index that  natural  abundance  incorporating of  human p r o b l e m s  provides  traditional  present  of  tests  the  of  of  the  effort  days,  or  any  or  biological variables  catch  1977).  and  and  fishery  and of  Effort  field  contained  each  management m a n i p u l a t i o n s quotas  2)  length  3)  d i r e c t l i m i t a t i o n of  of  fishery Uncertainties of  openings  during  or  the  limited  effort  limits, season  amount o f  proposed  i s based  upon  dissertation  salmon purse  seiners  indirectly  number o f  effort  i . e . , biomass  boats,  catch  either as quotas),  and, available  to  the  entry).  are  effort  and  prediction  r e f l e c t i o n s of  1  our  of  the  ignorance  the  translates  into  "optimize"  manifested  effort  to  dependent upon  (i.e., of  the  assumptions.  recruitment to  usually  standard  is usually  historical  and  indices  to  on  i n order  the  i n management o f  future  data  associated  The  This  of  contributing  Measurement  are  (including size  (i.e.,  behavior.  growth, m o r t a l i t y  catch  It  f i s h i n g season  i s regulated  errors  formulation  i n the  activity).  1)  effectiveness  uses  is directly  during  sets,  fleet  history.  r e l i a n c e upon  (CPUE).  This  the  assumptions.  component p r o c e s s e s  hypotheses  applied  trips  (Rothschild  major  fishing fleets  Management o f amount  the  effort  about  scientific,  observe populations  quantify  untested  abundance.  assumptions  review of  cannot  unit  complex  throughout w r i t t e n  adequately  and  usually  per  to  to  most  result i s a pervading  and  i s catch  Poisson  a  operation  boat  The  CPUE i s p r o p o r t i o n a l  simplistic,  unable  environment  estimates.  abundance  documented  the  of  the  yield  2 quantitative years  of  and  do  Ricker  fishermen  not  reflect  1940,  1944;  statistical (Kennedy Parrish 1963;  and  1970;  the  M i c h i e l s o n 1975;  scientists of  the  assumptions  (Tunstall  1969;  1973;  Poggie  components Empirical,  syntheses  the  scientists  of  fishing  to  structured  (e.g.,  or  Peterman  competition,  Lummis  mechanisms of  the  1969,  produced  1980; and  i n c l u d e d i n the  due  the  and  1976;  Todd  numerical to  the and  Steer  are  1978)  and  rare  and  grounds  as  Fisheries process  in  Hamley  w h i c h were  not  associated with  data  1981).  that  effort  and  Factors  of  theoretical  e m p i r i c a l models  and  1972;  1977).  interpretation or  (Pope  fishermen  Wadel  L a r k i n 1971;  the problems  Peterman and  of  Norr  fishing  overviews  of  their  fishing  are non-existent. of  1980).  effects  1972;  dynamics  on  Veen  formulations  Watanabe  fleet  components  de  adaptations  Norr  and  models  Scholes  summarized  1972;  group b e h a v i o r  and  and  Goodlad  1918;  1958;  qualitative  1977;  (Stiles  information (both negative  skill.  1972b;  descriptions of  testing  precise regulation  been adequately  skipper's  1981)  1972a,  i n these  theoretical  models  D i c k i e 1964)  Watanabe  Jones the  man  (Baranov  Zijlstra  sociological  process  Minami  for hypothesis  verification confound  1976,  comments o n  1974;  summarize  subset  ( e . g . , Maeda and Ricker  Gersuny  interrelated  studied a  Wadel  and  and  A n t h r o p o l o g i s t s have  and  quantitative  attempting  product  detail  of  and  Inove  R o b s o n 1966;  the  theoretical  measures used  1956a;  of  descriptions of  process  Paloheimo  u n d e r l y i n g the  concerning  Anderson  1957;  fishing  H o u g h t o n 1977;  have p r o v i d e d  Peterman e t a l . 1979).  Breton  1964;  thousands  to simple,  the  effort  Gulland  Although  research, past  limited  Holt the  Ostvedt  observations  1975;  and  1951;  1959;  and  related  complexities of  Beverton  anecdotal  the  fish  fishermen.  were p r i m a r i l y  Parrish  Keir  Hovart  violations  to  and  standardization of  1951;  Fisheries  the  fleets  have been devoted  fleets that  ecology  facilitatory),  which have are  search,  and  not  3 This  introductory chapter  concerning with  the  the  relation  outlined. behavior the  s t r u c t u r e and between  Subsequent of  of  review  dynamic  these  chapters  salmon purse  consequences  will  then  s e i n e r s i n an  this  behavior  on  current state  responses  responses will  the  of  and  fish  present  area  fishing  a  knowledge  fleets.  Problems  abundance w i l l  be  field  the  in British  exploitation  of  study  on  Columbia  r a t e s on  the  and  explore  salmon  stocks.  Responses of  Fleet in  effort  dynamics and  system  (Figure  1).  attack  Although predation explicit  to c e r t a i n  Three major response  to changes these  facilitates promotes  two  the an  as  the  temporal  abundance  this  papers  response  (Peterman and conceptual  (Peterman  classification  approach  comparison  to  other  to  of  1978;  stratification  1980,  Peterman and  to  fishing  the problem  of  predator-prey  of  Holling  context  Gatto  and  the  parameters  response  response  ( S o l o m o n 1949;  of  i n predation  d e n s i t y , the  numerical  patterns  responses  identified  were d i s c u s s e d i n the  of  ordered  the  by  spatial  state variables  have been  d e n s i t y and  systems  and  (CPUE) g e n e r a t e d  variables,  responses  processes  to  driving  i n prey  applications  limited  effort  Fishing: System  of attack rates to prey  in fisheries  Extension of  and  unit  rates to predator  abundance  been  the  d e f i n e d here  catch per  fishing  systems:  are  the  predator 1959).  non-human Larkin  to  1979),  fishermen  Steer  have  1981).  v e s s e l s and  skippers  describing fleet  situations  of  (see  dynamics  Holling  1973) . The predation  two  fundamental v a r i a b l e s  systems  (1980) example  are  (the  prey  Indian  that drive  d e n s i t y and food  the  predator  fisheries  on  three  density.  salmon  responses In  i n B.C.),  in  simple  Peterman's the  analysis  RESPONSES  COMPONENTS  STATE VARIABLES  , SATURATION .SELECTIVITY FUNCTIONAL RESPONSE' TO PREY DENSITY  •SEARCH  REGULATORY  •FISHING POWER  SCIENTIFIC  •SKIPPER'S S K I L L , STRATEGY and MOTIVATION  TECHNOLOGICAL  -COMPETITION FUNCTIONAL RESPONSE. TO PREDATOR D E N S I T Y '  -ECONOMIC  >  • INFORMATION  PARAMETERS INSTITUTIONAL  COMPETITION WITHIN SEASON / NUMERICAL (AGGREGATIVE) — RESPONSE  INFORMATION  \ ^MOBILITY  ANNUAL NUMERICAL RESPONSE  A CONCEPTUAL MODEL OF FLEET DYNAMICS Figure 1  ENVIRONMENTAL  5 can  be  restricted  fisheries  must  to  these v a r i a b l e s .  include  three  technological-economic, the  condition of  may  be  state  the  regulatory  fishing  aggregate  variable could  be  defined  relatively  The  general  constant  variables  and  responses  (see  Figure  1).  levels  equipment may  be  (e.g.,  amount o f  time  seasons,  commercial parameters;  fishing these  q u a l i t y of  fishing  industry  fleet  specific  catch  other  or  derived  etc.) are  classified determine  exchange.  affect  the  The  or  c h a r a c t e r i s t i c s (e.g.,  parameters;  a  few  as  (e.g.,  the  state  of  may  search,  in  regulatory  modify be  the  defined  knowledge  vessel  of  quotas, of  competition  importance  species  site  or  documented examples accounts w i l l  be  parameters. define  limitation the  success  of  the  empirical  analysis  of  the  responses  effects  mentioned  to  and  a  biology)  hold of  of  in  sections. The  as  institutional  institutional  offshore,  the  changes  general  intensity of  the  by  Motivational  (e.g.,  historical  published  The  hierarchical structure  the  evolution of  (inshore  are  the  by  v a r i a b l e can  schemes the  and  exist.  information  and  time  q u a l i t a t i v e form  etc.).  scientific  and  characterized  reflected  nets,  affect  regulatory  parameters.  changes w i t h i n  Regulatory  quotas,  be  transient boundaries The  p a r a m e t e r s may  and  the  the  fishing  institutional  --  larger processes  f i s h e r y can  sounders, term  openings  There  a  state v a r i a b l e s are  operations  rates).  these v a r i a b l e s  and  of  of  certainly  environmental parameters  fishery  combination  loops  factors).  may  a  maior  state variables  (e.g.,  Feedback  short  information  of  and  searching).  effort  stage  scale  scientifically  distributional  closed  The  spent  certainty of  fish  the  short  each  of  These v a r i a b l e s  the  radios,  a f f e c t e d by  structure  the  (e.g.,  scientific.  at  structure  Technological-economic fishing  as  affect  of  o f measurements  environmental  parameters  and  system  an  area).  similar descriptions  additional categories  q u a n t i f i e d as  fishing  But,  fish  and  of of  6 predator  densities  1)  i s dependent upon  an independent unit  effort  techniques,  estimate  data and  The  numerical  context under  types  (including  of catch per sampling  c a t c h o f anadromous  group  dynamics  s p e c i e s and  to catch  rates, fish  distributions  densities.  response,  as a response  gear  i n the form  e . g . , B o t s f o r d e t a l . 1983) o r t h e spawning  relating vessel  approaches:  o f abundance  of alternative  escapements p l u s  2)  two  however,  i s best  to information  understood  -- t h e p a s t  i n the f i s h e r i e s  catch  o f the gear  type  examination.  Components  The  qualitative  forms  o f the F i s h i n g  o f predation responses  relative  c o n t r i b u t i o n s o f components.  predator  d e n s i t y c a n be expressed  components. response  Changes  Process  are determined  F o r example,  as c o m p e t i t i o n  by the  the response  to  and i n f o r m a t i o n  i n the c o n t r i b u t i o n s o f these  components  are functions o f the technological-economic  to the  and r e g u l a t o r y s t a t e  variables.  Competition Knowledge o f c o m p e t i t i o n to  anecdotal  scientific  accounts  literature  among f i s h e r m e n  has u s u a l l y been  by a n t h r o p o l o g i s t s and f i s h e r i e s  restricted  scientists.  lacks q u a n t i t a t i v e demonstrations  o f the e f f e c t s of  competition. Anderson and S t i l e s trawlers.  Their research  (1973) examined r i v a l r y suggested  that  these  among  The  Newfoundland  fishermen  engaged i n  7 spatially sector to  oriented competition:  competed  f o r access  actual interference.  competition  evolved  boundaries.  Although  surreptitious  (blocking  access)  i s not  Shaefer  exploitation  competition  search  lobster  territorial were n o t  and  (competing  operations  may  element  be  an  the  state,  CYRA  1975;  they  fishery  1977),  resulting  factor  were  competition  tuna  Orbach  same f i s h )  important  secondary  protected  Interference  i n the  Psaropulos  was  interference  of actively  1975).  f o r the  techno-economic  competition  fishery,  system  (Acheson  Pella  same  r e c o g n i z e d by  a significant  1956;  u n i t s i n the  Exploitation  Maine  violence  (Shimada and  of  a  the  claims  b a c k e d by  overlap  points.  In  into  fishing  but  from  affecting  the  catch  rates. The  effects  of  Indeed,  innovations  of  term  long  mitigates  catches.  or  competitive  the Due  utilization  to  by  maintained  that  specializing  produce on  catch  Swedish  of  fishery  that  anecdotal  the  likelihood  effort  due  to  perceptions  social  of  (i.e.,  of  competition  a redistribution rates.  new  of  Lofgren  expanded such  effort  and  that  (1972)  competition  niches  others  as  and  declining  resource rocky  bottoms  from i n t r u d i n g .  valuable  input  scientists  observations  s p a c i n g mechanisms  decrease  causal  of  yet  technological inputs.  fishermen  discouraged  systems,  by  trawlers to  in exploiting  small yields  dispersion of  a major  fishermen's  t e c h n o l o g i c a l advances,  i n extensions  effects)  of  modified  a n t h r o p o l o g i c a l approach provides  perceptions errors  with  effects  adaptations  r e g i o n s where The  coupled  are  d e c l i n e s i n c a t c h may  the  documented  competition  to  t e c h n o l o g i c a l and  agent u n d e r l y i n g p o s s i b l e increases  our  make  conceptual  d y n a m i c s : McCay  minimization  overfishing.  may  to  A  of  (1978)  competitive  more r e a l i s t i c  view  is  m o t i v a t i o n a l changes  is  in exploitation  rates.  8 Information O r b a c h (1977) documented the s t r u c t u r e o f code g r o u p s i n t h e San tuna f l e e t .  The  that avoided  use  o f w a l k i e - t a l k i e s by c o o p e r a t i n g p a i r s o f  risking valuable  d i s c u s s e d by L o f g r e n s u c c e s s f u l U.S.  (1972) .  trawlers  information over other radio channels  was  S t u s t e r ( 1 9 7 8 ) o b s e r v e d t h a t many o f t h e m o r e  West c o a s t crews p r o d u c e d h a l f o f t h e i r t o t a l c a t c h  information obtained  from i n t e r c e p t e d and/or d e c i p h e r e d  o r d i r e c t c o m m u n i c a t i o n w i t h members o f o r g a n i z e d  radio  groups.  using  transmissions  Anderson  and  Wadel (1972b) r e p o r t e d t h a t f r a g m e n t a r y i n f o r m a t i o n d e t e r m i n e d t h e of Norwegian h e r r i n g fishermen. f l e e t i n 1966  (due  p o w e r b l o c k ) was rates.  the c a u s a l agent u n d e r l y i n g a decrease i n l o c a l  A n d e r s o n and Wadel d i d n o t i n d i c a t e t h a t o t h e r f a c t o r s  (e.g.,  have p r e c i p i t a t e d the  effort.  i n f o r m a t i o n exchange i s u s u a l l y d e c e p t i v e ( A n d e r s o n 1972,  1973;  i n f o r m a t i o n i s known t o be trawler operations,  S t i l e s 1972).  Exchange o f  E n g l i s h , French,  . The p r e v a l e n c e  s e r i o u s consequences f o r within-season commercial operations.  and t h a t v e r y l i t t l e  that  facilitation  negative  generally c h a r a c t e r i s t i c of eastern Canadian  and  ( A n d e r s o n 1973)  the  catch  M a j o r p a p e r s r e l a t e d t o i n f o r m a t i o n management h a v e r e p o r t e d  sea f l e e t s  the  t o movement o f v e s s e l s t o I c e l a n d w i t h t h e a d v e n t o f  d e c l i n e i n catch per u n i t  U.S.  success  They a s s e r t e d t h a t the d i s p e r s i o n o f  h e r r i n g p o p u l a t i o n s i z e o r s c h o o l i n g m e c h a n i s m s ) may  occurs  Diego  P o r t u g u e s e , and  of deceptive  management and  Spanish  deep  s t r a t e g i e s has  f o r the e f f i c i e n c y  a t t a i n e d t h e h i g h e s t l e v e l o f e f f i c i e n c y as v e s s e l s w e r e  dispatched  on t h e b a s i s o f a c c u r a t e  r e p o r t s from the s k i p p e r s .  But,  o b s e r v a t i o n o f t h e d a t a e x c h a n g e s r e v e a l e d t h a t much o f t h e i n f o r m a t i o n distorted.  of  A N e w f o u n d l a n d f l e e t owner s t a t e d t h a t h i s  operations  purposely  and  T h e s e f i s h i n g o p e r a t i o n s were n o t as i n t e g r a t e d as  appearances s u g g e s t e d (Anderson 1972).  was  9 The  prevalence  institutional  generating  payment  (i.e.,  skippers  secrets.  feel  competitors.  vessels  management  Anderson  and  their  the  the  the  tuna).  Saturation  and  Selectivity  s a t u r a t i o n was  summarized  the  other  t y p e s has  gear  Shardlow sport  gear  increased, the  fish  gill  net  (1983) g a t h e r e d to  the  facilitated  fish  followed  salmon  point,  the  for  an  other  gear  saturation  effects of  salmon  abundance would  salmon  into  the  (e.g.,  with  of  the  crew and  of  strategy  The  response  Stuster  (e.g.,  strategies fishermen  hunter  are  trap  or  often lobsters  Hamley  The  access  information  (1975)  selectivity  of  1963).  attack found  rate that  of as  More s a l m o n a t t a c k e d Shardlow  facilitation  industry.  information  nature  ICNAF  attack.  crew  kept  literature.  He  of  central  well  (1977) .  f o r the  the  the  salmon  w o u l d be  the  lure  catch  rates  At  the  sizes  of  to  and  encounter that  overwhelmed  of  to  abundance  d i d not  e f f e c t s t o become e v i d e n t .  search  time.  by  salmon  saturate.  (1981) a n a l y z e d  species  fishing  camera.  search.  of  the  Furthermore,  deceptive  (e.g.,  data  underwater  each  fisherman's handling  Ricker  field  of  company.  Rothschild  studied  that  system  form  stability  Fishing  size selectivity  a l s o been  sharing  parameter  r e v i e w e d by  attached  enough  the  technologies.  environmental  for  Gear  predominate  maintained  i s d e t e r m i n e d by  the  and/or  a t t r i b u t e d to  integrated  overt  the  be  co-adventure  productivity  facilatory  search  the  determines  can  1973)  vertically  earnings within  available  the  (1972,  resent  success  i s r e l a t e d to  and  the  c r e w may  and  that  determined by and  the  information  phenomenon a r e  that  Catch  (1978) s t a t e d  trapper)  this  shares)  Also,  to b e t t e r  deceptive  structure.  factors  Many  of  and  concluded  data that  concerning the  decrease  i n the  British  Columbia  i n d i v i d u a l weights  of  10 pink and  and  coho  troll  salmon can  gear.  reduction  the  i n size.  Ricker  pound r a t h e r  responded with  Fishing  explained  a t t r i b u t e d the  that  a piece  targeted  (1956a) d e f i n e d  of  particular  fishing  the  catchability.  the  the  largest  on  to  processors during  actions  of  gillnet  correlated with  trend  basis  vulnerable area.  S ince  absolute  fish  The  the  a  change  began  the in  t o buy  1940s;  the salmon  fishermen  fish.  absolute  Relative relative  to  Rothschild  fishing  the  CPUE o f  1977).  power e n t a i l  trips of  by  the  fishing  to v e s s e l  analysis  past  two  CPUE i s r a r e l y  a purely  valuable  information t h a t may (see  the  vessel  the  data.  This  the  boats  Gulland  as  1964)  CPUE o f  but  and  a  the  corresponding  and  of  normal  power  is  then  by  many  times  distribution  to have  s t r a t e g i e s and of  fishing  tonnage  underlying  appears  1966;  Beverton  been u t i l i z e d  the  shapes  vessel  variance  produced  horsepower  a  fisheries  relative  Fisheries scientists  the  a  (1956a) and  and  in  is  1956a; R o b s o n  the  the  quantities.  Relative fishing  skipper's  and  fleet  relative  the  a p p r o a c h has  i n the  interval  obtained,  stabilized  log transform  p e r t a i n i n g to contained  as  Gulland  different  such  to  a v e s s e l as  time  for a  (Gulland  log transform  pragmatic b a s i s .  be  given  for calculating  h a l f decades, --  power o f  rarely  analyses  p o w e r among b o a t s .  one  a  are  defined  methods  same o r  reported  on  distributions  of  methods. and  accepted  information  is often  characteristics  of variance  the  that  their  standard  normalization  distribution related  a  during  measurements  Traditional  (1957) r e p o r t e d  successive  power  taken  fishing  analogous parameter  managers have u s u a l l y r e s t r i c t e d  of  selective  time  s t a t e v a r i a b l e : the  t h a n on  gear  proportion  during  the  Power  Gulland  Holt  by  E n v i r o n m e n t a l v a r i a b l e s were not  technological-economic by  be  have  been ignored  skill,  original relationships  11 between  the  mean a n d  Treschev volume  of  the  horsepower shape  defined  water  gear. and  of  the  CPUE w i t h i n  More work  capability the  devised  an  variable  on  records.  gear be  of  and,  and  fishing  to  catch  has  hunter  the  fish.  moved w i t h that  or  accepted  This  the  apparent  the  the  area  zone  rate  or  of  o f movement  of  effects  parameter  environmental u n i t as  the  and  that  into  parameter  on  the  however,  as,  conditions.  of  perhaps, He  CPUE d i v i d e d b y  f o r the  then  the  standardization  the  mean  to  prey  of h i s t o r i c a l  relative  strategy  and  of  technological-economic  f u n c t i o n a l response  remains  skill,  scientists  not  i n search  family)  find  structure so  of  fishing.  (assumed) e f f e c t s o f  and  p o w e r among b o a t s ,  mortgages, and  of  ratio  and  catch  contains  an  motivation.  Motivation  and  chaser.  have r e c o g n i z e d  motivation a wide  b e e n made.  strategy  to p h y s i c a l c o n s t r a i n t s  to  absolute  strategy  success  differences  the  stratum.  skippers'  fisheries  skill,  in  trips.  o b j e c t i v e l y q u a n t i f i e d independently  Strategy  skipper's  the  fishing  ultimately,  component:  Although  of  different  Fishing capability,  additional  duration  incorporated  the  The  power as  i s necessary  same t i m e - a r e a  capabilities.  Skill.  the  be  gear under  relative  can  can  successive  fishing  f i s h e d to  tonnage  the  Treschev  density  of  i s c a l c u l a t e d i n terms  fishing  the  variance  (1978) d e f i n e d  the  influence  the  (e.g.,  Chasers used  scale  San  o l d or  new  boats),  He  relied  their  information  into aggregations  of boats.  different  of  risk  Diego  defined on  to  based  on  component  that  fleet  motivation  were r e l a t e d (e.g.,  two  strategies  --  own  experience  and  hunches  and  often  from  Both  tuna  in  the v a r i a t i o n  relate this  (1977) o b s e r v e d  the  radio  degrees  attempt  Orbach  differences  e x p l a i n much o f  within  personality. Hunters  may  that  other  groups  boats  contained  similar  the  skippers  information.  12 Cove offshore of  fishery,  Cornwall,  based the  on  of  capability  a hunter The  developed  or  a  Motivational the  and  B.C.  of  company  fisheries  fleet.  p a r a m e t e r was  boats  community  the  maximization stimulated  community  Palsson Icelandic They  cod  sizes  and  variance  success.  The  In  high  high.  the  fishery  kelp  taking  skipper of  etc.),  selection The  when u n c e r t a i n t y  inherent  and  risk  strategies.  Cove d i d n o t  skipper's  were  similar;  the  of  the  was  include  nature  Cornwall  oyster  the  near  an  that  of  to  fishery,  risk  rank  ownership that  of  small  past  the  fishery  taking behavior  statistical and  analyses  skippers'  i s a myth u s e d  made d u r i n g no  and  and  potential.  effect  T h e r e was  and  the  the  of  experience.  f o r crew  r h e t o r i c b o l s t e r s crew m o r a l e ) .  trips  system  ownership  knowledge  low  the  competition.  destruction of  (1982) p e r f o r m e d  skipper  intense  individual  The  of  coadventure  c o r r e l a t e d with  structure.  l e d to  parameter)  stimulated  vessel characteristics  skipper's  i n catch.  of  gregarious  institutional  technological  the  number  was  oyster  definition  rocks,  c h a r a c t e r i z e d by  Durrenberger  (i.e., the  of  that  or  demands f o r c o n f o r m i t y  catches,  concluded  management  the  and  near  the  performance  social  of production  non-implementation  Is  were n e g a t i v e l y  institutional and  His  p r e d i c t e d to occur  (i.e.,  relative  levels  motivation  technology).  motivation  the  Newfoundland  for differences i n risk  the  independent  and  the  (chaser)?  structure  and  fisheries:  fishery  a model  (setting  personality.  follower  importance  (i.e.,  and  salmon  resource,  t a k i n g was  low  --  the  features  catch  was  reward  of  gear  risk  factor  Newfoundland  within  He  the  average  level  important  the  inshore,  environmental  large or  low,  of  s t r a t e g i e s i n three  B.C.  uncertainty  capability  highest  the  England.  the  included by  (1973) compared  impression  The  season accounted  vessel  f o r most  r e l a t i o n s h i p between experience  c o r r e l a t i o n between v e s s e l  size  and  catch  may  have  and  of  13 masked  the learning  correlated with and  energy  ratios;  risky  boat  strategies  history  Also,  might have  c o u l d have  rhetoric.  -- s k i p p e r s ' e x p e r i e n c e  tonnage.  expenditure  t h e crews  skippers'  response  indicated  responded  The a u t h o r s  and concentrated  of continuous  quantification  their  of within trip  differences  to net cash  suggested  was n e g a t i v e l y  i n cost/benefit  r e t u r n s and ignored  that Icelandic  effort  activity  i n areas  fishermen  possessing  avoided a  catches.  Search Paloheimo  and D i c k i e  (1964) and Paloheimo  theoretical  models  o f the predation process,  of predator  search  times  distributions. in  abundance  to  abundance.  locating  Furthermore,  i n search Effort  fisheries  context  distribution  unless  day w i l l  not r e f l e c t  changes  the school density i sp r o p o r t i o n a l  was  detection  time  o f s e a r c h models  f o r optimizing search  involved i n  specified  by experimental fishing  such  (1977) d e s c r i b e d s e a r c h as weather,  The  random s e a r c h  The  i n v e r s e cube  water  fishing.  tactics.  factors.  left  off.  He  temperature  Shotton  as b e i n g  theorem  was  d i d not specify  dependent  and the b e h a v i o r  f u n c t i o n ( s e e Koopman 1 9 8 0 ) , law o f d e t e c t i o n , however,  Bayes'  were n o t i n c l u d e d .  f o r tuna  that describes the observer's  Paloheimo  i n the  a n d d e c i s i o n m a k i n g when t h e f i s h  f u n c t i o n s and competition e f f e c t s  Orbach  parameter  a good r e v i e w  a n d b e g a n h i s r e s e a r c h where  i n making d e c i s i o n s about  other  a r e dependent upon t h e p r e y  must be s t a n d a r d i z e d f o r t h e s e a r c h  (1974) p r e s e n t e d  c o n s i d e r e d methods  factors  using  stated that the d i s t r i b u t i o n s  catch per fishing  fisheries  1971b),  schools.  Shotton  used  and catches  (1971a,  of other  boats.  t h e r e f o r e , does n o t a p p l y .  contains  ability  o n many  an  additional  and m o t i v a t i o n , weather and  14 Both form, the of  the  resulting  next  time  previous  function  sensitive  to  complete  functions  important  increment,  primary search  a  result  ability  set.  in fisheries  independent  1975).  Also, variable  or  available  a priori  remaining  related  the  the  effort  and  (i.e.,  to  independent  random  rates  effort  than  is  the  catch  for specifying of  detecting in  target,  unit  technology  exponential  of  (1982) u s e d  probability  increments  an  probability  detect  i s necessary  search  i n the  tuna  i s more the  time  taken  detection  detecting concentrations  days,  openings  etc.)  is  of  not  increments. change w i t h  a  whether  s e t o f hunches  information, w i l l  change w i t h  scientifically  d e r i v e d i n f o r m a t i o n on  temperature).  The  affect  the  Mangel  probabilities, as  f u n c t i o n s have  that catch per  detection functions w i l l  and  to  f o r search  and  where  of previous  failure  was  Research  law  property:  given (Stone  i n s e q u e n t i a l time  skipper  i n v e r s e cube  i n h i s renewal model The  fish  i n an  increments  fishery.  to  random and  unconscious quality  of  d e f i n e d by  weightings  (i.e.,  distributional  r e g u l a t o r y s t a t e v a r i a b l e (e.g.,  the m o t i v a t i o n a l aspects  technological-economic  "objectively"  and the  the  of  the the  c e r t a i n t y ) of  factors  (e.g.,  water  shorter openings)  may  search.  Mobility Mobility  can  season numerical  be  o p e r a t i o n a l l y d e f i n e d as  (aggregative)  abundance.  It is affected  of  potential  existing  by  responses a l l three  i s bounded by  the  to  the  potential  for within  i n f o r m a t i o n about  s t a t e v a r i a b l e s and competition  and  fish implementation  information  components. The by its  Inter-American  Gulland effort  Tropical  1956b) f o r m e a s u r i n g on  higher  than  Tuna Commission u s e d the  average  success  fish  of  the  densities  an  fleet  index  (developed  i n concentrating  (Griffiths  1960;  Calkins  15 1961, of  1963).  fish  index  The c o n c e n t r a t i o n i n d e x  d e n s i t y d i v i d e d by the weighted  i s the t o t a l  catch  is  t h e sum  of  e x p l o i t e d areas:  o f t h e CPUE  catch  ET  effort  =  total  c = area  catch  e = area  effort  N = total  According areas be  to this  ( i . e . , uniform  equal;  average, index  i f more  (CT/ET)/(1/N  effects  producing  index  areas  the dynamics Hilborn  C  i  /  e  i  effort  d i v i d e d by the t o t a l  index number  )  1)  exceed  w h e r e CPUE  the weighted  o f one.  result Uniform  i n an i d e n t i c a l  o f the c o n c e n t r a t i o n index (1979),  included competition  using  effects  i s higher index.  formulation i s that  should  indices w i l l than  Therefore,  of successful concentration of  d i s t r i b u t i on o f e f f o r t  information)  results  this  to the e x p l o i t e d  t h e two d e n s i t y  one a r e i n d i c a t i v e  Optimal  and L e d b e t t e r  unweighted  and the weighted  i s devoted  of effort),  will  a c o n c e n t r a t i o n index  across  implicitly  i f equal  The problem w i t h  (and good  N Z i=l  i s a p p l i e d to areas  than  are ignored.  competition  effort  effort  effort  The  areas  application  greater  on f i s h .  of  of density.  index  index  view,  the unweighted  values  effort  of  -  number  index  each e x p l o i t e d area  I = the c o n c e n t r a t i o n CT = t o t a l  d e f i n e d as t h e unweighted  d i v i d e d by the t o t a l  from  I  Where  was  competition  i n the presence  i n equal  CPUE  and o p t i m a l  index  value  --  among  of areas,  application of  interpretation  becomes vague.  data  from  t h e B.C.  salmon  on m o b i l i t y p a t t e r n s .  fishery,  I f boats  16 optimize  with  individual  respect  fishing  each  area.  In  area  CPUE t o  reality,  B.C.  area  not  another  an  were y e a r - t o - y e a r  these  c h a n g e s may  an  abundance  in for  the  of  (1979) p u b l i s h e d  South A t l a n t i c  and  a  s t a t e v e s s e l movement  of  shrimp  and  abundance Liao  Fisheries 1957;  Pella  assumption  1969; that  catchability  remains  to  percentage  sockeye  in  of  these They  did  able  Furthermore,  ranks  of  skippers  regardless  analysis of  the and seem  of  areas; to  the  to  their  He  to  and  fishery  the  catch,  motivation. A  was the  linear  The  area  s i g n i f i c a n c e of  entry  specified  included  The  Models  1918;  Ricker  process  1979)  (R =  1940,  function for  i n terms  specific  of  to  an  ex-vessel  out  index shrimp  important  0.6).  1944;  Beverton  have been p r e d i c a t e d  is similar  index  vessel  d i f f e r e n c e s i n s t a t e p r i c e s were  Mangel  mobility  calculated a mobility class  state.  w e a t h e r ) and  constant.  shrimp v e s s e l  model c o n s i s t i n g o f  skill  (Baranov  fishing  ratios  fishing.  information  chase  (U.S.).  into a  and  of  CPUE  of mobile boats  relative  (some s e i n e  the  attributed  costs  imperfect  economic  state  that  Clark the  and  value  f a c t o r s must be  models  equalize  h a v e v a r i e d among a r e a s .  linear  (winter  concluded  t h a t many o t h e r  an  skipper's  of  to  then  salmon s p e c i e s ) .  states  f a c t o r s v a r i e d from  prices.  may  species  other  each v e s s e l , using  these  f a c t o r : the  area  competition,  Ledbetter  desirabilities  inexplicable desire  characteristics  and  f l u c t u a t i o n s i n the  perception  to  vessel  were d i f f e r e n c e s i n the  have been r e l a t e d to  relative  Liao  there  Hilborn  important  there  possess  CPUE.  and  move b e t w e e n a r e a s  however,  specific  successfully fish  fishermen's  abundance  should  total  to  to  fish  units  differences discuss  to  random  E v e n when h e t e r o g e n e i t i e s  on  sampling are  and  Holt  the --  examined  and  17 catchability Paloheimo the  and  models  this  change w i t h  school  distributions  Paloheimo  1971a,  1971b;  D i c k i e 1964;  i n c o r p o r a t e what  assumption; from  i s shown t o  fishing  appears  u n i t s operate  a s s u m p t i o n were n o t e d  (1975) , R a d o v i c h  (1976) , and  t o be  an  extremely  independently.  by  Gulland  Saila  were d i s c u s s e d  and  size  (e.g.,  Flowers  1969),  unrealistic  The  (1964),  and  effects  Garrod  of  departures  (1964),  i n more d e t a i l  by  FAO  Rothschild  (1977). Pella  (1969) and  stochastic they  models  Pella  f o r the  incorporated search  human i n t e r a c t i o n s w h i c h may Another they  noted  distributions Mangel  the  of  has  not  be  met  skills,  historical  Recently, critical 1976;  depensation  illustrated increases the  to  as  fish  mechanistic  Peterman fish  effort  not  been  model.  where  as  for cooperative  fishermen's  (1980) r e l a t e d d e n s i t y and  the  et a l . ignored  the  of  group  Mangel  over  dynamics  times. (1979)  and  non-random  of  search based  search  theory  strategies  assumptions  reflect of  upon  fish  will  specialized behavior.  examined p o s s i b l e mechanisms  for  (e.g.,  Walters  Mangel  C l a r k 1974;  1979).  depensatory  levels  upon  information sharing  i n t i m a t e knowledge  stocks  relationships  effects  Traditional  scientists  population  yet  solved.  The  critical  fleets,  search  of  C l a r k and  fishermen  of  of a l l o c a t i o n  in fish  P e t e r m a n 1977;  distributions  "realistic",  seine  aspects  C l a r k and  i n f o r m a t i o n and  fisheries  (1977),  by  analyzed.  in fisheries  Pella  utilized  (1982) d e r i v e d a model  r a t e s were n o t  s e a r c h i n g purse  Orbach  different  problem  fish  (1975) p r o d u c e d  a Poisson process.  m o d e l was  Koopman's random s e a r c h catch  as  documented by  Poisson  that  Psaropulos  operation of  l e a d to markedly  simple  and  Gulland  qualitative  possible critical  (1977)  a g e n t s when  decrease.  between the  Jones  and  qualitatively  catchability  He  d i d not  speculate  fishing  process  and  form  of  an  depensation  catchability.  empirical catch i n the  B.C.  about  response  native  Indian  18 food  fishery.  whether  depensation  forecasts  of  parameters the  But,  run  he  strengths  (which  catch  data  declines of  competition  decreases  information  q u a l i t y increases This  r e l a t e d to  and  changes  technological  and  fish  (refer  diminished.  functionally abundance  utilizing  are  very  that  speculative research  accelerated  are  fisheries  are  managers  can  determine  a model based  uncertain usually  on  preseason  estimates)  and  inaccessible until  after  has.ended.  Perhaps  stocks  that  i s o c c u r r i n g by  r e l a t e d to  fishery  asserted  on  mechanisms  stocks  should  to  Lofgren  the  (resulting pattern  for catastrophic  include  i n larger catch  in total  institutional  scientific  advances  possibilities  (1972) example  fleet  fishermen's perceptions  i n the  the  of  as  be  fish  o r may  the  that  coefficients)  decreasing  that p a r a l l e l  that  above) or  r e s p o n s e may  parameter,  or  simply  effects  mirror  of  overfishing. Under stock and  the  constraints of present  abundance are  our  models can  Rothchild response  rare. be  reworked  (1977) s t r e s s e d , to  effort  are  information,  exploitation  responses.  assumption  that  with  competition  of  an  estimates  at  information  of  100%  will  The  q u a l i t y and  involves  distributions  saturation, search  of  linear  the  fish  the  and  can  competition  technology predicated  rates  and  skipper's  qualitative  q u a n t i f i c a t i o n of  As  procedures.  upon  population.  of  responses  made  form.  affect  function of  independently  be  of  the e x p l o i t a t i o n  optimization  and are  behavior  more c o m p l i c a t e d  of  a  affect  fleet  estimates  form  to  fish  the  the  effort  or  Vessel of  the  g r e a t e s t p o t e n t i a l f o r q u a n t i f y i n g the  examination of  catch  models  are  independent  effort  ingredients  Traditional  of  slightly  measurements o f  asymptote  response.  information  into a  exploitation rates  and  exploitation  observations  necessary  Competition,  saturate  But,  technology,  effects  density  heterogeneous  interference  19 competition. opportunity skippers  queues  the  t e s t e d and  responses  British  for assessing  form  reflecting be  The  to  set  at  Columbia  information  defined  catch  rate.  inferences  about  fish  or  salmon  fishermen  access  fleet  provides  quality  and  interference  points  and  perceive  Fishermen the  seine  can  be  qualitative  abundance can  be  observed,  forms made.  of  a  an  unique  competition:  queue  as  hypotheses  exploitation  can  CHAPTER SALMON S E I N E BOATS AND  The of  new  and  degrees the  British ageing  of  while  Association  the  50  to  o l d e s t date  1981).  salmon  and  the  trollers  The  average  dollars.  The  divided  among t h e  representative expenses).  The  16,377 d o l l a r s  Committee samples  of  (Pearse  i n 1981.  seine  (Dept.  targets  of  chum  (0^ keta)  the  net  total  and  of  on  being  132  feet  built  i n 1969, i n 1969  the to  every Owners  number  532  seines  i n more  and  than  one  in  crew.  f o r 17  (boat  1980.  from  F i s h e r i e s and  84,940  and  net  fishing  produces  share  (Ch_ k i s u t c h ) .  In  1981,  (11,307 m e t r i c  after  salmon o n l y  Canada  smaller  is  obtained  salmon and  Oceans,  (Pearse  Fleet  (Oneorhvnchus n e r k a ) ,  salmon and  averaged  catch value  Federal  plus  fishing  was  species  total  The  vessels  seines  sockeye pack  of  Indian  and  fishery  f o r other  system;  incomes  20  i n 1980  p u b l i c accountants  sockeye  coho  halibut fleet  with  1982).  a share  Sixty-five  (CL. t s h a w v t s c h a )  percent  on  income  fleet  the  f o r salmon  skipper  seine  are  to  varying  growth were c r e a t i o n o f n a t i v e  interviewed  average net  39,126 d o l l a r s  g o r b u s c h a ) and chinook  net,  feet  group  (Fishing Vessel  369  62,500 d o l l a r s  operate  boat,  1903  from  FISHERY  possessing  40  boats  l i c e n s e s from  earnings  seine boats  Rationalization  The  this  from  entry began  increased  f o r salmon and  1982) .  New  f a r b a c k as  gillnetters  gross  feet.  SALMON  i s a heterogeneous  individuals  in size  limited  salmon  fleet  by  Some v e s s e l s p a r t i c i p a t i n g  97,150 d o l l a r s  averaged  as  transfer of and  seine  range 70  Although  fishing  JOHNSTONE S T R A I T  skippered  c o n t r i b u t i n g f a c t o r s to  licenses  54.9  salmon  Boats  averaging  seine vessels The  vessels  experience.  majority  year,  Columbia  THE  II  herring 1982a). pink  landings seiners  tons,  was  round  (0. of landed weight),  63.7  percent  of  the  chum p r o d u c t i o n and  and  to  Oceans,  (Ministry  The  51.8  seine  percent  Canada  of  catch  (2,757 m e t r i c  coho p a c k s .  amounting  pink  (23,807 m e t r i c tons)  the  1982b) w i t h  a  B.C.  landed  c h a r a c t e r i z e d by skipper  allows  the  to p u l l  a  net  four  the  are  stages:  net  time  ( w h i c h may  to  letting the  o f f the  perceptions the  net  increased  the  the  A  the  set with  risks  backhaul The  go,  of  tons  landings 63.9  to  towing,  and  the  the  the  of  chinook  salmon,  (Dept. F i s h e r i e s  million  dollars  fish.  closing  friction  Sets  and of  and  then  of  the  tide.  conditions or the  brings  of  go)  flow  behavior)  then  schools  (letting  the  became p r e v a l e n t  running  retrieve  m o d e r n drum bigger  catch  boat  drum  and  ( c l o s i n g ) and  fishing  s e t and  s e t and  day.  value  species, water  abundance  innovations  drum,  the  with  Columbia  of  the  are  pursing.  the  water  tows  the  with  net  After a  the  net  aboard  as  during  the  1960s and  in  period  skipper's  skipper brings  the  The  the  he  end  of  purses  the  edge.  Three  for  fish  together  submerged  seine  of  vary  percent  of  Operation  designed  movement o f  the  20  percent  1982).  semicircle usually perpendicular  of  to  nets  than  40,092 m e t r i c  British  Vessel  Salmon s e i n e  less  s e c t o r caught of  Environment,  and  t o n s ) , 45.7  line  power o f  risk the  the  and  the  bowthruster  fleet  associated with net  o l d powerblock gear  their  by  nets;  a  set within i f net  net  onto  the  running  line  contributes  (Figure  decreasing  the  net.  quickly, producing  s e i n e r s complete with  the  took 35  The  2).  the drum  minutes  minutes. occur,  time  (Cove  crew  the  shape  of  the  open  tools  the  of  crew  sets  per  1973); can  can  drum. to  the  necessary  allows  Skippers the  --  These  a g r e a t e r number 50  problems  1970s  set,  take  quickly  22  /——s  DRUM  Figure  2. F i s h i n g i n n o v a t i o n s i n t h e s a l m o n s e i n e f i s h e r y . The drum a n d r u n n i n g l i n e equipment a r e r e c e n t improvements. These i n v e n t i o n s a l l o w t h e f i s h e r m e n t o make more s e t s p e r t i m e p e r i o d a n d f a c i l i t a t e s e t s made o f f s h o r e .  23 particularly combination  i n high  not  the s k i f f  and, t h e r e f o r e ,  The b o w t h r u s t e r  the skipper  uses  this  o f h i s bow r e l a t i v e  collapse  around  line  around with  and  sit  (i.e.,  floats)  must be p i l e d  reflect  Different  sets)  maximizing  the p o t e n t i a l  skippers  a t low energy  and r i s k  missing  i s present  conserve  fuel  required  fora relatively  fishery.  skippers  of high  effort  The m a j o r i t y  determine  small  l i m i t e d by the s i z e  by remaining  levels:  periods  boat  t h e n u m b e r o f s e t s made d u r i n g  i s often  boats. a high  short  degree  relative  setting will  alone  join  of risk  a fishing  t o the reward  from  1 t o 18  that  Others  they  search  a rock  (less  make  alone,  The c h o i c e o f may  fuel) are  Strategies usually vary d e s i r a b l e areas  through respect a good pile).  a s many f i s h e r m e n  queue  risks  o f the  i s associated  The l i n e - u p avoid  i n the  lengths  to the d i s t r i b u t i o n that  with  during  a r e few v e s s e l s  different  spot  boats  periods  fish  opening.  boats  fishing Many  the c r u c i a l  few s e t s  i n less  i s to fish  (e.g.,  may s e t  of the vessel; large vessels  strategies with  strategy  during  i s i n set.  catch.  back  the f i s h .  l i n e - u p s when t h e r e  of skippers  term  Another  total  technology  (due t o t h e f a c t  i n l i n e - u p s where good  less  line-up strategies.  the b i g catches  ofnet  a n d rowed  catch per set a t p a r t i c u l a r  costs  and another  t h a t do  to c o n t r o l the  The queues v a r y  different  line-ups  strategy  effort  adopt  dispensed  sets  i n the s k i f f  than  sets.  o f net c o l l a p s e , the  possessing  line-up f o rsetpositions.  when a s c h o o l  with  Skippers  Seiners  i n long  other  by hand  to the sea conditions rather  presumably  shore  the p o s s i b i l i t y  I n the event  line  i n winds o r  p o s i t i o n e d prop  respect  fewer  and  i s also helpful  forward  t h e bow o f t h e b o a t .  during  i s on deck d u r i n g  t o the n e t and avoids  the end o f the v e s s e l .  spots.  the sea anchor-running  the end o f the n e t c a n be  a n e x t r a c r e w member  position  cork  currents;  associated with  r e q u i r e a t i e up.  currents;  or strong  s u b s t i t u t e s f o r t h e s t a t i o n a r y hook ups u s e d  Furthermore, with  winds  i s usually  to their  gear.  24 Salmon f i s h e r m e n a b i g catch. during with  According  the flood  the tide  similar  perceive a rising  to a roulette  as t h e most p r o b a b l e  time f o r  t o t h e s k i p p e r s , t h e salmon a r e most v u l n e r a b l e  (i.e.,  as b o a t s  tide  rising  water).  queue w i t h game  I n some a r e a s ,  the f l o o d  i n which  each  water.  line-ups  oscillate  T h i s phenomenon i s  s k i p p e r hopes  t o make a n  extraordinary set. Line-up regulation. the is  queue.  etiquette  i s enforced by gentleman's  Each boat  waits  Anyone  setting  said  t o have  "corked"  warning  shotgun  blasts  f o r i t s turn as determined  within a net length i n front  the other  o r rough  will  be c o r k e d  more  than  boat  tows f o r a l o n g e r p e r i o d .  tow  and closed There  beach the  i n the future).  twenty minutes  the net,  s k i p p e r and t h i s  language  over  fishermen  the radio  possess  As soon as a b o a t  another  with  the end o f the n e t t o a tree  upon  the tide,  injuries  and deaths  associated with rationale topography around  f o rthis along  type  their  landmarks  that  stationary  such  i n these  vulnerability  t h e way c u r r e n t s move a l o n g  or  the salmon ascend  a line  associated  object.  as l e a d i n g p o i n t s .  school  i s tucked  s e t t i e up,  to follow  i n close  serious  the shoreline  The the shoreline  areas  and cannot get  to shore.  may b e d u e t o a  the thermocline  Depending  The t i e up i s u s u a l l y  m i g r a t i o n path,  with  i f a  the legal  t o t h e t i e up man;  tend  increased fish  to cork  s e t t i e up,  the beach  salmon  between that  the r i g h t  o f s e t i s that  the end o f the n e t , which  speculate  tow h i s n e t f o r n o  and secure  occurred i n the past.  topographic  i n set  (and the c u l p r i t  has f i n i s h e d  During  or another  i s c o n s i d e r a b l e danger have  of a vessel  o f s e t strategy (Figure 3 ) : beach  man a n d t h e t i e u p man r o w a s h o r e  there  by i t s p o s i t i o n i n  skipper can take h i s spot.  s e t , open s e t and open s e t on a l i n e .  skiff  and by  may b e c a u s e f o r  A skipper can legally  and other  are four types  agreement  Others  relationship  and t h e shape  on t h e f l o o d ,  o f thenet  e n t e r i n g the  25  Figure  3. S e t s t r a t e g i e s . T h r e e t y p e s o f s e t a r e made i n t h e B r i t i s h Columbia salmon s e i n e f i s h e r y . T i e ups i n v o l v e wrapping a l e a d i n g rope a s s o c i a t e d w i t h the end o f the n e t t o a s t a t i o n a r y o b j e c t on t h e shore l i n e . B e a c h s e t s o c c u r o n s h o r e , b u t no t i e up i s made. O p e n s e t s a r e made away f r o m s h o r e . Line-ups are also illustrated.  26 effective sets  close  there a  volume o f  i s no  cliff  or  The  shore,  a  long  making sets  set  are  located  involved  i s higher  higher.  Rock p i l e s on  areas  the  and  set,  the  will  follow If  the  the  line-ups  take  first  fishery. to  an  Boats  are  shape  small and  mouth. by  The the  Information  a  visual  communication  and  at  or  the  because  bottom  involve  any  waiting  i n and  to  the  f i s h are escape  lines  legal  of  inspection  of  surveys.  of  or  form  a  boat open  risk  is  also  i n these  In  an so  net  shallow  ordinary that  the  (Figure  open salmon  2).  i s present  in  along  the  boundary  popular because  the  skippers  enter  the  central portion  f o r p o s i t i o n and  of  per  topographical  net  line  The  catch  manmade b o u n d a r y  also  i n the  catching tradition  catches,  are  formed  leads  stream  or  river  swept  salmon.  historical  radio at  the  in  b o u n d a r y w i l l be  (accumulated,  and  boundaries  otherwise protected  competitor's queues  a  of  often  i s rectangular  v i c i n i t y of the  this  e x p l o i t box  boundary  fish within  The  the  i n s i d e the  are  type  like  a  caught  single  beds.  the  net.  Fishermen  method o f via  the  end  they  refuge the  act  a  by  Specialized  more v u l n e r a b l e  back  this  that  fishermen)  from  the  f i s h are  strategy.  around kelp  supposedly  boundary.  hope  is characterized  sets  jockeying  a  and  many o p e n  or  The  creeks;  aerial  (e.g.,  fewer  contours)  i s transmitted  information),  line  skipper  currents  that  f i s h before  the  beach  will usually  establishes  --  the  strong  feel  arrive  depth  the  or  skippers tide  and  ensue.  of  usually  the  constantly  rivers  the  a hook a t  boats  at  overstepping  around  out  the  crack  attach  beds  prevent  (e.g.,  will  to  fact,  kelp  curvature  area,  longer a  and  w i l l keep  a natural  due  (according  obstacles  the  t i e up  fishermen  rock p i l e s  and  p e r f o r m e d when t h e  to  avoiding  shoreline:  skipper  fishing  the In  and  near  are  away f r o m  made.  set  sets  beach).  although  after  landmarks  upon which  occurs  are  Beach  does not  sloping  line-up;  more s e t s  net.  but  material  open s e t  shorter set,  to  the  traditional  27 fishing may to  spots  enter  a  which have  a potential  l i n e - u p , watch  t r y somewhere e l s e .  exceptional  a  few  catches  Line-ups  fisherman's  value  also  associated with  b e i n g made a n d  form  them.  make t h e  A  skipper  decision  a r o u n d known h i g h l i n e r s ;  reputation attracts  other  skippers  to h i s  the fishing  spots. Many g r o u p s  of  fishermen  interact  considerable  a m o u n t o f money h a s  descramblers  as  others.  Senior  skippers  in their  group  advice  concerning  hierarchical access  to  set of  or  in  to  order  their  pilots spot  skipper with  anymore  --  indicated  everyone t h a t good  surveillance.  fisherman  scrambled of  42  are  f l y over  i f an  fishes  of  A only  channels  t h e movements o f the  few  company  the  and  other  dispatcher  groups possess  a  inner c i r c l e  for spotting  fishing  areas  salmon.  having  the  and  before  the  Many s k i p p e r s w i l l  stated that there  spots.  Another  s p o t s become r a p i d l y  R e l a t i v e t o most  a day  catches  not  jumping openings bring  near.  experience  a l l of  fishing  with  used  airplane is  years  contact  a  and  communication  direct  strategy.  and  these.  planes  also  may  channels  large schools  c a t c h aboard A  a  his decision  Company o r p r i v a t e The  invested i n scramblers  s k i p p e r s sometimes  the most p r i v a t e  salmon.  radio channels  skippers a s p i r e to p r o t e c t t h e i r  to break  for  been  through  ecological  are  secrets  experienced  overcrowded  systems,  no  due  fisherman to  information i s  aerial near  perfect.  The  The  Johnstone  Strait  Passage,  Johnstone  Strait,  Goletas  Channel  and  Johnstone  fishery  comprises  Broughton  Gordon Channel  Strait  Strait,  Fishery  six distinct  regions:  Queen C h a r l o t t e  (Figure 4).  The  width  of  Discovery  Strait, the  channel  28  Figure  4.  The J o h n s t o n e S t r a i t s t u d y a r e a . The map is divided into p o r t i o n s w i t h the n o r t h w e s t e r n s e c t i o n o f the fishery i l l u s t r a t e d i n the top h a l f o f the figure.  two  30 varies  from  26  i n Queen C h a r l o t t e  km.  north  less  o f Vancouver  Queen C h a r l o t t e midchannel (75  are often  cm./sec.) d u r i n g are always  shore  are about  kn.  km.  20  and  and  over  tidal  1 kn.  Area  includes  12  Strait, The Area  (up  The  ebb  in  exceed  associated with half  fishery  1.5  kn.  rising  mile of  C u r r e n t s may  The  Ocean  between  currents  one  to  the  exceed  6  i s affected  15 m . / s e c . ) t h a t  usually  by  peak  1981). and  i s divided  Strait,  of Johnstone  Oceans a l l o c a t e s  areas  approximately half  Queen C h a r l o t t e  minutes  sometimes  currents  --  the P a c i f i c  160  currents within  t o 30 k n .  statistical  Strait  lower p o r t i o n  l a g by  o f K e l s e y Bay.  of Fisheries  c a t c h e s t o 29 Johnstone  and  D i s c o v e r y Passage  from  percent o f those i n midchannel.  Department  1979).  Tidal  t h a n 1 kn.  t h e a f t e r n o o n (Thomson  salmon  propagate  currents  tides.  f o g s and h i g h winds  The  and  (50 c m . / s e c . ) a n d  (3 m . / s e c . ) i n t h e v i c i n i t y  morning  Tides  Strait  D i s c o v e r y Passage.  spring  weaker  i n Johnstone  Strait.  Island  Strait  water  in  t h a n 2.5  ( s e e Map  into Areas  1, 12  of Johnstone  Goletas Channel Strait  British  Hilborn and  13  Strait and  Columbia  and L e d b e t t e r  at Kelsey and  Gordon  the  Broughton  Channel  and D i s c o v e r y P a s s a g e  Bay.  are  regions.  included  in  13. In  1981,  ranked  fourth  fourth  largest  five  Area  12 was  the l a r g e s t  f o r chum a n d fishery  fifth  f o r coho  f o r sockeye  areas f o r the o t h e r s p e c i e s  total  Johnstone  Strait  seine  p r o d u c e r o f p i n k and  a n d was  and not  c a t c h was  the pink:sockeye:coho:chum:chinook  weight)  was  38.7:29.5:2.1:2.0:1.0  Johnstone  are  dominated  ups  as  by  Strait,  a beach  D i s c o v e r y Passage  sets  ratio  (Dept. F i s h e r i e s  s e t t i e up  the most p r o f i t a b l e  and  and  strategy. line-ups  13 was  Oceans  17,277.9 m e t r i c  and  Area  salmon, the  r e p r e s e n t e d among t h e  (Dept. F i s h e r i e s  pieces)  The  chinook.  sockeye  and  tons  1982b).  Oceans  Broughton  landed 1982c).  Strait  Skippers perceive are prevalent.  The  (7,106,069  (based on  and  top  fisheries the t i e  Open s e t s  are  31 u s u a l l y p e r f o r m e d b y i n d i v i d u a l s who  wish to minimize t h e i r w a i t i n g time.  When t h e e x t e n d e d Adam R i v e r b o u n d a r i e s a r e i n e f f e c t ,  an open s e t l i n e  forms a l o n g the lower boundary and the b o a t s i n t e r c e p t the f i s h b e f o r e t h e y e n t e r t h e l o w e r s t r a i t ( F i g u r e 4) .  Queues a r e a s s o c i a t e d w i t h t h i s  line.  R o c k p i l e f i s h i n g i s found a l o n g the n o r t h e r n shore o f Hanson I s l a n d . O n l y a s m a l l p o r t i o n o f Queen C h a r l o t t e S t r a i t i s u t i l i z e d .  The  f i s h i n g a r e a s are the r e g i o n around White C l i f f I s l e t s n o r t h o f Hanson I s l a n d , the n o r t h and n o r t h w e s t s h o r e s o f Malcolm I s l a n d , the n e a r shore waters o u t s i d e o f W e l l s Passage on the m a i n l a n d shore, and the around D i l l o n P o i n t o u t s i d e o f P o r t Hardy. on a l i n e s t r a t e g y i s p r e v a l e n t . the  T i e ups a r e r a r e ;  islands  the open s e t  The n o r t h w e s t s h o r e o f M a l c o l m I s l a n d i s  major f i s h i n g a r e a ; an open s e t l i n e forms d u r i n g p e r i o d s o f h i g h  e f f o r t a n d t h e l i n e - u p s may b e c o m e a s l o n g a s t h r e e o r f o u r b o a t s . Fishermen's f o l k l o r e  i n d i c a t e s t h a t t h e s a l m o n sweep s o u t h f o l l o w i n g t h e  d e p t h c o n t o u r s , c h o o s i n g m i g r a t i o n p a t h s around the n o r t h e r n and s o u t h e r n shores of Malcolm Island.  A n o t h e r o p e n s e t l i n e d e v e l o p s when t h e  P o i n t - Doyle I s l a n d boundary  i s i n effect  Goletas Channel i s r a r e l y f i s h i n g d u r i n g t h e 1981  season.  numerous r o c k p i l e s and r e e f s .  Dillon  ( F i g u r e 4) .  f i s h e d b y s e i n e r s a n d was  u s u a l l y closed to  Gordon Channel i s c h a r a c t e r i z e d  by  Open s e t s a r e t h e p r i m a r y s t r a t e g y and  only  12 t i e u p s a r e u t i l i z e d . W i t h i n - s e a s o n management ( a s w e l l a s p r e s e a s o n p l a n n i n g ) r e s t r i c t s m o s t f i s h i n g o p e n i n g s t o 48 h o u r s  ( s t a r t i n g a t 6 p.m.  Sunday e v e n i n g )  manipulates boundaries i n order to protect various stocks of D u r i n g t h e 1981  salmon.  season, temporary boundaries c l o s e d the Gordon Channel  Malcolm I s l a n d f i s h e r i e s mainland pinks.  and  and  f o r the c o n s e r v a t i o n o f e a r l y Nimpkish sockeye  and  Boundaries from the south shore o f Malcolm I s l a n d to the  Vancouver I s l a n d shore e x c l u d e d the s e i n e r s from the p o o l i n g grounds o f the  32 Nimpkish  sockeye.  A box boundary  River.  The m a i n l a n d  Passage  were  openings Island  closed  inlets  restricted  over various  week o f t h e s e a s o n , and  chinook  salmon.  the  conservation  adjoining  f o r the p r o t e c t i o n  t h e b o a t s were  shore  protected  Area  portions  local  Johnstone  o f a l l salmon  species  t h e Adam  and D i s c o v e r y two  m i l e o f the Vancouver  Strait.  f o r the protection  A permanent box boundary  entering  p i n k s and d u r i n g  one h a l f  o f Johnstone  13 was c l o s e d  Strait  o f mainland  to within  sockeye  During  the second  of juvenile  coho  a t K e l s e y Bay c o n t r i b u t e d t o  spawning  i n t h e Salmon  River.  CHAPTER  III  DATA C O L L E C T I O N AND  Three seasons. basis  types First,  Seine the  two  fishing  various  logbooks  for  the  Strait  were  collected  data  were  f o r the  during  the  Johnstone  during  components time  anecdotal  An 1981  Strait during  1980  of  five  and  the  data  vessels  and  gathered  season.  Second,  area.  flights  1980  salmon  s e a s o n as  collection  observer  study  1981  32  on  the  ten  skippers  Third,  i n a Cessna  during  covered  data  the 180  a  coast  boats filled  primary over  data  Johnstone  1981.  observer  amount o f  on  the  during  emphasis  observed  American borders. areas  during  were c o l l e c t e d  s t r u c t u r e and  t h e s i s were c o l l e c t e d  The  and  the  operations  between  out  data  observer  for planning  1981.  time  of  VERIFICATION  data  of  the  spent  c o n s i s t e d of  catches  set  go,  (letting  in different  information.  time  components,  data  were  time  important  towing,  activities,  E m p h a s i s was  allocation,  f o r the  per  formulation  and  species  closing  queue  placed  line-up  set  on  lengths  and  pursing),  the  waiting  times  lengths, the  and  data  p e r t a i n i n g to  waiting  of hypotheses  (pieces),  times.  concerning  These  fleet  behavior. The  l o g b o o k s were  recording. types  were  For  beach  data  included eye  topography  example,  set  t i e up, i n the  (this and  performance  and  Acquisition  of  lengths  t i e up  beach  set,  not  used  fog patches),  logbook data  the  i n the  the  number o f  and  were  time,  fish  number  a n a l y s i s as  given  open s e t  open s e t and  l o g b o o k s were  was  the  for statistical  line-up  d i s t i n g u i s h e d as  than  unaided  designed  open  caught per  depended upon the  set  on  a  and  line.  observed  to biases  location,  and  ease  of  set  either/or) rather  set  of boats  as  intervals  (i.e.,  a n a l y s i s due the  as  well  the by  cooperation  with  Other the  introduced  by  crew/gear species. of  skippers;  this  34 requirement  restricted  it  i s hoped  t h a t r e p r e s e n t a t i v e d a t a were  of  the logbook  data  the s t a t i s t i c a l  analysis  cannot  supportability obtained.  be r i g o r o u s l y  o f t h e sample Therefore,  extended  though  the  to the  results  total  fleet. Sixty-one were  flights  terminated  due  were  attempted  to fog.  Line-up  close,  direction  during  t h e Sunday n i g h t o p e n i n g  Flights  were  temporal term  changes  four hours  i n fleet  fluctuations  Bay and t e r m i n a t e d  Kelsey  Bay.  cycle  daylight  strait  were  Line-ups access  (whether closer cause an  equal  numbers  obtained  and a c t i v i t i e s simply  open s e t area.  This  Bay;  the afternoon  impossible. o f seven  of total  with  Tuesday.  over  or to short  12  returned to  stages  of tides  at  o f the  and hours flights  were  stages  and a  p e r i o d s when m u l t i p l e  fishing  fleet  (fleet  of  attempts  size) for  flight. recorded  on an access  grid  point basis.  a line-up  occurred  i n the previous  chapter,  the fishermens'  i n the i d e n t i f i c a t i o n  associated with  of distributions  flight  o f t h e two h o u r  As m e n t i o n e d  aided  once  originated  Therefore,  d e f i n e d as a p l a c e where  fact  tow,  recorded  cycle  flight  the f l i g h t s  The one d i m e n s i o n a l  the problems  to the t i d a l  The m o r n i n g  a net length apart violate  f o r anger.  character  were  were  flights  (e.g.,  a d a y o n Monday a n d  during foggy  f o r each  one o r more b o a t s ) .  than  avoided  arrangement  Sample e s t i m a t e s  p o i n t was  and a c t i v i t i e s  apart) but the combination  followed except  were n e c e s s a r y . the  this  to achieve  p l a n was  linked  abundance. at Alert  Ten  o n t h e same d a y t o c o n t r a s t p o s s i b l e  made t o r a n d o m i z e  (two h o u r s  rendered  staggered flight  was  apart  completed.  and w a i t i n g )  and twice  behavior  in fish  Kelsey  tidal  lengths  o f movement, d e l i v e r i n g  spaced  An attempt  a n d 51 w e r e  rules  of access  c h a r a c t e r o f these  grids size).  (i.e.,  a n d may  An  sets be  points i n  measurements  the change o f the  35 Queues were set  easy  l i n e - u p s were  access  (a pursing boat  previous access  chapter)  points  identified for).  access  f o r shore  and spaced.  sets  has a v e s s e l associated with  and p u r s i n g and w a i t i n g boats  until  .identified repeatedly  recorded by f i s h i n g  without  photographs,  and designated observed  repeatability  as f i s h i n g  ( t h e rope allowed  marks  simple  t h e number o f go, t o w i n g o r  allocated assigned  a l l v e s s e l s were  i n the  t o these  t o each accounted  t h e maximum o p e n s e t l i n e - u p .  area.  areas  open  i t as mentioned  were  f a s h i o n ( v e s s e l s were  p o i n t one a t a time  One b o a t  of vessels letting  T h i s m e t h o d may h a v e u n d e r e s t i m a t e d  impossible  (Figure 5).  F o r open s e t l i n e s ,  a s t h e number  i n an i t e r a t i v e  s e t s were  this  common  p o i n t s was c a l c u l a t e d  closing  Open  t o count  Since  a grid  analysis  o f a g g r e g a t i o n were areas.  subjectively  T i e up l o c a t i o n s  s h o u l d be v i s i b l e  numerical  was  were  on the t r e e s ) and  identification.  Verification  The  overflight  temporally on  separated  a particular  date,  flight,  d a t a were  coded  i n order  t o minimize  location,  number  o f access  Another  s e t o f data  during which  a beach  s e t access  two s e t s o f d a t a w e r e  fishing  area)  observation assessment.  then  identification  error  misidentified  One d a t a  p o i n t s , number  the twenty minute  this  interval  a r e a was  i n access  comparison  of interpretation  fixation  o f boats and  compared f o r d i f f e r e n c e s  a n d number;  were  s e t contained the  p o i n t o r open s e t f i s h i n g  and f o r the degree  (Although  sessions  biases associated with  contained  and m i s s i n g  the coding process.)  access  points reached  spotted. point (or  tested f o r coding  involved i n the  l i n e - u p s were c h a r t e d as queues, a m i n i m a l  i n t e r p r e t a t i o n was r e q u i r e d d u r i n g for  The c o d i n g  mode o f p a t t e r n r e c o g n i t i o n .  activities.  The  twice.  amount o f  The p e r c e n t  17 p e r c e n t ,  error  b u t most  Figure  5.  A beach s e t queue. wait t h e i r t u r n to  Purse set.  seiners  line  up  at  historical  access  points  and  37 points  were below  The  total  recorded is  two  rank  Figure  The  6.  As  a 40  interval  minute  trend  i n the  (critical error  as  were  less  11  than  the  channels  The response  to boats  the  effort  ebb. the  flight.  This  appreciable bias over  relationships Skippers of  to  effort  land the  fish  used  A  was  34  out  of  0.05 to  in  48  approach  effort  indicated  =  of  substantial  produced  during  T h e r e was  no  effort The  percent  analysis  was  as  measurements  portion of boundary  this or  error  searching  t h a t moved o u t  observations  13  summarized  0.2192).  error  12-13  for fish  were  over  actual  36  and  twice  levels.  constant rho  12  observed counts  i n the  the Area  indicate  of  the  of vessels  and  the  fairly  fish  that a v e s s e l enumeration  rapidly  analysis.  levels  by  summarized  (the Area  repeated  calculated  across  response  their  are  and  Bay  fishery  remained  boundaries  may  the  =  boundaries.  the  reflected  13  Twenty-five  checks  data  data  comparative  at Kelsey  flights  (Figure 7). moving  a  at  presentations refer  percent  for various  effort.  Spot  error  12  These  error  the  fishing  occurred.  weight  low  5 percent  above  performed  and  at  of  These  areas  low.  i s 0.3313,  i n terms  rho  This  the Area  absolute  0.05  (critical  was  terminated  s u b s i d i a r y channel  on  searching  a =  percent  attributed  beyond  any  at  expressed  high  was  rho  or  was  o f each  the  constant  5 percent.  i n v e s s e l counts  data;  fishing  a l l correlation  error  a consequence,  difference  points or  coefficient).  than  originated  of access  fairly  0.3503;  percent  less  boundary).  the  =  observation error  Flights  as  rho  largest  number  s e t s was  correlation  measurements were coding  i n the  data  calculated  Spearman's  that  percent.  difference  i n the  0.2859,  10  s a t u r a t e d and  The trend  constant  at packers  s p e c i e s , the  c o d i n g was i n the  d i d not  code  fished  error  observation  or processing p l a n t s .  area  contribute  not s y s t e m a t i c a l l y  percent  absolute  learning  and  error. The  number  other p e r t i n e n t  38  1  o o_  0.12  r  v>  to IxJ o o <  ?  0.09  0.06 h  oo  o  UJ  UJ  O  or  O OO CD  O  UJ  Yr  0.03  O O  o ir  UJ  -O  Figure  6.  CO  CD  o z  Coding counted  COD  75 Qg> < B  150 EFFORT  error: percent during  two  QD ' O 225 ( N O . OF  0 O  ' 300  sessions.  O O 375  BOATS)  d i f f e r e n c e o f t h e number  coding  O  of access  points  39  O.I2  r  0.09  0.06  CD O  0.03  O  O  O  O CD  20  —Q-6-  40  ob O 60  E F F O R T (NO. OF  Figure  O  CDO  O  J  I  80  100  n  J  120  BOATS)  7. O b s e r v a t i o n e r r o r : t h e p e r c e n t d i f f e r e n c e i n t h e n u m b e r o f b o a t s o b s e r v e d i n A r e a 13 d u r i n g a 40 m i n u t e i n t e r v a l a n d two f l i g h t s .  40 information  are  opening  be  can  originating the  12  points  13  that  occurred  that  aerial  and  on  sales  c a l c u l a t e d as  from  repeated  Areas  recorded  area.  effort  counts  easily  when t h e  Juan  The  Fuca  catch  American  and  Obviously, as  Johnstone the  Juan  Fuca  de  Strait. the this  time  home p o r t Hilborn  which  the  associated upper  end  of  the  ( i n the The  in a  of  of  errors  not  the  with high the  of  8 and  to  9  effort  early  error  the  effort,  distribution.  catches  i s that  early as  boats  for  the  Johnstone represents  home p o r t  at  o r i g i n a t i n g from  are  recognized  are  sometimes  often  recorded  that  (small boat  the  (see  recorded  as  f o r weeks  in  standard  large  there  no  the  included  of  the in  well end  defined of  the  largest deviations  deviations  portion  was  densities at  were n o t  Although  smallest A  Fuca  o v e r f l i g h t counts.  departure,  the  salmon.  line  i n t e r v a l s (two  indicates  deviations).  as  data  are  equal  pink  their  in  Salmon  catches  to  few  far right  J u a n de  effort  catch  catches  landings The  accuracy  variance  standard  and  and  for  for a  fishery is  exited  their  slip  the  difference  others  return  to  produce  report  equal  the  sales  aggregate  open.  Figures  report  to  this  as  the  Skippers  i n the  1979);  r e s u l t i n g from of  left  season.  s i n g l e area  verify  of  c e n t r a l coast  rush) o f t e n  f i s h e r y was  calculation  for  as  measurement  Pacific  sockeye  to  of  Inspection  openings,  motivated  to  Ledbetter  relationship  River  point  area.  deviations)  Fraser  and  catch  good except  This  regulated  explanation  the  quite  International are  their  effort  open.  reported  lying  slip  area  r e l a t i o n s h i p between  lying  a l l vessels  and  originating  the  the  points  f i s h e r y and  opening  and  of  Another  f i s h e r y from  The  final  openings  fishing  reporting  sales  The  the  fishermen are  Strait.  the  f i s h e r y was by  Canadian catches  Canadian  entered  and  of boats  r e l a t i o n s h i p was  de  Commission,  where  and  explained.  administered  f o r any  8 demonstrates  be  Convention waters  Effort  number  Figure  combined.  can  the  slips.  also  the  occurred  variance  can  were  at be  the  41  Figure  8.  Reported and observed e f f o r t . R e p o r t e d e f f o r t was m e a s u r e d a s the number o f v e s s e l s l a n d i n g c a t c h e s a s J o h n s t o n e Strait. O b s e r v e d e f f o r t i s p r e s e n t e d a s t h e means o f t h e r e p e a t e d a e r i a l counts and the standard d e v i a t i o n s .  42  375  o o 300  O  CO  o  m u_ o  0 0  o  8  225  or 150  8 75  0  _J_  J  J  L 6  8  L 10  J 12  I 14  WEEK  Figure  9.  A e r i a l v e s s e l counts. M u l t i p l e e f f o r t c o u n t s were o b t a i n e d d u r i n g each w e e k l y f i s h i n g opening d u r i n g June t o September, 1981. M u c h o f t h e w i t h i n - o p e n i n g v a r i a t i o n was e x p l a i n e d b y e n t r a n c e and e x i t o f v e s s e l s .  the  43 attributed (which  to breakdowns,  opened  central  and  Vancouver  low  catch rates  the  logbooks).  c o a s t and early  During  recorded positions  did  not  to boats  d u r i n g the  aerial  fishery  f o r Juan  leaving last  f o r Campbell  day  of  the  were  or  the  intervals same a s  opening from  c o u l d n o t be  his activities  surrounding the those noted  identified  d u r i n g the  from  from  de  due the  the  to poor a i r and  that  air.  logbook  a f t e r n o o n of the  with  Island tides noted  or in  carried  spot checks, the  Fuca  exchanges  R i v e r , Quadra  o b s e r v a t i o n s w e r e made o f v e s s e l s  the hour  location  report  the  ( a l l o f which have been observed  Thirty-three  fisherman's  leaving  on Monday, T u e s d a y o r Wednesday e v e n i n g s )  the  logbooks.  to boats  31  of  the  One and  flight.  another  CHAPTER INDEPENDENCE AND  As  many f i s h e r i e s  classical vessels have  fisheries  operate  provided  fishermen  independently  their  chapter:  types  of  information  spots  to  fish. of  incorporated  fishermen  The  and  compete  information  the  lack of  i n data  are  contagiously ascertain c o u l d be  method are  being  made) t h e  distributions  were  ( C o h e n 1960;  presented  tested:  distributed.  (there  and  (defined here  the  rates and  for  times  distribution  and  the  intensity  of  phenomena a s s o c i a t e d w i t h or  are  artifacts  various  favourable reflect that  known  of  of  the  using  information  the  fishing  behavior  outlined in  waiting as  that  the  is  fish  competition. low  of  vessel  grid  recordings.  a l t e r n a t i v e hypotheses were  that  1971a),  Anthropologists  concerning  information  of vessels  information,  Line  distributions  for this  Paloheimo  assumptions  to p o t e n t i a l catch  and/or v u l n e r a b i l i t i e s  abundance  Two  upon the  information  in decision strategies),  distributions  (e.g.,  i n a random f a s h i o n .  respond  Random e f f o r t  manipulation  and  EFFORT  emphasized  predicated  distribution  active  concentrations  and  have  descriptions coincide with  previous  perfection  are  d e t a i l e d anecdotal  and  D I S T R I B U T I O N OF  scientists  models  IV  no  Up  Distributions  concerning  these  spatial  Since  the  physical limit  truncated  Poisson  fitted  the  to  Sampford  i n Figure  zero  and  queue  arrays  10. 44  were  category to  the  Examples  frequency  e i t h e r randomly  was  impossible  number  truncated  line-up data  1955).  length  of places  negative  or  to a  set  binomial  by  the  maximum  likelihood  of  the  line-up  distributions  45  Queue l e n g t h f r e q u e n c y d i s t r i b u t i o n s . The g r a p h s r e p r e s e n t the frequency o f l i n e - u p lengths observed d u r i n g d i f f e r e n t f l i g h t s and e f f o r t l e v e l s . E f f o r t was m e a s u r e d a s t h e t o t a l number o f v e s s e l s p a r t i c i p a t i n g i n t h e f i s h e r y .  46 The  truncated  Poisson  probability  P(x)  and  t h e maximum  likelihood  X  x  estimate  X  X i s the estimate  i s given by  - e" X /x!(l-e- )  V(l-e" )  where  function  2)  A  o f X i s given by  = x  3)  o f t h e p o p u l a t i o n mean a n d n i s t h e s a m p l e  size.  A.  The  variance  o f X i s given by  V(X)  -+(X)(X/n)  4)  where  +U )  One  P(x)  =  (l-e- ) /a-(A+l)e- ) X  formulation o f the negative  =  (k+x-1)!/(k-l)!x!  i s the d i s p e r s i o n  w = 1/1+p,  The  maximum  binomial i s  x  = l/(l+p)  coefficient,  x - 1 , 2 , 3 . . . ; p,k>0  k + x  =  <o /(l-o) ) k  likelihood  k  6)  7)  k  p = m/k  n = 1 -co, t h e t r u n c a t e d n e g a t i v e  P(x)  5)  X  p /(l+P)  P(0)  where k  2  and m  i s t h e mean.  Letting  binomial i s  ( k + x - 1 ) ! / ( k - l ) !x! n  x  8)  equations are  nk/w(l-w ) k  nlogU)/d-w ) k  +  - nm/(l-w) = 0  I i-1  f i Z l/(k+j-l) j-1  9)  - 0  10)  47 Table  I.  Parameter estimates f o r the t r u n c a t e d negative b i n o m i a l t r u n c a t e d P o i s s o n f i t s t o queue l e n g t h f r e q u e n c y d a t a , ns = n o t s i g n i f i c a n t .  and  48  EFFORT  A C C E S S POINTS  34 29 61 53 41 50  25 11 38  27 82 84 80  17 38 48 51  85 67  47 34  ns ns  111 110 105 100 95 58 54 52 66 38 50 55 58 114 118 120 190 178 184 166 228 260 239 241 298 280 325 341 361  64  ns ns ns  38 30 34  55 43 44 36 41 36 32 33 19 31 29 36 51 41 56 88 83 81 67 103 133 112 109 159 136 174 138 214  363 362 263  178 181  257 255 252 279  117  278 289 291  127 111 106 167 122 178 131  X  a(X)  0.58 0.50 0.15 0.53 0.32 0.39 0.23  0.04 0.08 0.01 0.02 0.02 0.02 0.02 ns ns ns  0.03 0.03 0.02 0.04 0.05  0.61 0.41 0.90 0.58 ns ns ns ns ns ns ns ns ns ns ns ns ns ns ns ns ns ns ns ns ns ns ns ns ns ns ns ns ns  a(k)  a(w)  w  parameter estimate negative parameter estimate negative parameter estimate negative parameter estimate negative parameter estimate negative parameter estimate negative parameter estimate negative 0.52 1.4 0.56 0.28 1.6 2.8 0.69 0.27 0.16 1.0 0.59 0.27 parameter estimate negative  ns ns 0.66  k  parameter estimate negative 2..5 0..70 1.5 0..23 1..1 0.82 0..54 0..19 0.05 0..44 0..27 0..13 0.53 0..87 0,.45 0..19 2..3 2.1 0..61 0..20 parameter estimate negative parameter estimate negative 22. 402. 0.98 0.30 53. 394. 0.98 0.12 parameter estimate negative parameter estimate negative 0.03 0.76 0.40 0.25 parameter estimate negative parameter estimate negative 1.4 1.7 0. 55 0.16 parameter estimate negative 0.13 0.45 0. 40 0.14 0.19 0. 42 0.52 0.15 0.84 0.86 0. 53 0.15 20. 93. 0. 95 0.23 1.5 1.3 0..60 0.15 0.43 0.49 0..48 0.11 4.1 3.3 0..77 0.13 0.14 0.93 0..53 1.1 parameter estimate negative 0.13 0.97 0..60 1.2 0.13 1.4 0..69 1.5 0.11 0.73 0 .51 1.2 0.13 4.3 0 .84 3.6 0.12 0 .65 1.0 1.3 parameter estimate 0.99 0 0 0.72 0 0.76 0 1.8 1.8 0 1.2 0.95 0 2.7 3.5 13. 0 7.4 0.73 0 0.90  1.0 0.73 0.95  negative 0.14 .59 0.13 .51 0.12 .54 0.16 .65 .68 .74 .91 .54  0.15 0.13 0.14 0.12  49 where n is  i s t h e sample  the l a r g e s t  from  value  line-up fits  I gives  o f x.  The v a r i a n c e s  the parameter  distributions  were  solutions  obvious  that effort  boats  the high  binomial  distributed these  effort  vulnerabilities summary, fit)  (50 b o a t s  only,  salmon v u l n e r a b i l i t i e s  queue  levels, lengths  points  were  The m a j o r i t y  was  hypothesis  usually i s that  t o salmon d e n s i t i e s or among f i s h e r m e n .  possessed sets  a  In  significant  ( a t low e f f o r t ) ,  theoretical  the problem  i s through  points represented  distributions  analysis  a non-uniform  the  in 2  p o i n t s s h o u l d have randomly  and access  effects  among a c c e s s  point effects  were  different  Table  c h a r a c t e r i z e d by d i f f e r e n t  queue  means  points).  Zeros  I I summarizes  significant  fashion  was p e r f o r m e d  by boundaries.  were  over  (i.e., A two-way f o r beach i n c l u d e d and  the data: the  (p<0.001).  lengths.  of  distribution of  and a c q u i r e d l i n e - u p s i n an o r d e r e d  one o b s e r v a t i o n p e r c e l l .  p o i n t and f l i g h t  both  few  samples.  d i d not fluctuate  access  (i.e.,  I ti s  by the truncated  then,  interactions  i n 10 o u t o f 51 d a t a  l i n e - u p s t h a t were n o t a f f e c t e d  t h e r e was  was u s e d .  f a s h i o n when v e r y  Effort,  a response  were d e s c r i b e d  some o f t h e s e  ANOVA c o n t a i n i n g f l i g h t  reflected  competitive  o f approaching  I f the access  whether the  and truncated  test  approximated  d i d not f i t ) .  i n 31 s e t s ,  and n e i t h e r i n 8  variance.  effort  with  only,  binomial  i n a random  were  calculated  deviations for  and i n d i c a t e s  f a s h i o n and the obvious  distributions coupled  A n o t h e r way  and s t a n d a r d  t o be t h e b r e a k p o i n t ) .  queue d i s t r i b u t i o n s  the distributions  instances  appears  and X  1955).  The Kolmogorov-Smirnov  (the Poisson  binomial,  estimates  was o n l y d i s t r i b u t e d  by the Poisson,  negative  ( s e e Sampford  f o r the truncated negative  i n a contagious  non-random  of the i t h category  o f to a n d k c a n t h e n b e  a l l the o v e r f l i g h t s  ( a =0.05).  were p r e s e n t  negative  from  significant  Poisson  set  i s the frequency  the variance-covariance matrix Table  of  size,  Some  access  F i g u r e s 11-13  50 Table  I I . A c c e s s p o i n t - f l i g h t ANOVA boundaries. Zero line-up  SOURCE access flight access  point point-flight  DF 155 45 6975  f o r beach s e t line-ups u n a f f e c t e d l e n g t h s were i n c l u d e d .  SS 1922.9 407.88 5660.9  MS 12.406 9.0641 0.81160  F-RATIO 15.286 11.168  by  PROBABILITY 0.0000 0.0000  51 illustrate  the d i s t r i b u t i o n  boundaries. vessels by  A  subset  as e f f o r t  constant  of beach  of access  intensified  boat  points  while  period  movements  (i.e.,  performed boats. The  hypothesis  This  alpha  equal  ratio  parameters with  behavior The  was  access  the lower  greater  (within-opening the  fish  north in  and  acquired  were c h a r a c t e r i z e d  Activity  than  X  sample  numbers  the expected s e t s were  1/20  sum  less  data  were  than  25.)  (Table ratio for  the n u l l  hypothesis  o f the i n d i v i d u a l  significant  boats  mobile  sets  rejection  grouped,  The  of  time  of  tests  sizes  sizes  15 o f t h e 46  o f f r e e d o m was  a short  or c h i squared  f o r sample  = 0.46).  2  During  i s that equal  Binomial  i n only  and f i s h i n g  grid  fishing  and were boundary  flights  areas  i n Area  (calculated  The measurement  group  test  X  =  2  search  as a  14  i n nautical summarizes  v e s s e l d i s t a n c e from and p r o g r e s s e d  area  Boundaries  of this  Figure  by s o l i d  i n the f i s h i n g fish.  digitized  to distances  13.  directional  are connected  incoming  were  converted  as t h e average  movement was  already present  14.  densities  constant.  to intercept  Figure  spots  t h e samples were v e r y h e t e r o g e n e o u s :  points  Fleet  and  performed  When t h e d a t a  movement w i t h i n o p e n i n g s boundary.  fishing  hypothesis  rejected  22 d e g r e e s  not  was  (calculated  longitude-latitude from  was  Therefore, was  other  random o r d i r e c t i o n a l .  the n u l l  test  t o 0.05.  not rejected  122.16).  boat  ( u n a f f e c t e d by boundaries)  c h a r a c t e r i z e d by adequate  (The b i n o m i a l  III).  be  o r down t h e s t r a i t .  for flights  null  was  may  a flight)  w e r e m o v i n g up  for different  densities.  Movement  Vessel  sets  lines).  directional  northwest caught  and then  had an e f f e c t , movement was  fleet  lower  Fishermen  on Sunday n i g h t also  the  the  to the  miles  as  moved noted  somewhat  Figure  11.  Beach  s e t l i n e - u p s : low  illustrated. near  The  the v e r t i c a l  effort.  southeastern axis.  Beach end  s e t and  t i e up  of the Johnstone  Salmon e n t e r  from  the  line-up lengths  Strait  northwest.  fishery  are  appears  Figure  12.  B e a c h s e t l i n e - u p s : medium e f f o r t . B e a c h s e t a n d t i e up l i n e - u p ^ l e n g t h s are i l l u s t r a t e d . The s o u t h e a s t e r n end o f t h e J o h n s t o n e S t r a i t f i s h e r y a p p e a r s near the v e r t i c a l a x i s . Salmon e n t e r f r o m t h e n o r t h w e s t .  Figure  13.  Beach s e t l i n e - u p s : h i g h e f f o r t . B e a c h s e t a n d t i e up l i n e - u p l e n g t h s a r e illustrated. The s o u t h e a s t e r n end o f t h e J o h n s t o n e S t r a i t f i s h e r y a p p e a r s near the v e r t i c a l a x i s . Salmon e n t e r f r o m t h e n o r t h w e s t .  55 Table  III.  S h o r t t e r m v e s s e l movements. The b i n o m i a l and c h i s q u a r e d s t a t i s t i c s were u s e d t o t e s t t h e h y p o t h e s i s t h a t e q u a l n u m b e r s o f b o a t s w e r e m o v i n g up a n d down t h e s t r a i t d u r i n g a flight. C r i t i c a l c h i s q u a r e ( a = 0.05) = 3.84.  2 X  NOT  SIGNIFICANT SIGNIFICANT  (n>25) 9 13  BINOMIAL  (n<25) 6 18  56  >-  FLIGHT  Figure  14.  W i t h i n - o p e n i n g f l e e t movements. The p o s i t i o n s o f a c c e s s p o i n t s were c o n v e r t e d t o d i s t a n c e s from t h e l o w e r fishing boundary. T h i s graph i l l u s t r a t e s the average v e s s e l d i s t a n c e from the lower boundary d u r i n g d i f f e r e n t flights and o p e n i n g s . W i t h i n - o p e n i n g measurements a r e c o n n e c t e d by solid lines. Major boundary r e s t r i c t i o n s are noted.  57  subjective: regions  open s e t f i s h i n g  o f aggregation  Fishermen around with  during  currents.  and a n u l l  alternative  hypothesis  the  tidal  compared  hypothesis  cycle.  proportions of active  and  remained  tides  effort  numbers  o f maximum c a t c h e s  catches  obtained by i n d i v i d u a l  The  maximum  catches  i n Area  were  c a t c h was a n i m p o r t a n t  and f o r t y - t h r e e  s e t s were  a  o f 16 o p e n i n g s .  Nineteen  taken  by the largest  o f important activity  were  active  restrictions,  12 p o r t i o n o f t h e f i s h e r y  were  Bay t i d a l  l a g f o r the stages were  i n c l u d e d (0.82). different:  only  data  o f the tide). equal The  (0.47)  observed  68 maximum  w e r e made  o n t h e ebb  on t h e f l o o d . component  of the gross  recorded by observers percent  s e t p e r opening  correlated  with  d u r i n g an opening  obtained  be  oscillated  12 w e r e  boats  distinct  strategies  o f boats  f o r t h e ebb and f l o o d  hundred total  numbers  according to A l e r t  s o when w a i t i n g v e s s e l s were  120 maximum  and s t r u c t u r e t h e i r  i s that equal  f o r the Area  as  point.  p a t t e r n s may t h u s  13 was n o t i n c l u d e d d u e t o t h e t i m e  The  while  cycle  I n the absence  and ebbing  identified  as a s i n g l e  s h o u l d be supported:  Activities  forrising  subjectively  digitized  Activity  t h e ebb a n d t h e f l o o d .  the  (Area  and then  were  a r e aware o f t h e t i d a l  the changing  tides  areas  o f the t o t a l  (3.6 p e r c e n t  catch.  Four  f o r 12 v e s s e l s a n d v e s s e l c a t c h was  of the t o t a l  sets).  Discussion  The  Johnstone  process.  Line-ups  queue  l e n g t h s were  Strait were  fishery  indicative  distributed  cannot  be p e r c e i v e d as a random  of the s p a t i a l  contagiously.  heterogeneity  Large  scale  and r e p r e s e n t  rational  behavior  -- c l e a n u p t h e f i s h  the  central  portion of the fishery  and then  move t o w a r d s  all  fish  The s u p p o s i t i o n t h a t s h o r t  term  and the  movements  directional  cross.  fishing  were  present i n  the boundary  which  s e a r c h was r a n d o m was n o t  58 rejected This  most  result  may  proportion The  of  the be  time,  but  indicative  of mobile boats  negative  k  the of  the  (less  estimates  data  than  not  be  described  estimates  difficult  to  explain  indicative However, low  During  of  a very  this  effort  view  levels;  distribution. infinity  point-flight response  than  component.  presented  i n Chapter  Constraints activity  over  change w i t h  the  skill at  a minimum  freedom  of  skippers  are  respect  long  hours  and  o f making  level.  to  and  maximizing  tuning  range. that  The the  a p p l i c a t i o n of  forced  timing.  number).  the  The  included  line-up  k  Also,  may  these  by  the  line-up  estimates,  at  Poisson as  of  weekly  been  (zeros).  negative  results  the  have  points  Poisson  This  a  few,  new,  k  approaches  the  access  numerical  distributions  is  technology number  Also,  for s k i l l of  there  sets  large  requires In  of  their the  and  fishery  with  vessels defined  sets;  costs  are  extensive  local  knowledge  the  present  skippers  often  made d u r i n g  activities  fishermen  congested  position in line-ups  Young  i s always  that  Knowledgeable  targeted,  their  stated  fleet  t e c h n o l o g i c a l l y advanced  timing.  to m a i n t a i n  constant  overcrowding  effort.  strategy  produced  oldtimers  recent  tides i s hindered.  the  of  described  approaches  random b e h a v i o r  action for precise  with  by  than  i n d i v i d u a l s running  i n terms  small  binomial.  access  empirical d e s c r i p t i o n of  tidal  tide  constant  the  a negative  occurrence were  and  the  VI.  other  the  inexperienced produced  An  vague  by  of p o s s i b l e a l t e r n a t i v e  of unexploited  binomial  heterogeneous.  average).  some o f  effort,  distributions  less  on  negative  i n terms  some n e g a t i v e  ANOVA w e r e  the  e x p l a i n the  negative  faced  percent  by  of high  l a r g e number  these  The  (rather  periods  does not  20  indicated that  could  distributions.  certainly  uncertainty  distributions are  s e t was  --  a chance  opening that  the  rather  and  fishery,  set  timing  substitute hard  t r y to maximize an  maintained  work,  their than  equipment  catch fine  will  59 break  down o r t h a t  enough. entered  F i s h i n g expenses  catch w i l l  have p r o b a b l y  b e made  increased  i f one s e t s  as young  often  technocrats  the f i s h e r y .  The  results  heterogeneity and  an unexpected  align  illustrate  o f t h e system.  themselves  interference  the pervading  according  competition.  Fishermen t o these  spatial  and temporal  are cognitive of this perceptions.  patchiness  The r e s u l t i s  CHAPTER V COMPETITION AND  Rothschild fishing  effort  relationship  (1977) r e v i e w e d and discussed  SET STRATEGIES  the problems  the effects  between e x p l o i t a t i o n  a p p r o a c h was p r i m a r i l y t h e o r e t i c a l .  are  managed o n a c a t c h  CPUE-effort the  effort  The m a j o r i t y basis  dependent  abundance  relationships  o f the competitive  process  a n d a s s o c i a t e d measurement e r r o r s .  (1981) d i s c u s s e d  the effects  and concluded  o f world  of effort  and independent v a r i a b l e s ) i s c i r c u l a r .  quantification  upon t h e of effort. fisheries  and any argument b a s e d on  r e l a t i o n s h i p s ( w h e r e t h e same m e a s u r e  confronting fish  o f competition  measuring  r a t e s a n d common d e f i n i t i o n s  The  per unit  associated with  contributes to  Major  barriers  are estimation of  Walters  and Ludwig  o f measurement e r r o r s on a p p a r e n t that observation  e r r o r s may h a v e  curvilinear  extreme  effects. Salmon  seine  dimensional relatively from  fishermen,  however,  s c a l e and accurate small, perceptions  fishermen  c a n be a s s u r e d  Line-up  The can from  relationship  distribution  1)  that,  of fish  counts  are possible.  and r e a l i t y  l o c a t e d o n a one Observation  c a n be compared  errors are  and c o o p e r a t i o n  and tested.  and E f f o r t  between average  be summarized by t h r e e the evidence  can be v i s u a l l y  Levels  a n d maximum q u e u e  alternative  hypotheses  due t o i n f o r m a t i o n ,  i n a non-random  I n a system p o s s e s s i n g  (Figure  skippers  and e f f o r t  15) w h i c h  respond  proceed  to the  fashion.  a n u n l i m i t e d number  60  lengths  of equally desirable  61  i EFFORT (NO. OF BOATS)  Figure  15.  Queue r e s p o n s e h y p o t h e s e s . The p r e d i c t e d r e s p o n s e s o f a v e r a g e l i n e - u p l e n g t h t o s a l m o n d i s t r i b u t i o n s a r e shown. These p r e d i c t i o n s a r e based upon the assumption that i n f o r m a t i o n i s good. 1) A n u n l i m i t e d number o f e q u a l l y desirable access points. 2) A l i m i t e d number o f e q u a l l y desirable access points. 3) A d i s t r i b u t i o n o f desirabilities.  62 access  p o i n t s , the r e l a t i o n s h i p  straight  line  maximum  2)  are a limited  linear,  increasing  maximum  line-up will  A distribution times  (which  points) w i l l that  number  f o l l o w t h e same  hypothesis  1 ) , b u t may  ( 3 ) was  illustrate supported  i s presented  assume  to exceptional catches. occurred  concerning  o f salmon  c a t c h among  cannot  waiting  access  curve  provided  d e s c r i b e d by  approach  that of  of hypothesis  The  distribution  i n c o r p o r a t i n g random o r for a distribution  uniform  of potential  i n a following section.  responses  schools  and the  restrictive  the c h a r a c t e r i s t i c s  evidence  stated that  information  a  densities.  and models  Fishermen  as t h e y  with  the s i t u a t i o n form  The  boat.  o r dome s h a p e d  the l i n e - u p data.  Further  t o one.  observed  available  t h e skew d o e s n o t a p p r o a c h  16-19  one  of a  trend.  coupled  a saturating  high vessel  equal  equal  s h o u l d be  equalize the t o t a l  were r e j e c t e d .  confirmed  also  the form  of equally desirable spots,  2); the q u a l i t a t i v e  hypothesis  term  will  relationship  produce  possess  and i n t e r c e p t  hypothesis  Figures  catches  zero  of d e s i r a b i l i t i e s  2) a t e x t r e m e l y  behavior  slope  l i n e - u p , o f course,  I f there  3)  with  should  the e x c e p t i o n a l l y long Observed  and r e p r e s e n t e d  a single  rapid  large set.  to follow a similar  path  line-ups reflected aggregations  short  were  dissemination of  The s k i p p e r s e x p e c t e d on t h e n e x t  tide  the b i g  (see Figure  17). Within-season available queuing  boundary  surface area.  behavior  changes produced  These m a n i p u l a t i o n s  (measured  as t h e average  severe  restrictions  apparently  d i d not  o f the affect  l i n e - u p l e n g t h ) , c o n s i d e r i n g the  63  to O CL CO CO UJ  2.25 r  CO  2.00 h  o o < o  CO  u. o  O  1.75  ooo  CD  .  9  0_ i  1.50  CO  UJ  UJ  C5 <  o  1.25  Q  •  or UJ  > <  1.00"  75  150  225  EFFORT (NO. OF  Figure  16.  300  375  BOATS)  Average l i n e - u p length vs. e f f o r t . The f i l l e d c i r c l e s r e p r e s e n t major boundary r e s t r i c t i o n s and the open c i r c l e s r e p r e s e n t d a t a r e c o r d e d when o n l y m i n o r b o u n d a r i e s w e r e i n effect.  64  O 0_ CO CO bJ O O <  I3i  CO I—  < o m  u.  10  o  o  o  oo ZD i Lu  oo o  oooo o  o« o  X  <  mm _L  75  150  225  300  375  EFFORT (NO. OF BOATS)  Figure  17.  Maximum l i n e - u p l e n g t h v s . e f f o r t . The f i l l e d c i r c l e s r e p r e s e n t major boundary r e s t r i c t i o n s and t h e open c i r c l e s r e p r e s e n t d a t a r e c o r d e d when o n l y m i n o r b o u n d a r i e s w e r e i n effect.  65  O QCO CO LU  tr  Q. — CO  o CD  2.5r  O d 5  2.2  0_ •  o°  •o  1.9  >o LU CO X  o <  LU CD LU CD <  1.6  •••  O  1.3  or  LU  75  150  225  E F F O R T ( N O . OF  Figure  18.  Average circles circles were i n  300  375  BOATS)  beach s e t line-up length vs. e f f o r t . The f i l l e d r e p r e s e n t major boundary r e s t r i c t i o n s and the open r e p r e s e n t d a t a r e c o r d e d when o n l y m i n o r b o u n d a r i e s effect.  66  o CL CO CO UJ  o o <  CO  \—  <t o  CD U.  o d z  CL => i UJ  2.25  r  l.90h  o o  1.55  O O  UJ CO UJ CL O UJ  0 ^ 0 °  o  •  o o  1.20  0.85  o <t or UJ  0.50  J_ 75  1  150  J_ 225  JL  300  375  E F F O R T ( N O . OF B O A T S )  Figure  19.  Average circles circles were i n  open s e t l i n e - u p l e n g t h v s . e f f o r t . The filled r e p r e s e n t major b o u n d a r y r e s t r i c t i o n s and t h e open r e p r e s e n t d a t a r e c o r d e d when o n l y m i n o r b o u n d a r i e s effect.  67 overlap  of points  The  saturating  different  the  of  At equilibrium a vessel  the other boats  sharing  relative  The  m i n u s h i s own  n  closing The  i s t h e queue times,  total  time  length,  the fishermens' line-up  presented  i n Table  IV.  towing  A  from  joined  in  the  and c l o s i n g  times  s k i p p e r b e g i n s h i s s e t as  on the b a s i s  f o r an  individual  of functional  data  as  11)  o f the l e t t i n g  go,  towing  the n e t and b r i n g  and  i t aboard.  given by  ( n - l ) S - P + S + P - nS  components  12)  f o r the observer data  E q u a t i o n 11  from  1980-1981  on queue  are  becomes  (n-l)21.3-13.1  d a t a on w a i t i n g times  o f w a i t i n g time  go,  calculated  i s demonstrated  The w a i t i n g time  taken to purse  W =  also  (n-l)S-P  to set i s therefore  o f the time  were  has not r e c e n t l y  p u r s i n g time.  S i s t h e sum  P i s the time  Estimates  regression  a boat  calculated  ST =  Observer  were  T h e maximum  o p e r a t i o n o f a queue  to purse.  a s p o t c a n be  per boat  f o r the l e t t i n g  W =  where  reflected  profitability.  sets  (i.e.,  only waits  the p r e c e d i n g boat begins boat  set line-ups  and average  distributions.  20.  line-up),  beach  s e t and open s e t c u r v e s  at 8 or 9 boats.  set effort  line-up  Figure  o f the beach  concerning their  saturated  Total  16-19.  portions  and the l a r g e r  perceptions quickly  i n Figures  are p l o t t e d  13)  i n F i g u r e 21.  length produced  The  linear  the equation  W = 29n-33  n>l  14)  W = 0  n-1  14)  68  O  WAITING T I M E FOR BOAT  1  2 3  ^  4  ^ o 1  BOAT ^  LETTING  o o  Figure  20.  NUMBER  GO  TOW CLOSE PURSE  O p e r a t i o n o f a queue. The s e t components a n d w a i t i n g times w i t h i n a queue a r e i l l u s t r a t e d f o r a n e q u i l i b r i u m s i t u a t i o n ( i . e . , a v e s s e l has n o t r e c e n t l y entered the l i n e - u p ) . Note t h e o v e r l a p b e t w e e n t h e p u r s i n g a n d l e t t i n g go c o m p o n e n t s .  69  Table  IV. S e t time components. a purse seine s e t .  VARIABLE  N  shoot tow  (s) (t)  472 474  close s+t+c purse  (c)  476 472 476  total  set  467  Observer  measurements  MEAN  3..303 12..77 5..164 21..28 13..09 34..38  f o r the  components  a  0..9271 4..471 2,.358 5,.862 6..000 9 .007  70  275 r  0  2  4  6  L I N E - U P (NO. OF  Figure  21.  8  10  BOATS)  W a i t i n g t i m e s as a f u n c t i o n o f queue l e n g t h . Both the f u n c t i o n a l m o d e l d e r i v e d f r o m t h e o p e r a t i o n o f a queue and the s t a t i s t i c a l model p r o v i d e d by l e a s t s q u a r e s r e g r e s s i o n are presented here.  71 w h i c h was h i g h l y s i g n i f i c a n t  (p<0.0001, R=0.97).  13) a n d s t a t i s t i c a l  (equation  21.  between those  The d i f f e r e n c e  caution.  Skippers  The given  number  14) p r e d i c t i o n s a r e a l s o  sacrificed  o f sets performed  i n Figure  as they  avoided  by an i n d i v i d u a l  boat  nets. participating  i na  line-up length i s  where T i s t h e t o t a l  fishing  = T/(S+P+W) time.  15)  The average  time  f o r a s e t g i v e n an  level i s  TS =  where  E i s t h e number  total  s e t time  estimated equal  compared  (equation  p r e d i c t i o n s c a n be e x p l a i n e d b y s k i p p e r s '  efficiency  Sb  effort  The f u n c t i o n a l  E ( Z (S i=l  s e t time  where A i s t h e t o t a l i and  number  ))/E  16)  maximum n u m b e r  of fishing  the  line-up distributions,  Table  A A Z n ^ / Z n i=l i=l  o f access  hours  S^ i s t h e  I f ES^/E i s  IV ( a n d w a i t i n g t i m e s a r e  equation  16 b e c o m e s  17)  L  p o i n t s , n^ i s the l i n e - u p length a t  from  equation  recorded  the average  i n the fishery,  f o r vessel i .  ( S t ) from  i s estimated  the  number  14.  Using  f o r a 48 h o u r  e q u a t i o n 17, opening  o f sets per boat  (T) and  was  as  Sb  (Figure  i  queue l e n g t h s )  TS = S t +  estimated  W  a n d Wj_ i s t h e w a i t i n g t i m e  as t h e average  point  +  of vessels participating  w i t h i n and between equal  access  i  22).  The t o t a l  number  = T/TS  of sets  18)  f o r the f l e e t  was e s t i m a t e d  a s ESb  72 (Figure  23).  absolute  set effort  competition per  boat.  per  boat  The s k i p p e r s '  at high  overcrowding; open  as a f u n c t i o n  between boats The f l i p  vessel  vessels  interference of  i n t h e number  of  a change i n s t r a t e g y  to regions  o f low l i n e - u p s  sets sets  due t o  a n d made  sets.  The  logbook data  or t i e up).  data per  increasing  a v e r a g e number  the increase  represents  offshore  an  density,' b u t intense  i n a decreasing  (i.e.,  densities)  moved  mechanisms p r o d u c e d  o f boat  resulted  i n the curve  Effects  set  spacing  length  included  on C a t c h p e r S e t  i n t e r v a l s and s e t s t r a t e g i e s  section presents  the e f f e c t s o f s e t strategy  The l o g b o o k s were  reflects  line-up  The f o l l o w i n g  and explores set.  o f Set Strategies  catch  structured  analyses  of this  and l i n e - u p  to test  p e r s e t a n d 2) o p e n s e t s  logbook  length  two h y p o t h e s e s :  (open  on  1)  are less desirable  catch  line-up than t i e  ups. Fishermen recorded Since  very  intervals  few queues were were u s e d  unbalanced extremely  data  boat  queue  array  (i.e.,  natural  a l l boats  o f a low f r e q u e n c y  range,  over  e x i s t i n g U.B.C.  o f empty c e l l s  deviations  o f the deviations  two  line-up  plus  1.0  The  t o be  software.  e n t a i l e d a one-way  (the boat  strategies)  as standard  only  a l l weeks) p r o v e d  effect  ANOVA  included  a n d a t h r e e - w a y ANOVA f o r  week a n d i n t e r a c t i o n e f f e c t s .  expressed  logarithm  i n t e r v a l s i n logbooks.  ( 1 - 2 a n d 3-5 b o a t s ) .  f o r week e f f e c t s  and s e t type  s e t type,  were  i n t h e 6-10  f o r analysis with  i n line-up  length,  32 v e s s e l s The  observed  effects standardized  differences  p e r s e t and l i n e - u p  i n t h e f o l l o w i n g ANOVA  cumbersome  Maintenance for  catches  from  Catches  per set f o r  the weekly  means.  produced normality.  Due  73  50 r  45 40 o  CO  35  to hUJ  to  9 ? °  «  o CO  30 0  <  DC  25  UJ  > <  o  oo  o o o ^ 75  o  O . Q ? 0  o  20 15  o  8  0  <s>  o  150  225  300  375  E F F O R T (NO. OF BOATS)  Figure  22.  A v e r a g e number o f s e t s p e r b o a t v s . e f f o r t . T h e number o f s e t s was c a l c u l a t e d f r o m t h e l i n e - u p d i s t r i b u t i o n s , t h e measured s e t time components and a p r e d i c t i v e r e g r e s s i o n e q u a t i o n f o r w a i t i n g times as f u n c t i o n o f l i n e - u p l e n g t h .  74  I300CV  to  o o o o o  9000  LU CO  o  OQO  5000  ° 1000  Figure  23.  CX 75  Oo 150 225 EFFORT (NO. OF BOATS)  300  375  Total set e f f o r t vs. effort. T h e number o f s e t s was c a l c u l a t e d from the l i n e - u p d i s t r i b u t i o n s , the measured s e t time components and a p r e d i c t i v e r e g r e s s i o n e q u a t i o n f o r w a i t i n g t i m e s as f u n c t i o n o f l i n e - u p l e n g t h .  to  the large  effects  were  variance  were  of levels,  significant  the variances  natural  logarithms  among b o a t s was  variance values  i n the a n a l y s i s .  indicated that  were  similar  5.3  o f the (Table  o f the catches per s e t plus  t o t h e s e t t y p e - l i n e - u p - w e e k ANOVA included  were h e t e r o g e n e o u s .  (p<0.0001) a n d t h e p e r c e n t a g e  attributed to differences  The input  number  Although  (Table  total V).  c o n s t i t u t e d the  V I ) : twenty-eight  vessels  the t e s t f o r homogeneity o f  the s e t type variances  ( 3 . 5 a n d 2.6)  1.0  Boat  a n d i t was  were d i f f e r e n t , t h e a c t u a l  assumed t h a t  the analysis  was  robust. Set  t y p e s were  predicted fish  means p l u s  o r minus t h e i r  standard  p e r s e t f o r t h e t i e ups and open s e t s ,  temporal values the  d i f f e r e n t (p<0.003), b u t t h e r a n g e s  and s p a t i a l  was  negligible.  difference  effects: medium  variability Queue  i n predicted  the short  (p=0.0) a s t h e s a l m o n  40-45  beach  sets  The  relative  ranks  The  means o f c a t c h  weekly  a n d 28-29  Considering  e f f e c t s , the d i f f e r e n c e  the  i n mean  d i f f e r e n t (p<0.00001) a n d  i n d i c a t i v e o f d e f i n i t e economic  mean was  per set.  27-28  Weeks,  salmon p e r s e t and the of course,  were d i f f e r e n t  and ebbed.  i n t e r a c t i o n was  present  t h e d a t a means:  open s e t s  queues;  32-36  ( p < 0 . 0 4 ) a n d may were  s e t t y p e s were e q u a l l y  be  l e s s p r o f i t a b l e than p r o f i t a b l e i n long  s e t type-week i n t e r a c t i o n r e f l e c t e d t h e f l u c t u a t i o n i n the o f open s e t s  analysis  fishermen's  from  made i n s h o r t  queues.  fish  run increased  A set type-line-up simply  means was  were  respectively.  i n t e r v a l s were a l s o  queue, p r e d i c t e d  q u e u e mean was  interpreted  and s k i l l  errors  o f the transformed  indicated  rates  decisions  a n d t i e u p s among w e e k s significant  d i f f e r e n c e s between  per s e t , but the important are the r a t i o s o f s e t type  r a t i o s were w e i g h t e d b y  their  (p<0.003).  variance  geometric  measurements f o r or line-up  catches.  and an average weighted  The ratio  76 Table  V.  SOURCE boat residual total  One-way ANOVA data.  DF 31 6443 6474  f o rvessel effects  SS 136.13 2325.2 2461.3  MS 4.3913 0.36089  on c a t c h  F-RATIO 12.168  p e r s e t i n the logbook  PROBABILITY 0.0000  77 Table  V I . S e t t y p e - l i n e - u p - w e e k ANOVA f o r 28 v e s s e l s f r o m t h e l o g b o o k d a t a , showing the e f f e c t s o f s t r a t e g y (open v e r s u s t i e - u p ) , l i n e - u p l e n g t h a n d week o f s e a s o n o n c a t c h e s p e r s e t .  SOURCE set line-up  DF 1 1  week 13 set-line-up 1 set-week 12 line-up-week 12 set-line-up-week 10 residual 4448 total 4498  SS  MS  19.650 96.614  19.650 96.614  2738.9 9.5900 64.069 25.010 19.009 9336.0 12360.  210.68 9.5900 5.3391 2.0841 1.9009 2.0989  HOMOGENEITY OF FACTOR set l i n e up week  BARTLETT  X  z  31.973 0.03404 163.78  F-RATIO  PROBABILITY  9.3621 46.030 100.38 4.5690 2.5438 0.99296 0.90566  0.00223 0.00000 0.0 0.03261 0.00238 0.45270 0.52684  VARIANCE  PROB.  DF  LAYARD  0.00000 0.85361 0.00000  1 1 13  40.503 0.04477 182.95  X2  PROB. 0.00000 0.83243 0.00000  78 for  the  s e a s o n was  c a l c u l a t e d f o r each  2 Sr^Ri  where (X^,  Sr^,  Sx^  Y^),  and  Sy^  are  =  the  S  2 _2 /X  X i  N Z Ri/Sri i-1  =  Sr  i s the  Category-week  combinations  rationale for this  the  number  of  information.  and  the  tie  up  was  are  the  The This  very  medium  data  the  ratio  (R^)  and  the  means  with  may  set  and set  the to  to  small  low  were m u l t i p l i e d by from  the  the  The  average  set  sales  type  was  day  than  set  20  VII.  to  the The  ratio  the  very  fluctuation:  In  the  0.844, was  smaller  long of  the  term  sets  the  small  line-up  f o r the  set  averages  made d u r i n g  medium  small  than  little  represented  a very  1.6  discarded.  Obviously,  number  most h i g h l y  variance.  were  samples  contained  i n Table  repeated  slips. was  for catch  value  per  categories  category,  the  difference.  open  set  category.  values:  set  catches  piece  ( f o r each  Twenty-eight vessels not  significant  a  line-up  economic d i f f e r e n c e .  seasonal  effect  that  mean r a t i o  F i s h e r m e n work on  of  significant  1981  in a  i s only  line-up  i s the  was  line-up.  open s e t  21)  sizes less  compared  represented.  indicated a  represented.  sample  explain part  under  Sr^  division  small  analysis of variance  calculated  and  fluctuate.  are  20)  Z 1.0/Srj; i=l  ratio  hoc  are  effects  line-up  result  ad  /  summarized  f o r beach  The  of  19)  L  2 Z 1.0/Sri i-1  The  fact  open  1.0  /  a vessel  samples here This  ratio  _2  yi  i +  combination  N  s e t s made b y  line-up  week.  =  2  mean w e i g h t e d  The  and  2  line-up  r e s p e c t i v e l y , i n week i ;  R  type  type  S /Y  variances  2  where R  set  species)  were  (p<0.1) and  the  79 line-ups  a n d weeks were  means w e r e The  86-91 a n d 139-161  s e t type-line-up,  t h e model  introduction.  The  within variance i n data  high  i s a possibility  of line-up  recordings;  boats  significance fact,  lied  about  o r low catches  individual  In  There  the use o f deceptive  catagories 1 suspect  not usually exhibit statistical  systematically all  f o r t h e l o w a n d medium  (p>0.1) b u t t h e s e t t y p e - w e e k  describing  the  should  with  only  the r e l a t i v e  Observer  catch  were  rate  standardized a large  a  line-ups, respectively.  interaction  records  contributed  by rank  Only  that  data  to line-up  catches  correlation  season might have produced  category), should  vessels  statistical  by the e f f e c t .  differences  explained  o f the seven boats  (i.e.,  o n e - w a y ANOVAS f o r  explained  boats  intervals  exhibit  significant  forindividual  was 8.4.  and d i s c r e t e possessed  a  line-up slight  a n d two o f t h e r e l a t i o n s h i p s w e r e  procedures.  different  lies.  I f the skippers  f o r line-up  o f the variance  length  contain  forindividual  significance.  possessed  three  was r e v i e w e d i n  was i n c r e a s e d b y t h e u s e o f  amount o f t h e v a r i a n c e  o f catches  analyzed.  the logbooks  f o r week e f f e c t s  5 o f t h e 27 v e s s e l s  response  significant  o f the geometric  information  that  i n t h e medium l i n e - u p  ( p < 0 . 0 5 ) a n d t h e maximum p e r c e n t  lengths  The r a n g e s  (p<0.01).  Literature  intervals  (p<0.00001).  line-up-week and s e t type-line-up-week i n t e r a c t i o n s  were n o t s i g n i f i c a n t to  different  Larger  sample  sizes  throughout  results.  Discussion  The catch to  hypothesis  rates  fishermen  and to w a i t i n g  s e t catch  restricted  that  rates.  the t o t a l  to a d i s t r i b u t i o n  t i m e s was s u p p o r t e d .  Interference catch  respond  competition  Line-ups i n the form  a v a i l a b l e a t an access  point.  of potential  were  a  response  of waiting  times  The dynamics o f  80 Table  VII.  Average w e i g h t e d r a t i o s f o r s e t type and l i n e - u p c a t c h e s . The w e e k l y r a t i o s o f t h e a v e r a g e c a t c h e s p e r s e t f o r s e t t y p e and l i n e - u p c a t e g o r i e s were w e i g h t e d b y t h e i r variances.  R Mean R a t i o T i e U p / O p e n S e t (Low L i n e - u p ) T i e Up/Open S e t (Medium L i n e - u p ) Medium L i n e - u p / L o w L i n e - u p (Open S e t ) M e d i u m L i n e - u p / L o w L i n e - u p ( T i e Up)  Sr Mean V a r i a n c e z  N  0.844  0.0072  615:3238  1.191 1.601 0.804  0.0060 0.0001 0.0097  144:427 427:3238 144:615  81 t h e f l e e t was d i c t a t e d b y t h e s e f a c t o r s i n t h e p r e s e n c e o f g o o d and p r o d u c e d i n t e n s e  interference competition  e f f o r t increased i n s p i t e o f the competitive have v a r i e d with e f f o r t  among v e s s e l s .  Total set  effect, yetharvest  r a t e s must  i n a c u r v i l i n e a r f a s h i o n as v e s s e l s e n t e r e d  d e s i r a b l e areas.  I t must be emphasized t h a t t h e l i n e - u p s  p o t e n t i a l catches  only.  as s u b j e c t i v e a v e r a g e s .  Skippers  less  reflected  The f i s h e r y i s a s t o c h a s t i c system w h i c h  view i n terms o f d e t e r m i n i s t i c p o t e n t i a l s . expectations  information  described  fishermen  their  Indeed, "average" impregnated  their  rhetoric. Past large scale aggregative  responses to the Johnstone S t r a i t f i s h e r y  were a l s o c o r r e l a t e d w i t h c a t c h r a t e s ( H i l b o r n and L e d b e t t e r i n p u t was l a r g e r e l a t i v e t o t h e v a l u e r e t u r n e d situation.  H i l b o r n and Ledbetter  1979) and t h i s  i n the competitive  a t t r i b u t e d t h i s fact to area  specific  d e s i r a b i l i t y , b u t fishermen e x p l a i n e d t h a t a major t r a d e o f f occurs J u a n de F u c a f i s h e r y i s o p e n . boats;  T h e J u a n de F u c a f i s h e r y r e q u i r e s  when t h e  large  t h e e x a g g e r a t e d r e s p o n s e t o t h e J o h n s t o n e S t r a i t f i s h e r y may  from the immobility  o f small boats.  A s new b o a t s a r e b u i l t  i n the future,  s k i p p e r s may o p t f o r t h e l u c r a t i v e J u a n de F u c a f i s h e r y a n d w i l l subside  result  competition  i nJohnstone S t r a i t , unless a l a r g e r proportion o f Fraser  salmon a r e d i v e r t e d by temperature regimes t o the i n s i d e passage.  (A l a r g e  p r o p o r t i o n o f t h e s a l m o n w i l l e n t e r t h e s t r a i t when t h e w a t e r i s c o o l r e l a t i v e t o t e m p e r a t u r e s o f f the west c o a s t o f Vancouver The  Island.)  p r o p o r t i o n o f open s e t e f f o r t i n c r e a s e d w i t h the d e n s i t y o f  v e s s e l s as beach s e t access what t h e y c o n s i d e r e d  p o i n t s were s a t u r a t e d and s k i p p e r s  shifted to  t o be l e s s d e s i r a b l e o p e n s e t a r e a s ( F i g u r e 24) . The  Department o f F i s h e r i e s and Oceans has e x p r e s s e d c o n c e r n t h a t t h e r e c e n t running  l i n e and bowthruster innovations  (which improved open s e t f i s h i n g  c o n d i t i o n s ) c o n t r i b u t e d t o i n c r e a s e d e x p l o i t a t i o n r a t e s as f i s h e r m e n  82  0.5r  $  or o LU  0.4  o  UJ CO  0.3 -  or o o_ o or  0-  o  o  Q. O ^  o  'OO 0.2  o o o  ° 0.1  o  o  c9>  o  8o  gs> o o  o o  o  75  150  225  300  375  E F F O R T ( N O . OF B O A T S )  Figure  24.  P r o p o r t i o n o f open s e t e f f o r t v s . e f f o r t . O p e n s e t e f f o r t was d e f i n e d a s t h e number o f b o a t s m a k i n g s e t s away f r o m s h o r e . The A r e a 13 c l o s u r e d u r i n g t h e s e c o n d w e e k o f t h e s e a s o n i s n o t included here.  83 dispersed up  i n t o open water.  o r open s e t ( i n order  analysis: The  beach  running  this  line  close  beach  that  also  b e c a m e common w i t h  concluded  that  setdesirability  s e t types  were  categorized  an e i t h e r / o r question)  t o shore were  included  during  innovations.  s e t category. beach  may b e b a s e d  s e t s and  I t may b e  o f t h e open s e t s t r a t e g y  and t h a t  as t i e  confounded the  i n t h e open  a i dthe skipper these  the advent  increasing e x p l o i t a t i o n rates  the on  t o produce  and bowthruster  set strategy  tentatively to  sets  The f a c t  the fishermens'  contributed  perceptions  more o n t r a d i t i o n  of  and f o l k l o r e  than  fact. An  place from  increasing  i n the near  future  t h e open s e t s t r a t e g y  as fishermen  exploitation rates  bowthruster decreased harvest  harvest  innovations  as b o a t s  that  rate  The  sets  a constant  -- a c t i n g  have p r o b a b l y  pertain  statistical to this  founded.  the equally Logic  average  analysis  a wide  range  for Area  o f experience  indicated  that  explained  by the s k i l l  a n d queue  a very  small  lengths  the s t a t i s t i c a l  queue  desirable  length  gained  take derived  Concern  line  over  and the  l i n e - u p has  open s e t s t r a t e g y , t h e  maintains  through  f o r the least  o f fishermen  and s t r a t e g y  Also,  a  sample  constant  technology,  desirable provided  and to Area could  i n catch  fishermen  t i e ups. conclusions 12  n o t be  was r e p r e s e n t e d  obtained,  and the r e s u l t s p e r s e t was  traditional  o f the s e t type  effect  that  ( v e r y few  the c o r r e l a t i o n s o f catches  the fishermen's  representation  observations.  I f the average  A random  supported  information  o f the running  amount o f t h e v a r i a n c e  effect.  probably  technologies.  o f the logbook data  13).  will  d o e s n o t summon t h e c o r o l l a r y  on i n f o r m a t i o n  p a r t i c u l a r sample  recorded  many s k i p p e r s '  on l e s s modern  s u b s t i t u t e d open s e t s  were  tides  i s well  developed  abandon o u t d a t e d  and t h e r o l e s  rate has i n t e n s i f i e d .  conclusion  Only  towards  t r a d i t i o n s w h i c h were b a s e d  increasing  yet  trend  with  statements.  contradicted  CHAPTER V I MODELS OF THE F I S H I N G  Fishing involved  power h a s b e e n  attempts  distributions been 1944)  effort  these fish  that 1961;  operate  and f i s h i n g  The  catch  from  population q,  t  gear  where fish  and N  t  a  over  as t h e p r o p o r t i o n  i s the area  population  t  usually  1940,  of fish i s  area  and that  A direct  consequence o f  to distribution  d e n s i t i e s (Paloheimo  chapters  and p r e v i o u s (Gulland  units  changes o f and D i c k i e  publications  1964;  Calkins  a t i m e p e r i o d may b e r e p r e s e n t e d  = qN  r e s p e c t i v e l y , over  of technological  r  1982).  t h e random model  a r e the average  and, i f t h e assumptions  absence  (CPUE) h a v e  But  1918; R i c k e r  the population  the previous  per unit effort  size,  i s defined  studies  the population  population  from  These  1970).  catch  (C/E)  (Baranov  are insensitive  (C/E)  where  per unit effort  (see Seber  a t given  i n the past.  and c a t c h a b i l i t y .  that  over  i s t h a t models units  times  equations  independently  often departs  Williams  and c a t c h  or uniformly  I t i s evident  fishing  effort  the assumptions  randomly  assumptions  1964).  fish  The c l a s s i c  a r e b a s e d upon  distributed of  to standardize  of effort,  ignored.  e x a m i n e d many  PROCESS  22)  t  catch time  per unit effort t.  o f the f i s h  described  above  and the average  The c a t c h a b i l i t y population are valid,  coefficient,  t a k e n b y one u n i t o f i s constant  i n the  changes.  swept b y one u n i t o f g e a r ,  present  by  i n a  r  C  r  i s the f r a c t i o n  c a u g h t b y one u n i t o f g e a r ,  84  and A  r  o f the  i s the  85 area  occupied  by the t o t a l  Paloheimo demonstrated sizes  that  (radii)  population  and D i c k i e  a n d t h e numbers  heterogeneity area  swept  (a ).  the  distribution  temperatures.  their of  Allen  model  the Inter-American  (1975) the  recognized  rates  Tropical  standardization gear  affects  should  abundance have  o f tuna  purse  the c a t c h a b i l i t y  s t u d i e s have increases  demonstrated  effort.  forC  indicated that  relationship  that  sea surface  included the area) i n  and  Area  (CYRA)  Psaropulos  effects  i n their  Competition  method o f  between  The i n t e n s i t y  of  within  units of  competition  and a .  r  r  catchability  (Peterman and Steer  this  Pella  r  indicating  the p o p u l a t i o n  those  coefficient.  i n the values  (1984)  (C ) i n  of population heterogeneities  include  seine  the t o t a l  caught  i n the Y e l l o w f i n Regulatory  the possible effects  be r e f l e c t e d  Many  within  school  distributed,  i s correlated with  Tuna Commission.  CYRA, b u t d i d n o t e x p l i c i t l y  analytically  Although  evidence  and Punsly  heterogeneity  f o r catch  schools.  (1970) p r e s e n t e d  (1977) and A l l e n  (i.e.,  and  a f f e c t e d the proportion  o f s c h o o l i n g s k i p j a c k tuna  effect  linear  within  model  1964).  q, i s d e p e n d e n t u p o n  t o be u n i f o r m l y  schools  Williams  r  and D i c k i e  a search  coefficient,  of fish  was a s s u m e d  i n the f i s h  the  (Paloheimo  (1964) d e v e l o p e d  the c a t c h a b i l i t y  of schools  temperature  population  d e c l i n e s as  1981; C r e c c o  using  t h e power  and Savoy  fish 1985) a n d  function  R+1 C/E where and  C i s the catch  for a fleet,  B are coefficients  abundance regression  If  on l o g a r i t h m s .  there  23)  E i s the e f f o r t , -1.  N i s fish  The a u t h o r s  The l o g a r i t h m random  o f measurement  v a r i a b l e with  i n estimation  abundance,  acknowledged that  e r r o r and, t h e r e f o r e , u s e d  distributed  i s a bias  air  and 0 > B >  was m e a s u r e d w i t h  t o be a n o r m a l l y  =  mean  a geometric e r r o r was  a  fish  mean assumed  zero.  o f N and the magnitude  of this  bias  86 changes with  N, t h e e f f e c t  o fthese  e r r o r s may b e r e p r e s e n t e d b y  ~ , . B' +1 v N = a'N e T  where v i s a n o r m a l l y (i.e.,  abundance  d i s t r i b u t e d random v a r i a b l e w i t h  i s i n c r e a s i n g l y overestimated  mean z e r o  a n d B' > 0  as i t increases).  Rearranging,  N  If  - (l/a'}  (  B  '  +  1  N " '  )  (  B  / B  '  C/E = qN a n d t h e e x p r e s s i o n  estimated  B obtained  negative of  /  and greater  the error  + 1 )  -1.  B  +1  e  above  by f i t t i n g than  ( ' )/(B'+D - v / ( B » + l )  +  i s s u b s t i t u t e d f o r N, t h e n t h e  equation  2 3 ) t o C/E a n d N d a t a  Peterman e t a l . (1985) s t a t e d  term must b e a s c e r t a i n e d  before  hypothesis  w i l l be  that  t h e form  t e s t i n g can be  undertaken. Regardless coefficients behavior.  o fthe error  target  (measured  as the p r o p o r t i o n  the  increases  relative  relative changes  plus  size  population  decreases,  invulnerable i n the s p a t i a l  t oe f f o r t  as f i s h  abundance  distribution  an increase could  fish/fisherman Studies the  o f the f i s h  changes  fisheries,  dependent  upon v u l n e r a b l e  invoking  i n the depth  abundance  only  as the stock  to vulnerable  Arguments  density  catchability  c a n n o t b e r i g o r o u s l y a t t r i b u t e d t o non-random  F i s h i n g gear  gear)  structure,  create  distribution  o ff i s h i n g  production  within  o ff i s h d i s t r i b u t i o n s  I ndepth  catchability  power have u s u a l l y  measured  be depensatory.  o fthe f i s h  the volume  i s susceptible to  can be extended  of the f i s h .  o f CPUE d i s t r i b u t i o n s .  that  I f vulnerability  catchability  will  scale  changes  i n t h e mean d e p t h depensatory  fish  fish.  fisherman  to include  regulated  with  increasing  independently  o fthe j o i n t  that  c a n b e swept.  ignored  the mechanics  Bannerot  and A u s t i n  (1983)  underlying assumed  87 that the  these  distributions  distributions  parameter, However, between  k,  of  they the  to  are  the  the  unit  related  is correlated  explicit effort  relationship  and  ( e q u a t i o n 23).  binomial  i n c l u d e an  mean c a t c h p e r This  binomial  power model  negative  d i d not  distribution.  negative  showed  with  fish  of  the v a r i a n c e  determines  the  skewness  They  examination  and  the  the of  dynamics  that  of  the  abundance.  relationships  the  o f k,  as w i l l  be  shown b e l o w . Traditional (Beverton behavior  and  the  for  a  Holt  or most  overlap). and  models have  i n c l u d e d the  1957), b u t  forms  have not  of competition  t r u n c a t e d form  the  potential  exploitation  rates for vulnerable fish.  regarding theory  allocation  data  derivation  Two  based  assumption  derived  from  by  to  fish  CPUE  a  use  set of  the  and  leads  to  patch  the  catches  and  sizes)  parameters patch)  estimates  given  dispersion,  of  assumed  hypotheses  within v e s s e l aggregations,  anecdotes  models  concerning  models  this  are  can  be  provide fleet  formulated. a  solid  behavior,  in this  distributions  good  and  assumptions  Both models gear  chapter.  and  the  a  The  framework f o r salmon  and  The  first  second  to  catch  model  i t s p a r a m e t e r s were  i n c l u d e d the  competition.  The  behavioral  information pertaining  information rationally.  statistical  fishermen  presented  effort  possess  CPUE d i s t r i b u t i o n s .  and  known,  Furthermore,  recorded  upon measured  and  are  (or f i s h  search  distributions.  that fishermen  opportunities  fits  of r e a l i s t i c and  rates  o f CPUE d i s t r i b u t i o n s  and  distributional  m o d e l was  the  generation analyses  distributions  of v a r i a b l e  i n t e r f e r e n c e or  (or v u l n e r a b l e f i s h  This procedure  for vessel aggregation  f o r the  previous the  the  catch  catch  can  rules  estimated.  stock depletion  (e.g.,  aggregation  distribution  decision  be  of  reflect  and  of  r e p r e s e n t e d n o n - r a n d o m human  of v e s s e l competition  I f v e s s e l aggregations  dynamics  effects  distributions  Responses  of  was found of  exploitation  88 rates sets  to fishing  vessel  abundance,  only,  were  examined.  Complimentary  f o r f l u c t u a t i n g salmon abundance on a s i m i l a r time  scale  data  were n o t  available.  The  Data presented fleet  rationally  points queue of  relative  i n Chapters  line-ups  usually  seasons.  points  acquired  vessels  preceding  were  that  rates  their for  that  (i.e.,  mean c a t c h Although  (Profitability, catch  rates  and  detection  fishing  openings  access  entrant  boats  v u l n e r a b i l i t y and  per access  of variance  point.)  The  as an i n t r o d u c t i o n  o f s e t type  to the  rates  were  similar.  sets  do n o t e n t e r  taken  o r because  i n similarly  f o r t h e same l i n e - u p  should  t i e u p s , t h e ANOVA  i f fishermen  s i z e d queues  view  as a f u n c t i o n o f  t h e y want  expect  i n t e r v a l s should  significant  although  open s e t areas because  i n t h e b i g s e t ) we  t h e ANOVA p r o d u c e d  However,  o f o p e n a n d t i e up s e t s p o t s  they  and l i n e - u p  information:  are l e s s p r o f i t a b l e than  a r e r e p e l l e d by crowds  of bringing  t i e ups and open  Therefore,  of previous  access  increased,  t h e most d e s i r a b l e  i s expanded h e r e  open s e t s  desirabilities  spirits  chance  that the  the d e r i v a t i o n o f an e x p l o i t a t i o n model.  the catch  alone  independent  rates.  i n t e r p r e t e d as i n d i c a t i v e o f i m p e r f e c t  indicated  relative  that  as e f f o r t  and, a s queues became l o n g ,  as t h e t o t a l  r e s u l t s o f the analysis  stated  catch  initially  section  underlying  fishermen  the  I t i s probable  are defined  discussion  assumptions  the hypothesis  fashion  was n o t i n d e p e n d e n t  to less p r o f i t a b l e spots.  desirability  effects  i n a non-random  desirabilities  fishing  The  IV a n d V s u p p o r t  r e f l e c t e d mean s e t c a t c h  and/or  dispersed  Model  e x p l o i t s a d i s t r i b u t i o n o f salmon v u l n e r a b i l i t i e s ;  developed lengths  Overflight  their  t o maximize  the catch  rates  t o be equal;  the  be s i m i l a r .  d i f f e r e n c e s between  s e t types,  the  89 geometric  means w e r e v e r y  were  similar.  also  average  points fleet  i n a broad  information.  ANOVA  f o rcatch  interactions; tentatively  set  These  among m i x t u r e s  pieces three  this  that  good  the  ANOVA b a s e d  First,  contributed  measured  line-up.  open  s e t access  the fishermen possessed and  these  of fish  exhibited  i n t e r a c t i o n s were  size effects.  However, when c a t c h  the s e t type-line-up,  i n this  valued  to the within  on monetary values  representation  they  line-up-week and Also,  could  (pinks  different.  and sockeye) the  allocate their  categories variance  were  of that  indicated,  grouped  variable.  the linear  was n o t e x a c t  into intervals  (i.e.,  o f t h e r e l a t i o n s h i p s between dependent and  was l a r g e l y d u e t o s a l m o n m i g r a t i o n  points tides  queues,  t a l k i n terms  periods  a t spots  f o r catch  t h e m o d e l was n o t a  individual  behavior,  Second, as  model  Third,  schooling  effort  p r e d i c t i o n e r r o r was p r o d u c e d b y  independent v a r i a b l e s ) . access  the line-up  species.  The l a r g e  of fish  fishery  rates  f o r t h e s e t t y p e - l i n e - u p - w e e k ANOVA ( i n  the line-up  as p i e c e s  mixed  information:  sets  T h e ANOVA r e s u l t s a n d  a n d s e t t y p e s were n o t s i g n i f i c a n t l y  o f s a l m o n ) was l a r g e .  perfect  as p i e c e s  r e s i d u a l sum o f s q u a r e s  and  rates  measured discussion  of dissimilarly  factors.  t i e up  i n t e r a c t i o n s were n o t s i g n i f i c a n t .  results indicate  fishermen possessed  t i e ups.  that  as monetary v a l u e s ,  was s i g n i f i c a n t  The  rates  i n the previous  type-line-up-week  effect  the average  indicate  a t t r i b u t e d t o sample  were computed  than  t h e f i s h e r m e n were c o r r e c t :  responses  good  r a t i o s f o r t i e up/open  18 a n d 19 shows t h a t t h e  l e s s p r o f i t a b l e than  distributional  The  was s m a l l e r  sense,  are generally  utilized  The w e i g h t e d  Comparison o f Figures  open s e t l i n e - u p  Perhaps,  close.  the v a r i a b i l i t y  and other,  o f averages  characterized  i n s e t catches a t  "random" f a c t o r s .  and o f t e n  Since  make many s e t s  by f l u c t u a t i n g catch  rates,  r a t e s and skippers  over  form  extended  the v a r i a b i l i t y  90 and  resulting  sizes  overlap  i s probably Based upon  overflight  1)  ignored  presented  total  information  a t access  points  be able  the  distribution  the  same l i n e - u p s , b u t t h e y  for  any queue.  o f these  Given  a better  profitable  definition operating  catches  reflection  sites  first  times  costs.  p e r v e s s e l minus of entering  i s relatively  the f u e l  waiting  cost  times  may  queues o r  participating i n  than  rationally:  high,  to less  per boat  this  assumption  the traditional  value  that  profitable  will  i s larger, y e t value  with  access  25).  This  a response to  skippers  per vessel  a two b o a t  associated with  e x p l o i t the  intensifies  (see Figure  operating  a skipper  are shorter).  skippers  r e c e i v e bonuses based  i t i s assumed  value  to  of reality  Many f i s h e r m e n  Therefore,  value  They  within  analyses,  does n o t i n c l u d e  catch  catch  data  are shorter  p e r v e s s e l o r mean c a t c h  where  among b o a t s  move  catch  cost  the f i s h e r y .  and, as c o m p e t i t i o n  they  of rationality  instead  the distribution  c a n p r e d i c t t h e mean c a t c h  information  waiting  production.  example,  within  the previous  v e s s e l entry,  where  model  assertion.  Fishermen use t h e i r  points  concerning  t o p r e d i c t the v a r i a b l e s e t catches  "random b e h a v i o r "  increasing  This  assumptions.  catches  probably  a n d queue  expectations.  a n e x p l o i t a t i o n m o d e l was c o n s t r u c t e d .  the f o l l o w i n g  most  term  sites  i n C h a p t e r s IV a n d V a n d u p o n t h e  not  is  among d i f f e r e n t  of long  Fishermen possess p e r f e c t of  2)  rates  i n favour  the r e s u l t s  data,  incorporated  i n s e t catch  costs  equalize  rather  minus  t h e more f r e q u e n t  For  value  a one b o a t cost  mean  t h a n mean  per vessel.  l i n e - u p where join  upon  minus  line-up  i s l o w e r due sets  (i.e.,  91  Figure  25.  The s e l e c t i o n r u l e f o r e n t r y and e x i t o f e f f o r t . Due t o h i s t o r i c a l information regarding the r e l a t i v e d e s i r a b i l i t i e s o f known f i s h i n g s i t e s , t h e s k i p p e r s a r e a b l e t o e x p l o i t t h e most p r o f i t a b l e s p o t s f i r s t . As t h e f l e e t s i z e increases a n d w a i t i n g t i m e s become l o n g , v e s s e l s d i s p e r s e t o l e s s desirable sites.  92 3)  Skippers' line-up of  tactical  lengths  skippers  exploiting  to  that rock  choices catch  fished piles,  do  not  rates.  affect The  differently another  structured their  rates  among l i n e - u p c a t e g o r i e s w e r e  skippers'  choices  little  the  Violations  of  of  of  set  variance  assumptions  1)  logbook (one  (which types  per  3)  to  queue  response  included  yet  lengths)  in  another  tides) yet  catch  different  included  of  groups  specialized  significantly  implicitly  and  i n catch  through  data  group  strategy according  skipper/vessel effect  overall  made o p e n s e t s , a n d  group  the  the  and  the  explained  very  set.  were e x p l o r e d  using  monte  carlo  simulations.  4)  As  in Clark  two  fishing  seine  The  a vulnerable  line-up  point  of  capture  i s one.  site  are  As  i n ChapterIV,  at  a very  1)  salmon are  population  i n order  The  is constantly  exploited  Assumptions  the  distributed  that  i s not  (e.g.,  to minimize  the  the  catch  vulnerable  depth of  among  of  the  deep  chinook).  probability  access  strategy  and  (1979),  a background p o p u l a t i o n  i s regulated  swimming  6)  Mangel  populations:  to  5)  and  effect) lead  3)  a vulnerable  volume o f water  fished;  fish  at  an  exploited  associated with  a l l vulnerable  fish  present  a at  an  caught.  i t i s assumed  l a r g e number  through  of  of  that vulnerable  access  salmon  are  present  points.  (perfect information,  rational  behavior  and  no  to  n  ±  =B  C  ±  24)  93 where  a n d C^ a r e t h e l i n e - u p  interval  a t access  opening  or f l i g h t .  point  length  and t o t a l  f o r some  i , r e s p e c t i v e l y , and 3 i s c o n s t a n t  time  within  an  Therefore,  s i /  n  E  s n  i  =  c  i /  i i-1  E c  i-1  n /E L  where  catch  En^ i s t h e t o t a l  effort  25)  ( E ) , EC^ i s t h e t o t a l  (C)  a n d s i s t h e number o f l i n e - u p s  the  mean c a t c h  per vessel  = Cj/C  i n the f i s h i n g  i s predicted  catch area.  t o be e q u a l i z e d  f o r a l l vessels Rearranging  among a c c e s s  25), points  C/E = C i / n i  Note  that  access or  catches  point  are not equalized  when t h e m o s t catch  the  total  total  equivalent and  fish  more t h a n The  catch  a position within  are present,  fleet  catch  taken during  a v a i l a b l e to the f l e e t .  to the vulnerable  swept).  population  o f capture  Note  Thus t h e c a t c h  i s the proportion  that  i n order  within  catch  a t an  Due t o l u c k  t o make a s e t  t h e same q u e u e  a time p e r i o d  will  The t o t a l  as  available catch  o f salmon (see assumptions  may b e e x p r e s s e d  (CA) i s 4)  points are  as  (l-b)CA  o f the a v a i l a b l e catch  CA c a n b e e x p r e s s e d  i s a proportion of  i s one a n d t h e e x p l o i t e d a c c e s s  C =  where b  of s e t catches.  a line-up  some s k i p p e r s  The t o t a l  others.  5) -- p r o b a b i l i t y  constantly  among f i s h e r m e n .  ( C ^ ) i s t h e sum o f a d i s t r i b u t i o n  the a b i l i t y to p i c k  26)  27)  that  i s not exploited.  94 A i V  CA =  28)  a  a-1  where V number  i s the v u l n e r a b i l i t y  a  of catchable  number o f a c c e s s simplify most  a  =  < V  a  =  exploited  a  s  +  access  i  < V  2  site < C  point  (V  a  =  a =  5)  a  =  =  A  s +  of  total  In order to  i s d e f i n e d as t h e i n d e x A l l other than  o f capture  < ^a=A^  access  or equal  o f the  points are t o VMAX  of a vulnerable  fishing imply  "  v  spots  fish  are exploited  that catches  at  a t an first:  exploited  a  29)  s u b s c r i p t e d w i t h i n t h e framework  population of unexploited plus  a r e A-s+1  unexploited  a  a n d l i n e - u p s a r e now  a n d A,  access  respectively).  Normally,  (vulnerability)  =  type  rather largest  T h e number o f u n e x p l o i t e d s a l m o n i n  2) ( r a t i o n a l  c a t c h a t the behavior)  A-s Z V /CA a-1  30)  a  i s a distribution  this  points  f o r the s m a l l e s t and  p o i n t s and g i v e n assumption  there  access  (bCA) i s , t h e r e f o r e , t h e p o t e n t i a l  b  Obviously,  exploited  o f l i n e - u p s ; the index values  the v u l n e r a b l e p o p u l a t i o n  points.  i s the  v u l n e r a b l e salmon.  that are less  (the best  2  point catches  t h e sample  queues  i . e . , the  p o i n t s aire e q u i v a l e n t t o v u l n e r a b i l i t i e s :  the t o t a l  than  p o i n t a and A  = VMAX).  (the probability  i s o n e ) a n d 2) A_  or d e s i r a b i l i t y  VMAX).  C  (Access  A  by v u l n e r a b i l i t i e s  Assumptions  C _k_  at access  points associated with  d e s i r a b l e access  1  present  the f o l l o w i n g presentation, a = A  characterized (V  fish)  (profitability  of vulnerabilities  of distribution  is illustrated  on t h e a b s c i s s a and t h e f r e q u e n c y  among with  o f the event  access the event  ( t h e number  of  access  points  ordinate.  Since  total  access  i t i s assumed  point  vulnerabilities distributions in  Therefore, An are  I t was  an  empirical  important  p l o t t e d as  a  the  number  cumulative access be  defined  at  to  as  line-up  as  that  24)  lengths  and  that  are  catches  truncated  forms  the  frequency  d i s t r i b u t i o n s of  fits  finding a a l l data  a p p r o a c h was  these  distribution.  sets well  any  Pp.  points  of  The  points  arbitrary, equally  summed or  equivalent  fish  may  be  i s described  to  patch  queue  lengths  be  sum.  from  the  below.  sum  expressed  that  difficult.  vulnerabilities  rank order  can  c o n t r i b u t i n g to  available fish  to  single, theoretical  c h o s e n and  i n d i v i d u a l access  access  are  the  that  of  the  proportional  q u a l i t a t i v e f o r m b e c o m e s a p p a r e n t when  proportion  point  29),  cumulative  of  that  apparent  distribution  a p a r t i c u l a r v u l n e r a b i l i t y ) on  (equation  were examined  vulnerabilities of  catches  (equation  C h a p t e r IV.  probability  c h a r a c t e r i z e d by  of as  Let  function  the  least  more d e s i r a b l e  a  desirable  access  point  (a=F)  Then  F P  and V  a  =  F  2  also  represents  •  • <  V  The  proportion  a  =  F  plotted against  be  a  the  rank  of  Z V /CA a-1  31)  a  a p o r t i o n of  of  total  access  F/A  (with  Pp  straight lines  order  =  the  fishing  area  with  on  points the  represented  ordinate)  the  increasing slopes  increase  i n magnitude) or  a  depending upon the  sizes of  groups  points  be  sizes.  a p p r o x i m a t e d n i c e l y by  of  access  In  the  Johnstone  an  exponential  by  F <  A  and  V  Pp  i s F/A.  q u a l i t a t i v e form  (i.e.,  sum  same s a l m o n p a t c h  (1 <  a =  ^  <  If  Pp  )-  is  set  F  the  elements  smooth a c c e l e r a t i n g  Strait  function:  sets,  this  of  curve,  c h a r a c t e r i z e d by  data  will  the  curve  can  96  P p . F / A . e ^ ^ "  where  c i s a scaling  distribution. a uniform are  32) r e p r e s e n t s  Substituting  Recall  available not  fish: fish  caught  (A-s). sites  F  =  < V  a  A  t h e most  A  .  s  < V  P  n  s  =  (A-s)/Ae « C  M  a  .  A  s  sites .  +  B  s  +  =  (  )  B  C  a  a=A-s+l  = V  a  (equation  ^ a=A-s+2  a  a n d one.  - >/ >- > S  A  33)  1  and e x p l o i t a t i o n o f are f u l l y  exploited ( a l l  A  relatively  fish  present ^  -  poor among  B  fishing  spots  unexploited  5; > a = l s  that i s  v  ^  v  a=2  and  .  s  +  B  )  /  A  c ( ( ( A -  e  A-s Z V /CA a=l a  +  S  +  B ) / A ) - l )  A-s+B Z V /CA a=A-s+l  a  a  ^  n  (equations  a=A)  A-s+B Z C /CA = a=A-s+l a  34)  a  29) a n d n / E = C / ( l - b ) C A n  A-s+B Z V /CA = a=A-s+l  o f the f i s h  r e f e r r e d t o above.  sites  ( B ) i s Pp=A-s+B  • • • ^ a=A-s+B  n  representing  the p r o p o r t i o n o f the a v a i l a b l e catch  a t the remaining,  =  ( A  desirable fishing  =  Since  .  are taken);  some f i s h e d =  Pp v a r i e s b e t w e e n z e r o  patch  32) i n t o 3 0 ) ,  The p r o p o r t i o n o f v u l n e r a b l e plus  line  I f c i s l a r g e , most  pertaining to rationality  i s present  32)  F/A i s a s t r a i g h t  the e m p i r i c a l approach  = P  the assumptions  vulnerable  points.  equation  b  Pp v e r s u s  of vulnerabilities.  a t a few a c c e s s  )  d e s c r i b i n g t h e skewness o f t h e f i s h  I f c i s zero,  distribution  present  Equation  constant  1  A-s+B (l-b)/E Z n, a=A-s+l  25 a n d 27,  97 A-s =  PF=A-s+B  _  Referring  to equations  =  a  (A-s+B)/A e  exploitation  of  access  portion the  rank  points  catches) points  (A-s)/A  e  area  approximations. points  exploitation  i n the area  under  (c).  i n the f i s h i n g  the t o t a l  points  by the corresponding  points  6) s t a t e s t h a t area.  I t represents  number  fish,  the  (B) a n d a p a r a m e t e r d e s c r i b i n g  points  are associated queue  (i=l...s)  length: and t h e i r  (a=A-s+l...A).  t o a one p a r a m e t e r m o d e l w i t h  Assumption  ranked,  i n h a b i t e d by v u l n e r a b l e  among e x p l o i t e d a c c e s s  36) r e d u c e s  o f the  o f l i n e - u p s (and,  (1-b),  The e x p l o i t e d a c c e s s  among a l l a c c e s s  rate.  distribution  examination  are determined  desirability  Equation  a t some s e t o f l o w e s t  The c u m u l a t i v e  (A) p r e s e n t  which  desirability  access  e  i s a function of exploitation  o f the f i s h e d  rank  c(((A-s)/A)-l) (A-s)/A  c(((A-s)/A)-l)  (B) t o t h e t o t a l  distribution.  two r a n k s  their  35)  A  b  F=A-s+B "  r a t e produced by the boats  salmon d i s t r i b u t i o n  with  C  36) i s a n e m p i r i c a l m o d e l r e p r e s e n t i n g t h e r a t i o  access  truncated  therefore,  a /  36)  Equation  a  V  c(((A-s+B)/A)-l) -  1 -  exploited  2  a=l  3 3 ) , 34) a n d 35)  A-s+B n /E Z a=A-s+l  P  "  there  Therefore,  we  a few  a r e a l a r g e number o f c a n make t h e  approximations  (A-s+B)/A o r (A-s)/A  and  substitute this  parameter  c, making  into  the equation.  this  substitution  * 1  37)  Depending upon the magnitude i n the exponential  o f the  p o r t i o n o f the  98 model the  could  lead  to  serious  error  s u b s t i t u t i o n i s made i n b o t h  Substituting  these  P  s u b s t i t u t i n g equation  38)  finally  e  i s unknown,  m o d e l was  easily  a relative  f i t by  (  s  '  B  /  )  =  value  non-linear  exploitation rate as  average  the  maximum l i n e - u p  fishermen  line-up versus  fishery  the  and,  spots  also  33)  and  32)  3  39)  to  9  )  give  40)  presumably,  where w a i t i n g  fishing  area,  the  competition.  times w i t h i n  queues  for  moved  effort  the  and  saturated  desirable  saturated  t i m e s were  and  as two  one  parameter  effort boat  Since  saturation should can  be  with  increased  line-ups into  salmon be  measured  River  while  appeared  less  constantly  p r i m a r i l y due as  vessel distribution.  i n Campbell  increasing  areas.  o f movement  short.  competition  F i s h Co.  have  indicative  the  This  41)  squares.  m o r e one  were  - b)/(l-b)  is -ln(b)/s.  should  curve  also affects  Canadian  (b  into less  predicted This  (s-B)/s =  least  saturated;  interference  dispatcher  into equations  38)  for c  (1-b)  The  profitable  exponent).  S  B Z nj/E i=l  1)  The  enter  b  tested.  the  when  ln(b)  F o u r m a j o r h y p o t h e s e s were  effort  in  one  to  a  A  the  equal  c«-s+B)/A)  =  F  b would  and  37)  into equation  A-s+B Z n /E a=A-s+l  Since  course,  multiplier  -A/s  =  of  (equation  =  F  P  leads  the  approximations  c  and  (and,  called  waiting The this  to  99 phenomenon t h e where  they  desirable of  "funnel  become v u l n e r a b l e spots  packers  are  in  they  Chapter  fishing axis;  IV a r e  area.  half  the  The  salmon enter  distribution of  the  was  Strait  access  end  from  north.  the  Most  of  located north  b o u n d a r y was  lifted.  points.  This  2)  The  As the  some o f  the  salmon  created  a  the  of  the  less  the  and  dynamics  as  effort  lengths  throughout  edge  of  in effect  the  the  vertical  first  the  lifted,  desirable  salmon d i s t r i b u t i o n area,  (c)  especially  response  the  d e s i r a b l e area,  desirability  access  hypothesis.  interception  relative  the  sites,  these  the  of  was  the  produced  which good  spots.  Two  additional  3)  h y p o t h e s e s were  I f the total  exploitation catch per  salmon abundance  tested.  response  opening  to  fisherman  s h o u l d be  ( e x c l u d i n g the  the  model  best  abundance index  output).  12  line-up  b o u n d a r y was  This  i n the  and  (smaller  lifted.  decrease  11  the  f o r the  to another  entered  most  number  were e x p l o i t e d a f t e r the  few  fish  Figures  m a j o r b o u n d a r y was above  the  strait.  reached  leads  the  area.  most p r o f i t a b l e  they  area as  increase  the  northernmost  skewness o f  decreased  saturates  d e s i r a b l e open s e t areas  salmon b e f o r e  f o r the  small  i s located near  i n c r e a s e d and/or  spatial  a  v e s s e l s c a t c h i n g the  queue  that boundary  of  rate  enters  fishery  The  into  does n o t  that remained  northwest  of  parameter  should have  by  of  effort  the  summary  after  of beach  southern  to  Co.  i s produced by  a major boundary  aggregated  exploitation  more e f f o r t  distribution  season.  intercepting  as  funneled  p o i n t s f u r t h e r down t h e  q u e u e s ) were  boats  the  Canadian F i s h  competition  reach  Salmon a r e  and  filled.  i n Johnstone  Exploitation before  effect."  of  saturates, vulnerable  100 4)  The  The (>  and d e s c r i b e d by  distribution  (i.e.,  s h o u l d be  less  beginning  o f the  results  26  (smaller  The  representation c ) on t h e ebb  squares  shows a r a p i d l y  f i t were  good.  saturating  s a l m o n d i s t r i b u t i o n became l e s s  rank c o r r e l a t i o n =  -0.6094,  negatively  by  the  salmon  of fish  tide  A l lR  response  test  patches)  and a t the  were  2  of  high  exploitation  rho @  a = 0.05  i s 0.2829).  fish  abundance  s a l m o n d i s t r i b u t i o n became  less  skewed  -0.8197,  critical  results,  competition  rho @  a clear  creates  as e f f o r t i n c r e a s e d .  f o r t h e p a r a m e t e r c a n d t o t a l e f f o r t was  critical  correlated  skewed  with  these  exhibited  opening.  of the l e a s t  Figure  the fishermen.  the line-up  skewed  behavior  to e f f o r t . The  (rho  r e f l e c t the f i s h  logbook data  0.96).  rates  parameter c should  a  = 0.05  cut test  a less  significant c was  also  (measured as t o t a l c a t c h ) ;  as abundance  i s 0.3643).  increased  I t i s apparent  o f the hypothesis  skewed  However,  A  that  the  (rho =  that  given  exploitation  d i s t r i b u t i o n of v u l n e r a b i l i t i e s cannot  be  made. A n o t h e r model t h a n CPUE s i n c e catch  rates  prediction  was  the e x p l o i t a t i o n  that rate  catch  i s a better  saturated  rapidly.  index  of  abundance  The model f o r  is  C = pN(l-b)  where  1-b  abundance to  i s the e x p l o i t a t i o n o f salmon and p  the gear.  exponential fish  and  Although equation,  rate  42)  of vulnerable  i s the p r o p o r t i o n  equation  42)  the f i t t i n g  f i s h e r m e n and the d e c i s i o n  rule  N  o f the f i s h  i s similar  process  fish,  i s the t o t a l that  are vulnerable  to the t r a d i t i o n a l  included governing  the d i s t r i b u t i o n o f the fleet  behavior.  Most  101  100 90  o o  80 LU  o  o fccog° o  <P °  70  o  o o o  o o o  <  or  60  <  50  r-  X LU  8  40 30 h 20  1  100  _L  200  300  400  EFFORT (NO. OF BOATS)  F i g u r e 26.  E x p l o i t a t i o n rates as a f u n c t i o n o f e f f o r t . These estimates were p r o d u c e d b y the n o n - l i n e a r o v e r f l i g h t model f i t s t o line-up d i s t r i b u t i o n data.  102 important,  exploitation  abundance The  or  model  equivalent index  salmon  to  independently  C/(l-b). the  Using  total  abundance  the  total  catch  indices  non-parametric  available  (C)  and  CPUE w e r e  the  low  and  (critical  rho  @  a =  0.05  i s 0.2829),  catch  (critical  rho  @  a =  0.05  i s 0.5140) and  --  CPUE a n d  respectively. not  rejected  may  have  to  The the  the  time  series  beginning  those  was  times.  0.9204 f o r t h e  0.9766 a n d  0.9189  0.9341 a n d  total  0.9231 f o r CPUE.  0.1190 f o r  the  comparisons,  hypothesis  of equal  correlation  coefficients  this  sizes  opening  on  (13  result.  of parameter  usually But  for  less  or  C  i n d e x was  i n Figure  during  skewed  low  flood,  the  distributed  i n a contagious  manner  (larger  variability  and  the  28  patterns  linear  tides,  salmon and c).  the  the  a  few  were  27).  salmon dispersed  were  there  i n Figure  index  patterns.  apparent  fishermen  CPUE  CPUE  (Figure  Patches  Although  illustrated  was  f o r c a t c h and  exhibits  (smaller c).  the  overlap,  points)  G r a p h i c a l l y , however, the  c  data  per  model  l i n e - u p rho  sample  this  two  CPUE l o w  low  o f an  to  --  s a t u r a t e somewhat w h i l e  distribution at  and  w e r e 0.9702 a n d  total null  is  l i n e - u p mean c a t c h e s  0.1814 a n d  catch  (pN)  sales slips,  compared  f o r extreme v a l u e s were  contributed to  appeared  At  The  values  high  index  Z probabilities  rho  --  c a t c h r e p o r t e d on  The  C/(l-b)  salmon  salmon p o p u l a t i o n s i z e  set.  The  of  catch.  s t a t e s t h a t the  along with  independent  r a t e s were e s t i m a t e d  i s some  28  appear  to  distinct. In p r i n c i p l e , important  overflight  management q u e s t i o n .  economically defined  the  as  the  cost  of  the  optimal  fished?  the  number  I f the of  model c o u l d be  How  many f i s h i n g  o p t i m a l number o f  sites  with  set  fished  to  access  greater  fitted  can  the  number o f  sites:  model  address  locations  catch values  operating a vessel, exploited  used  be  than used  an  can  be  points i s or to  equal  to  estimate  be  103 Figure  27.  C a t c h a n d CPUE v e r s u s l o w l i n e - u p c a t c h p e r s e t . T o t a l c a t c h e s a n d CPUEs w e r e o b t a i n e d f r o m s a l e s s l i p d a t a . A v e r a g e c a t c h p e r s e t was c a l c u l a t e d u s i n g l o g b o o k d a t a . Each data p o i n t r e p r e s e n t s a weekly opening.  104  < O m oo  4500  LU O LU Q_  O  3000  LU  ZD  or  o  1500  X  o <  o  0  o  o o  50  100  X  150  CATCH PER SET (PIECES)  1,500,000  UJ 1,000,000 o LU  CL  x o r<  500,000 V-  0  50  100 150 CATCH PER SET (PIECES)  105  Figure  28.  The t i m e s e r i e s o f t h e f i s h skewness p a r a m e t e r c. Open c i r c l e s a r e ebb t i d e s a n d f i l l e d c i r c l e s a r e f l o o d tides. The d a t a p o i n t s w i t h i n o p e n i n g s a r e c o n n e c t e d .  EBB • FLOOD  O  o  MAJOR BOUNDARIES LIFTED  oV  30 FLIGHT  40  50  107  V(C/(l-b))(b  where x in  i s the  equation  value  per  number X  41)  fish.  vulnerable  of  access  i s the  V  fish  at  43)  a l l the  catch  equals  operating  where  catch  values  are  total  population  vessel  will  -  1 +  of vulnerable  equal  one.  the  recent  s  a  Canada and  kind  of  monte  line-up  data  interesting  the  the  operating and  ((i-b  1  1  and  of  seine  1982a) c o n t a i n e d  /  s  )/b  1  cumulative points  costs,  earnings. data  is  The  /  s  the  of  equation  and  taking  adjacent  points  of  i n c l u d i n g the present  times the  the  at  sites  value  operating  spot  of  the  cost  of  a  v  ))/ln(b)  1 / s  not  were n o t  be  made s i n c e  available.  (Dept.  of  collecting  good  Even  Fisheries  disclaimer concerning of  44)  their  large  data  the and  data  sample  on sizes  of  evident.  effects  results.  distribution  average  X (l-b)/CV  )=  Report  importance  carlo simulation and  i s the  proportion  proportion  could  vessels  a  V  (s-B  43),  q u a n t i t a t i v e assessment costs  43)  f o r optimum h a r v e s t ,  d i v i d e d by  F l e e t R a t i o n a l i z a t i o n Committee  expenses  A  /  =  v  access  minus  fish  ) / X  v  operating  Oceans,  this  that  Rearranging  x  S  s(ln(X )+ln(l-b)-ln(C)-ln(V)-ln(l-b  Unfortunately, for  than  /  operation  ranked  costs  less  b  x  states  X  utilized  of vessel  lowest  where  D  -  1 ) / s  points  cost  Equation  ~  ( x  of  as  the  provides  a  probable  upon parameter  Equation  queues  the  41)  difference of estimates  of  the  the  structure  estimation  describes  function of  error  the  rank  line-up  lengths  the  y i e l d e d some order  parameter b.  cumulative  in  cumulative  Rearranging  distributions  that  between  108 B n  i  =  =  B  B-l  Z n  - I nj_ = E ( ( b ( " / s ) s  t  i-1  where  B  by  o f the l i n e - u p .  equation  45)  a  u  i  deviation  by  a standard  of  calls  normal small  Test  i n absolute  values  value  independent  search,  spots  may  access sites.  variance The  Twenty  data  sets  f o r n^  were  component:  46)  R  distributed  variable with  mean z e r o  o f t h e random n o r m a l d i s t r i b u t i o n between  o f R were  than used  3 a n d 4,  and  limited  t o t h e r a n g e 4-8  f o r a given  to describe  what  effects  queue  represented effects  were  due  about  Note  (n).  that  I t was  insure not  The  assumed  random  t o be  individual sub-areas the  create  many, o f the  movements  only,  standard  assumed  to skipper's  that  to  A perfect reflection  information  length  t h e number  l i n e - u p was  d i s t o r t e d by  and s t r a t e g y .  defined  depending upon  the magnitude o f the l i n e - u p .  information,  and a g g r e g a t i v e  to catch  points  n  random number  have been p o o r l y  Observation  45)  s  < i/ )  U  t h e l i n e - u p s was  increase with  experience  responses  by  inadequate  aggregative  deviations  )/ )/(l-b))  carlo  and a d d i t i v e e r r o r i n p u t s .  salmon d i s t r i b u t i o n s  and  value  e r r o r s t r u c t u r e was  based upon  +  normally  the smallest negative  greater  i  n  d e v i a t i o n o f 1 was  made.  B + 1  n^/R.  T h e maximum a b s o l u t e  that  =  i s an independent,  standard  Monte  and an added e r r o r  n  where  s  i-1  i s the rank  generated  . b< "  B  that  secrets,  overly large  the best strategy queue  rates.  e r r o r was  ( s ) t h e monte trials  were  also  included.  carlo used  F o r a g i v e n number  simulations  f o r two  of exploited  p r o d u c e d more o r f e w e r  effort/access point  and  fished  five  categories. initial  parameters  f o r low and h i g h  effort  levels  (60 a n d 250)  and  109 low  and  ranges  high  access  r e s u l t i n g from  ( r o u n d i n g ) and inspection at  low  queue  from  levels  the  the  variance  i t i s obvious  that  d i s t r i b u t i o n could was  probably  parameters  discrete  biased  the  severe.  of  at  the  access  estimates.  Large  queue  exploitation  rates  predicted  by  the  effects.  The  certainly  a f f e c t the  qualitative  response  i n Table  estimates  a b o v e 0.5  for  sample  sizes.  field  data usually  insects  or  these biases  error variances (low  b).  fell  coupled with  to  The  indicated  that,  accuracy  of  exploitation - effort  the  the  perfect This  Fortunately,  b e l o w 0.3.  The  relatively  slightly  the  bias  exploitation  although  uncertain  b a c t e r i a etc.)  were  have been s t a b i l i z e d  From  fitting.  the  dampened  large  VIII.  become v e r y  access point  p r e c i s i o n and the  recorded  and  responses  model  effort,  d a t a may  vessel  during  (compared  high  the  p a r a m e t e r means  distinguished  the  points  of  the  Parameters  fisherman predator  were h i g h  of  140),  parameter  b).  be  from  simulations  form  the  e f f e c t of  At  field  and  l e v e l s are  (high not  estimated  nature  aggregations  an  (35  discrete nature  exploitation rates  result the  point  by  also  less  when  rates  these  response  small  contradictory  errors  estimation  will  process,  r e l a t i o n s h i p may  the  remain  intact.  The  Seine boats is  made,  the  statistical value served of  of as  catch  d e l i v e r to packers  skipper area,  the  rates  fills  number  catch  the  Sales  input  and to  out  a  Slip  or  their  sales  slip.  The  pieces  of  o f pounds and  other the  Model  pertinent  data  home p o r t s .  are  vessel each  among v e s s e l s  and  the  total  for  delivery  number,  salmon  recorded.  f o l l o w i n g p r e d i c t i v e model  When a  species,  These  the  data  the d i s t r i b u t i o n  exploitation rates.  LOW EFFORT  0.1  0.2  0.4  0.6  0.7  0.16  0.22  0.34  0.50  0.50  4  0.14 (0.11-0.18)  0.19 (0.13-0.22)  0.25 (0.20-0.30)  0.32 (0.26-0.37)  0.32 (0.26-0.37)  5  0.15 (0.12-0.18)  0.20 (0.17-0.24)  0.28 (0.24-0.32)  0.37 (0.33-0.43)  0.37 (0.33-0.43)  6  0.15 (0.13-0.18)  0.21 (0.17-0.24)  0.29 (0.24-0.33)  0.41 (0.37-0.48)  0.41 (0.37-0.48)  7  0.16 (0.13-0.18)  0.22 (0.18-0.24)  0.31 (0.26-0.35)  0.45 (0.38-0.50)  0.45 (0.38-0.50)  8  0.16 (0.14-0.18)  0.22 (0.19-0.25)  0.32 (0.28-0.35)  0.47 (0.41-0.50)  0.47 (0.41-0.50)  b di screte R High Variance  Low Variance  Table VIII.  Monte c a r l o s i m u l a t i o n of e r r o r i n the o v e r f l i g h t model. Randomly s e l e c t e d v a l u e s f r o m n o r m a l d i s t r i b u t i o n s w e r e a d d e d t o l i n e - u p l e n g t h s p r e d i c t e d by t h e o v e r f l i g h t model. The m o d e l was t h e n f i t t o t h i s f a k e d a t a . The mean p a r a m e t e r e s t i m a t e s f o r twenty t r i a l s are g i v e n . The r a n g e s a r e r e c o r d e d i n p a r e n t h e s e s .  HIGH EFFORT  0.1  0.2  0.4  0.6  0.7  0.15  0.21  0.38  0.58  0.58  4  0.13 (0.11-0.14)  0.17 (0.15-0.18)  0.24 (0.22-0.26)  0.33 (0.31-0.37)  0.33 (0.31-0.37)  5  0.14 (0.11-0.15)  0.18 (0.16-0.19)  0.27 (0.24-0.30)  0.39 (0.35-0.43)  0.39 (0.35-0.43)  6  0.14 (0.13-0.15)  0.19 (0.17-0.19)  0.29 (0.26-0.32)  0.45 (0.40-0.49)  0.45 (0.40-0.49)  7  0.14 (0.13-0.15)  0.19 (0.18-0.20)  0.31 (0.29-0.33)  0.50 (0.46-0.54)  0.50 (0.46-0.54)  8  0.14 (0.13-0.15)  0.20 (0.19-0.21)  0.33 (0.31-0.34)  0.53 (0.49-0.56)  0.53 (0.49-0.56)  b di screte R High Variance  Low Variance  Table VIII. (continued)  Monte c a r l o s i m u l a t i o n of e r r o r n o r m a l d i s t r i b u t i o n s were added The are  i n the o v e r f l i g h t model. Randomly s e l e c t e d v a l u e s from t o l i n e - u p l e n g t h s p r e d i c t e d by t h e o v e r f l i g h t m o d e l .  m o d e l was t h e n f i t t o t h i s f a k e d a t a . The mean p a r a m e t e r given. The r a n g e s a r e r e c o r d e d i n p a r e n t h e s e s .  estimates  for  twenty  trials  112 The  basic  hypothesis  aggregation organisms  Effectiveness capturing, riot,  skews  attacking,  or  is  r e s u l t i n g competition  the  d i s t r i b u t i o n of  cornering and  to  individual is trained  to  the  effectivity  effort.  of  may  The  be  fleet  (those  access for  intensity  model  as  access  are  to  is  between  the  usually  to minimize  and  a  by  the  time/area  --  killing,  intent  curtail other's  i s to  start  a  effectivity, reciprocal  d i s t r i b u t i o n of  stratum  and  the  following  and  with boats,  is a  subsidiary  i s composed poor  to  there  rates  per  e x p l o i t a t i o n competition  d i s t r i b u t i o n of  catches  or  of  i s very to  access  vessel  hypotheses.  little  room  or  increasing  Although may  (see  the  skippers.  the  point  increase  of  of  highliners  average  e x p l o i t a t i o n competition. catch  function  dynamics  d i f f e r e n t s t r a t e g i e s due  and and  form  stratum  extremely well)  filled  the  time/area  mathematical  adopt  line-ups  the  the  data presented  catch  point  extended  model  the  become the  less  overflight  effectivity  should  skewed.  First,  will  of  output)  a vessel's  do  points  effort  become more  i n any  interference  distribution skewed  The  characterized  that  skippers of  the  effect  Unless  hypothesis,  aggregation  chance  of  effectivity.  intended  interference  effectiveness within  As  an  a market.  skipper/vessel  1)  formulation  lucky.  According  distribution  the  the  relative  competition  e x c e p t when t h e effects  and  i s defined  crowds,  underlying  time  reflect  sets  i s t a k e n by best  fish  one  represent  interval. the  i n C h a p t e r IV i n d i c a t e d set. the  Therefore,  It  i s probable  d i s t r i b u t i o n of only  distribution (i.e.,  a portion those  of  that  that  at  that  the  l e a s t 20% largest  salmon patches the set  vessel on  the  of  over  an  catches infrequent  113 large  schools).  lengthening  Second,  a  queues w i l l  smaller  encounter  Third,  the  distribution  of  points  are  filled:  skippers  catches the  are  smaller  overflight  points  many than  model  queues  those  The  define  while  the  have  fewer  the  mode s h i f t s chances  however, w i l l fishery  (see  2)  In  only  the  hand  tail  and  do  origin. their and  Ledbetter  summary,  vessels  the  rapidly  than  mean c a t c h  become  Repeated  the  Many c o n c e p t u a l (Bliss the  (Note  vessel at  effectivity taken  lucky  catches  from  always  that  access  distribution the  change w i t h  are  big  longest  vessel  entry)  skippers  will  present  in  the  1985).  enter  less  (see  an  d e s i r a b l e spots  effort  squared  line  decreases  implications of  equation  and  this  up  at  more  statement  49).  individual  v e s s e l are  affect  shape  d e s c r i b e d by  the  distribution.  distribution,  CPUE f o l l o w s  the  knowledge; h i g h l i n e r s  The  from  not  where  queues. per  access  limited  variance.  landings  more  salmon.  inexperienced  unit  apparent  as  of  Fourth,  per  Salmon abundance  been proposed  the  effectivity  effective  others,  of  catches  implement  as  mean c a t c h  the  schools  change  longer  set  the  in  d e s i r a b l e spots  largest  H i l b o r n and  Poisson  4)  to  to  remain  will  3)  highest  less  vessels  large  will  associated with  the  the  infrequent,  enter  right  stationary (i.e.,  the  v e s s e l catches  stated that  i s equalized).  remains  the  proportion of  does n o t  which  and  .  formulation  A  theoretical  is a  distribution.  expected  skipper/vessel effectivities  f o r the  model  o f Greenwood and  binomial  of  the  CPUE  binomial.  mathematical models  1953)  compound  i s negative  the  negative  f o r the  Yule  distribution  (1920):  The  distribution  may  be  of  represented  binomial  the  a  of  negative  average by  have  or  gamma  114 distribution of  the d i s t r i b u t i o n  driving  process  Compounding the  of Poisson  i s a scaling (salmon  f(X,k,ct) = a  e"  k  parameter  a negative  describes  reflecting  t h e shape  the a c t u a l  abundance).  X "Vr(k) k  X a  catching process  of observing  binomial  47)  f o r the i n d i v i d u a l  distribution  a c a t c h per boat,  x^,  vessels  through  of catch per boat.  i s p r e d i c t e d by the  The  negative  t o be  P(  where  (X) where k u n i q u e l y  o f the system  gamma p r o d u c e s  binomial  and a  the Poisson  probability  parameters  X i  )  =  t h e mean, m,  (k/(m+k))  = k/a, a  2  (m/(m+k))  k  = k/a + k/a  2  / o  k  = m  a  = m / a  2  *  m  2  -  (k+j-l)/j  48)  and  m  2  Fitting it  follows  the negative  that  binomial  - m  49)  to the frequency  t h e mean c a t c h p e r b o a t  A  distribution  of  CPUE,  i s a f u n c t i o n o f k and a:  A.  C/E = k / a  where  C i s the t o t a l  catch  i n a time/area  50)  stratum  and E i s the t o t a l  effort. Equation and  a.  The p a r a m e t e r  negative large,  50) c a n b e  binomial  k  f u r t h e r c h a r a c t e r i z e d by hypotheses i s always  distribution.  k decreases.  concerning  k  d e f i n e d as r e p r e s e n t i n g t h e shape o f t h e As  In the context  t h e skewness o f a d i s t r i b u t i o n o f dynamics,  k  becomes  i s a v a r i a b l e and i s a  115 function of  If  a)  skippers  b)  gear e f f e c t i v e n e s s ,  c)  the d i s t r i b u t i o n  d)  competition,  e)  d i f f e r e n c e s i n volumes  f)  luck.  i t i s assumed  following  skill,  t h a t these  o f salmon  factors  patches,  swept,  a r e independent  theorem c a n be a p p l i e d (Kennedy  If  XQ_, X 2 . . . x  distributions a  and Keeping  a r e independent  n  d e f i n e d by parameters  common p a r a m e t e r ,  gamma v a r i a t e s , t h e 1951):  gamma v a r i a t e s k^,  from  • • • kn and  a , X = E x ^ i s a gamma v a r i a t e  with  p a r a m e t e r K = Zk^  Therefore,  k from  parameters  f o r many i n d e p e n d e n t  Now,  the primary  fishing  sites  the negative  hypothesis  a r e not,  the  competition  components.  of fish.  Some k ^ s f r o m  for  t h e component  (competition)  while  so t h a t  t h e sum r e p r e s e n t s  term  of effectivity  are functions o f vessel aggregation  sum o f p a r a m e t e r s  error  t o CPUE i s t h e sum o f t h e  i s that k i s a function o f competition  k  where  fits  distributions  and f o r l a r g e schools  gamma d i s t r i b u t i o n s others  binomial  =  n ( I k ) + e i=l  the distributions  that vary  51)  t  affected  independently  by competition  o f competition.  and e i s  I f this  i s t o o l a r g e o r v a r i e s t o o much, n o c o r r e l a t i o n b e t w e e n k a n d will  be e v i d e n t .  116 Another  necessary hypothesis  is  proportional  of  the d i s t r i b u t i o n .  f o r the complete  t o salmon abundance.  formulation  The v a r i a b l e  i s that  1/a d e s c r i b e s  1/a  the scale  A  1/a  where h  i s a s c a l i n g constant  population 50)  (N) t h a t  - hpN  and p  i s vulnerable  52)  i s the proportion  within  From  equations  = k h p N  A  C  Assuming  that  A  a = C/hpN = k E  the parameters h and p a r e A  then,  i s the r e l a t i v e  i n t h e same  overflight  fashion  model.  determines  A  1)  a  (1-b)  54)  of available  as the e x p l o i t a t i o n r a t e s  4 2 ) a n d 52) i n t o  considerable  E  F o r 52)-54) t o h o l d ,  the r e l a t i v e  constant  exploitation rate  CPUE i s ( h p ^ N ^ + p N ) ( l - b ) / E . equations  53)  A  k  vary  area.  a n d 52)  C/E  kE,  the f i s h i n g  o f the salmon  This  equation  estimated  i t was a s s u m e d  e q u a t i o n was 49).  derived  Since  contribution of N , 2  salmon and  that  from the the variance  in  by s u b s t i t u t i n g  the magnitude  this  should  assumption  of h incorporates  flexibility.  few model p r e d i c t i o n s  The changes predicted line-up entering model  can be  made.  i n t h e d i s t r i b u t i o n and s i z e s  t o a f f e c t the shape  results  (as the data  indicated)  were  o f t h e CPUE d i s t r i b u t i o n .  d i s t r i b u t i o n s are a function the area  o f queues  I f these  o f t h e amount o f e f f o r t  i n Chapter V and the o v e r f l i g h t  k i s highly,  negatively  correlated  with  117 effort.  As t h e skewness o f t h e n e g a t i v e  magnitude  o f k decreases.  and  expands  is  expected.  2)  changes  effort.  Assuming  distribution for  3)  The  that  local  effort  54) p r e d i c t s  should  saturate.  negative  binomial  was  tested  using  fish.  T e n o u t o f 14 w e e k l y  result  was  Also,  t h e sample  stationary of  than  and mobile.  t h e 14 o p e n i n g s .  negative  binomial  small.  of  for total  k to effort  exploitation The error  sales  term,  was  rate  correlate  sets  exploitation rate  sets  Strait  i n units  f i t the negative  split  into  reported  (kE)  sales  1953) a n d g o o d n e s s  1/20 r e j e c t i o n r a t i o  vessels  well.  slip  o f f i t was  of pieces  binomial.  of This  f o r a n a o f 0.05. two  catches  f o r the stationary boats  categories: for at least f i t the  (Table I X ) .  O n l y p r e d i c t i o n 2) was parameters  should  C a t c h was  Boats were  Stationary  A l l data  o f t h e CPUE d i s t r i b u t i o n s  effort  (Fisher  test.  CPUE d a t a  the expected  s i z e was  the range and  f i t t o t h e 1981 J o h n s t o n e  the Kolmogorov-Smirnov  larger  reflect  the r e l a t i v e  d a t a b y t h e maximum l i k e l i h o o d m e t h o d  the  no c o r r e l a t i o n  of marginal  the parameters  that  behavior,  the entry  skippers  and t o t a l  increases,  d i s t r i b u t i o n contracts  of fish  i n k do n o t r e f l e c t  of skill,  stationary  Equation  I f the vessel  s o l e l y as a f u n c t i o n  Temporal  binomial  e x h i b i t e d by the data  and s t a t i o n a r y  dome-like - effort  slip  model  reporting  effort  and s c a t t e r e d  were  (Figure  29); the  correlated.  (Figure  30).  The  The  response  relative  relationship d i d not saturate. i s very  errors  uncertain.  In addition  c e r t a i n l y a f f e c t the t a i l s  t o t h e model  o f t h e CPUE  10  118 Table  IX.  The for  Total  k 0.9 1.3 0.9 1.5 2.4 1.7 2.4 2.5 1.5 1.5 2.1 0.8 1.2 1.3  parameter v a l u e s ( k ) , s t a n d a r d e r r o r s and t h e n e g a t i v e b i n o m i a l f i t t o CPUE d a t a .  Fleet  a(k) 0..2 0..2 0,.1 0..2 0,.4 0..2  sample  sizes  Stationary Fleet ( f i s h e d > 10 o p e n i n g s ) n 34 50 82 109 60 118  0..1 0,.1 0..1 0..1  193  0..1 0..1 0..1 0..1  376 253 291 224  247 330 388  k 0.7 1.8 1.2 1.6 2.8 2.2 3.0 2.3 1.6 2.4 3.3 0.8 0.8 1.4  o-(k)  n  0.,2 0.,4 0..2 0.,3 0..5 0..4  23 38 52 56 45 55  0..5 0..4 0..3  59  0..4 0.,5 0.,1 0..3 0..2  65  65 64 66 60 65 57  119  2.4  o o  2.2 2.0 1.8 >or < O  1.6 1.4  <  o  CO  1.2  o o  1.0 0.8 0.6  Figure  29.  1.0  2.0 3.0 TOTAL K  4.0  T o t a l f l e e t k v e r s u s s t a t i o n a r y f l e e t k. The e s t i m a t e s f o r t h e n e g a t i v e b i n o m i a l p a r a m e t e r , k, w e r e o b t a i n e d f o r t h e t o t a l f l e e t CPUE d i s t r i b u t i o n s a n d f r o m t h e CPUE o f v e s s e l s f i s h i n g a t l e a s t 10 o f t h e 14 o p e n i n g s .  120  •2 9  •2.8  2.4 2.2 2.0 1 . 8 1 . 6 1 . 4 1 . 2  J.  6 0*  1 . 0 0.8 0.6 0  >02  mo.5  I  100  #0-2  200  300  400  EFFORT (NO. OF BOATS) Ok  • k' * reporting  Figure  30.  error  k vs. effort. The p a r a m e t e r e s t i m a t e s a n d s t a n d a r d e r r o r s w e r e c o m p u t e d f o r f i t s o f t h e n e g a t i v e b i n o m i a l t o GPUE frequency d i s t r i b u t i o n s . T h e maximum l i k e l i h o o d m e t h o d was used. These e s t i m a t e s appear as open c i r c l e s . The f i l l e d c i r c l e s r e p r e s e n t p r e d i c t e d k' v a l u e s . These p r e d i c t i o n s were p r o v i d e d b y t h e o v e r f l i g h t model e s t i m a t e s o f l i n e - u p l e n g t h s and a model f o r t h e v a r i a n c e o f v e s s e l c a t c h e s within line-ups.  121 distributions. independent their  of  effort  catches  recorded  dynamics  statistical  and then  converted  that d i d n o t comprise  component  proportional The  i n Chapter IV ( F i g u r e 8 ) .  i n t h e wrong  alternative  variance  e r r o r s were d i s c u s s e d w i t h i n t h e c o n t e x t  counts  as weight  salmon An  These  to pieces  a random  k varies with  a n d O r d ( 1 9 8 3 ) t h e minimum v a r i a n c e  finite  population  (N) s a m p l e d  sample  mean  The v a r i a n c e  where n i s t h e sample competitive sampling This  process  without  complexity The  size  total  was  2  w i t h i n queues  at individual  avoided  f o r the access  According  estimator  points  to Kendall,  f o r t h e mean o f a  replacement  i s the  o f s a m p l e means i s  ( 1 / n - 1/N)  55)  i s the population variance. i s probably  but with  per set i s  catch.  o f the d i s t r i b u t i o n  2  weight  abundance  (when mean c a t c h  randomly b u t without  and a  replacement,  variance  the salmon  the line-up d i s t r i b u t i o n s .  V(m) = a  i s sometimes  a possible explanation  Stuart  (m).  catch  report  sample.  The v a r i a b l e c a t c h i n g p r o c e s s through  often  b a s e d u p o n t h e mean  i s p r o p o r t i o n a l t o abundance  following derivation offers  was c o m p o u n d e d  Also,  e x p l a n a t i o n was e x p l o r e d  t o abundance);  o f k.  areas.  Vessels  of  The  better represented  variable selection  as  probabilities.  here.  o f t h e mean c a t c h p e r s e t w i t h i n a q u e u e was  assumed t o  be  V(Cs"i) = O i  where  (1/ti - l / t  i  n  i  )  56)  C s ^ i s t h e mean c a t c h p e r s e t f o r a n i n d i v i d u a l  population boat  2  variance  of catch  a n d n ^ i s t h e number  assumed  that  per set,  t ^ i s t h e number  of vessels participating  boat,  o^  2  i s now t h e  o f s e t s made p e r  i n queue  i .  I t was  122 2  cfi where  Csp^ i s the population  number  o f s e t s made  T / n ^ i s t h e mean c a t c h  this  mean  vessel  56) r e p r e s e n t s  per set - population  degrees into  point  per boat  among q u e u e s ,  per set,  TC/Eti  57)  T — ±^i  i s the t o t a l  n  and x i s a c o n s t a n t .  Since  a n d i t was p r e v i o u s l y a s s u m e d  that  i t c a n b e r e p l a c e d b y t h e mean c a t c h p e r  (C/E).  Equation catch  T/n^t^ =  i  mean c a t c h  a t the access  Csp^  i s equal  iCsp  = iCsp-L =  o f freedom  one o f t o t a l  (n^-1). catch  the expected  mean c a t c h  sum o f s q u a r e s  o f the v e s s e l  mean  per s e t d i f f e r e n c e s , d i v i d e d by the  M u l t i p l y i n g by t ^  2  transforms  the expression  per vessel.  SSi  = TC/E ( (  n  i  - l)/n )(n i  - 1)  i  s V ( C P U E ) = xC/E ( E - 2s + Z  l/n )/E  58)  L  i-1  where s  S S ^ i s t h e sum o f s q u a r e s  i s t h e number  population  boats  o f e x p l o i t e d access  variance  among q u e u e s ,  there  be d e r i v e d  i s no  a t access  and V(CPUE)  Since  t h e moment  k'  equations  - C /(T[E  are equalized  The t o t a l  so £SS^ i s d i v i d e d by t h e p o p u l a t i o n analogous  to those  point i ,  i s the predicted  mean c a t c h e s  "among" sum o f s q u a r e s .  f o r parameters  from  points  o f v e s s e l catches.  i s represented, Expressions  can  f o r the v e s s e l catches  population of  size.  o f the negative  binomial  (49)  - 2s +  Z  l/n ] ±  -E)  i-1  s a'  = E /(x[E  - 2s +  Z 1/njJ i-1  - E)  59)  123 k',  then,  (C =  i n c l u d e s t h e salmon abundance  (l-b)pN).  The v e s s e l d i s t r i b u t i o n  brackets.  I f a l l vessels fish  expression  i s zero,  uniform 2)  (E  As e f f o r t  t h e e x p r e s s i o n becomes k' v a l u e s .  - 2s) o f f s e t s  driving scale  process  £l/n^.  catch  observed  average did  queues.  n o t always  Consequently, effort This  f o r each  (< 109 v e s s e l s )  indicated  per  s e t changed  small),  the f l e e t  line-up of  value of the physical  size  and the  a random  errors  (equation 45).  sample  T = 5 0 0 0 was u s e d  30) a n d r e p r e s e n t  entered  between  per  opening  distributions. A t low  f o r a l l other  to d u p l i c a t e the scale  the r e l a t i o n s h i p  lengths at  overflight  of overflights  of fleet  slip  to represent the  i n Figure  T h e number  The  f o r mean k ' s w e r e n o t i n c l u d e d .  x = 2000;  as p i n k s  59), the sales  o f the k  openings. response  t h e mean a n d v a r i a n c e  what h a d b e e n a p r e d o m i n a n t l y  of catch  sockeye  fishery. The  b a s i c form  characterized noted  opening reported  i n Juan their  o f the k response  was d u p l i c a t e d .  by d i s c r e p a n c i e s between observed  (cf. Figure  8).  A t those  de F u c a  Strait  total  a  resulting i n  the negative  using equation  are presented  was n e c e s s a r y  that  indicating  2s ( a n a v e r a g e  model p r e d i c t i o n s f o r queue  f o r each opening.  standard  manipulation  k' i s n e g a t i v e  r o u n d e d u p a n d down i n o r d e r  constitute  and  flight  point levels  The r e s u l t s  k' v a l u e s  effects  E "= s , t h e b r a c k e t e d  a' does n o t r e p r e s e n t  abundance) b u t r e f l e c t s  and access  model p r e d i c t i o n s were discrete  i s -E.  two e x t r e m e s ,  and the o v e r f l i g h t  effort  rate  distribution.  was c a l c u l a t e d  estimates  •  ( a n d £ l / n ^ becomes  The parameter  (salmon  s  i n c r e a s e s beyond  Between these  of i t s spatial k'  large  exploitation  i s captured by the expression i n  £l/n^ ^  and the denominator  distribution.  smaller  alone,  and f l e e t  times,  Openings  and r e p o r t e d e f f o r t are  vessels fished  part  or the n o r t h - c e n t r a l areas  c a t c h as Johnstone  Strait  fish.  o f the weekly and apparently  The d a t a  point at  124 224  vessels/k=l.3  reported catches out  of  their into  the  Reporting larger k's.  k'  departed  values  Within  generally sigmoid affected  the  to  fleet  ks.  A (1-b) effort  Although the  d u r i n g two the  both  of  by  k  r e p o r t i n g catches in  error. was  area produced Again,  smaller  vessels  contributing  CPUE  their  Reporting  (reported catch the  areas, the  to  the  distributions.  counterparts, 4 deviations  reporting errors  openings  this  high  low  The  cannot  of  be  and  size  the  explained.  overflights  sample  and,  made w i t h i n  among o p e n i n g s ,  distribution  included  as  fleet  c a t c h equal  to  have  and  5000 a t h i g h  distribution distribution  around  presumably,  s k i p p e r s may  this  k.  the  total  fished  of  differences  the  numerical  effort)  term  ks  k'  followed patch  response  fleet  the  of vessels.  effort  The  to  and  differently,  a  response total  stationary they  sizes. the  estimated  salmon abundance p r o d u c e d  Thus  skew t h e  the  c o r r e l a t i o n between  the  a constant  effort  Variability  same s a l m o n p o p u l a t i o n  increased.  of  fish.  also  labelled.  s m a l l number  c a t c h and  catch.  effort.  simulation with times  c l o s e to  was  upwards  fishing  ( x •= 2000 a t  o r d e r i n g o f k'  e x p l a i n s the  k  k'  skippers  good.  increased with  catch  exploited  and  reflected  response  t o k'.  biasing  variability  T levels  o f k'  t o k',  r e p o r t i n g out  and  very  season;  while  relative  other  counts  the  k  d i s c r e p a n c i e s caused  the  were q u i t e  response  to  of  area  data points are  reporting errors, and  opening  c a t c h as homeport  relative  while  fell  final  a r e a b i a s e d k'  effort  b e t w e e n k'  opening  results  the  catch)  in effort  differences  each  or  represented  the  decreased  into  low  the  Strait  increased k  two  from  Eight  Given  area  actual  Also,  k  the  catches  variability  from  Johnstone  area  than  arrived  represents  response  effectiveness.  of  exploitation  a rapid the  decrease  fishing  When q u e u e r e s p o n s e  among mean c a t c h r a t e s  rates i n k'  fleet errors  (the d e v i a t i o n s of  may were  the  as  125 predicted did  not  queue  change  It  2s.  positively system:  The to  E-2s  are  the  size  described  parameters  by  There rates are is  or  to  note  t e r m was  few of  Distributions were  by  i s no  the  represented  of  catches  direct  as  of  method  total  fleet  from catch  skewed  salmon d i s t r i b u t i o n  access  points  the  contribute  few  rates fleet  to  with  the  fish  are and  are  high. the  a  be  exceeds  100  exploitation rates. operations.  best 100  to  k'  response  Since  the  boats.  that  d i d not two  before  E  contribute  properties  waiting  times  set  of a  the  upper  sites.  means a n d  dissimilar  rather  than  variances  Poisson  of  a'.  index  the  the  i s not  CPUE.  Both v a r i a b l e s f o r k'.  inverse  of  the  l/(a'x) fleet  effort  of  of  aggregation  equivalent  to  c  and  since  points  still  The  effort  response  1/a'x  also  versus  Omitting  saturated  estimate  of  the  and  openings  may  x must be  model  is proportional  be  to  an  became  the  that index  obtained  estimation  rapidly (i.e.,  a  exploited  e x p l o i t e d access  overflight  catch  of  of e x p l o i t a t i o n  l a r g e number  outside  vessels.  An  estimates  functional equation  relatively  exploitation saturated assume  saturated  ( l a r g e r 1/a'T) i s i n d i c a t i v e  present  r e p o r t i n g e r r o r s , 1/ax  may  and  those  w e i g h t e d by  This  of  and  distributions  i n the  number  magnitude  approximately  that  at  distribution and  line-up  reflects  points  equal  the  contained  indicated  fact  for obtaining  at  fishing  the  distributions.  saturated  relative  average  This  aggregation  clumped v e s s e l  --  the  usually negative  gamma  A  of  manifestation)  actual vessel distributions  size.  size  that  aggregations  salmon abundance  exploitation  integral  e x c e l l e n t access  theoretical  a measure  their  f l u c t u a t i o n s i n k'.  there  on  from  significantly.  is interesting  reached  limit  lengths  of  from  test  results constant),  a b u n d a n c e when  i t  effort  126 Discussion  The  critical  directly  assumption  access  supporting  evidence  point catch rates was  Model r e s u l t s  parameter  c coincided with  behavior. and  According at  appear  to  assertions.  In  on  tide.  flood  the  of  was  negative  confounded by  T h e r e was result  a  a  similar  was  the  result  of  the  that  the  fish  spread  more c o n c e n t r a t e d also  reflect  fishery  the  during  the  fishery.  and  schools) change  the  this dynamics  28  mirrors  catches  of  fisherman  d i s p e r s e d on  apparent  a new  the  the  ebb  skipper's  usually  appeared  patterns  as  a  abundance  of  the  season  were  subset  and  in  of  effort  abundance.  lifted.  This  salmon and  and  a  i s postulated, i t  increased.  and  and  salmon  abundance  g r e a t e r volume  i n species composition.  the middle  of  c,  c o r r e l a t i o n between c  between e f f o r t  occupied  index  boundaries  of  I f the  the  cause/effect relationship  out  The  of  skewness parameter,  fishing  inclusion  correlation  distribution-abundance  are  the  correlation with  i n c as  reflected into  fish  with  interval).  salmon and  largest  c o r r e l a t i o n between the  vulnerabilities a  agrees  of  not  information  assumption:  Figure  the  w h i c h was  skewness.  sudden change  probably  the  one  the b e g i n n i n g  this  opening.  analysis,  result  queue/salmon d i s t r i b u t i o n The  the  time  at  accounts  fishermen,  logbook That  support  and  perfect  (catch per  anecdotal  the  the b e g i n n i n g  to  model,  possess  discussed i n detail  chapter.  the  overflight  tested, i s that a l l fishermen  concerning  tide  i n the  effort salmon appears  (rather than  forming  T h i s phenomenon  Pink  salmon e n t e r e d  were more a b u n d a n t  may the  than  sockeye. The result of  exploitation  was  supported  set catch  rates.  rate by  the  Since  (1-b) less effort  on  available  evident and  fish  saturated rapidly.  saturation of  CPUE a s  v u l n e r a b l e abundance were  This  a function correlated  127 and  e f f o r t was  saturated, Errors high the  weighted  the  CPUE c u r v e  in reporting  catch-abundance response  vessels.  If  operation  costs  situation), consider  the  of  vulnerable  100  as  boats  error.  abundance,  of  than advocate  optimum.  abundance w i l l  a  at  slope  abruptly  of  exploitation  monte c a r l o  100  intensive  decide rate  at  minimize  however,  B i o l o g i c a l m a n a g e r s may  i n the  and  labour  Economists,  structure  Their  of  the  exploitation rate  results  often  that  an  i s around  These  models,  the  error.  More  simulations response  stock-recruitment  indicated  that  contradictory  deterministic  be  80%  differences  this  of  i n the  the  a  responses,  function the  can  be  produce  explained  overflight  error  included  formulations,  or  errors  in variables  research and  a  compensatory  e f f o r t do  not  of  variable  relationships  with If  the  salmon run  timings,  between weekly  was  vulnerable  abundance. the  A  weekly  annual  c a t c h a b i l i t y and  the  required.  weekly,  effect.  change w i t h  is  by  and  exploitation-effort relationship  produce to  preserved.  i n the  r e l a t i o n s h i p between annual be  error  r e s u l t s may  components  is  indicated  models which  d e p e n s a t o r y when e f f o r t i s c o r r e l a t e d  exploitation  the  errors the  salmon p r o d u c t i o n  the  correlation will  responses  numerical  increasing  r e l a t i o n s h i p between c a t c h a b i l i t y ( ( l - b ) / E )  abundance w i l l negative  (rather  well.  effort variable  measured without The  The  e f f o r t saturated  maximize  (1981) p r e s e n t e d  i n the  stock-recruitment the  to  to  large;  q u a l i t a t i v e forms.  that  area,  i s too  q u a l i t a t i v e form  observation  fact  the  exploitation  increased.  this conclusion.  into  rates  i s probably  the  differences  while  r e l a t i v e abundance  affect  catch  maximum  assumed e r r o r  Ludwig  the  CPUE i n d i c e s  fish.  and  false  that  The  Walters  as  not  exploitation  s o c i a l aspects  of  that  do  reporting  vessels  level  the  flattened  producers wish  effort  i n the  relationship.  of  at  100  heavily  catches  e f f o r t involved  The  too  salmon  annual  salmon  annual  salmon abundance  and  128 weekly  effort  levels,  variable  vulnerabilities  and t h e number  and l e n g t h o f  openings. The  fishermen  distribution abundance be  an  equal  abundance  increases.  to the volume  overflight  Indeed,  fishery:  model  supported  by p r e v i o u s  fulfilled  a priori  accounts.  The  through  spatial  decreases.  If  the f i s h  the f l e e t .  will  A l l other  e t c . ) Peterman and not hold here:  the f i s h  may  the  not decrease  exploitation  Steer's ratio as  remained  fish  fairly  levels.  was  appears  small;  to represent  t h e component  the dynamics o f the  assumptions  were  and the dynamics o f the e s t i m a t e d  p r e d i c t i o n s based  upon  independent  o b t a i n e d by compounding  the v e s s e l d i s t r i b u t i o n s  and A u s t i n  CPUE d i s t r i b u t i o n s  catchability variance  being  of their  case,  data  the v a r i a b l e  appear to support  moment e s t i m a t e ,  (1983) s t a t e d t h a t  with  decreasing  fish  negatively related CPUE d i s t r i b u t i o n s  correlations  when c a t c h a b i l i t y  between  i s constant.  and  parameters  anecdotal  catching the  overflight  i n c r e a s e d skewness abundance  t o N.  They a l s o  tended  skewness I f C/E  (N)  ( s m a l l e r k)  i s consistent with  s t a t e d that the  t o b e p r o p o r t i o n a l t o N.  o r k and N  = qN  and k  s h o u l d be  i s expressed  expected as i t s  then  k  where  by  the  structure. Bannerot  this  by  may  as c d e c r e a s e d ,  analyses  results  fished  catchability  output  observation error  level,  occupied by  run timings  occupied  for equivalent effort  The  of  lengths,  f o r depensatory  swept  model  i n c r e a s e i n the volume  (opening  o f volume  effort  c o n t r a c t as abundance  i n c r e a s e i n the volume  (1981) mechanism  process  f o r a given  will  i n c r e a s e s , any  being  constant  that,  of the f l e e t  t r a c k e d by  things  state  T i s the constant  -  (qN) /( N 2  T  - qN)  of proportionality  -  q N/(x-q)  f o r the  2  variance-abundance  In even  129 relationship. decreases) initially C/E  I f C/E s a t u r a t e s w i t h  and the v a r i a n c e increase with  constant.  These  increasing  continues  N and then  arguments  n  i=li-1  C^ a n d  a r e c a t c h and e f f o r t  unpooled  data,  C/E  Johnstone  as  C/E, t h e n ,  k  effort  were  at high  distributions changing  of fleets  distributions  variable,  scientists  fleet  changes  i n the size  Attempts  size  and d i s t r i b u t i o n  catches  that i s randomized with  be supported.  the t i d a l  the s t r a i t  catchability  from  from  cycle;  R f o r the  f o r t h e maximum x varied.  from  In  (represented were  other  areas);  a n d CPUE s a t u r a t e d  the sizes  as v a r i a b l e s  and  spatial  CPUE d i s t r i b u t i o n s . i s viewed  predictive  as a random  equations  which  c o u l d be r e l a t e d t o  as salmon d e p l e t i o n w i t h i n a  skippers, tides decreasing  If  p o p u l a t i o n a n d x.  I t i s impossible  over  o f N.  ( t h e k' e s t i m a t e s  patches  of the vulnerable f i s h  cannot  vary  fish  to quantify exploitation  o f the range  o f abundance.  and the k estimates  opening  rates  effort  d e v i a t i o n s o f CPUE k e s t i m a t e s  include  that  f o r boat i .  salmon abundance  should monitor  of exploited  index  indicated  model p r e d i c t e d depensatory  fisheries  with  For their  f o r most  calculated  reported into  a function of catch per set indices Perhaps  constant  the value  This result  catch); k d i d decrease  overflight  relationships.  was c o r r e l a t e d w i t h  u p w a r d when c a t c h e s  increases  measurements  s h o u l d have been a good  - N comparison.  Strait,  total  biased the  was e s s e n t i a l l y  - N c o m p a r i s o n was g r e a t e r t h a n  likelihood  as  N.  should  •  a n d A u s t i n d i d n o t comment o n t h e s e  estimated  k  B+l  Bannerot  of  then  = qN o r aN  i  i-1  catchability  N,  as t h e v a r i a n c e  n  i  -1.  catchability  require  E (Cj/EiVn - lC /lE  0 > B >  (i.e.,  to increase with  decrease  n  where  N  t o o b t a i n a sample and access  trends  fishing  ofset  points.  i n within-opening  Catch  130 catches the  p e r s e t may  lunar  multiple  just  calendar. openings  reflect  I f total  and the t i d a l  depletion  or exploitation  desirable  spots  The  plot  counts  Figure  Figure slip  8 exhibits  26.  effort  catchability  from  the o v e r f l i g h t  a near  effort  flights  constant  the response  estimates  will  but the general  measurements.  k ' was e s t i m a t e d  decreases.  The  of effort  process.  be c o n s i d e r e d a  provides  an  important  for aerial  independently  o f t h e k-E r e s p o n s e are substituted  independently  The  effort  be c l o s e t o t h a t p r e s e n t e d i n  estimates,  estimates  to less  o f (1-b) t o t h e  k and kE were n o t e s t i m a t e d form  cannot  1:1 r a t i o  Similarly,  c h a n g e when o v e r f l i g h t  to  model were n o t  i n the f i t t i n g  graphical analysis  measurements;  sales slip  s t a n d a r d i z e d f o r salmon  may p r o v i d e b e t t e r i n f o r m a t i o n .  with  estimated  within  obtained f o r  e n t r a n t v e s s e l s move  measurements u s e d  effort  were  opening  means c o u l d n o t b e r e l a t e d  competition:  Yet, this  and s a l e s s l i p  independent,  these  rates estimated  of the e f f o r t  procedure.  conclusion:  cycles,  o f c a t c h r a t e s and e f f o r t  o f (1-b) v e r s u s  rigorous  o f s e t catches  d u e t o i n t e r f e r e n c e -- a v e r a g e  exploitation  independent  samples  of the f i s h i n g  a n d t h e mean c a t c h r a t e s w e r e  abundance  distributions  the p o s i t i o n  of sales slip  of sales w i l l not  f o r sales effort.  slip  CHAPTER  VII  GENERAL D I S C U S S I O N  The to  Johnstone  repeated  was  fishery  exploitation  d e s c r i b e d by  model  Strait  f o r beach  along  Beverton sets  and  and  fish  were  the  fish  exhibited different  biomass  gear  His  the  of  and  but  sales slip  fishermen of  Indeed,  should  as the  may  reflect  the  effects  of  change  in fish  and  opening  distribution a more sales  was of  at  the  skewed d i s t r i b u t i o n slip  model,  gauntlet  the  effect  the  as  taken  data  i n skewness  be  o f Kennedy  quantified  131  by  and an  supported  was  suspect. effect.  sites the  were  after the  of  high  season,  lifted  the  to  the  Sunday  uniform up"  context  leaving of  (1951) p o s t u l a t e s  independent  and  (Figure  According  i s "cleaned the  British  uniform  reach  Within  Keeping  in  competition  throughout  opening  salmon  It is  competition.  of v u l n e r a b i l i t i e s .  and  data  route.  they  that  Gardner  gauntlet  a more  that  indicate  effort  quality  competition;  o f an  fishery  gauntlet.  vessel distributions  beginning  of  competition  here  exploitation  before  exploitation  a  escapement  produces  subject  type  Fraser River  migration  of exploitation  theorem  can  the  c h a n g e o c c u r r e d when b o u n d a r i e s  a result  fish  and the  change  decrease  abrupt  the  are  the  are  a s s u m p t i o n was  i n c l u d e d the  competition  fish  This  functions of  again  models  salmon along  that exploitation of catches  once  salmon  presented  along  for catch  t h a t an  night  data  estimates  fact  skippers,  The  vulnerabilities  hypotheses,  route.  a major  parameter  vulnerability.  the  uniformly.  yet  approaching  abundance  distribution  28),  lines,  i n which  They p r e s e n t e d  fisheries  overflight  conceivable  the  (1957).  gauntlet  distribution  affects  Holt  migration  a c a t c h m o d e l b a s e d u p o n power  competition The  The  distributed  f o r the  Columbia.  their  open s e t  the  (1980) u s e d  i s a gauntlet  gamma  k.  the that  132 An dive  a l t e r n a t i v e hypothesis  below  the  behavior. and  nets  and  plungers  fish  d i v i n g under  from a  portions  of  particular The  sets  desirable  proportion  of  effort. moving where  The away  they An  may  boat  boat  as  s t r a t e g y was anecdotal  the  The  beach  sets  net.  Fishermen  turbulence  and  noise  w h i c h keep  net  i s pursed.  same f i s h  enter  are  not  the  The  follow  the  s a l m o n must  probably  not  the  vulnerable  high  field  evident  accounts, skill  at  "flips"  16  and  "flip"  pass  vulnerable  same p a t h  depth  and  at  The  The  number  constant.  areas  of  and  in a  into the  average  line-up  per  size  are  the  boat  curve  open s e t s  relating  perceived increased  F i s h e r m e n were  entering  less  exploiting  sets  Open s e t s  making  of  average  appeared  effort.  remained  graphs  more b o a t s w e r e  also  to  salmon v e s s e l s  i n the  22).  of vessels  line-up  the as  with  apparently  less desirable  spots  sets.  the  concerning  overall  the  observations, a l l levels  the  strategy  a maximize  logbook was  the  sites.  proportion  i s that  d i s p e r s a l of  line-ups  make more  From  Skippers'  salmon  the  s a l m o n do  the  line-up  fishermen with  fishery.  fish  under  indicating that  maximum l i n e - u p  areas  of  (Figures  effort.  The  could  the  the  s u p p o r t e d by  s i n g l e boat  from  escaping  only  a l t e r n a t i v e hypothesis  desirable effort,  but  concerning  one  desirable.  as  i s m i n i m i z e d by  phenomenon i n t o a c c o u n t :  underwater  Schools  effort,  high  from  boat  nets,  this  i s that  sites.  per  at high  at  the  population  fishing  and  increased  the  the  fish  create  spots.  a r e a s was  decreased  less  of  hypothesis  desirable  less  to  gauntlet  a l l fishing  line-up  e x p l o i t a t i o n competition  prevent  o f t e n use  at  e x p l o i t a t i o n competition  F i s h i n g s t r a t e g i e s take  rockpile sets  through  to  of  accounts  incorporated  of  number  the  the of  fleet sets  maximize  effort. and  movement o f  the  This  fact  overflight  i n the  sales  fishermen changed  strategy number was  to  at  less  high  entered  of  sets  supported  by  observations.  slip  model  as  a  gamma  133 variate.  The  o v e r f l i g h t model  Skipper/vessel catch per  per  set  much t o  e f f e c t s accounted  set.  and a  The  short  time  r e v i s e d model.  that  skipper/vessel  per  skippers  and  to  Columbia effort  take  and  but  salmon purse  cell  the  the  temporal  cells  the  trends  (rather  northwest  and  their  movement p a t t e r n s ,  t h a t movement  knowledge  and  within  Allocation analytical account:  catches  search of  tides,  multiple  strategies.  A l l o c a t i o n of  complexity.  Mangel  and  a brief an  the  an  found in  best  most p r o f i t a b l e s e t s  square)  as  areas.  implies  that  are  opening progresses  to  by  dynamics of  d i d not effort  points  and  across  (or the  a  by  this  the  and of  a  cells  movement  data  i n many o f  these  Mangel and  Clark)  vessels  The  large  parameter  were  their  the  moved scale  c  result  of  representation  fishery.  cell  queue  cells  acknowledged  the  effort  shape  within  of  search  definition  (i.e.,  b e c a m e more c l u m p e d ) . the  British  many s u c h  expected  presented  the  their  Their  According  factors considered  Clark  data,  variance  i n t r o d u c t i o n to  fishing  3 cells  effort  throughout  slip  the  catch  contribute  d e s c r i p t i o n of  Random e n c o u n t e r s  access  not  indicated that f o r the  in  information.  redistribution  cooperative  variance  compounded  percent  fishery.  and  theory)  p r o b l e m when t h e  30  good c a t c h e s  the  common s e n s e .  fisheries  km.  Strait  as  may  of  f i s h e r y as  18  and  therefore,  effects.  function of  explained  distribution  indicated  a  sales  than within  set  as  largest risks  i n c,  number d i m i n i s h e s  formulated  (1985), w o r k i n g w i t h  for multiple  Johnstone  the  d i f f e r e n c e s are  time  skill  of  Skill,  (1983) i n c l u d e d seine  include  5 percent  observations  real  (approximately  within  small  Clark  the  and  a l l o c a t i o n model  fishing exist  and  effect  Personal  based upon h i s t o r i c a l Mangel  Vessel  Ledbetter  b o a t week. learned  for only  intervals.  Hilborn  catch  explicitly  o v e r f l i g h t m o d e l was  opening: the  d i d not  i s an  enormous  fishermen sizes,  includes "curse  are  local  into  knowledge  another of  taken  level  and  of  dimensionality."  134 Yet  fishermen  niche  carve  i n terms  skill,  and  ability  do  to  of  out  traditional  quite  "think  by  one  unit  strategy fishing beach have  of  (and  and  the  In  the  seiners  fleet  and  Calkins  their  set  areas  (Pella  moved  group. the  the  and  conclusion increased  was  into  f o u n d new  of that  salmon  the  tuna. the the  skippers Francis  efficiency expansion  to  and  of  the  volume  the  open  the  swept  set  proportion  sets  of  the  away f r o m  per  boat  less  the  must  crowded  1967,  affect  the  fleet, fish  fishing  power. fish  into offshore  their  Tuna  and  search  the  area  i n terms  areas.  to  fishermen  was  much  that of  overlap  leave  revolution  unexploited,  data  that  search  were w i l l i n g  previously  fleet,  increased  (1977) e m p h a s i z e d  technological but  1963;  1960's  consequently,  of  the  Furthermore,  i n the  fishing  to  power o f  (Alverson  1971).  vessels  and,  of baitboats  effort  Rothschild  the  of  the  (1974) p r e s e n t e d of  the  and  rapid conversion  aggregations  seine  develop  therefore,  t o move o f f s h o r e  increased  s i m i l a r to  and  line  swept  m i n i m i z e d when some s k i p p e r s  Columbia  and  decreased.  seine  1975).  this  knowledge  they  l e s s d e s i r a b l e but  Chatwin  purse  as  area  a v e r a g e number  the  strategies also  s i t u a t i o n was  with  volume  c r u i s i n g speeds  Psaropulos  allowed  aggregations  of  and  running  distribution  and  local  d i s t r i b u t i o n s and, fishing  the  1950's  spatial  improvements  further offshore,  dispersion  late  Calkins  in fishing  British  moved  operations,  efficiencies,  The  in a of  The  way  measure  fish."  interference competition  1975;  (competition)  caught  competition,  their  vessel  advent  fleet  a f f e c t e d the  1963,  dimensionality,  F i s h e r m e n were a b l e  the  during  technological  changes  The  CYRA t u n a  purse  affect  conditions.  as  Direct  comes  drum) a f f e c t e d t h e  crowded  this  [non-random]  advances  utilized.  increased  areas.  when l u c k  a  effort.  within  information,  available fish  of  area  well  like  Technological proportion  a niche  the  within  larger  and  large  supported  the  catchability,  Individual vessels  were  135 doing better.  Both  innovations  disperse  did  not  to  this  possible.  At  the  to  queue  of  largest set  was  of  Although  The  the  overflight predicted  technological  Their  line-up  The  a  that  they  behavior  the  model this  general  by of  to the  nominal,  of  line-ups  the  set  the  fact  unit  of  as  various  from  of  the  rates.  during  A  conclusion  that  access  that  tests  flood that  of  distributed in  directional  and  tides.  queue  information  lengths  the  quality  apparently  concerning  a near  the d i s t r i b u t i o n  competition.  vessel  dispersion  linear fleet  Predicted  to  relationship size.  exploitation rates  effort.  many  detailed interpretation  evident,  and  underlying  descriptions  were  d i s t r i b u t i o n s were  fleet  would  historical,  and  were  hypothesis  created  sets  fishermen  mechanisms  salmon seines  frequently  was  made o p e n  impossible.  of variance  the  ways.  exploitation rates  resulting interference  made b y  illustrated  innovations  decreased  information  competition  small sets  good  i n two  chapters provided  Analysis  catch  fleet  l i m i t e d number  previous  supported  the  interference  as  fisherman behavior  local  to  seine  s c a l e movement p a t t e r n s  data to  B.C.  d i s p e r s a l was  non-random v e s s e l  salmon and  number  by  fish.  saturation  a p p e a r e d most  responses  characterized  between  and  Large  logbook  fleet  vulnerable  areas  point,  assumptions.  responses  good.  p r o d u c e d by  the  have d i s c u s s e d  results provided  quite  used  fishermen maintain  increased  per  Past  assumptions.  catches  of  measurable these  catch  fish  fashion.  Analysis are  of  d i s t r i b u t i o n s indicated that  a non-random the  of  traditional  length  fleets  B.C.  confinement w i t h i n  scientists  departures  these  affected  areas.  fleet  "random b e h a v i o r " of  average  some t h r e s h o l d  Fisheries possible  but  aggregations  exploitation rate  desirable  h a v e b e e n due points.  large  salmon  areas,  competition  the  But,  less  new  B.C.  perception.  Interference Historically,  CYRA a n d to  e n c o u n t e r new,  reflected  entered  the  The  cannot  be  exploitation  136 saturated  as  e n t r a n t v e s s e l s moved  into  less  d e s i r a b l e areas;  catchability  decreased. Analysis may  be  o f CPUE d i s t r i b u t i o n s  reflected  boat.  But,  variance fashion  by  changes  a major problem  of  the  and  t h a t changes  in  catchability  distributions  of  catch  i n the  frequency  may  encountered  be  CPUE d i s t r i b u t i o n s  independently  indicated  of  can  fishing  during  fluctuate  effort,  future analyses:  i n an  fish  per the  unpredictable  abundance  or  catchability. In within were  summary, the  incorporated  An  responses  effort  not  exploitation  and  of exploitation  population  of  model  fishery, The than  power o f  o f CPUE a n d  i s that access  resulting,  relative  the  access  major problem once.  debris In  after the  and  historical  m o d e l was  rates to e f f o r t .  index  of  abundance  (1957) w i l l  rates to  a level  not  and  90%  of  This  model  fishermen  and  parameter  produced  Catch  capture  below  of  Model  information  behavior  assumptions  proposed.  of vessels. good  random  the  per  exponential  the v e r y the  unit  rapid  vulnerable  fish.  fishing  distributions  Holt  exhibit  the non-random b e h a v i o r  distribution  p r o p o r t i o n a l to an  of Beverton  The  exploitation  that competition of  d i d not  salmon f i s h e r y .  the  saturation  The  fishermen  regarding  concerning  saturating  formulation  the  alternative  indicated  was  and  Strait  assumptions  data  estimates  fish  Johnstone  rejected.  utilized  the  fleets the  fleet.  p o i n t s are parameter  setting  An  p o i n t a p p r o a c h may  a  tagging  access  assessed  important  identified.  estimates  is identifying  Perhaps  s h o u l d be  are  A  by  looking at  aspect  grid  avoided.  the  of  the  overflight  analysis  and  the  In  the  CYRA  tuna  work w e l l f o r l o g o r p o r p o i s e points  t h a t have been  a p p r o a c h w o u l d work as  each  fished  sets. more  s k i p p e r marks  on i t .  large search  fisheries  f o r tuna  and  h e r r i n g , the  overflight  the  137 m o d e l may  describe  high  effort.  will  be  very  fulfill effort  dynamics  Information uncertain.  levels  saturation probably  due  have  not  Hold to  about  in fisheries  fish  small  fisheries,  the  fisheries and  function of where  will  handling  skippers'  spatial  overflight  exhibit  about  exploitation  at  for exploiting  i s not  intense.  of  areas  model w i l l low  fish rate  Exploitation rates  skill  competition  periods  search  fisheries  information  times.  during  i n large  Developing  accumulated h i s t o r i c a l  limited  sub-area  distributions  predictive role.  satiation  primarily a  i n a very  In other  a d e s c r i p t i v e or  distributions.  regions  the  are  local  not  LITERATURE  A c h e s o n , J . 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