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Comparative fish population studies Ni, I-hsun 1978

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COMPARATIVE FISH POPULATION STUDIES  BY I-HSUN £ 1 National  Taiwan U n i v e r s i t y , 1S69  B . S c , National  Taiwan U n i v e r s i t y , 1972  B.Sc.,  A THESIS SUBMITTED IN PABTTAL FULFILIHENT OF THE REQUIREMENTS FOB THE DEGREE OF DOCTOR OF  PHILOSOPHY in  THE FACULTY OF GRADUATE STUDIES {Department o f Zoology)  Be accept t h i s t h e s i s as conforming to the required  standard  THE UNIVERSITY OF BRITISH COLUMBIA March, 1978  (^T^L-hsun N i , 1978)  In  presenting  an  advanced  the I  Library  this  degree shall  f u r t h e r agree  for  scholarly  by h i s of  this  written  at make  that  thesis  it  may It  is  University  British  1978  of  Columbia,  British  by  for  gain  Columbia  shall  the  that  not  requirements I  agree  r e f e r e n c e and copying  t h e Head o f  understood  Zoology  of  of  for extensive  permission.  of  fulfilment  available  be g r a n t e d  financial  2075 Wesbrook P l a c e Vancouver, Canada V 6 T 1W5  Date  freely  permission  purposes  for  in p a r t i a l  the U n i v e r s i t y  representatives.  Department  The  thesis  of  or  that  study.  this  thesis  my D e p a r t m e n t  copying  for  or  publication  be a l l o w e d w i t h o u t  my  ABSTRACT This  project  variability  i n fish  population  designed  populations.  patterns should  (phylogenetic  patterns} ,  p a t t e r n s ) , and should  was  be  their  detected  f  size  at  and  life  My h y p o t h e s i s  i s that  distributions.  the natural mortality ( L M ) , age a t f i r s t  weight-length (T95) ]  which  (f a u n a l patterns  parameters coefficient  m a t u r i t y (TM),  exponential are  concepts  These  population  of  specific  considerations  maturity  span  patterns  zoogeographic  by c o m p a r i n g c e r t a i n  first  the  evolutionary  vertical  s i z e a t age 1 (L1) , t h e (b) ,  study  be r e l a t e d t o  [growth parameters (K, L I N F ) , (H)  to  coefficient  intrinsic  biological  features of the population. Comparative published  fish  methods  were  population  used  to  analyze  data  s t u d i e s by c o m p a r i n g f i s h  from  population  parameters, i n d i v i d u a l l y , i n p a i r s ( r a t i o o r l i n e a r r e g r e s s i o n ) , or grouped t o g e t h e r classification differences into  { d i s c r i m i n a n t a n a l y s i s or Cooley and tonnes*  method), i n o r d e r t o  find  the  among d i f f e r e n t c a t e g o r i e s , a n d t h e n t o g r o u p  or these  patterns. Published data  families  (171  provided  species)  of  682  parameter  fishes.  would  volume o f d a t a .  a l l the analyses  families  Cyprinidae, Percidae,  Therefore,  with  large  Engraulidae, Pleuronectidae,  sample  be  records  from  Hy f i n d i n g s s u g g e s t e d  more s a t i s f a c t o r y r e s u l t s  15  similarities  obtained  sizes  Gadidae, Salmonidae,  from  a  43 that  greater  were b a s e d m a i n l y {Bothidae,  Hiodontidae, Sciaenidae,  on  Clupeidae, Osmeridae, Scombridae,  Scorpaenidae,  Sparidae,  Sample  sizes,  and  Sgualidae).  mean  values,  standard  errors,  c o e f f i c i e n t s of v a r i a t i o n f o r p o p u l a t i o n parameters and characters  of  the  15  families  summary t a b l e . These data results  would  of  fishes  enable  relative  are l i s t e d  the  and  i n the  extrapolation  based on many areas f o r management of o t h e r f i s h  of  stocks  where data are l a c k i n g . In the m a j o r i t y of f a m i l i e s s i g n i f i c a n t relationships and  between  asymptotic maturity  were  found  M-—K. length  This  means  that  fish  (LINF)  also  have  a  larger  length i s  a  greater  size at  first  (M) , and  a  reached.  the F - t e s t and t h e a p p r o p r i a t e t - t e s t as a b a s i s f o r  comparison of v a r i a n c e s and  means of i n d i v i d u a l  parameters,  it  evident t h a t i n most cases t h e r e are s i g n i f i c a n t d i f f e r e n c e s  between f a m i l i e s . T h i s confirms one that  having  (LM), a lower n a t u r a l m o r t a l i t y c o e f f i c i e n t  Using  regression  between 1/K—LINF, between LM—LINF,  lower r a t e (K) a t which the asymptotic  is  linear  differences  between  of  families,  my as  hypothesis; shown  by  namely  population  parameters, e x i s t from p h y l o g e n e t i c c o n s i d e r a t i o n s . By comparing the f o u r c h a r a c t e r s the f i s h f a m i l i e s can A)  Shoaling  pelagic  (K, LINF, LM,  and  be d i v i d e d i n t o the f o l l o w i n g groups: fishes  -  Engraulidae,  Clupeidae,  Osmeridae. These f a m i l i e s have the highest K v a l u e s Engraulidae, LM, B)  over  0.-4  pelagic  fishes  moderately high K value  and  (1.6 f o r  f o r the o t h e r s ) , the s m a l l e s t LINF,  and a very high LM/LINF r a t i o  Large  LH/LINF)  -  (over  Scombridae.  (around  0.35)  0.7). This  and  family  has  the l a r g e s t LINF.  a  iv  C)  Demersal  fishes  Sparidae 0.25),  -  Gadidae,  Pleuronectidae,  e t c . These f a m i l i e s have low K intermediate  LINF  size,  Scorpaenidae,  values  and  lower  {less  LM/LINF  than ratios  {less than 0.6). D)  Freshwater f i s h values but  which  - Cyprinidae. are  h a s a s m a l l e r LM  LK/LINF  family  s i m i l a r t o those length  (0.4) and TH/T95  Stepwise  This  and,  has  especially,  classified  could  be  families.  C o o l e y and  utilized  among  correctly  Lohnes*  species  ranged  within  from  620  classification 5  major  Cyprinidae, Gadidae, P l e u r o n e c t i d a e ,  the  5 8.6%  and  p a t t e r n s by e x a m i n a t i o n  cases  the r i g h t  method  was  Scombridae).  (Pleuronectidae) the  of population  out  affinities  among t h e 15 f a m i l i e s . the  between  ecological, families.  rather  also  (Clupeidae, Correct to  87.6%  existence  of  parameters.  C l u s t e r a n a l y s i s based on 7 p o p u l a t i o n p a r a m e t e r s  brought  lowest  considered  into  families  ( C y p r i n i d a e ) . These r e s u l t s f u r t h e r confirmed  closeness  fishes,  d i s c r i m i n a n t a n a l y s i s b a s e d on 7 v a r i a b l e s i n t h e  independently  the  LINF  (0.2) r a t i o s .  the  population  and  of t h e demersal  15 f a m i l i e s showed t h a t o v e r 90% o f  classification  K  displayed  Dendrograph r e l a t i o n s h i p s than  the  systematic,  V  TABLE OF CONTENTS ABSTRACT ................... ...... ..................... , . i i TABLE OF CONTENTS  .  ..  L I S T OF FIGURES  V ..  v i i  L I S T OF TABLES  ... i x  ACKNOWLEDGEMENTS  . . . . . . . X  I INTRODUCTION ...... ....... ..... . .... ............. ... ..... 1 I I BASIC THEORY OF FISHING  5  I I I RESEARCH APPROACH : COMPARATIVE POPULATION STUDIES ....15 1. A g e i n g P r o b l e m  ..................................... 15  2. F e a t u r e s o f P o p u l a t i o n  P a r a m e t e r s .................. 17  3. U n r e a l i t y o f t h e U s a g e o f P o p u l a t i o n  Parameters  IV MATERIALS AND METHODS  ....19  ......22  1. R e s e a r c h Scheme  ...22  2. S u r v e y Data  24  3. M a t e r i a l s ............................ .............. 26 4. M e t h o d s o f A n a l y s i s  44  Y CHARACTERISTICS OF POPULATION PARAMETERS ................ 47 1. I n d i v i d u a l P a r a m e t e r s .............................. 47 2. R e l a t i v e C h a r a c t e r s  ................................ 65  3. C o r r e l a t i v e C h a r a c t e r s  ............................. "75  V I POPULATION PATTERNS .................................... 87 1. C o m p a r i s o n  between F a m i l i e s  87  2. C o m p a r i s o n  among F a m i l i e s  89  3. C l a s s i f y i n g  Families  4. C l a s s i f y i n g F a m i l i e s  (Discriminant Analysis) ( C c o l e y and Lohnes*  5. C l o s e n e s s among F a m i l i e s  .......97  Method) ... 105  (Cluster Analysis)  ........108  vi  V I I GENERAL DISCUSSION  111  A. Comments on C o m p a r a t i v e S t u d i e s B. D i s c u s s i o n o f t h e R e s u l t s C. F u t u r e  111  .......................... 114  Studies  V I I I CONCLUSIONS  ......131 ................134  I X LITERATURE CITED  137  X APPENDICES ................ ......  138  vii  L I S T OF FIGURES Figure  Page  1.  R e s e a r c h scheme  2.  The  3.  4.  5.  6.  7.  8.  9.  10.  11.  12.  13.  14.  23  e s t i m a t i o n o f g r o w t h p a r a m e t e r s by f i t t i n g o f von B e r t a l a n f f y growth e q u a t i o n from a g e - l e n g t h d a t a .  25  Mean v a l u e s , 9 5 % c o n f i d e n c e l i m i t s , r a n g e s , and s a m p l e sizes among species within families f o r the i n s t a n t a n e o u s n a t u r a l m o r t a l i t y c o e f f i c i e n t (M) .  48  Mean v a l u e s , 95% c o n f i d e n c e sizes among species growth parameter K  50  limits, within  r a n g e s , and s a m p l e families f o r the  Mean v a l u e s , 95%. c o n f i d e n c e l i m i t s , sizes among species within a s y m p t o t i c l e n g t h (LINF)  r a n g e s , and s a m p l e families f o r the  53  Mean v a l u e s , 9 5 % c o n f i d e n c e l i m i t s , r a n g e s , and s a m p l e sizes among s p e c i e s w i t h i n f a m i l i e s f o r t h e s i z e a t f i r s t m a t u r i t y (LM)  56  Mean v a l u e s , 9 5 % c o n f i d e n c e l i m i t s , r a n g e s , and s a m p l e s i z e s among s p e c i e s w i t h i n f a m i l i e s f o r t h e age a t f i r s t m a t u r i t y (TM)  58  Mean v a l u e s , 9 5 % c o n f i d e n c e sizes among species l e n g t h a t a g e 1 (L1)  60  limits, within  r a n g e s , and s a m p l e families f o r the  Mean v a l u e s , 9 5 % c o n f i d e n c e l i m i t s , r a n g e s , and s a m p l e sizes among species within families f o r the w e i g h t - l e n g t h e x p o n e n t i a l c o e f f i c i e n t (b)  61  Mean v a l u e s , 9 5 % c o n f i d e n c e l i m i t s , r a n g e s , and s a m p l e s i z e s among s p e c i e s w i t h i n f a m i l i e s f o r t h e ' l i f e s p a n * (T95)  63  Mean v a l u e s , 9 5 % c o n f i d e n c e l i m i t s , r a n g e s , and s a m p l e s i z e s among s p e c i e s w i t h i n f a m i l i e s f o r t h e r a t i o M/K  68  Mean v a l u e s , 9 5 % c o n f i d e n c e l i m i t s , r a n g e s , and s a m p l e s i z e s among s p e c i e s w i t h i n f a m i l i e s f o r t h e r a t i o LM/LINF  70  Mean v a l u e s , 9 5 % c o n f i d e n c e l i m i t s , r a n g e s , and s a m p l e s i z e s among s p e c i e s w i t h i n f a m i l i e s f o r t h e r a t i o L1/LINF  72  Mean v a l u e s , 9 5 % c o n f i d e n c e  limits,  ranges,  and sample  viii  s i z e s among s p e c i e s w i t h i n TM/T95 15.  16. 17. 18. 19. 20. 21.  22.  23.  24.  families  f c r the r a t i o 7 4  Mean v a l u e s , 9 5 % c o n f i d e n c e l i m i t s , r a n g e s , and s a m p l e s i z e s among s p e c i e s w i t h i n f a m i l i e s f o r t h e r a t i o T50/T95 Linear regression families Linear regression families Linear regression families Linear regression families Linear regression families  analysis  between  1/M—T95  7 4  within 7 7  analysis  between  1/K—LINF  within 7 9  analysis  between  LM--LINF  within 8 1  analysis  between  L1—LINF  within ^  analysis  between  1/M—T95  2  within 8 4  Mean v a l u e s , 95% c o n f i d e n c e l i m i t s , r a n g e s and s a m p l e sizes o f i n d i v i d u a l p a r a m e t e r s among 5 f a m i l i e s (group I ) Mean v a l u e s , 9 5 % c o n f i d e n c e l i m i t s , r a n g e s and s a m p l e sizes o f i n d i v i d u a l p a r a m e t e r s among 10 f a m i l i e s (group I I )  9 0  9 2  Mean v a l u e s , 9 5 % c o n f i d e n c e l i m i t s , r a n g e s a n d s a m p l e sizes o f c o r r e l a t i v e c h a r a c t e r s among 5 f a m i l i e s (group I) Mean v a l u e s , 9 5 % c o n f i d e n c e l i m i t s , r a n g e s and s a m p l e s i z e s o f c o r r e l a t i v e c h a r a c t e r s among 10 f a m i l i e s (group I I )  94  ^  9 5  99  25.  Discriminant analysis  i n 5 families  26.  Discriminant analysis  i n 10 f a m i l i e s  27.  Discriminant analysis group II)  in  15  (group I ) (group I I )  families  (group I and 1 0 2  L I S T OF TABLES Table  Fage  1.  Collected data populations  2.  Sample sizes of i n d i v i d u a l p a r a m e t e r s and r e l a t i v e characters i n f a m i l i e s analyzed  3.  Summary t a b l e o f mean v a l u e s , sample sizes, standard errors, and coefficients of v a r i a t i o n for i n d i v i d u a l parameters i n each f a m i l y  j  on  population  parameters .  in  fish  a.  Summary t a b l e o f mean v a l u e s , sample sizes, standard e r r o r s , and c o e f f i c i e n t o f v a r i a t i o n f o r r a l a t i v e c h a r a c t e r s i n each f a m i l i t y  5.  Summary table of l i n e a r correlative characters  •.. (  f  8  6  regression analyses f o r 5 w i t h i n f a m i l i e s ..........  6. ' The c o r r e l a t i o n m a t r i x between p a r a m e t e r s d a t a o f 15 f a m i l i e s  f o r combined  88 7.  The F - t e s t  and t h e t - t e s t between  families  8.  Discriminant  analysis  i n 5 families  9.  Discriminant  analysis  i n 10 f a m i l i e s  98 (group I) ........  98 10.  Discriminant analysis in g r o u p I I combined)  11.  C l a s s i f i c a t i o n function with 7 variables f o r each f a m i l y i n d i s c r i m i n a n t a n a l y s i s .................  12.  Summary  13.  C o o l e y and L o h n e s (qroup I)  table  15  (group I I ) ......  of discriminant  1  families  analysis  classification  in 5  I  and  families families 1  Cooley and Lohnes' classification f a m i l i e s (group I I )  15.  Cooley and families  16.  Summary table analysis method  17.  f o r 15  method  14.  Lohnes classification (group I I and g r o u p I I ) 1  of and  (group  method  method  in  in  10  l f )  15  i n  the r e s u l t s from discriminant Cooley and L o h n e s * c l a s s i f i c a t i o n  Dendrographic r e l a t i o n s h i p s  0  15 f a m i l i e s  ,  _  , i  among  6  U  n  R  B  ^ ®  X  ACKNOWLEDGEMENTS I  would  supervisor. and  able  like Dr.  t o help  to  express  my  deep  willing  and  criticism  of  my  c o m m i t t e e members. D r . H. D. F i s h e r , D r . W. S. H o a r , D r . McPhail.  During t h i s study I received individuals.  For t h e i r  help  valuable  and  encouragement  suggestions,  t o t h a n k D r . P. A. L a r k i n , Mr. N. G i l b e r t , D r . Dr.  my  me.  G. C. Hughes, and Dr. J . D.  many  to  Norman J . W i l i m o v s k y , f o r a l w a y s b e i n g  I am g r a t e f u l a l s o f o r t h e a d v i c e thesis  appreciation  «3.  McLeod  and  C.  I would J.  with  me,  l a m  like  Halters,  D r . H. Khoo. F o r s p e n d i n g much t i m e  over e a r l i e r d r a f t s o f t h i s t h e s i s  from  pcring  especially  g r a t e f u l t o Ms. Wendy C r a i k , Ms. J u d y Mah, and Mr. Sam G o p a u l .  1  Fish,  protein-rich  most important fishing  food  and  renewable, c o n s t i t u t e s one o f the  resources  f o r human  beings.  i s one o f man's o l d e s t occupations and has a continuous  h i s t o r y of e x p l o i t a t i o n o f these resources. dynamics  Therefore,  of  fish  populations  i s among  The  study  the  of the  o l d e s t and most  advanced aspects of man's s c i e n t i f i c s t u d i e s . There a r e s e v e r a l important  questions  that  need t o be answered when c o n s i d e r i n g  the e x p l o i t a t i o n of f i s h r e s o u r c e s . How do we use wisely?  What  i s the  increasingly  a c t i v i t i e s , through d i r e c t populations?  serious  exploitation,  the  resource  e f f e c t t h a t nan's  are  having  on  fish  How do we estimate t h e biomass of f i s h and p r e d i c t  c a t c h i n order t o o b t a i n a s u s t a i n e d y i e l d ? How do we provide an adequate s c i e n t i f i c b a s i s f o r c o n s e r v a t i o n ? Intelligent the  dynamics  fishery  management r e g u i r e s sound knowledge  o f f i s h p o p u l a t i o n s . An e s s e n t i a l f e a t u r e of t h i s  theory i s the y i e l d eguation  which r e l a t e s the o b t a i n a b l e  to  as  such  stock  parameters  of  understanding are  fishing.  In  natural other  mortality  words,  i t includes  that  can  and an  stocks  and how t h e i r y i e l d s a r e r e g u l a t e d , the e f f e c t s  of f i s h i n g on a stock, and t h e k i n d s , g u a n t i t i e s fish  rate  of the b i o l o g i c a l mechanisms by which f i s h  maintained  yield  t h e number o f r e c r u i t s , r a t e o f  growth at v a r i o u s stages of l i f e , intensity  of  be  taken  on  a  and  sizes  of  c o n t i n u i n g b a s i s by d i f f e r e n t  amounts and/or kinds of f i s h i n g . F i s h e r y science a l s o endeavours to e x p l a i n the causes of h i s t o r i c a l changes i n t h e f i s h e r i e s and t o p r e d i c t the f u t u r e s t a t e  of  stocks  and  yields  f o r given  2  conditions pressure. applied  of  the  "Fishing for  environment models '  and  have  1  intensities  already  been  of  developed  over t h i r t y years. These models have worked  w e l l d e s p i t e the f a c t t h a t some of the assumptions the models are not One  of  Many approaches have raised  direction  fairly  inherent  in  the t a s k s before modern f i s h e r i e s b i o l o g i s t s i s to  c a t c h b e t t e r and  frequently  and  true.  improve these models or to f i n d predict  fishing  the  effort  more  reliable  to save time i n e s t i m a t i n g  been is:  new  tried.  "is  it  should  As  a  result  models  to  parameters.  the  question  p o s s i b l e to determine i n which  be  concentrated  in  order  to  e l i m i n a t e randomly d i r e c t e d attempts?" One  of  the primary i n s t i n c t s of a b i o l o g i s t i s t o  comparative  methods  comparative p h y s i o l o g y , order  that  (e.g. as etc.)  for  comparative  comparative  d i s s e c t the p o p u l a t i o n by a n a l y z i n g the r e a l i t y parameters.  population study which  fishing  i s to models  The  The  objective  of  and this  re-examine  the  fundamental  are  and  to  d i r e c t i o n the models should practical  organisms  may  P e c u l i a r to f i s h e r i e s b i o l o g y i s the great amount  of a v a i l a b l e data which makes p o s s i b l e  population  anatomy,  to s y s t e m a t i c a l l y produce f a c t s i n  s i m i l a r i t i e s or d i f f e r e n c e s i n l i v i n g  be d i s c o v e r e d .  utilize  based be  improved  methods  to  stability  of  comparative theory  determine  and  then  on  i n which  applied  in  situations. c h a r a c t e r i s t i c s of f i s h p o p u l a t i o n s e x h i b i t both common  properties variability  (homogeneity) of  fish  and  variability  populations  (heterogeneity).  depends  upon  The  genetic  3  constituents  as  well  as  envircnmental  factors. This project  i n v e s t i g a t e d the p a t t e r n s of v a r i a b i l i t y of f i s h hypothesis  i s that s p e c i f i c population  populations.  patterns sould be r e l a t e d  to e v o l u t i o n a r y concepts  (phylogenetic p a t t e r n s ) ,  considerations  patterns),  (faunal  These p a t t e r n s were examined parameters  [growth  by  parameters  and  vertical  comparing  and these the  fLM) , age  the weight-length  distributions. population  of von B e r t a l a n f f y growth model  maturity  (M), s i z e at  (TM) , length a t age  first 1 (L1) , (b) ]  r e l a t i o n s h i p exponential c o e f f i c i e n t  p o u l a t i o n parameters are i n t r i n s i c b i o l o g i c a l f e a t u r e s population.  the widely yield  at f i r s t  zoogeographic  certain  (K, LINF), the n a t u r a l m o r t a l i t y c o e f f i c i e n t maturity  My  The  c h a r a c t e r s chosen are d e r i v e d mainly from  used von B e r t a l a n f f y growth model  model or are r e a d i l y a v a l a b l e from the To  of  and  Beverton-Holt  literature.  e l u c i d a t e f i s h p o p u l a t i o n p a t t e r n s , comparative methods  were used i n the a n a l y s i s published  fish  of  population  population studies.  parameter  This was  determine whether the r e l a t i o n s h i p s between natural  mortality,  growth,  and  size  common p r o p e r t i e s .  were  into  then  grouped  patterns  s i m i l a r i t i e s or d i f f e r e n c e s . The population  patterns  exist  the  The  parameters maturity various  depending  in  itself,  be  Further,  the p h y l o g e n e t i c  parameters would serve as  an  studies.  patterns,  The  ecological  p a t t e r n based on  additional such  tool as  for for  of  fishes  confirmation that s p e c i f i c  would,  to  among  upon  their fish  significant  advancement of e x i s t i n g r e s e a r c h and l i t e r a t u r e i n the biology.  from  done i n order  at f i r s t  v a r i o u s f i s h e s have any  data  fisheries population systematic  faunal  and  vertical  distributions,  exploitation  could  models  by  two  applied  multi-species  the  generalized  parameters.  practical  considerations  One  was  with  a v a i l a b l e data i n order to d e r i v e ideas  for  modifying  other  to  substituting  c h a r a c t e r i s t i c s of p o p u l a t i o n In so doing, I had  be  to examine the c h a r a c t e r i s t i c s o f population  was  fishing  the  situations  models,  application  by making these  of  about  in  mind.  parameters the  steps,  which  must be taken next.  these  results  in  The  practical  f i n d i n g s a v a i l a b l e f o r management of  other f i s h s t o c k s i n those r e g i o n s where data are l a c k i n g . This report f i r s t theories in  the  offers  a  thorough  review  of  to point out the s i g n i f i c a n c e of p o p u l a t i o n Beverton-Holt  discussion  of  the  yield  model.  is  parameters  followed  methods o f a n a l y s i s are  provided.  Analyses  i n d i v i d u a l l y or i n r e l a t e d p a i r s ( r a t i o s and  regressions)  and  grouping  fishes into  parameters  patterns  simutaneously.  attempted to d i s c u s s the r e s u l t s and  present  by  linear  considering  Finally, my  are  population  parameters,  population  a  of the research scheme, data  mainly based on examination of the c h a r a c t e r i s t i c s of  all  by  background and g e n e r a l i d e a s o f comparative  s t u d i e s . Subsequently, e x p l a n a t i o n s c o l l e c t i o n and  This  fishing  I  conclusions.  have  5  IS The  fisherman  BASIC 2JEOBY OF FISHING  and the f i s h are t r e a t e d as  a  predator-prey  system, with the c e n t r e of i n t e r e s t t o f i s h e r y r e s e a r c h e r s l y i n g i n the b e n e f i t s to the p r e d a t o r . Man the  cannot do much t o r e p l e n i s h  stocks of sea f i s h to compensate f o r the y i e l d  has to r e l y on the n a t u r a l r e s i l i e n c e make  up  for  the  loss  caused  of  by  and,  populations  f i s h i n g . The  t h e r e f o r e , to l e a r n about the behaviour s t a t i s t i c a l aggregates  fish  of f i s h  i n p a r t i c u l a r , how  he t a k e s .  He to  main task i s ,  populations  as  they r e a c t to the  v a r i o u s amounts and k i n d s of f i s h i n g a c t i v i t y to which they have been,  or  might  in  the f u t u r e be, s u b j e c t e d . The  f i s h e r y b i o l o g i s t s concerned  with the improvement  a t t e n t i o n of of  fisheries  has thus become focused on the need t o p r e d i c t catches to ensure that  the  increased  a c t i v i t y w i l l continue  to provide at l e a s t  the same given r e t u r n . Hence, many b i o l o g i s t s have on  concentrated  the r e l a t i o n s h i p s among p o p u l a t i o n s i z e s , f i s h i n g  and catches. In p r a c t i c e , they have t o begin by  activities  making  certain  kinds of s i m p l i f i c a t i o n s to enable  them to c o n s t r u c t models. The  simplifications  the  will  depend  on  a v a i l a b l e , as w e l l as the p a r t i c u l a r population  and  its  associated  growth  f i r s t method used pattern  of  a  fish  is  to  result  concerning  the  In what f o l l o w s , two  developed. investigate  stock,  c o n s i d e r i n g the growth increment.  and amount of data  guestions  fishery.  g e n e r a l types of approach have been The  kind  or  a  Increase  the  population  group of s t o c k s , by in  biomass  is  the  of the elemental r a t e o f recruitment, growth and n a t u r a l  m o r t a l i t y , and hence c a p a c i t y t o  increase,  which  is  regarded  6  primarily  as  a  function  of  the s i z e of the stock w i t h i n the  a v a i l a b l e l i f e span of the f i s h . T h i s approach concept  of  the  represented been  to  the  curve or a d e r i v a t i v e of dynamics  of  This  the  (1954,  makes o n l y a s m a l l demand on data - good s t a t i s t i c s of catch  and  direction  sampling  The  apparent  (1935,  and  improving  has  Schaefer  has  advantages of s i m p l i c i t y  e f f o r t . The  model  by  be  i t , and  a f i s h e r y by Graham  1939). I t has s i n c e been f u r t h e r developed 1957).  from  l o g i s t i c law of p o p u l a t i o n growth which may  by a sigmoid  applied  stems  of improvement f o r t h i s method  is  simply  techniques.  second  method,  most  widely  used  in  theoretical  p o p u l a t i o n dynamic s t u d i e s and which provides an e x p l a n a t i o n the  dynamics  and  also  enables  prediction  of  c o n s t r u c t mathematical models of p a r t i c u l a r f i s h rates  of  recruitment,  represented and  by  individual  functions  growth,  and  by  B u s s e l l (1931), Thompson and  Bolt  (1957) and  s t o c k s i n which  and  death  analytical  Bell  1958), and o t h e r s , has been developed  and  i n d e t a i l by  w i l l be r e f e r r e d to here as the  1  of  of  fishing  of the s i z e s and ages of f i s h accepted  fishing The  size  (1945  Beverton "Beverton-  offers  the  p r e d i c t i n g the e f f e c t s on catches of changes i n  f i s h i n g a c t i v i t y by the s e l e c t i v i t y terms  are  approach,  (1934), B i c k e r  Holt * model. An advantage of t h i s method i s t h a t i t possibility  i s to  d e r i v e d from an a n a l y s i s of the  age s t r u c t u r e of the p o p u l a t i o n . T h i s  used  yield,  of  operations  in  or r e j e c t e d by  the  gears. Beverton-Holt  considering  the  catch  model can be d e r i v e d most c o n v e n i e n t l y obtained  from  a  given  by  year-class  7  throughout  its life.  [wherein the f i s h the  entire The  I t i s simpler to consider f i s h a b l e  i s o l d e r than c a t c h a b l e age ( t r ) 1  age composition of the f i s h following  are  defined  stock  instead  of  population.  below  (following  Holt et a l  1959): B«  : biomass of f i s h  i n the e x p l o i t e d  phase  b  : weight-length r e l a t i o n s h i p  C  : t o t a l number of f i s h caught f o r one y e a r - c l a s s  F  : instantaneous f i s h i n g m o r t a l i t y  f  : fishing  K  : r a t e at which f i s h reaches i t s asymptotic  lc  ( = l ) : length of f i s h a t age t c  exponential  coefficient  coefficient  effort length  t  .LINF (=L ) : asymptotic l e n g t h o f the f i s h 0o  It  {=lt) ' l e n g t h o f f i s h a t age t  B  : instantaneous n a t u r a l mortality  Nt  (=N )  q  : catchability  E  : number o f r e c r u i t s , i . e . t h e number o f  t  : number o f f i s h  coefficient  a l i v e at age t  coefficient fish  alive  at  age t r B' : number first tO  of  fish  a l i v e at t h e age t c a t which they a r e  r e t a i n e d by the gear i n use  ( = t ) : time at which t h e f i s h was t h e o r e t i c a l l y 0  at  zero  size tc  (-t ) : a d j u s t a b l e  age  at which f i s h are f i r s t  liable to  capture by f i s h i n g gear i n use TL  (=T^) : maximum age f i s h a t t a i n e d by the f i s h  tr  (=t ) : age at which f i s h r  are r e c r u i t e d  to fishable  stock  8  HINF (=W ) : asymptotic weight of f i s h C0  wt  (=Wt)  Y  : t o t a l weight of f i s h caught f o r one y e a r - c l a s s  Z  : instantaneous t o t a l m o r t a l i t y  :  average weight o f an i n d i v i d u a l  For the p r e - e x p l o i t e d  dNt dt  f i s h at age t  coefficient  period, t r < t < t c  = - fl Nt  (1)  i . e . the instantaneous r a t e at which f i s h are dying o f causes  i s egual  coefficient  to  the  product  of  times the number o f f i s h .  the  natural  natural  mortality  Therefore,  -H ( t - t r ) Nt = R e  (2)  because N = B when t = t r , and  when t = t c -H(tc-tr) 8* = R e  For the p o s t - e x p l o i t e d  period, t > tc,  (3)  when  both  fishing  and  natural m o r t a l i t i e s are operating dNt = - (F + M) Nt = -Z Nt  (4)  dt  An estimate o f the instantaneous t o t a l m o r t a l i t y r a t e  (Z)  is  9  Z = - In [ (Nt+1)/Nt ]  (5)  from the b a s i c equation  7,  we  can  = M + F = M «• q f  c l o t the t o t a l m o r t a l i t y  <6)  (2) a g a i n s t the f i s h i n g  ( f ) , and we w i l l f i n d t h a t a l l the p o i n t s  lies  on  a  effort straight  l i n e . The i n t e r c e p t i s H and the slope i s q.  from (4) - CF + H) (t - t c ) Nt = R* e or Nt = R e The  (7)  -fl (tc-tr)-(F+M) ( t - t c ) 18)  number o f f i s h caught i n the time i n t e r v a l  w i l l be F*Nt*dt, so t h a t the t o t a l number given by d i v i d i n g  caught,  ( t , t = dt) C,  will  be  up the t o t a l time between t c (the age a t f i r s t  capture) and TL (the maximum age a t t a i n e d ) i n t o and adding the c o n t r i b u t i o n s from each  short  intervals,  interval.  Mathematically, t h i s i s expressed by the i n t e g r a l  =  r  J  tc  TL  F Nt dt  <9)  10  The t o t a l weight caught w i l l t h e r e f o r e be given by  r  TL  = J tc  i  p s t i t at  (10)  Where Wt i s the average weight o f an i n d i v i d u a l f i s h o f age t . The  expression  Bertalanffy  f o r the weight has been developed by von  (1938), namely:  -K(t-tO) Wt = WINF [ 1 - €  3 ]  (11)  i n which WINF i s t h e asymptotic weight t o which f i s h i n c r e a s i n g age, K i s a c o n s t a n t which which  the asymptotic  determines  tends with  the r a t e  at  weight i s reached, and t o i s t h e time a t  which t h e f i s h was t h e o r e t i c a l l y a t zero s i z e . Or,  writing  the  r i g h t hand s i d e as a summation, 3 Wt = WINF 5 1 U (n) n=0  e  -nK (t-tO)  (12)  Where U(0) * 1,  0(1) = -3,  0(2) « 3,  0(3) = -1  b assuming w e i g h t - l e n g t h r e l a t i o n s h i p i s W = aL and b = 3 then —K (t-tO) I t = LINF [ 1 - e  ]  (13)  11  Walford It,  (1946)  the asymptotic  showed that when I t + 1 i s p l o t t e d a g a i n s t  l e n g t h i s t h e point where  the  straight-line  r e l a t i o n s h i p c u t s the 45° d i a g o n a l from the o r i g i n . By s u b s t i t u t i n g Nt, Wt into'.equation  Y =  r TL  J  tc  -(F+M)(t-tc)  F R* e  (10), then  -nK (t-tO)  3  WINF^TtHn) e n=0  dt (14)  Or, w r i t i n g t - to = ( t - t c ) - (tc-tO) and r e a r r a n g i n g the terms 3  Y = F R» W I N F 2 I U ( n ) J n=0  pTL  tc  - (F+H+nK) ( t - t c )  e  -nK(tc-tO)  e  dt (15)  on i n t e g r a t i n g t h i s becomes (16)  3 Y = F R» WINF]TJ n=0  Which,  i f TL  0(n) F+H+nK  -nK(tc-tO) -(F+M+nK) (TL-tc) e [ 1 - e 1  i s sufficiently  large  f o r the l a s t term t o be  d e l e t e d , then the y i e l d i s given by -nK (tc-tO) 3 U(n) e Y = F R* WINF^T" ~ — n=0 F • - H + nK or,  (17)  s u b s t i t u t i n g f o r R*  -M(tc-tr) 3 Y = F R e WINF ] T n=0  D(n) e  -nK (t-tO)  • F + M • nK  (18)  12  Because calculated  recruitment as  "yield  i s unknown,  yields  are  normally  per r e c r u i t " . By assuming t h a t H, t r , t o ,  K, WINF are constant and can be estimated from the c a t c h and  the growth curve, t h e " y i e l d  per r e c r u i t "  curve  <Y/R) can be used  to compute e i t h e r the e q u i l i b r i u m r e l a t i o n s h i p between c a t c h and f i s h i n g e f f o r t by v a r y i n g the v a l u e changing  the s e l e c t i v i t y  of  F,  or  the e f f e c t  of  of the gear by a l t e r i n g t h e value o f  the aqe t c a t which f i s h enter the c a t c h a b l e stock. From the f o r e g o i n g equation, i n which Y i s determined, biomass, B», can a l s o be computed of f i s h i n the e x p l o i t e d (since  the y i e l d  the phase  i s F times t h e average biomass o f f i s h ) , by  using the equation  B» = B* WINF  We can reduce length-weight the  3  0(n) e  n=0  -nK(tc-tO) (19)  F + H + nK  the c a l c u l a t i o n s and a l s o take i n t o account a  r e l a t i o n s h i p other than the c u b i c ,  y i e l d Y i n a simple form u s i n g t h e incomplete  by  expressing  Beta f u n c t i o n  (Jones, 1957). Using t h e t r a n s f o r m a t i o n g = F/K, m = M/K, -K(tc-tO) c = 1 - e  lc =  ( l c : the l e n g t h o f f i s h LINF  at age t c )  13  b : weight-length  r e l a t i o n s h i p exponential  the y i e l d equation  Y =  coefficient,  c a n be d e r i v e d as  M(tr-tO) -g R WINF e g (1 - c) B 1-c  (ni+g, b + 1)  (20)  or i f b = 3 M(tr-tO) -g R WINF e g (1 - c) B  Y =  This expression parts,  1-c  (ra + g, H)  f o r the y i e l d can be H (tr-tO)  the f i r s t { fi WINF e  considered  of f i s h i n g . T h i s part can t h e r e f o r e be considered the e f f e c t  on  f i s h i n g . The second p a r t  the  yield  contains  (Jones,  of  the incomplete  or  pattern  as constant i n  d i f f e r e n t patterns of four  parameters,  the  and b.  Beta  1957; Wilimovsky and Wicklund,  have been given by Holt as  of  only  r a t i o s m = M/K, g = F/K, c = lc/LINF Tables  i n two  ] does not c o n t a i n e i t h e r o f  the parameters (F o r tc) which depend on t h e amount  studying  (21)  function  are a v a i l a b l e  1963). T a b l e s o f  g(1-c)g  (1957b) . Thus the y i e l d can be expressed  the product o f a constant  and two q u a n t i t i e s o b t a i n a b l e  from  the t a b l e s . Beverton and H o l t slightly  different  (1964) deduced the y i e l d  form and t a b u l a t e d d i r e c t l y  (=m) , c, and E f> F/(F • M) = g/(g *• m) ]. I f  equation  in a  i n terms o f M/K  M(tr-tO) Y« *  Y/E  Y* =  E {1 -  3  M/K  The  t a b l e of  recruit)  D(n)  Y:  C)  n=0  values  forms  , then  WINF e  (22)  1+ (nK/M) (1-E)  Y*  of  (1-c)  (proportional  the e q u i v a l e n t of a y i e l d  to  the  yield  i s o p l e t h diagram from  which the form of the r e l a t i o n s h i p between y i e l d and f i s h i n g or s i z e at f i r s t In  conclusion,  Beverton-Holt  the i n f o r m a t i o n of the n a t u r a l growth  parameters  LINF) by  assuming  mortality  (F)  and  of  amount  capture can be determined very  the  the  that  von  (tc) are able to be a d j u s t e d  coefficient  (H)  a  constant.  on and  B e r t a l a n f f y growth model (K is  of  easily.  y i e l d model i s based  mortality  recruitment  the age  per  and  Fishing  at which f i s h are l i a b l e t c capture i n order t o o b t a i n the  same  given  y i e l d . To s i m p l i f y the c a l c u l a t i o n f o r t h i s y i e l d model r e q u i r e s information  on  the  M/K  comparative f i s h p o p u l a t i o n  and  Ic/LINF  studies  ratios..  will  rely  Therefore, on  the  population  parameters and r a t i o s but not on a d j u s t a b l e c h a r a c t e r s .  15  I I I RESEARCH APPROACH Z_ CGMPA RATI VE POP 01 ATI ON STUBIES  Aoeinq  Problem  The  methods  equation stock.  used  to estimate parameters  (18) r e q u i r e data on the If  the  age  composition  ages of f i s h i n a sample can be  then the c o e f f i c i e n t s of m o r t a l i t y may  (equations 5  growth  be  parameters  may  and  the  von  estimated  Bertalanffy  from  growth  and  the (the  from r i n g s on such opercular 1973).  bones,  Examples  composition  are  hard  structures  fin-rays of  or  other  from  as  the  Walford This  tropical  be  determined  scales,  otoliths,  vertebral  methods  the  linear  equation).  where the aqes o f f i s h cannot r e l i a b l y  the  determined,  presents d i f f i c u l t i e s i n many a r e a s , e s p e c i a l l y i n waters  of  6),  r e g r e s s i o n of the l o g r i t h m i c f i s h s i z e on age for  yield  be estimated from  age compositions of catches  method  i n the  for  centra  (Baqenal  inferring  age  polyiaodal l e n g t h freguency curves or  from the seasonal p r o g r e s s i o n of modal s i z e s . However, these two  methods are not u n i v e r s a l l y a p p l i c a b l e . Even i n the most  favourable  circumstances  distinguish  only  the  the few  former  can  youngest  age  p o p u l a t i o n . The l a t t e r method may spawning Holt  or  were  be  groups  used  to  in  the  successful  when  recruitment i s spread over a v e r y l o n g season.  (1960) pointed cut that i f two  values  not  be  suggested  or  more  possible  age  by d i f f e r e n t i n t e r p r e t a t i o n s o f the  16  r i n g s on one o f the hard s t r u c t u r e s , i t could be checked comparison with i t s expected growth parameter Even  when  time-consuming  age  by  (K) v a l u e .  can be determined i t i s u s u a l l y such a  procedure that there i s a g e n e r a l i n t e r e s t i n  f i n d i n g a means by which t o a v o i d i t o r , at l e a s t , to reduce i t s d u r a t i o n . , H o l t (1958) sexual the  maturity  occurs  f i n a l length  that  a t a size  to  in  scombroid  i s about one t h i r d o f  (UINF). I f the weight  the  of  a  growth i n weight which  and  between  require  at  are  at  first because  maturity  of  Bastrelliger  i s about  kanagnrta  in  does  known  the I n d i a n  22.5 cm, which would imply t h a t LINF i s  about 33 cm. For t h i s stock the l e n g t h at ages years  curve  a g e - d e t e r m i n a t i c n . , For example, the l e n g t h at  f i r s t maturity fisheries  size  growth parameters be undertaken  determination of the mean or median s i z e net  the  (1959b) then suggested t h a t a  comparative study of the r e l a t i o n s age  is  i s one of the f e a t u r e s o f the von  E e r t a l a n f f y growth model. Holt  maturity,  fish  cube of i t s l e n g t h , the s i z e a t f i r s t  maturity corresponds with the i n f l e x i o n p o i n t o f of  fish  (IM) about t w o - t h i r d s o f  (LINF), when the f i s h  i t s asymptotic weight proportional  showed  from  the  movement  of  one  or  two  modes i n l e n g t h -  frequency d i s t r i b u t i o n s . Given LINF and the s i z e s a t the two ages, i t i s p o s s i b l e to determine K, and a v a l u e of 0.65 was obtained by t h i s method. T h i s i s not a p r e c i s e can be most u s e f u l l y a p p l i e d f o r t r o p i c a l  method,  fishes.  but  17  Features  of Population  Holt  (1957a,  Parameters  1958,  p o p u l a t i o n parameters certain  1959a,  are  generalizations  s a r d i n e s . Sot invariable,  only but  grouped appear  are  their  these  level  (e.g. sexual)  of  and  in  in  has shown t h a t i f a  particular  scombroid  LH/LINF  ratios  l i m i t e d range of values f o r taxonomic  1962a)  may  groups  of  and  a characteristic up  to  the  'Order'. In other words, i n t r a s p e c i f i c interspecific  Holt  (1959)  amount of data and concluded between  in  relatively  fishes  relations  parameters seem g e n e r a l l y t o be of a s i m i l a r Beverton  f i s h and  ratios  have  way,  longevity  and  presented  that t h e r e growth  is  patterns  q u a n t i t a t i v e l y among c e r t a i n f a m i l i e s .  They  between  these  kind. a  considerable  a  relationship which  differs  developed  the  idea t h a t the value of the n a t u r a l m o r t a l i t y c o e f f i c i e n t can  be  gauged  concerned. A  from  fish  g u i c k l y - i . e . has natural low  the  which  growth  approaches  its  the  species  ultimate  length  a high K value - i s l i k e l y t o have a  a l s o to have a low  H and K appears t o d i f f e r from one for  clupeoids,  M  is  M. The r e l a t i o n  high (a  between  group of f i s h to another;  g e n e r a l l y between one  times K,  f o r gadiforms fl i s between two and  If  ratios  M/K  of  m o r t a l i t y r a t e , whereas a f i s h t h a t grows slowly  K) i s l i k e l y  thus,  pattern  (M)  are f u r t h e r confirmed  three  and  two  times  K.  ( i . e . more s u p p o r t i n g  18  evidence  i s f o u n d ) by  particular  deriving  taxonomic  theoretically  or e c o l o g i c a l groups,  p o s s i b l e to undertake  a s e p a r a t e e s t i m a t i o n o f M and utilized  characteristic  values  t h e n i t becomes  stock assessment  K. T h i s  ratio  b u t i t i s o f t e n most u s e f u l i n t h e e a r l y  studying  a  mortality,  or  whether  fishing  mortality,  in  total  dominant element criticized  judge  their  the  study  for  is  or  not  having  Engraulidae. f a m i l i e s and exploited which  found  Bicker enough  families  t h a t the s i z e a t (lc)  was,  maturation  the  the  be  the  (1960) data  yield  Clupeidae  fish  enter  and two the  i n e f f e c t , t h e same a s t h a t a t  i s  reached  equation  recruit for this special  which  to  {1963) d i d  considered the c h a r a c t e r i s t i c s of these  phase  first  modified  He  within  of  natural  to  s u b s t a n t i a t e the c o n c l u s i o n s . T h e r e f o r e , Beverton a more d e t a i l e d s t u d y  be  stages  not  likely  mortality.  can  method i s n o t  precise,  to  without  also  f o r e s t i m a t i n g f i s h i n g m o r t a l i t y . The  fishery  for  for  ( i . e . 1c eguilibrium  case o f f i s h e r i e s based  =  LM) . catch on  He per  mature  f ish. Taylor  (195 8,  1959b)  found  that K increases roughly  p r o p o r t i o n a l l y with the l o g a r i t h m of water the  instantaneous  natural mortality  i n t h e same d i r e c t i o n . that  the  Holt  interspecific  (1959b,  variability  l e s s than the v a r i a b i l i t y o f e i t h e r it  seems  that  because they  there  is  no  temperature,  coefficient 1960)  then  of the r a t i o M o r K.  relationship  (M)  and varies  suggested M/K  may  be  Mathematically, b e t w e e n K and  are d e r i v e d i n d e p e n d e n t l y , a l t h o u g h  many o f  M  the  19  above-mentioned relationship biological  references  between  K  suggest  that  there  is  a  and M which may be of c o n s i d e r a b l e  significance.  Holt  (1962b)  looked  at  this  g u e s t i c n from an e v o l u t i o n a r y viewpoint. For s u r v i v a l o f t h e population,  sufficient  fish  must reach maturity. Even i f M  had been determined  by p r e d a t i o n , K  natural  selection  so  breeding  stage.  3Unreality  The rate  as  to  might  allow  be  enough  adjusted fish  to reach  of the Usage o f P o p u l a t i o n Parameters  Beverton-Holt  to  be  model assumes the  age-independent.  However,  natural  mortality  Beverton  and Holt  (1959) showed t h a t M i s not constant but i n c r e a s e s with age  of  by  the  the f i s h , with an e s p e c i a l l y sharp d i s c o n t i n u i t y a t  the onset o f m a t u r i t y , as evidenced by the c u r v i l i n e a r i t y o f logarithmic relative  age and  data. absolute  i s o p l e t h s obtained using Beverton-Holt allometric  yield  Paulik  and  Gale  differences isometric  (1964)  between  growth,  on  the  yield  which  the  model i s based, and those obtained using  growth  f o r taxonomic  groups  with  c h a r a c t e r i s t i c growth p a t t e r n s and l i f e spans. suggested  examined  when t h e r e i s g r e a t e r m o r t a l i t y among a  year  class,  S i c k e r (1969) the  faster  a curve f i t t e d  to the  growing  members  observed  s i z e s of the s u r v i v i n g f i s h at s u c c e s s i v e ages w i l l  underestimate  of  different  the t r u e r a t e of growth o f  the  fish  i n the  20  p o p u l a t i o n . However, the M/K  r a t i o would remain the same.  Because of the s i g n i f i c a n t l i n e a r c o r r e l a t i o n  between K  and the l o g r i t h m of s u r f a c e water temperature, T a y l o r 1959a,  1959b,  1960,  1962)  b e l i e v e d t h a t we may  e v e n t u a l l y abandon some fundamental model  of which form a dangerous,  and r e a l i t y . G u l l a n d able  to  characteristics  temperature, better  analysis  of  studies,  they  is  the  what  foregoing  systematic  consideration. 1  of  particularly  the  model  surface  and,  is  should be such  water  hence,  as  achieve  a  l i k e l y t o happen i n the  future.  In summary,  literature  multitudinous  l a r g e gap between theory  factors, cf  i n t o the y i e l d  understanding  immediate  the  (1972) a l s o suggested t h a t we  f i t environmental  physical  did  dealt  only  take  from  environmental  these  factors  environment.  the  to  suppose  into  papers I could f i n d no other  d e a l i n g with more k i n d s of comparative reasonable  with  groups. With the e x c e p t i o n of T a y l o r ' s  not  aside  papers  that  not  studies.  only i n d i v i d u a l  animals, but a l s o whole p o p u l a t i o n s are adapted t o their  fishing  theory i n favour o f more p r o f i t a b l e hypotheses and t o  factors  to  be a b l e t o  premises of the  d i r e c t more a t t e n t i o n to the environment,  It  (1958,  some  degree  In the l a t t e r case t h i s would mean t h a t  the magnitude of one or more of t h e v i t a l r a t e s was  such that i t  i M i t a n i (1970) d i d a s i m i l a r comparative study by only a few r e f e r e n c e s .  listing  21  best enabled the p o p u l a t i o n t o occupy niche be  a  (faunal pattern) and p e r p e t u a t e i t s e l f .  grouped  according  to  common  i n independent  this  case,  there  w e l l be some p a t t e r n of a s s o c i a t i o n between parameters  as growth, maturity and about  In  ecological  Moreover, f i s h can  developments  c a t e g o r i e s such as v e r t i c a l d i s t r i b u t i o n . may  particular  adaptation  of  natural  the  mortality  fish  which  would  such bring  p o p u l a t i o n to i t s environment,  thereby e n a b l i n g i t to perpetuate  itself.  From above d i s c u s s i o n i t f o l l o w s t h a t the time has come use  comparative  to  s t u d i e s t o examine the s t a b i l i t y of p o p u l a t i o n  parameters  and the r e a l i t y o f f i s h models.  In  fact,  this  suggested  by  It  seems  that only  Holt  over  15  years  f i s h e r i e s r e s e a r c h has the necessary permit t h i s kind of comparative  study.  ago.  accumulation  of  data  was  to  22  I I HATEBIALS AND  METHODS  IJL Research Scheme  The fish  first  step  was  to f i n d a v a i l a b l e data from  population s t u d i e s . Emphasis was  needed  f o r stock assessment and  put  on  the  published  information  management. Comparative methods  were used to examine f i s h p o p u l a t i o n parameters i n d i v i d u a l l y order  to  display  their  stability  I n t e r r e l a t i o n s h i p s between parameters  and  (ratio  in  variability.  and  correlation)  were a l s o examined so as to f i n d the s i m i l a r i t i e s or d i f f e r e n c e s among  d i f f e r e n t c a t e g o r i e s . I n t r a - s p e c i e s s t u d i e s were based  comparison between sexes and comparison among d i f f e r e n t This  would  make  known  the  distribution  p o p u l a t i o n parameters c o u l d be r e l a t e d factors  fish  local  patterns,  in  fauna p a t t e r n s , and  step of t h i s study existng  three  directions  stocks. and  Inter-species -  systematics  vertical distributions.  The  i s to apply these p a t t e r n s to develop  fishing  models.  (Refer  c h a r t f o r the e n t i r e research scheme)  their  environmental  i n order to f i n d s p e c i e s c h a r a c t e r i s t i c s .  s t u d i e s were concentrated  modify  to  of  on  to F i g u r e  final or  1, the  to flow  FIND AVAILABLE DATA biologyof  fish  studies  READ IN DATA species, l o c a l i t y , habitat, feeding h a b i t s , f i s h i n g g e a r , w a t e r temp., sex, sample s i z e , sample age range, natural m o r t a l i t y c o e f f i c i e n t , growth parameters, maturity s i z e and age, l e n g t h a t a g e 1, l e n g t h - w e i g h t r e l a tionship c o e f f i c i e n t s , author  INTRASPECIES STUDIES  COMPARE  ?-<  > $ -  DISTRIBUTION RELATE TO ENVIRONMENTAL FACTORS FIND SPECIES CHARACTERISTICS  INTERSPECIES STUDIES  SYSTEMATICS  FAUNA  species genus family order  tropical temperate cold  VERTICAL DISTRIBUTION large pelagic shooling " demersal  CHARACTERISTICS OF PARAMETERS  M A T U R I T Y  G R O W T H  D E A T H  '"  M  t95  K  b'~"  (W= a L b )  INTERRELATIONSHIP BETWEEN PARAMETERS  WHAT ARE THE - SIMILARITIES - DIFFERENCES  FIND SYSTEMATICS PATTERNS  FIND FAUNA PATTERNS  APPLIED TO FISHING THEORY 'igure 1. Research scheme  FIND VERTICAL DISTRBN PATTERNS  24  2  A  Survej  Data  Most t o t a l l e n g t h values were taken d i r e c t l y from p u b l i s h e d reports;  where  reported,  either  these  were  c o n v e r t i o n r a t i o was  A.  Age-length  length  or  converted  into  total  length  length  if  was the  data Bertalanffy  growth  equation,  231  age-  data s e t s were a n a l y z e d . A sample run i s shown i n F i g u r e  2. Only a few of these d i d not LINF,  fork  available.  By using the von length  standard  in  particular  the  provide  fishes  estimations  with  short l i f e  of  K  spans  E n g r a u l i d a e , Osmeridae, Scombridae, e t c . ) . The e s t i m a t e d  and (e.g.  K  and  LINF values were then entered i n the parameter r e c o r d when there were no estimated K or LINF v a l u e s i n the o r i g i n a l  B.  paper,  Farameter data I  have  compiled  i n one r e c o r d , s p e c i e s names, t h e i r  stock  areas, sample s i z e s , n a t u r a l m o r t a l i t y c o e f f i c i e n t  (M),  parameters  (LM), age a t  first  (K,  maturity  LINF), (TM),  where:  at  length a t age  exponential c o e f f i c i e n t The  length  weight-length  (b), and  first one  maturity  (L1),  the  growth  weight-length  author.  relationship  coefficients  are a and b  2'S  FITTING OF VON BERTALANFFY GROWTH EQUATION SPARIDAE(CHRY50PHRYS MAJOR)  14.IB  1  10-54  8 o  8 n  ^  R r  u  8 c  8 u  r  8  S n  4  "  T  8 i  n  8  R i  D  i  r  ffi  R  )  C  N  8 D  AGE Figure  2.  The e s t i m a t i o n o f g r o w t h p a r a m e t e r s b y f i t t i n q of von B e r t a l a n f f y g r o w t h e q u a t i o n f r o m a g e - L e n g t h d a t a (a s a m p l e p r i n t o u t )  26  W = a L  b  The age at which t h e f i s h length  95%  of  the  asymptotic  (T95) i s an index of ' l i f e span', as suggested  (1959), and i s c a l c u l a t e d from 1 T95 = - In K T50,  attains  the  asymptotic  age  at  by T a y l o r  K, t o , and LINF by using  LINF + tO LINF - 0.9 5 LINF  which  the  fish  has  attained  501  of the  l e n g t h , can be c a l c u l a t e d i n the same way.  3. M a t e r i a l s  P u b l i s h e d f i s h p o p u l a t i o n dynamic s t u d i e s have provided 682 parameter  data  records  from  43 f a m i l i e s  (171 s p e c i e s ) and a r e  l i s t e d i n Table 1. The growth parameters (K and LINF), found  in  the  original  (refer  to  not  papers, are estimated by u s i n g the von  B e r t a l a n f f y growth equation based on age-length paper  when  data  from  the  F i g u r e 2). Table 2 summarizes sample s i z e s of  data c o l l e c t e d f o r i n d i v i d u a l parameters and r e l a t i v e c h a r a c t e r s i n 13 f a m i l i e s . Because more s a t i s f a c t o r y r e s u l t s are to be obtained from a g r e a t e r volume o f data, a l l the analyses are based 15 f a m i l i e s having l a r g e s t sample  mainly on the  sizes.  Group I (5 f a m i l i e s ) ; Clupeidae - h e r r i n g s , C y p r i n i d a e - minnows and c a r p s , Gadidae c o d f i s h e s , P l e u r o n e c t i d a e - r i g h t e y e f l o u n d e r s , and Scombridae -  Collected Note :  I SP|  d a t a on  SPECIES NAME  I S| |E| M I X|  AREA  _i—i  L.  1|Acipenser 1 IAcip^nser 2|Acipenser 4|Acipenser  transmontanus | C a n a d a : F r a s e r R i v e r t r a n s m o n t a n u s |Canada:Fraser R i v e r |Wisconsin:Lake Sturgeon fulvescens |Europe nudiventris  i  Sand  Airmody t i d a e 1|Ammodytes 1 | Ammodytes 1|Ammodytes 2 | Annnod y t e s 2|Amroodytes 2|Ammodytes 2 | ADimodytes  Freshwater  •1 | Anguilla anguilla  |Windermere  Aplochitonidae  I  | LM | TM | L1 | |(cm) I C/r) I (cm) |  b  IAU1H0R  (WITH YEAR  19  )  -I—T  T  1  1  T  |3.15 |3.13 | |  Ifl |0.005| | | |m| |0.035| 216.3| I | |0.01|0.05 | 178.0|112.5| | | |0.04 | 250.0|130.0|  ISemakula, 63 ISemakula, 63 | P r o b s t * C o p p e r , 54 I P a c c a g n e l l a , 48  1 I I I  T  |o.289T  I  I  15.6|  |0.89  |  I  I  2 1.8| I 30. 3| 20.3| 41.7|  I 0.326 | |0.382| 10.228|  I  I  eels District  I I  |0.02  | 165.01  1  1  | 7. 9 | l-Molloy, 67 1.0| |3.169|Reay, 70 2.0) |3.068|Macor, 66 | |3.153|Kohler e t a l , 70 | 8.0| I S c o t t , 73 | 5.4) I S c o t t , 73 |14.0| I S c o t t , 63  I 9.0|  60.01  L  1  IFrost,  45  Whitebait  1|Lovettia.seali  I  6.5|  Ifl I n. | I I  |0. 129 | |0. 145 | I 1.2 I -j.  41.4| 37.9| 19.0| x  I I  T3.7  |Tasmania -j. Argentines  Argentinidae 1|Argentina silus 1 | Argentina s i l u s 2|Argentina s e m i f a x i a t a  -T—r  |Nova S c o t i a INova S c o t i a I Japan  (Blackburn,  -l  I I I  50  r-  7.5| 7.5| I  IZukow.ski, IZukowski, lllanyu, 56  72 72  Silversides  Atherinidae — T  sicculus  I  J_  Blennidae 1|Blennius  I  I  | LINF | (cm)  lances  | I r i s h Sea:west INorth A t l a n t i c (North S e a : F a r o e |Nova S c o t i a |Emeral:west IBanguerean I Nova S c o t i a Banks  marinus marinus marinus dubius dubius dubius dubius  Anguillidae  1|Labidesthes  I  I  Sturgeons  Acipenseridae  ...Table  populations  (1) H - n a t u r a l m o r t a l i t y c o e f f i c i e n t ; K and LINF a r e growth parameters; LM = s i z e a t f i r s t m a t u r i t y ; TH = age o f f i s h a t l e n g t h LM; L l = l e n g t h o f f i s h at age 1; b = w e i g h t - l e n g t h power c o e f f i c i e n t (2) The growth p a r a m e t e r s (K and L I N F ) , when not found i n the o r i g i n a l papers, a r e e s t i m a t e d by u s i n g von B e r t a l a n f f y growth e q u a t i o n cased on a q e - l e n g t h data from the paper (3) Most t o t a l l e n g t h v a l u e s were taken d i r e c t l y from p u b l i s h e d r e p o r t s ; where e i t h e r s t a n d a r d l e n g t h or f o r k l e n g t h was r e p o r t e d , t h e s e were c o n v e r t e d i n t o t o t a l l e n g t h i f the c o n v e r t i o n r a t i o was a v a i l a b l e .  N0|  1—  Table 1 p o p u l a t i o n parameters i n f i s h  U.  A  Commbtooth pholis  1 continued  |Welsh on  next  page  Coast  .1  J  —  -TI  9.2|  |  17. o j  blennies  I  10.9  |0.30  7. 0| 1 8. 0 J  'Hubbs • 21  _J  J  —1—  I  ^1 IQasim, 57  J  • Lefteye  •  1  Bothidae  I* •  i  I  1|Citharichthys sorididus ICalifornia 1|Citharichthys sorididus ICalifornia 2|Paralichthys olivaceus |East China Sea 3|Pseudorhorabus cinnamoneu|Northwest Kyushu  I  I  •  0. 3 |0.3 If 0.3 |0.3 1 1 1 1  i  i  "T  "  | E n g l i s h Channel l E n g l i s h Channel  Carangidae  J a c k s and  i  »  •  Cichlidae  |01|Tilapia  melanotheron  " r  harengus harengus harengus harengus harengus harengus harengus harengus harengus harengus harengus harengus harengus ha rengus ha rengus harengus harengus ha rengus harengus harengus harengus ha rengus  C l u p e a harengus  -}—+  C l u pea harengus C l u p e a harengus  ...Table 1 continued  I AUTHOR  (with y e a r 19  )  • 1  i  — r - • • i _ ... ,. ... 1 30. 0 | 1 30.01 19.0| 1 1 1 48. 0| 3.0| | 38. 4 | 1 I 18. 5 L_ 1  1  1 1 1 1  1  |Nigeria:Lagos •  Lagoon  17. at I  25.01 17.5|  1  ' i—  I  1  I 0.297|  ,  i  T  \ .  25. 7 J  i  i  1  •• -  , IChanq, 51 IChanq, 51,.,  i  —  J  IChanq e t a l , 7 2 ; 121.3 1. 054|Chanq+ Shaw,75 | 24.8| 1.289|Chanq et a l , 7 2 ; |Chanq+Shaw,75 —i  f. I  _ _|  i.  i  1 1 1 l 10.135| 59.9| 24. 0| I 0.302 | 39. 1 | 24.0| I I I 1 i i  i  T  |Arora,51 |Arora, 5 1 I S a i s h u , 57 |Matsuura, 61  ,.. .. J  . _. J  Cichlids  Clupeidae Clupea Clupea Clupea Clupea Clupea Clupea Clupea C l u pea Clupea Clupea Clupea Clupea Clupea C l u pea Clupea Clupea Clupea Clupea Clupea Clu pea C l u pea Clupea  i  | | 1 1  |m 0. 96|0.43 | If 0. £610.55 | •  '.  pompanos  1  T  |  #  }. .  | TH | Ll | (YR) | (CM) i • • , 4  ,., — J  I 1|Deca p t e r u s I | | k u r r o i d e s aka-adsi|Taiwan:Nanfanqao t 1|D. k u r r o i d e s a k a - a d s i |Taiwan:Kaohsiung 1 1 1  •  | LM | (CM) i  Dragcnets  i  1  ,,  LINK (CH)  flounders  1 | I |  | Callicnyraidae 1 T | 1|Callionyraus l y r a I 1ICallionymus l y r a  1 1 ,  I  |  | | 1  IE  no | ] •  I 13. 9 i  —  |Faqade,  73  i  Herrings harengus harengus har eng.us harengus harengus harengus harengus harengus harengus harengus ha rengus harengus harengus harengus hareng us harengus harengus harengus harengus harengus ha reng us harengus  T  Noruay:Lusterfjord Dunmore Norwegian,Iceland North Sea North Sea - s o u t h I r i s h Sea - n o r t h I r i s h Sea - s o u t h Gulf St.Lawrence:south Iceland B a l t i c Sea:north Atlanto-Scotian C e l t i c Sea Bay o f Fundy B a l t i c Sea:south Gulf St.Lawrence:south Greenland Spain:Atlantic coast North A t l a n t i c r C l y d e North A t l a n t i c : H i n c h F o r t u n e Bay (Newfoundl.) Newfoundland Newfoundl.:south west (Autumn spawning) harengus Newfoundl.:south west ( S p r i n g spawning) harengus North S e a : n o r t h harengus Norwegian Sea + -+on next page  0.7810.65 10.35 | 0.2 35 0.2=10.38 0.2 10.375 10.30 0.2 10.39 10.25 10.25 10.15 0. 16| 0. 17|  21.0 29. 5 36.0 30. 0 29. 29.5 29. 5 36. 36. 5 25.  |0.575 |0.499 | 0. 20 0. 27 | I 0 . .15 |0.35 10.462 10.348 0.20|0.260  22.5 32. 8 41.  0.20|0.282  35. 2  J0.39 0. 20|0.27 +  31. 34.0  Aasen, 52 I B e v e r t o n , 63 I B e v e r t o n , 63 B e v e r t o n + H o l t , 59 Burd, 62 Bowers, 60a ; S m i t h , 56 Burd, 59 Lea, 19 ; Day, 57 F r i d r i k s s o n , 50 Hannerz, 56 ICES, 70, 72 ICES, 71 3. 1 8 1 | I l e s , 73 J e n s e n , 47 K e s s i e h + T i b b o , 71 N i e l s e n , 60 O l i v e r , 50 10.5| I P a r r i s h + S a v i l l e , 65 11.5| I P a r r i s h + S a v i l l e , 65 3. 293 | P a r s o n s * i l o d d e r , 73 P a r s o n s * H o d d e r , 73 2.903|Parsons+Hodder, 75 ; W i n t o r s * H o d d e r , 75 3. 328| P d r s o n s m o d d o r , 75 ; W i n t e r s + i l o d d c r , 75 P a r r i s h + C r a i q , 63 Runnstrora, 36 11.0| 8.5|  24.0| 23. 5| 24. 5 | 24. | 28. |  I 18. | I  31.5 31.5 3 5.1 34.5 36.4  24.5| 28. |  +-  co  SP| no|  SPECIES NAME  | I  AREA  | 1|Clupea harengus harengus | Norway I 1|Clupea harengus harengus|Newfoundland | 1|Clupea harengus h a r e n g u s I C h a l e u r Bay | 2|Clupea harengus p a l l a s i |Okhosk Sea | 2|Clupea harengus p a l l a s i |Hokkaido | 2|Clupea harengus p a l l a s i |Canada:west c o a s t | 2|Clupea harengus p a l l a s i |Alaska | 2|Clupea harengus p a l l a s i |Japan Sea | 2|Clupea harengus p a l l a s i | E r i t i s h Columbia | 2|Clupea harengus p a l l a s i |White S e a r Z o l o t a y a | 2|Clupea harengus p a l l a s i |White Sea: Mezen ' | 2|Clupea harengus p a l l a s i |White Sea:Kandalaksh j 2|Clupea harengus p a l l a s i |Wliite Sea:Onega | 2|Clnpea harengus p a l l a s i |White Sea:Dvina | 3|Sprattus sprattus | B a l t i c ( B a y o f Gdansk) | 3|Sprattus sprattus I North Sea | 3|Sprattus sprattus IBrittany | 3|Sprattus s p r a t t u s (Swedish Coast | 3(Sprattus sprattus |Spain:Atlantic coast | 3|Sprattus sprattus |North Sea | 3|Sprattus s p r a t t u s (Norwegian c o a s t | 4|Sardinops c a e r u l e a |San Pedro J 4|sardinops c a e r u l e a (California | 4|Sardinops c a e r u l e a ICalifornia |05|Sardinops m e l a n o s t i c t a INorthwest P a c i f i c | 5|Sardinops melanosticta |Japan | 6|Sardinops neopichardus (Australia | 7(Sardinops o c e l l a t a |South A f r i c a I 7|Sardinops o c e l l a t a ISouthwest P a c i f i c | R|Sardina p i l c h a r d u s |Mediterranean:Formentera | 8|Sardina p i l c h a r d u s |Bay of B i s c a y j 8|Sardina p i l c h a r d u s I P o r t u g a l ( A t l a n t i c coast) I 8|Sardina p i l c h a r d u s I M e d i t e r r a n e a n - west | 8|Sardina p i l c h a r d u s ( E n g l i s h Channel | 8|Sardina p i l c h a r d u s (Adriatic | 8|Sardina p i l c h a r d u s I Mediterranean | 9|Sardinella aurita |Aegean l09(Sardinella aurita |Lastiglione(Spain) 109(Sardinella aurita |Lastiglione(Spain) 1091Sardinella a u r i t a (Algeria |09|Sardinella aurita |Algeria I 9(Sardinella aurita |Mediterrean - east ( 9|Sardinella aurita |Mediteran.:Israel coast I 9|Sardinella aurita IMediterranean:west I 9|Sardinella aurita IBelearic Island | 9|Sardinella aurita (Canaries | 9|Sardinella aurita IMoyen Congo |09|Sardinella aurita ISeneqal I 9|Sardinella aurita |West A f r i c a n : P o i n t N o i r e | 9|Sardinella aurita IBrazil |10|Sardinella longiceps l l n d i a n Ocean 1 1 1 | S a r d i n e l l a maderensis llsrael | 1 1 | S a r d i n e l l a maderensis |Senegal  | E| fl | |x| |  K  | JO. 1*7)0.21 I | |0.25 I I f 0.30 I | 10.35 I I I I |0.56|0.29 I | |0.25 I 10. 2 |0.19 I | 10.475 I | 10.20 II I I | |0.4 I | |0.4 | | |0.15 I | |0.75 | | |0.8 | | 10.9 ( | (0.45 I | | 1.2 I | 10.8 I | |0.65 I | I I |0.15|0.39 I |0.4 |0.45 | I I | | 10.65 I | I0.22 I | (0.45 I | I | | |0.5 I | 10.70 | | (0.65 I | |0.55 | | (0.50 II |0.43 I | I I | "0.55 |f| I jm| I |f| I |m| I I | (0.4 | | 10.192 | | |0.55 | | | | | | I | I I | |0.196 | | |0.7 | | |0.4 I | |0.4 I | I ( | I  LM (CM)  TH  L1  (YR)  (CM)  AUTHOR  28. ! 30. 25. 23. 5| 23. 0 | 3. 5 15.0 I  21. 23. 19. 15.-0| 13.0| 13. 0|  1.5  18. 3  1.5  16.0  1.5  10.4  2.0  12.9  1.5  14. 1  15.8 1.5 2.0  14. 0  15.0 15. 5  22.0| 18.0| 18.0| 11.5 15.0 +  ...Table  1 continued  cn next page  19  )  Sund, 43a, 43b T i b b o , 56, 57 T i b b o , 56, 57 Ayushin, 63 K i t a h a m a + N a k a y a m a , 58 H i c k e r , 58 Rounsefell, 30 T a n a k a , 60 ; A y u s h i n , 63 T e s t e r , 55 Tarabovtsev, 57 Tamhovtsev , 5 7 T a m b o v t s a v , 57 T a u b o v t ^ e v , 57 Tarabo vtsi->v , 57 Elwertowski, 60 Elwertowski, 61 Faure, 50 M o l a n d e r , 43 O l i v e r , 50 Robertson, 38 S u n d , 11 Ahlstrom, 60 B e v e r t o n « - H o l t , 57 Clark+Marr, 55 N a k a i + H a y a s h i , 62 T o k a i R e g . F i s h . R e s . L a b . 60 Blackburn, 50 D a v i e , 58 ; D e J a g e r M a t h e w s , 60 A n d r e u e t a l , 50 Bouqis, 52 Rouq i s , '52 Larraneta, 60 Gushing, 61 M u z i n i c , 54 Rodriguez-Roda"-Larraneta,55 Ananiades, 51 A n d r e u + R o d r i q u e z - r o d a , 51 AndreutRodriguez-roda, 51 B o u n h i o l , 21 B o u r i h i o l , 21 Ben-Tuvia, 60 Ben-Tuvia, 56 Navarro, 32 Oliver+Navarro, 52 P o s t e l , 60 P o s t e l , 60 P o s t e l , 55 Rossignol, 55 R i c h a r d s o n e t a l , 60 C h i d a m b a r a m , 50 ; N a i r , 60 Ben-Tuvia, 60 P o s t e l , 55  25. 01 29. 0 I  11. 10. 13. 14. 18. 22. 5| 17.0| 20. 0| 10. 23.0| 18.5| 15.01 14. 5| 14.8| 12.51 17. 5| 13.5| 12.0| 16. 5| 19.4| 16.9| 13. 5| 12.0| 15. 12. 5| 17.5| 16.0| 14.0| 22. 0|  (with year  -+-  --4  SP| no |  SPECIES NAME  12|Etrumeus m i c r o p s 13|Konosirus punctata 14| Ethmalosa f i m h r i a t a 14|Ethmalosa f i m b r i a t a 16|Pcmolobus a e s t i v a l i s 17|Pcmolobus pseudoharen 18|Ililsa h i l s a 18|Hilsa h i l s a 18|Hilsa h i l s a 19|Brevoortia tytannus 19|Brevoortia tyrannus 19|Brevoortia tyrannus 19|Brevoortia tyrannus 19\ B r e v o o r t i a t y r a n n u s 19|Brevoortia tyrannus  ASEA | Hiuqa-Nada |Wakasa Bay | Nigeria | Nigeria (George Bank | George Bank I R i v e r Hooghly I R i v e r Hooghly IGodavari ( I n d o - P a c i f i c ) |North A t l a n t i c |Middle A t l a n t i c IChesapeake Bay |North C a r o l i n a |North C a r o l i n a c o a s t |North C a r o l i n a c o a s t  Co11 i d a e 1|Cottus g o b i 1 |-Cottus g o b i I | Cottus gobi II C o t t us g o b i  I  2 2 2  2 2 2 2 2 2 2  2 2  2 2 2 2 2 2 2 2 2 2 2 2  | Windermere I Windermere I R i v e r Brathay I R i v e r Brathay  —i  Minnows and c a r p s  Cyprinus carpio Cyprinus c a r p i o Cyprinus c a r p i o Cyprinus carpio Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama A t r a m i s brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Ahramis brama  India Indonesia Japan Europe Sweden:Hjalmaren(Lake) Sweden:Toften Sweden:Havqardsjon(Lake) Sweden:Yxtasjon C a s p i a n Sea Poland:Oswin Poland:Wadag P o l a n d : Z n i n Duzy Poland:Goldopiwo Lake Poland:Goldopiwo Lake Switzerland-germany Denmark:Haderslev Dan K a r e l i a : S a m o z i e r o (Lake) US5R:Ladoga (Lake) Danube near Medvedov E a l t i c Arkona 36 north German l a k e s Dneper,middle c o u r s e Dneper D e l t a ( r i v e r ) uSSR:Ilmen (lake) Ural Delta (river) Pskov R e s e r v o i r U S S R : I t k u l (lake) A r a l Sea  ^ — +  .Table  1 continued  | T M | L1 | | (YR) | (CM) |  15.0| 30. 3| 25.01 35.6| 30.0|  fI m|  113. 3| . 5 | 1 5. 01 I I I I I I 141. 51 I I 113. 7| 115. 11 112. 81  |AUTHOR (with y e a r 19 I -+ IYokota+Asarai, 56 IKu wa t a n i , 56, 58 |Lo n q h u r s t , 6 3 |Longhurst, 6 3 I N e t z e l + S t a n e k , 66 I N e t z e l + S t a n e k , 66 IChacko+Gnapati, 49 IChacko+Gnapati, 49 I P i l l a y + R a o , 62 I R e i n t j e s , 69 I Re in t ~jes , 69 |R e in t iesy 69 | R e i n t i e s , 69 I R i c h a r d s , 68 I Rich ar ds, 68  Sculpins  Cyprinidae  T1 1 1 1  LM (CM)  x| -+I I f I m|  on next page  I f | 0 . 9 !0.4 | 7. 3| I m | 1. 1 | 0 .7 | 7. 2| I f | 0 . 8 |0.5 | 6.5| I m | 0. 9 | 0 . 9 |6.5|  0.047  91.8  0.137  67.2  4. 21 4. 61 5. 0 | 5. 0 l  0.045 0.080 0. 135 0.066 0.04 1 0. 209 0.212 0.900 0.429 0.126 0.076 0.257  3.7 7. 5  0. 17  0. 148  _i  17. 5 35.0 34.0 42. 5 31.6 31.6 22. 8  0.016 0.092  ISmyly , ISmyly, ISmyly, ISmyly,  8.0 6. 1 5. 4 7. 2  215. 89. 35. 4 31. 6  7.0 6.0  25. 4  8. 0  72.2 115. 7 85. 4 6 2. 1 91, 6 117. 9 63. 8 69. 3 88, 0 51. 9 70. 9 115. 3 52. 6  -+  26. 5  4. 3 8. 2 6.7 6. 1 5.9 10.3 10.9 8. 2 9.6 7.8 11.6  57 57 57 57  | A l i k u n h i , 66 l A l i k u n h i , 66 l A l i k u n h i , 66 l A l i k u n h i , 66 |Alra, 17 |Alm, 19 i Wundsch, 39 I L a s k a r , 48 IBackiel+Zawisza, IBackiel+Zawisza, |Backiel+Zawisza, IBackiel+Zawisza, IBackiel+Zawisza, |Backiel+Zawisza, (Backiel+Zawisza, IBackiel+Zawisza, I B a l a g u r o v a , 63 IBalagurova, 6 3 | B a l o n , 63 I Baiich, 6 J IDauch, 63 | B e l y i , 62 I B e l y i , 62 IBerg, 49 I B e r q , 49 | Berq, 49 .. |Berg e t a l , 49 IBerg e t a l , 49  68 68 68 68 68 68 68 68  1  )  SPECIES  ft 1  NftUE  2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 02 2 2 2 2 .2 2 2 3 3 3 3 3 4 4 4 4 4  Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Afcramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Abramis brama Rutilus r u t i l u s Rutilus r u t i l u s Rutilus r u t i l u s Rutilus r u t i l u s Rutilus r u t i l u s Leuciscus leuciscus Leuciscus leuciscus Leuciscus leuciscus Leuciscus leuciscus Leuciscus leuciscus Leuciscus l e u c i s c u s a Leuciscus leuciscus a Leuciscus leuciscus a Leuciscus leuciscus 4 Leuciscus leuciscus Leuciscus leuciscus 4  ..Table  1 continued  C a s p i a n Sea DSSR:Azov Volgograd Reservoir V i s t u l a F i r t h (lagoon) Germany:Gr.Ploner Ob.Ausgrabensee V i e r e r See Hungary:Lake F e r t o Netherland (inland) E n g l a n d : M a d i n g l e y Lake E n g l a n d : N o r f o l k broads Finland:Onkamo Finland:Tuusula Poland:14 Mazurian l a k e s Caspian Sea:north Ammersee S i mssee Greece:Lake V o l v i E n g l a n d : R i v e r Wellan DSSR:Aral USSR:Aral USSR:Ilmen Lake uSSR:Ilmen Lake Vitava (river) Rybinsk R e s e r v o i r Danube D e l t a ( r i v e r ) Poland:Szczecin F i r t h K a r e l SSR:Siamozero K a r e l SSR:Niukozero N e t h e r l a n d (pond) Hommanas-Pellinge DSSR:Volga Azov Sea Muggelsee Lake Langer See V i s t u l a near Warsaw DSSR:Ziemen ( r i v e r ) Netherland (inland) N e t h e r l a n d (pond) de B i e s b o s de B i e s b o s Lake I j s s e l W i l l c w Brook England:Afon L l y n f i England:Afon L l y n f i E n g l a n d : R i v e r Lugg E n g l a n d : R i v e r Lugq R i v e r Funshion R i v e r Can N e t h e r l a n d (pond) R i v e r Thames R i v e r Frome R i v e r Thames  on next page  u  a  r  |  L O  (CH) | (CM)  0.255|  53.4|  30.2 38. 0  0.099 | 94.3| 0.109| 60.0| 29.0 0.030 | 201.3 I 38. 0 20. 3 31.6 17. 7 0.122 | 71.41 0.062 | 106.81 0.233  1 1 1 1 1 1 1  42. 0  1  0.076 | 0.168 | | | | 0.293 | 0.056 | 0.090| 0. 267 | 0.079 | |  0.041 | 0.111| 0.199|  | | | | |  0.186 | 0.301 | 0. 198|  21.5| 2 5. 3 | 20.2|  u  i  (CM)  4. 4.5  9.0  6.0 7.0 5.5 6.0 2.5  6.5 6.2 7. 01 7. 6|  24. 0| 6. 0 1 | 13*. 3| 5. 5| 6. 61 15. 2| 6. 0 1 2. 8| 6. 1 | 31.6| 38.0| 20. 3 | 29. 11 35.4| 31.6| 34.2| 32.9|  79.31 38. | 73.5| | 36.7| | 36. 1| | 36.7| 47.8| 69.7| 88. 5| 36.7| 57.91 54. 1 | 25.3) | 22. 21 132. 3| 97.9| 33. 1 |  0.323| 26. 11 0. 304 | 24.6| 0.057| 100.2| 0.371| 22. 9| 0.286 | 23.8| 0.317| 24.01 0.361| 22.6| 0.319| 2 3.8| 0.693 | 24. 1 | 0. 562 | 22. 8 |  r a  (YR)  8. 0 7. 5 3. 0 5. 0 5. 0 4. 0 6. 5 6. 0  | | | | | |  7.8) 6. 1| 14.2| | 6. 0 8. 0 | 9. 0 7. 4 | 3. 2 | 7. 0 5. 8 | 10.1| | 6. 5 | 6. 0 7. 1 I 8. 5| 6.0 | 10.01 6. 3| 6. 4 | 6.0| | 9. 5  | | | | |  12.0| | |  1  Dementeva, 52 Dementeva, 52, 55 E l i z a r o v a , 62 F i l u k , . 57, 62 G e y e r , 39 Geyer, 39 G e y e r , 39 Geyer+Mann, 39 I H o f s t e d e , 73 I H a r t l e y , 47 I H a r t l e y , 47 I J a r n e f e l t , 21 I J a r n e f e l t , 21 |Karpinska-walus, Lukashov, 61 I L a s k a r , 48 I L a s k a r , 48 |Laskar , 48 |Leeming, 6 3 IMorozova, 52 IMorozova, 52 |Morozova, 52 |Morozova,52 l O l i v a , 58 |Ostroumov, 55 I Papadopol, 6 3 I P e c z a l s k a , 63 IPotapova, 54 I P o t a p o v a , 54 I S t e i n m e t z , 73 | S e q e s t r a l e , 33 I S h a p o s h n i k o v a , 48 ITimofeev, 64 |Wundsch, 39 JWundsch, 39 |Za w i s z a , 51 IZhukov, 58 I H o f s t e d e , 73 I H o f s t e d e , 73 . | H o f s t e d e , 73 I H o f s t e d e , 73 I H a v i n q a , 45 |Cragq-nine*Jones, l l i e l l a w e l l , 73 I H e l l a w e l l , 73 l l i e l l a w e l l , 73 I H e l l a w e l l , 73 I H e a l y , 56 I H a r t l e y , 47 I H o f s t e d e , 73 | Mathevs + ^ . i l l i a m s , |Mann, 67 | W i l l i a m s , 67  SP I  AREA  SPECIES NAME  no |  1—4-  5|Cotla c o t l a 5|Cotla c o t l a 5|Cotla c o t l a 7|Phoxinus phoxinus  -4-  i  i  I I •4-44I0.28 | I I |0. 306 | If I |0-306 | I ml I H 1 10.55 | I x|  Easyatidae  I R i v e r Yamuna | R i v e r Yamuna I R i v e r Yamuna I Windermere Stinq  akajei akajei  LINF | (CM) | 1127.51 115.9| 115.91 9.0|  LM | TM | L l | (CM) I (YR) I (CM) |  H  '  | 2.0 | 44. 2 | 2.0| 44.2| 2.0 | 3. 8|  +  D  AUTHOR  |3.1513 199 I 3 264  ( w i t h  y e a r  | Japan |Ja pa n  1  T  Im| |0.1 |f|0.45J0.1  i  J h i n g r a n , 68 Natarajan*Jhinqran, Natarajan+Jhinqran, F r o s t , 43  1  )  -  63 63  i  rays -T—1  1|Dasyatis 1|Dasyatis  (1  T  .j  +  1-  | 105.0| | 150.0| i  40.0| 44.0|  Y o k o t a , 51 Y o k o t a , 51  i _  Drepani dae 01|Drepane I  africana  ) Nigeria  L  Embiotocidae 01ICymatogaster a g g r e g a t a 0 11Cymatogaster a g g r e g a t a Engraulidae 1|Engraulis encrasicholus 1 | Engraulis encrasicholus 1|Engraulis encrasicholus 1|Engraulis encrasicholus 1 | E n g r a u l i s enc r a s i c h o l u s 2 | E n g r a u l i s japon i c u s 2 | E n g r a u l i s ja pen i c us 3|Engra u l i s mordax 0 3 | E n g r a u l i s mordax 4 | Cetengraulis mysticetus 4|Cetengrau l i s m y s t i c e t u s 4|Cetengraulis mysticetus 4|Cetengraulis mysticetus • 4 | C e t e n g r a u l i s ra y s t i c e t u s 4|Cetengrau l i s m y s t i c e tus 4|Cetengraulis mysticetus 4 | C e t e n g r a u l i s m yst i c e t u s 4|Cetengraulis mysticetus 4|Cetengraulis mysticetus 4|cetengraulis mysticetus 4|Cetengrauli s mysticetus 4|Cetengraulis mysticetus Ga didae  -^—r  16.0|  31.oI~15.57  I I  _x i _  u.  Lonqhurst,  63  4,  Surfperches | Canada:Keates I s l a n d |Canada:Keates I s l a n d  -T  •i—r~ lf I  | |  1  1  r-  10.0| 9.0|  2.0| 1.5|  7.4| 7.3|  Gordon , 65 Gordon, 65  Anchovies | Romania |North Sea | M e d i t e r r a n e a n - e a r l y spwn | H e d i t e r r a n e a n - l a t e spun |Cali fornia ITohoku and T o k a i r e g i o n | Japan (California (California |Almejas Bay IGuaymas Bay |Ahome P o i n t | Banderas Bay I G u l f of Fonseca,1952 IGulf of Fonseca,1954-55 I Monti j o Bay IGulf of Panama (1 951-60) I G u l f of Panama (196 1-63) IColumbia I Ecuador-Peru IGuaymas, Ahome, Fonseca (Peru  1 .0 1.4 1.8 1.5  | | | |  1.6 0.4 0.5 1.23 2.58 2.42  | | | | | |  2.9 2 0.90 2.42 2.36 1.3 1 2.09 1.34 1.7 1 .3  | | | | | | | | |  | 12. 5| 1.0|  | 13. 5| 1 1 10.51 1 1 11.5| 1 1 11.0| 1 1 8. 8| 1.0|10.5| 10.5| 1 1 | 1 1 15.0| 1 1 12.7) 1.0|12. 1 | 12.8| 1.0|12.7| 13.21 1.0|13.2| | 11.5| 1.0| | 15. 4 | 12.8| 1.0| I 17. 1 | 12. 8| 1.0| | 15.9) | 14.9| | 15.0| 12.6) 1.0|12.7| 17.0) 12.6| 1.0 | 13.7| 14.3| 12.6| 1. 0 | 1 2. 71 14.5| 11.8| 1.0|11.8| 17.5) 13. 5| I I I 18.0| I 1  20. 0 | 16.5| 16.0| 15.01 16. 0 | 15.0| 21.0| 19.0| 16.6| 14.2| 14.6|  I C a r a u s u , 52 IFaqe, 20 |Faqe, 20 |Fage, 20 I F u r n e s t i n , 45 I H a y a s h i , 61 IHatanable, 58 |Clark+ P h i l l i p s , 52 | M i l l e r + W o l f , 58 I B a y l i f f , 69 I B a y l i f f , 69 | B a y l i f f ,"69 I B a y l i f f , 69 I B a y l i f f , 69 I B a y l i f f , 69 I B a y l i f f , 69 I B a y l i f f , 69 • I B a y l i f f , 69 | B a y l i f f , 69 I B a y l i f f , 69 ( B a r r e t t + H o w a r d , 61 I B a r r e t t+Uoward, 61  Codf i s h e s  02|Gadus m a c r o c e p h a l u s |Canada:west c o a s t 02|Gadus m a c r o c e p h a l u s |Canada:west c o a s t |Canada:Pacific coast 2|Gadus m a c r o c e p h a l u s | B e r i n g Sea 2|Gadus m a c r o c e p h a l u s IJapan Sea 2|Gadus m a c r o c e p h a l u s IF.nglish Channel 3|Gad us minutus | E n g l i s h Channel 3|Gadus minutu s .+ -J—+. . . T a b l e 1 c o n t i n u e d on next page  m| fl  |m|1. 1 I 0. 42 If I 0.9 I 0 .40 -+H  93. 0 | 93. 0 | 94. 0 | 91.0| 100.01 20.0| 24.0| +-  49.0| 2.0| 55.0| 2.5| 55. | 3.0|26.0 118.0 I 16.8 I 11. 13.  (Forrester, 69 | F o r r e s t e r , 69 I K e t c h e n , 61, 64 | Mo i s e e v , 5 3 I S v e t o v i d o v , 49 |Menon, 50 IMenon, 50  !—+ 3 4 4 4  4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 6 07 7 7 7 7 07 07 07 07 07 07 07 07 07 7 7 8 8 9 10 11 11 11 13 14 14 14 14 14  —  Gadus minutus Gadus morhua Gadus morhua Gadus mcrhua Gadus morhua Gadus morhua Gadus morhua Gadus morhua Gadus morhua Gadus morhua Gadus morhua Gadus morhua Gadus morhua Gadus morhua Gadus morhua Gadus morhua Gadus morhua Gadus morhua Gadus morhua Gadus morhua Gadus morhua Gadus morhua Gadus morhua Gadus v i r e n s Melanogrammus a e g l e f i n u s Melanogrammus a e g l e f i n u s Melanogrammus a e g l e f i n u s Melanogrammus a e g l e f i n u s Melanogrammus a e g l e f i n u s Melanogrammus a e g l e f i n u s Mela nogrammus a e g l e f i n u s Melanogrammus a e g l e f i n u s Melanogrammus a e g l e f i n u s Melanogrammus a e g l e f i n u s Melanogrammus a e g l e f i n u s Melanogrammus a e g l e f i n u s Melanogrammus a e g l e f i n u s Melanogrammus a e g l e f i n u s Melanogrammus a e g l e f i n u s Melanogrammus a e g l e f i n u s Merluccius merlucius Merluccius merlucius Boreogadus s a i d a Eleginus g r a c i l i s T h e r a g r a chalcogramma T h e r a q r a chalcogramma T h e r a g r a chalcogramma Gadus merlanqus M i c r c u e s i s t i u s pontasson M i c r o r a e s i s t i u s pontasson M i c r o m e s i s t i u s pontasson M i c r o m e s i s t i u s pontasson M i c r o m e s i s t i u s pontasson  +  ...Table  .  LINF (CM)'  AREA  SPECIES NAME  SP no  M e d i t e r r a n ean ICNAF 4x ICNAF 4VW North Sea West Greenland Eastern Scotian Shelf West Greenland west Newfoundland Labrador e a s t Newfoundland F l e m i s h Ca p Grand Bank S t . P i e r r e Bank Labrador Labrador \ North Sea George Bank B a r e n t s Sea Newfoundl.:west(offshore) Newfoundl.:west(inshore) Newfoundland:west Newfoundl.:west ( o f f s h o r e ) Newfoundl.:west(offshore) Norwegian Sea Norwegian Coast North Sea ICNAF ' 5 ICNAF 4VW ICNAF 3N0 Eastern Scotian Shelf Southern Nova S c o t i a Southern Nova S c o t i a Iceladn Arcto-Norwegian North sea-slow growth North s e a - f a s t growth Faroe Faroe North Sea Brown Marmora Sea Marmora Sea A r c t i c Ocean Hokaido:Pacific coast B e r i n g Sea B e r i n g Sea Japan Sea:south I r i s h Sea Western M e d i t e r r a n e a Tuscan A r c h i p e l a g o Fa roe Scot.land:west c o a s t Iceland  +  1 c o n t i n u e d on next page  2. 3 |0. 10| I 0.20| |0.2 |0.18| I  |0. 18 | 10. 15| I I 10.25| I 0.25| |0. 2'. I I 0. 18| I I I 0.201  10.15| I  |0. 2 10.201 | 0.20| 10. 25| 10.20| 10.23 I 10.20|  0.15| I |0.20| 10. 6 10. 5  0.2  LM •~M)  TM (YR)  21.0 105. 0 1 10. 0 132. 0 87. 5 105.0 94. 0 1 15. 0 67. 5 100. 0 100. 0 130. 0 95.0 67. 5 105. 0 112.5 134.0 93. 91.0 1 10. 0 107. 0 53.0 73.0 67. 5 57. 5 77.5 68. 8 67.0  70. 85.  45.5 49.7 71. 30. 0 26.  48.3 58. 1 77.9 33. 5 | | 67. 5 | 44. 0 | 23. | 60. 0 | 27. | | 22.0| 40. 0| 30. | | 94. 8 ( | 79. 6 | 55.0 31.3| 27. 9 28. 1 33. 4 | 39. 9 43. 2|  19.0| 19. 3| 20.01 20.0| |  L1 (CH)  AUTHOR  (with  year  19  )  +  Vives+Suau, 56 B e v e r t o n , 65 B e v e r t o n , 65 B e v e r t o n + H o l t , 57 Hansen, 61-63 3 . 0 7 5 | H a l l i d a y , 72 H o r s t e d , 69 K o h l e r , 64 May et a l , 64 May e t a l , 64 May et a l , 64 May e t a l , 64 May e t a l , 64 May, 67 Pinhorn, 7 5 P a r r i s h , 56 18.0 S c h r o e d e r , 30 T a y l o r , 58 Wiles+May, 68 Wiles+May, 68 Wiles+May, 68 Wiles+May, 68 5. 1 Wiles+May, 68 6. 1 G o t t l i e b , 57 Blacker, 7 1 3.0 B e v e r t o n + H o l t , 57 B e v e r t o n , 65 B e v e r t o n , 65 B e v e r t o n , 65 H a l l i d a y , 72 Hennemuth e t a l , 64 Hennemubh e t a l , 64 I c e s , 69 I c e s , 69 J o n e s , 62 J o n e s , 62 J o n e s , 62 P a r r i s h * J o n e s , 53 P a r r i s h , 56 3. 5 U.S.Res.Rep, 62 (ICNAF) B e v e r t o n + H o l t , 59 B e v e r t o n + I i o l t , 59 B e v e r t o n + H o l t , 59 Ilaqa e t a l , 57 2. 5 20.0 H i r s c h h o r n , 73 H i r s c h h o r u , 73 Ogata, 56 3. 5 10.5 G a r r o d , 64 Bas, 6 3 1. 0 19.0 2.970|Matta, 59 1. 0 20.0 P a i t t , 66, 68 3. 0 19.5 H a i t t , 66, 68 3. 0 18.9 R a i t t , 66, 6 8 20.4  OJ  I—+-  | | ..j  IE  AREA  SPECIES NAME  SP|  r  14 | M i c r o m e s i s t i u s p o n t a s s o n | N o r t h S e a : n o r t h I North S e a : n o r t h 15|Trisopterus esmarkii ISouthern New England 16|Merluccius b i l i n e a r i s I G u l f o f Maine 16|Mcrluccius b i l i n e a r i s IScotian Shelf 17|Erosrae brosme IScotian Shelf 17|Brosn\e brosme  K +  I I I |0.405| 18.9| |0.402| 46.8| |0.181| 63.0| |0.051| 125.5| I I I  If If I f I m  | TM | L l | I A U T H O R ( w i t h year | (YR) | (CM) | (-| | | 2 . 8 6 6 | R a i t t , 66 14.5| 2.0| | I R a i t t , 66 | |11.0| I N i c h y , 69 | I 14.2| I N i c h y , 69 50.7| 6.5| |3.000|Oldham, 72 43.5| a.7| |3.025|01dham, 72  | LINF | LM | (CH) | (CM) 1-  +  +  Sticklebacks  Gasterosteidae  T~  0. 9 |0.64 1.1 |1.6  | C h e s h i r e (3-spined) I C h e s h i r e (10-spined)  11Gasterosteus aculeatus 11 G a s t e r o s t e u s a c u l e a t u s  | |  -~i  |Canada:west c o a s t |Canada:west c o a s t  01|Ophiodon e l o n g a t u s 0 11Ophiodon elonga t u s  |Lake H i n n i p e g o s i s |Lake W i n n i p e g o s i s |Saskatchewan D e l t a |Saskatchewan D e l t a |Lake C l a i r e |Lake C l a i r e  alosoides alosoides alosoides aloso ides alosoides aloso ides  Freshwater  Ictaluridae punctatus  If |m  -l—  If |m If I m If I to  ( |  araericanus audax albidus albidus albidus  IForrestar, |Forrester,  69 69  _i  |0. 352 | |0.535 | |0.171 | I 0.2 33| |0.127| 10.178|  _l  :  —r-  36  I  —1—  |0.06  | 119 0|  | Atlantic (Western p a c i f i c |Atlantic | Atlantic | Atlantic  T  T  (1.1 | I I I I  | 236.0| | | 290. 0 J 190.0| I |130.0| I I I I I  If I m  •T  |South C h i n a Sea: G. "Conking | ISouth C h i n a Sea:southwest| Threadfin  Nemipteridae  1(Nemipterus v i r g a t u s 1|Nemipterus v i r g a t u s 11Nemipterus v i r g a t u s  | K e n n e d y * S p r u l e s , 67 |Kennedy*Spru l e s , 67 | K e n n e d y ^ S p r u l e s , 67 |Kennedy*-Sprules, 67 |Kennedy+Sprules, 67 |Kennedy+Sprules, 67 L  |Appelget*Smith,  0|  51  T  r  | |De S y l v a , 57 | |Ueyanagi+Wares, 75 | 3.915|Mather, C l a r k + Mason, 75 | 3.0 |De S y l v a + D a v i s , 63 | 3.6 |De S y l v a + D a v i s , 63  T  T  |0.142( |0.148|  breams  92.7( 96.51  I  ISouthern E a s t C h i n a I (Taiwan S t r a i t I ISouth China Sea:G.Tonking|  I I  r-  | I  J 20.8 J2. 8 0 2 | L a i t L i u . 74 |21.6|2.871|Lai+Liu, 74  18.0| 16.0| 15.0|  | K j o » L i u , 74 | K a o + L i u , 74 | K.io+Liu, 74  Smelts  Osmeridae  -T-T  1|Mallotus v i l l o s u s 1|Mallotus v i l l o s u s 1 continued  | | | | |15.7| (16.5| | 6.9) | 6.9|  36. 0 | 32. 2 | 44. 4 | 39. 6 | 50.8 | 42. 2|  Snappers  11 L u t j a n u s s a n g u i n e u s 1|Lutjanus sanguineus  ...Table  r5.0| 2.0 |  T  Billfishes  Lut -janidae  1—  T  137.0| 70.0| 90.0| 46.01  catfishes  ( M i s s i s s i p p i River  —JL  Istiophoridae 1|Istiophorus 2(Tetrapturus 3(Tetrapturus 3|Tetrapturus 3|Tetrapturus  50 50  Mooneyes  Hiodontidae  11Ictalurus  |Jones+Hynes, |Jones+Hynes,  6. 7 | • 3. 6J 3. 7 | 4. 3|  Greenlings  tl e x a g r aram i d a e  1|Hiodon 1 | Hiodon 1|Hiodon 1|Hiodon 1|Hiodo n 11Hiodon  )  (Trinity ITrinity cn next  page  Bay Bay  IfI I ml -+-'  T  1  1  1  T-  I I  I I  I 16.0| I 18.0|  T  | |  | |  -i  -i  +  +  +-  +  | J a II q a a r d, 74 I J a n g a a r d , 74 + I  |SP| 1 no |  •  I  SPECIES NAME  i  1  1 11 M a l l o t u s v i l l o s u s I 11 M a l l o t u s v i l l o s u s I * IM a l l o t u s v i l l o s u s t 11 M a l l o t u s v i l l o s u s I 2|Osmerus e p e r l a n u s I 21 Osmerus e p e r l a n u s 1 2|Osmerus e p e r l a n u s 1 2|Csmerus e p e r l a n u s 1 2| Csmerus e p e r l a n u s 1 2|Osmerus e p e r l a n u s 1 2|Csmerus e p e r l a n u s 1 2 |Osmerus e p e r l a n u s 1 2|Csmerus e p e r l a n u s ! 2|Osmerus e p e r l a n u s 1 2 |Osmerus e p e r l a n u s 1 2| Osmerus e p e r l a n u s 1 2|Osmerus e p e r l a n u s 1 2|Osmerus e p e r l a n u s 1 2|Osmerus e p e r l a n u s 1 2|Osmerus e p e r l a n u s 1 2|Osmerus e p e r l a n u s 1 2|Osmerus e p e r l a n u s 1 2|Osmerus e p e r l a n u s 1 2|Osmerus e p e r l a n u s 1 21 Osmerus e p e r l a n u s 1 2|Csmerus e p e r l a n u s 1 2|Osmerus e p e r l a n u s 1 3|Hypomesus o l i d u s  1  AREA  E| « x1  t | Labrador |Labrador | Newfoundland | Newfoundland ILadoga Lake I G u l f o f Ob | Kandalaksha Bay | Huron |White Sea - Onega bay |Michigan |Pakovsko-Chudskoya Lake IWhite Lake |Neva R i v e r |Dvina Bay'white s e a ) IChesha Bay |Rybinsk |Elbe R i v e r IKurishes Haff:non-migrant IKurishes Haff:sea-migrant IPyaozero ( K a r e l i a ) JMiramichi River |Yenisey R i v e r |Lena R i v e r |Basin of Maine |Onega Lake IDadey Lake ILazmiaden Lake |Japan:Lake Suwa  fI m| f| m1  1  K  1  o.48 1 o.48  1  | LINF | LM (CM)' | (CM)  |  | | I | I | l | l I l I | 1 10. 061 | | 1 | 1 1 | 10. 204 | |0. 135 | |0. 18 | | 1 I 0.265| | 1 I 1 I 1 I 1 |0. 264 | I 1 | 1 10. 372 | | 1 I 1 11. 65 |  19.01 20.01  90.1 |  25.4 40.7| 31.6 32.6  28.5 12. 5 11.5  b  | TM | L1 I | (YR) I (CM)  17. 0| 18.01 | | | 2.0| I 4. 5 | 1 3. 5| I 2.0| | 3.0| | 2. 0 | I 1. 0 | | 1.5| | 3.51 I 3. 5| I a. 51 I 1.5| 1 2.0| I 1.0| 1 2.0| 1 5.0| I 2.0| I 5.5| 1 7.5| 1 2.5 | I 3.0| 1 1.0| 1 2. 5| 10.01  3.25 3. 41 8.0] 4.7 4.7 9.2 7.2 6.0 7.8 4. 1 3. 5 5. 9 7. 1 6. 3 6. 5 4.6 6. 3 7. 1 8. 2  |AUTHOR  (with y e a r  |Templemau, 48 ITempleman, 48 | W i n t e r s , 70 I W i n t e r s , 70 | A r k h i p t z e v a , 56 | A m s t i s l a v s k y , 59 | B e l y a n i n a , 69 I B a l d w i n , 48 | B a l a g u r o v a , 57 I C r e a s e r , 29 I F e d o r o v a , 53 |Fe dorova, 5 3 |Kozhevnikbv, 56 | K i r p i c h n i k o v , 35 | K i r p i c h n i k o v , 35 |Lapin , 56 I L i l l e l u n d , 61 IMarre, 31 IMarre, 31 |Melyantzdv, 46 |Mckenz i e , 64 INeiioan, 57 I P i r o j n i k o v , 50 |Rupp, 59 | S t e f a n o v s k a y a , 57 I W i l i e r , 26 I W i l l e r , 26 I S h i r a i s h i , 57  Derches  Percidae  i — i  1|Perca fluviatilis 1|Perca fluviatilis 01|Perca fluviatilis 2 | S t i z o s t e d i c n canadense 3|Lucioperca l u c i o p e r c a 3|Lucioperca l u c i o p e r c a 3|Lucioperca l u c i o p e r c a  I  | Sweden |Sweden | Sweden |Canada:Lake N i p i g o n |24 German l a k e s ( T o f t e n Lake |24 German Lakes Righteye  Pleuronectidae  30.0| 16. 0 30. 0| 10.0 34. 0| 40.0| 78.8| 102.0| 82.4|  I0.054 I I I I I |m| (fl |0, 36 |m| |0 26 If I If I |0 ,244 |m| |0 281 I I I I |0.36|0.,4 Ifl 10.,02 |m| |0..04 -+H——+-  "T rI i I I I I I I |13.0| I 7.0| | 1 5. 0 |  _l  flounders  11Hippoglossus s t e n o l e p s i s |Alaska 1 | H i p p o g l o s s u s s t e n o l e p s i s I North P a c i f i c 02|Isopsetta i s o l e p i s |Canada:west c o a s t 02 I I s o p s e t t a i s o l e p i s |Canada:west c o a s t 2|Isopsetta i s o l e p i s |Canada:west c o a s t 2|Isopsetta i s o l e p i s |Canada:west c o a s t 02|Isopsetta i s o l e p i s (Hecate S t r a i t 02|Isopsetta i s o l e p i s IHecate S t r a i t 3|Tseudopleuronectes I | americanus ( S t . Mary Bay 4|Hippoglossus vulgaris INorth A t l a n t i c 4|Hippoglossus vulgaris INorth A t l a n t i c _ ,..Table 1 c o n t i n u e d on next page +  1 —  f |0.29|0. m|0.29|0. |0.16 10. |0.44|0. I 10. I 10. I 10.  214. 9 270. 0 39. 0 45.0 38.0 42.0 41.7 36. 6  10. 0 25.0 18. 0 21.0  250. 0 132. 0 95. 0 170.0  L.  |Alm, 52 |Alm, 52 l A l m , 52 I R i c k e r , 49 IBauch, 53 |Mnar, 47 |Ne uhaus, 34  .j  1Southward+Chapman, 65 7.4 | |Thompson+Cleave, 36 7.6 | | F o r r e s t e r , 69 6. 3 | | F o r r e s t e r , 69 6.11 | ( H a r t , 48 | |Hart,48 6.5|3.094|Kutty, 63 6.1|3.021|Kutty, 63 I  I Dickie+McCracken, |Devoid, 38 |Devoid, 38  55  AREA  SPECIES NAME  9 10 11 12 12 13  m m  15 15 15 15 15 15 15 16 18 18 18 18 19 19 19 19 19 19 19 19 19 19 19 19 19 20 20 20 20 20 20 20 20 z1  Pleuronectes platessa Pleuronectes platessa Atheresthes evermanni P.einhardtius hippoglossoides R. h i p p o q l o s s c i d e s Hippoglossoides dubius Hippoglossoides robustus Cleisthenes herzensteini Eopsetta g r i g o r j e w i Limanda a s p e r a Limanda a s p e r a Clidoderraa a s p e r r i u m Glyptocephalus stelleri Glyptocephalns stelleri Glyptocephalus cynoglossoides G. c y n o g l o s s o i d e s G. c y n o g l o s s o i d e s G. c y n o g l o s s o i d e s G. c y n o g l o s s o i d e s G. c y n o g l o s s o i d e s G. c y n o g l o s s o i d e s Microstomias achne Eopsetta j o r d a n i Eopsetta j o r d a n i Eopsetta j o r d a n i Eopsetta j o r d a n i Hippcglossoides platessoides H. p l a t e s s o i d e s H. p l a t e s s o i d e s H. p l a t e s s o i d e s H. p l a t e s s o i d e s II. p l a t e s s o i d e s H. p l a t e s s o i d e s H. p l a t e s s o i d e s H. p l a t e s s o i d e s H. p l a t e s s o i d e s H. p l a t e s s o i d e s II. p l a t e s s o i d e s H. p l a t e s s o i d e s Lepidopsetta b i l i n e a t a Lepidopsetta b i l i n e a t a Lepidopsetta b i l i n e a t a Lepidopsetta b i l i n e a t a Lepidopsetta b i l i n e a t a Lepidopsetta b i l i n e a t a Lepidopsetta b i l i n e a t a Lepidopsetta b i l i n e a t a Limanda f e r r u g i n e a  z1|Limanda  Man I s l e Scotian Shelf Scotian Shelf Nova S c o t i a : s o u t h Nova S c o t i a : s o u t h Nova S c o t i a : s o u t h G.St.Larence o f f Kinkazan (miyagi Canada:west c o a s t Canaea:west c o a s t Canada:west c o a s t Canada:west c o a s t Scotian Shelf Scotian Shelf New England New England Cape Breton I s l a n d Cape.Breton I s l a n d East Newfoundland E a s t Newfoundland Grand Bank Grand Bank G.St.Lawrence:south G.St.Lawrence:south G.St.Lawrence:south Canada:west c o a s t Canada:west c o a s t Cox I s l a n d Cox I s l a n d Western G u l f o f A l a s Western G u l f of A l a s B r i s t a l Bay Norswest B r i s t a l Bay Norswest Sable I s l . Bank ; Ranquerean New E n g l a n d : s o u t h  on  next  page  M  |  K  I |  | LINT  I (CM) |  | LM | (CM)  f |0.12|0.08 m I 0.22|0.15  | 'rn | (YR)  |  1  —[  1  |  (CM)  I  L  j.  A U I M U K  i w i t n year  11_  1  Bevertcn+Uolt, 59 | 70.0| 28. 01 B e v e r t o n + H o l t , 59 | 45.0| 25. 0 | Kasahara, 55 1 1 80. 0| 4 0. 0 | 7.5| 11.21 1 1 3. 230 L e a r , 69 1 1 Mikawa, 63 1 1 90.0| 60. 0| 13.0 14.4| Y o s h i i k e , 62 I 1 41.5| 25. 5| 5. 5 12.5| Pruter+Alverson, 62 4.4| 1 1 32. 0 | 19.5| Katanabe, 56a 1 1 39.0 | 18.0| 3.0 8. 5 | O u c h i , 56 1 1 34.0| 20. 5 | 3.5 8.5| Pruter+Alverson, 62 8.0| 1 1 36.0| Polutov,: 67 1 1 50. 0 | 23* Oj 6.0 3. 5| Kinoe, 52 I I 49. 0| 30. 0| 4 .0 | 11.01 Hamai+Ishido, 58 1 1 4 5.0| 30. 0| 6.0 11.01 Watanabe, 56b 13. 0| 6. 7 | 1 1 1 1 40. 0 | Bowers, 60b 7.7| 1 1 H a l l i d a y , 73 f 0.1510.07 | H a l l i d a y , 73 m 0.2010.12 | Powles+Kennedy, 67 f I0.07 | 83.8| Powles+Kennedy, 67 m 10.12 | 60.9| I I 3.649 Powles, 67 3.576 Powles , 67 1 1 K a s a h a r a , 53 5.6| 1 1 40.0| F o r r e s t e r , 69 f 1 1 70. 0| 44. 0 8.0 F o r r e s t e r , 69 tn 1 1 53. 0 | 38.0| 7.0 Ketchen+Forrester, 66 f 0.20|0.167 | 58. 6| 44. | 8.0 Ketchen+Forrester, 66 ID 0.25|0.160| 49.0 | 38.0 7.0 1 1 H a l l i d a y , 73 f 0.20|0.013| 229.8| H a l l i d a y , 73 m 0.25|0.114| 44.6| Lux, 70 f 10.15 | 67.5| Lux, 7 0 m 10.27 | 45. 0 f 10.06 | 78. 1 | 3.423 M i n e t , 73 m |0.10 | 54.4 3. 194 M i n e t , 73 P i t t , 73 f 0.25|0.06 | 81. 1 P i t t , 73 m 0.2310.11 | 55. 2| P i t t , 73 f Q. 1810.11 | 72. 5 P i t t , 73 m 0.26|0.15 | 58. 51 I I 3. 1 39 Powles, 67 f 3. 234 Powles, 67 I I m 2. 814 Powles, 67 I I F o r r e s t e r , 69 f 60.0 36. 0 4.0 I I F o r r e s t e r , 69 ro 53.0 28.0 4.0 I I f m  I  I  | 0.254| 40. 1 |0.158| 41.2 m |0. 168| 3 5. 9 fI 10.1541 44.6 |0.109| 50. 1 m i i I 1 0.30 I 0.063 | 77. 9 f 0.22|0.583| 47.3 f  +H  +  1 continued  coast  T r i n i t y Bay B e r i n g Sea:Tohoku area Wakasa Bay B e r i n g Sea Sanin D i s t r i c t Japan Sea:south B e r i n g Sea Kamchatka:Okhosk c o a s t o f f Miyako Tohoku Region Hokkaido '  ferruginea  — +  ...Table  North Sea North Sea Hokkaido:pacific  E| x|  +-  9.5| 1 9. 5 | 1 7.4| 7. 2| 6.8j  Levinqs, Levinqs, L o v i n g s, Levin<js, Levinqs, Levinqs,  65 65 65 65 65 65  H a l l i d a y , 73 Lux+Nichy, 69  |SP| | no | T  —  | I  SPECIES NAME  +  |z1|Limanda f e r r u g i n e a |z1|Limanda f e r r u g i n e a | z 1 | Litnanda f e r r u g i n e a | 2 11Limanda f e r r u g i n e a |22|Parophrys v e t u l u s |22|Parophrys v e t u l u s | z2|Parophrys vetulus |z2|Parophrys v e t u l u s  AREA  i1 |New E n g l a n d : s o u t h IGeorge Ank IGeorge Ank |G.St.Lawrence:south |Canada:west c o a s t |Canada:vest c o a s t IWashington:Carr I n l e IWashington:Carr I n l e  |E| Ul i  i.i  i  |m| If 1 |m| 1 1 1 fl |m| If 1 1 m|  I LINF | | (CM) I -+ -+10 ,838 | 39. I 50. 21 10 ,512| 42. 21 10 ,693| I 57. 0| 49.01 10 ,243 | 4 1.6| 30.7| 10 ,347 | I I  | TM | L l | LM (CM) I (IfR) I (CM) | • + —  30. 25.  holhrookii holbrookii  |Portugal I Portugal  | m|  Th r e a d f i n s  Polynem idae  | 0. 8 I 1.2  -+—. • |Lux*Nichy, 69 6. 3 | |Lux+Nichy, 69 7.0| |Lux*Nichy, 69 7.0| 12. 829|Powles, 67 | F o r r e s t e r , 69 • 0| | F o r r e s t e r , 69 • 0| l l l o l l a n d , 69 M5. 0| | H o l l a n d , 69 114. 5|  i_.  INigeria (Nigeria  i  _j  jubeiini  | Nigeria  Salmcnidae  T  "  I I  I 40.0|  15.0| 21.01  I  I  T  r  |  20.0|  •1  T~  I 8.5| |11.0|  I L o n g h u r s t , 63 |Longhurst, 6 3  ILonghurst,  63  Trouts |North P a c i f i c |Oregon ( t i l l a m o o k Bay |Oregon ( t i l l a m o o k Bay |Canada:Columbia R i v e r |Canada:Columbia R i v e r |Canada:Columbia R i v e r |Canada:Columbia R i v e r |North P a c i f i c |Hokk aidoanean | Yukoslavia | W i s c o n s i n : T r o u t Lake | W i s c o n s i n : T r o u t Lake | W i s c o n s i n : M u s k e l l e n g e L. I W i s c o n s i n : M u s k e l l e n g e L. | W i s c o n s i n : S i l v e r Lake | W i s c o n s i n : S i l v e r Lake | W i s c o n s i n : C l e a r Lake | W i s c o n s i n : C l e a r Lake |Canada:Lake N i p i g o n |Canada:Shakospenre Lake | W i s c o n s i n : T r o u t Lake |Canada:Lake Opeongo |Canada:Lake Opeongo I USA | OS A |Alaska:Lake I k r o a v i k |Canada:Gt.Slave Lake |Canada:Cultus Lake _ on next page  Oncorhynchus k e t a Oncorhynchus keta Oncorhynchus keta Oncorhynchus keta Oncorhynchus keta Oncorhynchus keta Oncorhynchus keta Oncorhynchus keta Oncorhynchus keta Thymallus t h y u a l l u s Coregonus a r t e d i i Coregonus a r t e d i i Coregonus a r t e d i i Coregonus a r t e d i i Ccregonus a r t e d i i Coregonus a r t e d i i Coregonus a r t e d i i Ccregonus a r t e d i i Coregonus c l u p e a f o r m i s Coregonus c l u p e a f o r m i s Coregonus c l u p e a f o r m i s Coregonus c l u p e a f o r m i s Coregonus c l u p e a f o r m i s Coregonus k i y i Coregonus k i y i Ccregonus s a r d i n e l l a S a l v e l v i n u s namaycush Oncorhychus nerka  +  1 continued  T  I I  Grunts  Pcmadasyidae  ...Table  | F r a n c a , 53 | F r a n c a , 53  6- 2 | 3. 6 |  ,  01|Pentanemus g u i n a r i u s 02|Galeoides decadadylus  i  (with year  —+-  .J  01|Pristipoma  IAUTHOR  Livebearers  Poeciliidae 1|Gambusia 1|Gambusia  I)  | j | | | | If I I m| | | |0.30 | 1f I 0.27 | 1m 10.39 | |f 10.45 | 1 mj | | | | | | | | 0,335| |f 1. 1 10.65 | 1 m 1. 1 10.65 | If 1.2 10.36 | 1 n 1. 2 |0.36 | If 0. 9 10.06 | 1 1. 1 |0.06 I I f 0. 3 10.27 | 1 m 0.4 |0.27 | | 0. 17 10.13 | | 0.15 |0.09 | | | 0.09 | |0.06 | | | 1.3 |0.43 | | f 0. 8 10.51 | 1 ro 0. 9 10.51 | I 0. 6 10.4 | | 0. 6 |0.07 | 1 |0.58 | + +m  | I I 105.01 120.0| 102. 0| 106.01 | | 46.7| 19.0| 19.0| 21.0| 21.0| 32.0| 32.01 39.0| 39.0| 50. 0 | 49.0| 4 4.0| 70.0 | 14.0| 28.0| 28.0| 38.0| 56.0| 6 9.0| +  I B a k k a l a , 70 i 1 a. o | 1 1 3.0 |Henry, 54 1 1 1 3. 2 I Henry, 54 1 75.01 IMarr, 43 1 12.6 81.0| 1 12.6 |Marr, 43 70.0| 1 12.6 |Marr, 43 IMarr, 4 31 12.6 75.0| 1 1 3. 2 | R i c k e r , 64 1 | | 2 . 8 1 7 | S e l l a , 29 1 | J a n k o v i c , 64 1 3.0|15.6| | H i l e , 36 12.5| 1 1 I H i l e , 36 12. 5| I I | H i l e , 36 15. 0| 1 1 15.0| • | H i l e , 36 1 1 | H i l e , 36 14.01 | | | H i l e , 36 14. 0| I I I H i l e , 36 13.0| | I I H i l e , 36 13. 0| I I | H a r t , 31 I | 27. 01 111 d r t , 31 I | 27. 0 | | II i l o * Deason, 34 23. 0 | | I |Kennedy, 43 I 1 1 I I 1 I | Deason«-Hile, 47 18.01 | | | Deason + t l i l e , 47 | | 18.0| I W o h l s c h l a g , 5 4a + b I | 1 |Kennedy, 54 18.4| | | | F o e r s t e r , 29 I | 60.0| +—+ 4. 4.  1 "J  )  SP| no |  SPECIES  AREA  NAME  1—+-  10|Salmo t r u t t a 11|Salvelinus alpinus 11 | S a l v e l i n u s a l p i n u s i Sciaenidae \  |England:L.Windermere |Canada:Daffin I s l a n d |Canada:Baffin I s l a n d  | LINF | LM | TM | L l | IE|M | (CM) | (CM) | (YR) | (CM) | IXI I H + 1 + ++-+30. 0| 24.01 | |0.9U|0.36 | I 140. 0| 60.0| |fI 0.24|0.03 | | 150. 0| ImI 0.24|0. 02 I I I  IThunnus thynnus IThunnus t h y n n u s IThunnus thynnus | Thunnus thynnus | Thunnus t h y n n u s IThunnus thynnus IThunnus a l a l u n g a IThunnus a l a l u n g a IThunnus a l a l u n g a IThunnus a l a l u n g a IThunnus obesus IThunnus obesus IThunnus obesus IThunnus obesus IThunnus obesus |Thunnus obesus IThunnus obesus lEuthynnus a f f i n i s y a i t o lEuthynnus a f f i n i s y a i t o ISccmber j a p o n i c u s |Scomber scombrus ISccmber scombrus | Thunnus r s a c r o y i i | Thunnus Ibacares 1 continued  1 <J_  I F r o s t + Srayly, 52 I G r a i n q e r , 53 I G r a i n g e r , 53  |0. 165| |0.38 | 10.31 | I0.37 | I I |0.345| |0. 375 | I I0.33 I0.34 |0.20 | 0. 6 6 I0.44 |0.35 | 0.29 10.37 I I I 0. 3 | 0. 3  I | | | | | | | | I I I |  76.9| 45. 0 | 46. 9| 42. 0 | 48. 0 | 34.01 34.9| 81.01 80. 0 | 47. 8| 54.0 | 52.7| 103. 0 | 61.21 79.01 128.0|  I L o n q h u r s t , 63 21.01 1 8.5| I L o n g h u r s t , 61,69 I 15.0| 32.6| |Lonqhurst,69 |16. 1 | 32.6| | |Lonqhurst,69 |13.0| | I L o n q h u r s t , 63 115.0| 16. 5| 1.0|16. 3 | 3. 0411Liu+Tzenq,72; Tzenq+Liu,72 16.5| 1.0|16.2|3. 182|Liu+Tzenq,72; Tzenq + Liu,72 • | | 1 |22.9| | Bayaqbona,66 |Bayaqbona,66; L o n q h u r s t , 6 9 122.31 35.01 | C o l l i g n o n , 6 0 ; Lonqhurst,69 |24.0| 28.01 | L o n q h u r s t , 61 |29.4| 35.0| | | P o i n s a r d + T r o a d e c , 66 |29.0| I T r o a d e c , 66; L o n q h u r s t , 6 9 |24.5| 28.0| | |Bayaqbona,66; L o n q h u r s t , 6 9 I 29. 1 | I L o n q h u r s t , 63, 69 |30.3| 48.3| | P o i n s a r d + T r o a d e c , 66 |24.9| 1 i i • 1 1 1 35.0| |Lonqhu r s t , 6 3 1 1 IBerdeque, 55 I 1 1  s  M a c k e r e l s and t u n a s  Sccmbridae  ...Table  (with y e a r  Drums  01|Pseudotolithus elcngatuslNigeria 1 | P s e u d o t o l i t h u s e l o n g a t u s | S i e r r a Leone 1 | P s e u d o t c l i t h u s e l c n g a t u s | S i e r r a Leone 1|Pseudotolithus elongatus|Congo 02|Argyrosomus a r g e n t a t u s |Nigeria | East China Sea: s o u t h 2|Argyrosomus a r g e n t a t u s ITaiwan S t r a i t 2|Argyrosomus a r g e n t a t u s 3|Pseudotolithus I.Lagos (West A f r i c a ) | senegalensis |N i g e r i a 3|P. s e n e g a l e n s i s I Congo 3|P. s e n e g a l e n s i s | S i e r r a Leone, 3|P. s e n e g a l e n s i s | Ghana 3|P. s e n e g a l e n s i s ICongo 3 IP. s e n e g a l e n s i s |Lagos (West A f r i c a ) 4|Pseudotolithus typus 4|Pseudotolithus typus INigeria 4|Pseudotolithus typus |Conqo 05|Pseudotolithus I | brachygnasus INiqeria 6|Cynoscion macdonaldi IMexico  T"—4  I AUTHOR I  on next  South P a c i f i c South P a c i f i c Portuguese coast M e d i t e r r a n e a n Sea North A t l a n t i c North Sea North P a c i f i c : e a s t South P a c i f i c South P a c i f i c North P a c i f i c South P a c i f i c South P a c i f i c T r o p i c a l I n d i a n Ocean Tropical Pacific:west Hawaii Hawaii o f f Peru Ph i l i p p i n e s Aburatsu Tohoku and T o k a i Region C e l t i c Sea Northwest A t l a n t i c Australia South P a c i f i c page  If 1 1n|  | | | | |  | | | | |  1 f1 1 m|  | |  1f1 1 n1  | | | |  I f| 1 1 m  | | j |  | | | | I 10.22  | | | |  1 f1  172.01 172.01  |  I 85. 0 | 2.0 100. | 3. 300. 0 97. 5| 3.0 0. 6 1 270.0| | 13 5.6| 89. 0 | 4. 5 118.0| | 1 18.0| | 124. 0 90. 0| 6.0 160.0| I 160. 0 I 92. | 95. | 2.0 I 0. 167 | I 0. 114| 236.0 | 100. 0 45. 0 | 63. 0 I 30. 0| 2.0 41.2  |  45.0 34. 0| 2.0 222. 5 120.5| 5.5 156.0 1  2.98 2.92  52.0 3. 09 2.98 28.0 2.79 2.72 47.5  15.0 22. 5 26.0 2.85  | de J a e q e r , 63 | de J a e q e r , 63 F r a d e + V i i e l a , 60 Le G a l l , 54 S e l l a , 29 T i e w s , 57 C l e m e n t s , 61a | de J a e q e r , 63 | de J a e q e r , 63 Yabuta+Yukinawa, 63 | de J a e q e r , 63 | de J a e q e r , 63 Kume, 62 Nakamura, 65 Shornura+Keala, 6 3 Shomura+Keala, 63 Yuen, 55 Wade, 50 Yahe, 53 K o n d o, 66 ICES, 71 S e t t e , 43, R o b i n s , 63 | de J a e q e r , 63  SP I no |  8|Thunnus a l b a c a r e s 8|Thunnus a l b a c a r e s 8)Thunnus a l b a c a r e s 8|Thunnus a l b a c a r e s 8)Thunnus a l b a c a r e s 8|Thunnus a l b a c a r e s R|Thunnus a l b a c a r e s 8|Thunnus a l b a c a r e s 8|Thunnus a l b a c a r e s 8|Thunnus a l b a c a r e s 8|Thunnus a l b a c a r e s 8|Thunnus a l b a c a r e s 8|Thunnus a l b a c a r e s 8|Thunnus a l b a c a r e s 8|Thunnus a l b a c a r e s 8|Thunnus a l b a c a r e s 8|Thunnus a l b a c a r e s 8|Thunnus a l b a c a r e s 9|Katsuwonus p e l a m i s 9|Katsuwonus p e l a m i s 9|Katsuwonus p e l a m i s 09|Katsuwonus p e l a m i s 09|Katsuwonus p e l a m i s 09|Katsuwonus p e l a m i s 09|Katsuwonus p e l a m i s 09|Katsuwonus p e l a m i s 1 0 | A u x i s tapeinosoma 11|Scomber t a p e i n o c e p h a l u s 12|Pnema tophorus d i e g o 12|Pnematophorus d i e g o 13|Neothunnus m a c r o p t e r u s 13|Neothunnus m a c r o p t e r u s 13|Neothunnus m a c r o p t e r u s 13|Neothunnus m a c r o p t e r u s 13|Neothunnus m a c r o p t e r u s 13|Neothunnus macrop t e r u s 13|Neothunnus m a c r o p t e r u s 14 | Cory phaena h i p p u r u s 1 5 | R a s t r e l l i g e r neglectus 15|Rastrelliger neglectus 15|Rastrelliger neglectus 16|Pneumatophorus j a p o n i c u s 17|Parathunnus s i b i 17|Para thunnus s i b i 17|Parathunnus s i b i 17|Parathunnus sibi 17|Parathunnus sibi 10|Parathunnus 18|Parathunnus mebachi 18|Parathunnus mebachi 19 | R a s t r e l l i g e rmebachi kanagurta 1 9 | R a s t r e l l i g e r kanagurta 1 9 | R a s t r e l l i g e r kanagurta .Table  1 continued  LINE (CM)  AREA  SPECIES NAME  on next  South P a c i f i c North Amer.:west c o a s t North Amer.:west c o a s t Eastern T r o p i c a l P a c i f i c South-west P a c i f i c I n d i a n Ocean:east Indian Ocean:central I n d i a n Ocean:west Southern Taiwan North Araer.:west c o a s t Eastern A t l a n t i c • Eastern A t l a n t i c Tropical Pacific Paci f i c Japan:Pacific coast, Paci f i c Paci f i c Atlantic Southern Taiwan Southern Taiwan Northwest P a c i f i c Australia Hawaii Philippines Philippines Sulu Sea Tohoku East China Sea California C a l i fornia Hawaii Paci f i c Philippines Philippines Philippines Philippines Japan s e a Gulf of TailandG u l f of T a i l a n d Gulf of T a i l a n d Japan Western P a c i f i c Marshall Isl.south Philippines Philippines Pacific Paci f i c Pacific Pacific Tndia:Cochin India:Andaman I s l a n d India:Karwar page  0.60 0.66 0.136 0.386 0.278 0.290 0. 349 0.333 0.60 0.3 84 0.42 0.33 0.55 0.66 0.356 0. 278 0.302 0.432 0.77  156.0 167. 0 167 326 174 212 215 191 192.8 169. 191.7 194. 8 190.1 100. 0 190. 1 168. 150. 195. 2 222. 8 103. 6 10 3. 8 105. 5 46.5 222. 5 120.0 82. 3  0. 131 | 15 3.2! 50. 01 43. 0 | 39. 6| 40.0| 0. <* I 0. 5 I 190.01 0. 070| 247.81  0.7 0.325  LM (CM)  175.0 22.0  60. 0 17.  46. 0  30.5  409.0 93.0 103.0  0.30  22.8 22.4  AUTHOR  L1 (CM)  2.0  5.5  3.0  +  (with year  iy  )  de J a e g e r , 63 D a v i d o f f , 63 D i a z , 63 Hennemuth, 61 55. 0 Huang et a l , 73 5 3.9 Huang e t a l , 73 59.9 Huang e t a l , 73 55.0 Huang e t a l , 73 53.6 Huanq+Yanq, 74 48.9 Hennemuth, 61 Le Guen et a l , 69 63.8 Le Guen+Sakagawa, 73 62.2 Nakamura, 65 51.0 Yabuta e t a l , 60 54. 3 Yabuta+Yukinawa, 57 Yabuta+Yukinawa, 59 51.0 Yang e t a l , 69 45. 9 Yang e t a l , 69 66. 1 Chi+Yang, 73 27. 4 Chi»Yang, 73 Kawasaki, 65 3 5.0 2. 906 R o b i n s , 63 R o t h s c h i l d , 67 965 R o n g u i l l o , 63 096 R o n q u i l l o , 63 l Y o k o t a , e t a l , 61 37. 5| I H o t t a , 55 25.0 | |Oka-ji e t a l , 58 28.7| | F i t c h , 51 23.0 | | F u r n e s t i n , 45 | | Moore, 51 54.0 | |Nose, Kawatsu+Hiyama, 64. 3| 788 R o n g u i l l o , 63 . 736 R o n q u i l l o , 63 . 876 R o n q u i l l o , 63 . 847 R o n q u i l l o , 63 92. 3 Yahuta et a l , 60 38.0 Ko-jima , 66 H o l t , 59b . 146 V a n i c h k u l + H o n g s k u l , 63 .123 V a n i c h k u l + H o n q s k u l , 63 H o l t , 58 2. 930 I v e r s b n , 55 Kikawa, 53 .74 7 R o n g u i l l o , 6 J . 944 K o n q u i l l o , 63 Suda, 61 47.5 Kikawa, 61 Kikawa, 61 Nose, Kawatsu+Hiyama, 35. 5 George + Bar.er i i , 60 309 J o n e s + S i l a s , 62 174 Pradhan, 56 3. 18  27. | 1. 0 28.7| 1. 5 29.21 2. 0 32. |  95.0  0.072  TM (YR)  AREA  SPECIES NAME  SP no  I  LINF (CM)  E x  LM (CM)  TM (YR)  +  h  India:Valtair India:Valtair Indo-Pacif ic Gulf of Tailand India:Andaman Island Indo-Pacific Gulf of T a i l a n d Gulf of T a i l a n d C a l i f o r n i a coast North P a c i f i c Pacific ' "• Eastern P a c i f i c Atlant i c Marmara and B o s p o r u s Eastern Atlantic ' Eastern Atlantic P a c i f i c Ocean Philippines Philippines Philippines Philippines Western Atlantic  kanagurta 19 R a s t r e l l i g e r kanagnrta 19 R a s t r e l l i g e r kanagurta 19 R a s t r e l l i g e r brachysoma zO R a s t r e l l i g e r brachysoma 20 R a s t r e l l i g e r brachysoma 20 R a s t r e l l i g e r brachvsoma 20 R a s t r e l l i g e r brachysoma 20 R a s t r e l l i g e r z 1 T h u n n u s gerrao 21 T h u n n u s g e r m o 21 T h u n n u s g e r m o lineatus 22 E u t h y n n u s alletteratus 23 E u t h y n n u s 24 S a r d a s a r d a 24 S a r d a s a r d a 24 S a r d a s a r d a z5 Thunnus o r i e n t a l i s yaito 26 E u t h y n n u s yaito 26 E u t h y n n u s 27 Gyrr.nosarda n u d a tonggol 28 K i s h i n o e l l a atlanticus 29 T h u n n u s  •1  »  ...Table  — T  0.6  0. 38 0. 199  22. 9  18.  0.7  0.233 0.169 0.025  109. 1  35. 55. 37. 39. 0. 176  3. 279 R a o , 62 3. 263 R a o , 62 3. 193 S u d i a s t a n i , 3. 578 2. 880 3. 763 3.038  2.0  50.0  302. 4  year  -  2. 949  2. 3. 2. 3.  T  -  '  1—  m  on  next  page  )  838 206 308 104  74 H o n g s k u l , 72 J o n e s + S i l a s , 62 S u d i a s t a n i , 74 V a n i c h k u l + H o n q s k u l , 63 Vanichkul+Honqskul, 63 B e l l , 62 C l e m e n s , 61b N o s e , K a w a t s u + H i y a m a , 57 C a l k i n s + K l a w e , 63 De S y l v a + K a t h i e a , 61 Numann, 55 Postel, 55 Postel, 55 Y a m a n a k a e t a l , 63 Ronquillo, 63 R o n q u i l l o , 63 R o n q u i l l o , 63 R o n q u i l l o , 63 I d y l l + d e S y l v a , 63  T"  40.0| 45. 0 | 40.0| 45. 0 | 47. 8| 55.0 | 60. 0| 52. 5 | «5. | 48. 0 | 23.5 48.0 | 23.5 43. 2 | 40.31 44.3| 3 3.4| 39. 7 | 3 5.2| 43. 0 | 31.01 34.21 3 3.0| 38.4| 36.0| 38.5| 34.4| 44.8| 3 8.5| 41.51 +-  19  +—  57.3 52.0 38.0  454. 6 63.6  IICNAF 3NO |0.115| 0. 2 |0. 1 | IICNAF 4RST 0. 20|0.1 15 | |G. S t . Lawrence I0.07 | I F l e m i s h Cape Im | f 10.13 | | F l e m i s h Cape I0.05 | |Hamilton I n l e t Bank 1 o | f 10.10 | ( H a m i l t o n I n l e t Bank 10.1 | |Labra dor 10.12 | I F l e m i s h Cap (North P a c i f i c | | | B e r i n g Sea | | 1.018 | |f (Washington c o a s t I.020 | |m (Washington c o a s t I0.09 | ( G u l f of Maine If 10.13 | |Gulf of Maine 1 o |0.113| IHermitage Bay If |0.119| IHermitage Bay 1 HI 10.10 | (Hermitage B:53 y e a r - c l a s s | f |0.17 | IHermitage B:53 y e a r - c l a s s 1 H 10.13 | If ISouthwest Grand Bank |0.05 | (Southwest Grand Bank 1m 10.13 | | f |Gulf St.Lawrence |0.06 | | G u l f St.Lawrence 1 |0.15 | I f |Flem i s h Ca pe 10.17 | ( F l e m i s h Cape 1 m | f 10.11 | ( H a m i l t o n I n l e t Bank 10.16 | IHamilton I n l e t Bank 1 K 10.16 | | f IHarailton I n l e t Bank + -  marinus marinus marinus marinus marinus marinus marinus marinus marinus alutus alutus alutus alutus mentella mente11a mentella mentella mentella mentella mentella mentella ment e l l a mentella mentella mentella mentella mentella mentella  1 continued  20.  0.232 0.28  (with  Scorpionfishes  Scorpaen idae  1 T I 1 I Setastes I 1 I Sebastes I 01 | S e t a s t e s I 1 I Setastes I 1 I Sebastes Sebastes I 1 ( | 11 S e b a s t e s I 1 iSebastes I 11 S e t a s t e s 10 2 l S e b a s t e s 1 021 S e b a s t e s | 0 2 JS e b a s t e s | 02 |S e b a s t e s | 0 3 |S e b a s t e s |03| S e t a s t e s 1 3| S e b a s t e s 1 3| S e b a s t e s 1 3| S e b a s t e s 1 3| S e t a s t e s 1 3| S e t a s t e s 1 3 Sebastes 1 3| S e b a s t e s 1 3| S e b a s t e s 1 3| S e b a s t e s 1 3| S e h a s t e s 1 3 Setastes 1 3| S e b a s t e s 1 3| S e t a s t e s  23.9 20.9  0.37  AUTHOR  L1  (CM)  Beverton, Beverton,  4.5  65 65 K e l l y 4-Wolf , 59 S a n d e m a n , 69 S a n d e m a n , 69 S a n d e m a n , 69 S a n d e u a r i , 69 B e v e r t o n , 65 B e v e r t o n , 65 G r i t z e n k o , 63 P a r a k e t s o v . 63 3.119 W e s t r h e i m . 58 3.250 W e s t r h e i m , 58 Ketchen, 72 Ketchen, 72 Sandeman, 6 9 S a n d e m a n , 69 S a n d e m a n , 69 Sandeman, 6 9 Sandeman, 69 S a n d liin.i n. 69 S a n d e m a n , 69 Sa ndem.i n, 69 Sandeman, 6 9 S a n d e m a n , 69 S a n d e m a n , 69 S a n d e m a n , 69 S a n d e m a n , 69  SPECIES NAME  SP| no | — h -  3|Setastes 3|Setastes 3|Setastes 3 j Sebastes 3|Setastes 3|Sebastes 3|Setastes 3|Setastes 3|Sebastes 3|Sebastes 3|Setastes 4j S e t a s t e s 5|Setastes  mentella mentella mentella mentella mentella mentella mentella mentella mentella mentella mentella inermis marmorata  Sillaginidae  AREA I -I IHamilton I n l e t Bank I H a m i l t o n I n l e t Bank IHamilton I n l e t Bank I Labrador ILabrador l e a s t Newfoundland l e a s t Newfoundland I F l e m i s h Cap I F l e m i s h Cap IGrand Bank IGrand Bank |Northwest Kyushu I Northwest Kyushu Sand  sihama  S c i e idae 1|Solea  vulgaris  Sparidae 1|Chrysophrys major 11Chrysophrys ma j o r 11 C h r y s o p h r y s major 11Chrysophrys major I | C h r y s o p h r y s major 1|Chrysophrys major 11Chrysophrys major 11Chrysophrys major 1|Chrysophrys major 1 1 C h r y s o p h r y s major II C h r y s o p h r y s major 11 C h r y s o p h r y s major 02|Pagrus e b r e n b e r g i Sgual idae'  |India:sout h  |  |  _j i  ...Table  28.3 34.5  INorth  TM | L1 (YR) | (CM)  | AUTHOR  (with year 19  Sandeman, Sandeman, Sandeman, ITokareva, ITokareva, ITokareva, ITokareva, ITokareva, [Tokareva, ITokareva, ITokareva, Mio, 61 I a i o, 6 1  33. 0 12.0| 29. 0 9.5| 28.7 10.3| 28. 0 9.1| 29. 10. 0| 27. 0 9. 0| •24. 7. 7 | 23.0 6.8| 13. 0 2.0 | 12.0 2 .0 |  1  |0.4  i  1  i  |  37.0  I  _l  Soles Sea  Porgies  7  |0.2sTo.4  .J.  1  "T  I  |  )  69 69 69 66 66 66 66 66 66 66 66  I  |Radhakrishnan,  57  | Be v e r t c n + l i o l t ,  57  l_  39.0  L  |0.1 13 | |0.077| |0.077 | |0.115| |0.114| |0. 1151 10.12 | |0.127 | |0.136| |0.090| 10.095 | |0.116| I I  IWakasa Bay |Taiwan:Pescadores I s l . ITaiwan:Pescadores I s l . | Izu |Hiuchinada |Saganoseki |Kii | amaknsa |Northern Kyushu | E a s t C h i n a + Y e l l o v Sea | East China • Y e l l o w Seas | Hiroshima |Nigeria  71.0 98. 3 98. 3 82.5 77. 8 51.4 97.3 89. 1 80. 3 74.0 74.9 66.2  36.8 31.9  15. 0  5.0 4.0  9.9| l A k a z a k i , 60 14.6|2.649(Chahg+Chen,72;Huang et a l , 7 4 14.6|2. 64 9|Chang+Chen,72 ;Huanq e t a l , 7 4 8.3| | E b i n a , 36 | | E b i n a , 40 | | E b i n a , 40 8.5| IKawase, 53 21.3| |Murakami:Shindo, 49 13.0| IMio, 62 13.0| |Murakarai+Okada, 67 | |Okada, 70 10.9j |Kang, 37 | | L o n q h u r s t , 63  Dogfish sharks "T—T~  1|Sgualus a c a n t h i a s 01|Squalus a c a n t h i a s 1|Squalus a c a n t h i a s 1|Sgualus a c a n t h i a s 1|Squalus a c a n t h i a s 1|Squalus a c a n t h i a s 1|Squalus a c a n t h i a s 1|Squalus a c a n t h i a s 1|Squalus a c a n t h i a s 1|Squalus a c a n t h i a s 1|Squalus a c a n t h i a s 1|Squalus a c a n t h i a s 1|Squalus a c a n t h i a s  36. 5 52.0 93. 0  0.21 0.08 0.02  LM (CM)  whiting -T—T  11Sillago  LINF (CM)  |E| f. Ul -+--I— |m| If I |m| If I I m| If I | m| Ifl 1m| Ifl |m| I I I I  I European waters (Washington c o a s t INorth Sea INorth Sea |Canada:west c o a s t |Canada:west c o a s t |I!ecate S t r a i t |Hecate S t r a i t IGeorge S t r a i t IGeorge S t r a i t (Washington Coast (Washington Coast | Cana<3a: e a s t c o a s t  1 c o n t i n u e d on next page  I I I I Ifl I ml Ifl I ml Ifl I m| Ifl I ml t fl |m|  | 0.024 | 0.022 10.11 10.21 (0.048 | 0.070 |0.031 |0.0 92 |0.034 |0.067 |0.036 10.071 (0.110  216.7| 186.4| 101.4| 82.0 79.7| 60.0 125.3| 93. 5 99.8| 72. 125.1| 84.7| 129.1| 103. 2 96. 1 | 75. 9 152.9| 101.8| 1 17. 3  I 29. 1 | I 39.0| 11 .0|39.6| 5.0|41.3| 23.0| | 14.0| | 34.0| | 17.01 | 31.0|31.0| 16.0|32.HI 1 1 1 1 |43.5|  |Aasen, 61 IBonham e t a l . 49 |Holden+Meadows , 62 | Holden + Meadows, 62 |Ketchen, 72 ; Ketchen, 75 | Ketchen, 72 ; Ketchen, 75 | K e t c h e n , 72 ; Ketchen, 75 | K e t c Ii e n, 7 2 ; Kotchen, 75 | Ketchen, 72 ; Ketchen, 75 | K e t c h e n , 72 ; Ketchen, 75 I K e t c h e n , 75 I K e t c h e n , 75 |Templeman, 44  1  1 1 ISP| |no| '  1 | 1—  •r i |S| 1 E| B |x|  1  7 -'  SPECIES NRSE  1 | 1  AREA  1  .  •  •  i  1  ••  "T  1—  T"  If I |m|  |01|Anoplarchus purpurescenslVancouver 1 • |01|Anoplarchus p u r p u r e s c e n s | V a n c o u v e r 1 L P i p e f i s h e s and s e a h o r s e s | Syngnathidae 1 r i r i ) 11Hippocampus h u d s o n i u s |Florida i i T L  J  lepturus  |  "' f  _ L  J  1  12 .5  _  |  |East  .. j  -T—r  China Sea  i i  _J_  X.  T  1  j.-  |  J  • —  I  1 10 .209|  Cutlassfishes  Trichiuridae T  | 011Trichiurus L  X  L  | , —  K  Pricklebacks  Stichaeidae T  ,  1 | 1 J _  1  1 T— -•" r| | | | TM 1 L1 | | LINF | LH (CM) | (CM) 1 (YR)I (CM) | • j 1  T  1  1 18.6| i  j  14.01 •  2. 01  b  | |AUTHOR I  )  : —J  J  r  (with y e a r 19  1  •• — —  | 7.1|2.986|Peppar, 65 | 6.5|2.986|Peppar, 65  I A  I . 1  |Herald+Rakowicz, J  —  51 '  •i  :  130.0| 97. 5| 1. i  3.5|27.0| i i  IMisu, j  58,59  -fx CM.  43  Table 2 Sample s i z e s o f i n d i v i d u a l p a r a m e t e r s and r e l a t i v e characters i n f a m i l i e s analyzed NO.  FAMILIES  Clupeidae Cyprinidae Gadidae Pleuronectidae Scombridae Bothidae Engraulidae Hiodontidae Osmerida e Salmonidae Sciaenidae Scor paenidae Percidae Sparidae Sgualidae Acipenseridae Aromodyt idae Anquillidae Aplcchitcnidae Argentinidae Atherinidae Blennidae Callienymidae Caranqidae Cichlidae Cottidae Dasyatidae Drepanidae Embiotccidae Gasterosteidae Hexagrammidae Ictaluridae Isticphoridae Luianidae Nemipteridae Poeciliidae Polynemidae Pomacentridae Sillaginidae Soleidae Stichaeidae Syngrathidae Trachipteridae Total  PARAMETERS  R E L A T I V E  OF Sp.  M  19 7 17 22 29 3 4 1 3 11 6 5 3 2 1 4 3 1 1  17 2 28 14 6 2  1 1 1 1 1 1 1 1 1 1 1 3 1 1 1 1 1 1 1 1 1 171  19 1 2 4  1 2 4  2  K LINF LM 70 47 45 38 36 2 20 6 10 28 16 29 7 11 13 4 5 3 3 1 2 2 1 4 2 2 1 1 2 2  1  1 1 1 1  82 62 38 51 56 26 61 28 60 3 2 4 2 19 21 6 10 5 28 21 17 12 33 12 7 . 2 11 1 13 6 3 2 5 1 3 1 1 3 3 3 1 1 2 2 1 4 4 2 2 1 1 2 2 2 2 2 1 1 1 2 2 3 2 2 1 1 1 1 1 1 1 1  TM 9 35 5 19 19 1 12 23 2 1 12 8 2  Ll 22 39 8 31 34 2 9 4 10 1 14 3 3 8 7 4  b T95  2 3  70 47 45 36 32 2 20 6 10 28 15 29 7 11 13 3 5  2  3 3 1 2 2  4 4 5 1 1 34  2 4 2 2 1  2  6 1  2  1 2  2 1 2  1  12 2 20 14 4 2  51 10 20 27 19  TM T50  22 29 7 30 27 2 9 4 7  8  19  3 21  2 4  11 4  12 3 3 8 3  6 2  2  2  2 2 1 1  7  8  2 1  4 2 1  1  2  70 47 45 36 33 2 20 6 10 28 15 29 7 11 13 5 3 3 2 2 4 2 2  2 2  1 1 1  1  81 404  88  2  10  2  3  4  8 6 2 2  4  1 1  1 1  1 1  213 175  45 402  1 1  1  105 417 507 297 155 214  L1  K LINF IINF T95 T95  4 2  2  LM  2  2  2  M  CHARACTERS  mackerels  and  tunas.  89, 70, 69 and 104  These have very l a r g e sample s i z e s ;  100,  respectively.  Group I I (10 f a m i l i e s ) ; Bothidae  -  Hiodontidae  lefteye -  flounders,  mooneyes,  Osmeridae  salmcnids, S c i a e n i d a e - drums, Percidae  - perches,  Engraulidae -  -  smelts,  Scorpaenidae  -  anchovies, Salmonidae  scorpionfishes,  Sparidae - p o r g i e s , and Sgualidae - d o g f i s h  sharks. These have r e l a t i v e l y l a r g e sample s i z e s ; 5, 22, 6,  30,  33, 19, 41, 7, 12, and 13 r e s p e c t i v e l y .  4. Methods o f A n a l y s i s  The  first  step  was  to  examine  the  c h a r a c t e r i s t i c s of  p o p u l a t i o n parameters by l o o k i n g at the f o l l o w i n g c h a r a c t e r s ; (a) e i g h t parameters •B  = instantaneous n a t u r a l m o r t a l i t y c o e f f i c i e n t  K =  c u r v a t u r e of the growth curve, or the r a t e at which the f i s h reaches  LINF  <cm)  i t s asymptotic  = asymptotic  size  l e n g t h f o r which the r a t e of  growth i s zero LH  (cm) = s i z e at f i r s t which  50%  {or c r i t i c a l TH  (yr) = age at f i r s t  maturity, which  of  the  length  the f i s h are at the maturity  at  stage  length) maturity a t which f i s h has l e n g t h LM  L1 {cm) = l e n g t h o f f i s h b =  is  at age 1  e x p o n e n t i a l c o e f f i c i e n t of weight-length  relationship  T95  (yr) = age at which the f i s l i a t t a i n s 95% of asymptotic length  (b) f i v e r e l a t i v e c h a r a c t e r s M/K,  (ratios) :  LM/LINF, L1/LINF, TM/T95, T50/T95  where T50 i s the age at which f i s h a t t a i n s 50% of asymptotic  length.  (c) f i v e c o r r e l a t i v e c h a r a c t e r s : H—K,  1/K—LINF, L H — L I N F , L 1 — L I N F ,  Estimation sizes  of  of means, standard  the  individual  1/M—T95  errors,  parameters  ranges, and  of  and the  sample relative  c h a r a c t e r s are c a l c u l a t e d i n each f a m i l y . The v a r i a t i o n f o r each c h a r a c t e r can be compared by the c o e f f i c i e n t of v a r i a t i o n  (cv),  which i s cv = s/x * 100 where x : the mean value of t h e c h a r a c t e r s : the standard  d e v i a t i o n of the c h a r a c t e r  The c o r r e l a t i o n s between parameters w i t h i n each f a m i l y were c a l c u l a t e d by l i n e a r r e g r e s s i o n a n a l y s i s . Comparisons  of  variances  of the f o u r parameters with and  LH)  were  based  on  l a r g e sample the  s i g n i f i c a n t d i f f e r e n c e was  and mean values between f a m i l i e s  F-test  shown  approximation method was u t i l i z e d Stepwise  discriminant  from  sizes and  the  the  F  according  to  analysis  their  LINF,  t-test. value,  T95, If  a  Welch*s  i n s t e a d of the Student t - t e s t . is  used  means of d i f f e r e n t f a m i l i e s of f i s h e s by a s e t functions  (K,  population  t o q u a n t i f y the of  discriminant  parameters. I t a l s o  46  shows how groups are demarcated i n The  general  in the  and  multi-dimensional  of  properties.  cases  into  predetermined  groups  I t i s c a l c u l a t e d from the pooled  matrices  variances  in  and  among  i s maximized i n o r d e r t o d i s c o v e r the s m a l l e s t number  of dimensions i n which the p o p u l a t i o n means l i e .  analyses  were  group I (5 f a m i l i e s ) , group I I (10 f a m i l i e s ) , and a l s o  with groups I and I I combined Cooley  (15 f a m i l i e s a l t o g e t h e r ) ,  and Lohnes' c l a s s i f i c a t i o n method was a l s o  T h i s method i s o b t a i n e d  f a r as  classification  conducted among s p e c i e s  utilized.  by x e n o r m a l i z i n g t h e c a n o n i c a l v a r i a b l e s  i n the d i s c r i m i n a n t a n a l y s i s . The n o r m a l i z a t i o n as  with  covariances among c h a r a c t e r s w i t h i n each group. D i s c r i m i n a n t  f u n c t i o n s are c o n s t r u c t e d such t h a t t h e r a t i o w i t h i n  done  space.  o b j e c t o f t h i s method i s t o f i n d r u l e s o f behavior  assignment  optimal  a  is  within  concerned. 5  major  The  is  immmaterial  analyses  families  were  (Clupeidae,  C y p r i n i d a e , Gadidae, P l e u r o n e c t i d a e , and Scombridae). Dendrograph  relationships  among  p o p u l a t i o n parameters have been surveyed  15  families  based  on  using c l u s t e r a n a l y s i s .  T h i s method c l u s t e r s cases t h a t have the l e a s t d i s t a n c e  between  them. The two cases c l o s e s t together a r e amalgamated and t r e a t e d as one case and then, i n turn c l u s t e r e d with  others.  V CBABJCTJBISTICS OF POPULATION PARAMETERS  The analyses are based greater  mainly on the 15 f a m i l i e s »hich have  sample s i z e s . At t h i s stage, there are s t i l l  not enough  data to show s i g n i f i c i a n t r e s u l t s i n the i n t r a - s p e c i e s s t u d i e s . ,  1. I n d i v i d u a l Parameters The parameter examined i n d i v i d u a l l y data  records f o r a l l f a m i l i e s i n parentheses)  K (417), LINF and  T95  (507), LM  (404)  (297), TM  (155), L1  because of my  published age-length  data s e t s  growth  equation.  a.  species  within  c a l c u l a t i o n s based  using  ranges of  families.  natural  the  von  individual  For  (81),  on  231  Bertalanffy  parameters  s p e c i e s index number  mortality  a g r e a t deal o f v a r i a t i o n . Only  (Clupeidae, Gadidae, were  b  1.  The i n s t a n t a n e o u s shows  (21H),  (105),  F i g u r e s 3 to 10 show sample s i z e s , means,  95^ c o n f i d e n c e l i m i t s , and  r e f e r to Table  were M  of  (Table 2) . Large sample s i z e s were a v a i l a b l e  for K, LINF, and T95  among  (and the number  there  enough  Pleuronectidae,  coefficient  (M)  i n four f a m i l i e s and  Salmonidae)  data to be analyzed. These r e s u l t s  are shown i n F i g u r e 3. Gadidae  (n =28) has the 1  largest  OJLFEIGAE  F^ajROXeCTIQAE  1*2.  0.30,  1.1 .  0-27  1*Q.  0*24  0-B  0.21  0-7  o-in  O.K.  0.5.  ct  o.ia  0.4  O.CQ  0-2.  o.os  0-1.  o*oa  O-QJ  o.oa  O.  1.  a.  3.  4.  3.  6-  7.  B.  0.  0. 10. U> 12. 13* 14. 13. IS. 17. IB* l f l .  STCIES  1. 2. 3*  S-  G* 7. 8> 8* lO. 11* 12* 13* 14* 15* 16- 17. 10* 13* so* a . B2% S=ECXES X  I  GADIDAE:  SALMZNIOAE 1*3.  2*1  1*E  1*0  1*0  1-6  0.3  1*4  ca  0*6. o*s. 0-4. 0.3. •  to  i  O-  !•  E*  3*  -v.  3-  G* 7.  e-  8.  SPECIES  Figure  3.  e  0.1  10* 11* IE. 13. 14. u . IB* 17. I  S* SPECIES  F* I  Mean values, 95% c o n f i d e n c e limits, r a n g e s , and sample s i z e s among s p e c i e s w i t h i n f a m i l i e s f o r thf? instantaneous natural- mortality c o e f f i c i e n t (M) ( s p e c i e s i n d e x r e f e r t o T a b l e 1)  00  49  variation (n=14)  (cv =125.3%)  among  2  shows  Salmonidae  has  species. Pleuronectidae  the  least  variation  the  highest  mortality  f o l l o w e d by 0.354 o f Gadidae, 0.33 0.222  of  Pleuronectidae.  families,  Scombridae  rate  (0.755)  o f Clupeidae  Apart  (n=6)  (cv=23. 32%) .  from  also  has  (n=17) ,  these  four  a high H value  (0.478) .  b.  K i s the r a t e at which the f i s h reaches length.  The  reaches  higher  the  its  K value, the sooner the  i t s u l t i m a t e l e n g t h . Eight f a m i l i e s  Cyprinidae,  asymptotic  Engraulidae,  Gadidae,  fish  (Clupeidae,  Pleuronectidae,  Salmonidae, Scombridae, Scorpaenidae) with sample larger  than  19 were analysed. The r e s u l t s are shown i n  Figure 4. In these from  42. 26%  eight  (cv)  families,  for  (1.654),  followed  (0.347),  Salmonidae  and  In  Clupeidae  (0.207),  to  highest  (0.431), fishes  Scorpaenidae  90% K  for value  Scombridae [Gadidae (0.107)3 K  other f a m i l i e s of f i s h e s ; Osmeridae (n=10)  has a K value  (0.409) s i l m i l a r t o Clupeidae,  the  variation  largest  range  f i s h f C y p r i n i d a e (0.216) ] have lower  but  (cv=111.83%) ; S c i a e n i d a e  n i s the sample s i z e 2 cv i s the c o e f f i c i e n t of v a r i a t i o n 1  the  (0.329). Demersal  Pleuronectidae  freshwater  values.  by  variations  Engraulidae  P l e u r o n e c t i d a e . Engraulidae has  (0.243),  sizes  with (n=16)  *r  S.EL  t't.  e-s  t  e  t.Q  S-3  o-a 0-7 0-6 6  S  o-s;  j  ...  o.a  0-E  0.&  0.11  0 . 3  O-oL 0.  1.  e.  3.  <.  3.  6.  7.  e- a- 10. ii. 12.  13.  i<.  13.  is-  17.  us. ia<  species 1  CTFWINIOAE  . GATJ1TJAE  e-a.  o-ca  o-<> o-3a 0-E7  i.ua  0 . 1 a  e I  0 > 1 0  o.ccj  1.  srarics 1  Figure  4.1  3.  6.  7.  0.  O- U>. 11. 12- 13- 1«- 15. IS- 17.  species 1  wean v a l u e s , 95% confidence limits, ranges, and sample sizes among s p e c i e s w i t h i n f a m i l i e s f o r t h e growth p a r a m e t e r K ( s p e c i e s i n d e x r e f e r t o T a b l e 1)  ^ o  SCDveRIDAE  F * L E X J R Q N E C T I O A E  8.77 0-75  o.ta  o.c  o.e.  0.54 O.SO  ^  o.«l  C34  e  CES. 0-17,  O. 1.  4. 2.  2> 3.  6. 7. 0-  11. 12. 13. 14. l i . l£. 17. Ifl. SPECIES I  •1 0 .  o. 1* c* 3< 4* 3. 6< 7* a* 0.iu.ii>ti:.t'j>i4.ui.tG.t7.u].uj.ra-t.n.ca.tr3>e4.u3.ct;^27.£u^3». SPECIES X  11).  S»JJ-(ONIOAE  S C O R P A E N I D A E  e  C-73.  0.2L  0-O3  b-ia  O-CD  0.17  o-sa  o.is  0-45  0-13  o.u O-CQ  O'CG  0-04  o-ce.  3. E. SPECIES I  Figure  4.2  *0.  o.ooj  e  I  a.  j .  SPECIES I  Mean v a l u e s , 95?. c o n f i d e n c e limits, ranges, and sample sizes among s p e c i e s w i t h i n f a m i l i e s f o r t h e growth p a r a m e t e r X ( s p e c i e s i n d e x r e f e r t o T a b l e 1)  52  has a K value  (0.345) s i m i l a r to p e l a g i c f i s h e s ;  for  (n=11) and 0.179 f o r P e r c i d a e a r e s i n i l a r  to  Sparidae  demersal f i s h e s ; Sgualidae  value  0.111  (n=13) has the s m a l l e s t K  (0.07) among a l l f i s h e s . G e n e r a l l y speaking,  K is  a r e l a t i v e l y stable character.  c.  LINF i s the asymptotic is  zero.  Eight  Engraulidae,  l e n g t h f o r which the growth r a t e  families  Gadidae,  Scombridae, Scorpaenidae)  (Clupeidae,  Cyprinidae,  Pleuronectidae,  Salmonidae,  with sample s i z e s l a r g e r  than  20 were analyzed. The r e s u l t s are shown i n F i g u r e 5. I n these e i g h t f a m i l i e s , v a r i a t i o n s range from for  Engraulidae  to  Scombridae  has  (152.7 cm),  followed  Gadidae  (75.72  (61.35 cm), (28,88  101.55S  the  for  greatest by  Scorpaenidae  Pleuronectidae.  asymptotic  Pleuronectidae  cm), C y p r i n i d a e  13.943? (cv)  length  (78.18  (73.34 cm), Salmonidae  (43.02  cm),  and  Clupeidae  cm) . E n g r a u l i d a e has the s m a l l e s t l e n g t h  cm).  In other f a m i l i e s o f f i s h e s ,  the  second  has  an  largest  asymptotic  Sgualidae  (31.19  cm)  (16.15  (n=13)  LINF (124.3 cm); Osmeridae length  cm),  has  (n=10)  similar  to  Clupeidae;  f o r Sparidae(n=11) LINF i s 78.44 cm and f o r  Sciaenidae  (n=17) i t i s 65.37 cm. Again, the asymptotic  length i s a f a i r l y s t a b l e character.  d.  The s i ^ e a t f i r s t maturity  (LM) i s t h e length  of  fish  at the time when they s t a r t to switch t h e i r energy from  CULPErOAE  ENGRAULIDAE  LL  •  O.  1.  £•  3*  4.  3.  6-  7.  B.  8.  10.  11. 1 £ . 13. 14.  I  13. IS. 17. 18. I f l .  SPECIES I CYPRINIDAE  SPECIES I GADIDAE  e  . I 10  I  SPCCIES I  O.  1.  2.  3.  A. 3-  6.  7.  B-  3-  10-  11.  12.  13-  14.  13.  1£.  17.  S=ECIES I  Figure  5.1  Moan v a l u e s , 95% confidence limits, r a n q e s , and sample sizes among s p e c i e s w i t h i n f a m i l i e s f o r the asymptotic length (LINF) (species index refer to Table 1)  CO  RJELROteCTIOAE  SCDMSRIOAE  s  «S5-  X  UL  133' US' e  1 O-  !•  E*  !•  -»  3>  n i  • • • • I £•  I  3  •  7.  8'  8- 10- U ' 12' 13- 14< 13'  *S  3  0* 1* E» 3* 4. S . 6* 7- tt' 9.io.u.l2.l3-14.!5.16'17.ia«13*«0>21'2e.e3-e*'E3'€£-Z7»£B-»  IB' 17- IB. IS- E0- 2 1 . 22«  SPECIES I  SPECIES I  SCORPAENIDAE  SALMXIOAE  ia  e  •  -  a z  iceu. X  2  j so.  o-  i.  e.  3-  3-  6.  SPECIES I  Figure  5.2  7.  B-  a.  ia.  u..  e.  a< SPECIES I  Mean values, 9 5 % confidence limits, ranges, and s a m p l e s i z e s among s p e c i e s w i t h i n f a m i l i e s for the asymptotic length (LINF) (species i n d e x r e f e r to T a b l e 1)  ui  55  growth  to  reproduction.  Cyprinidae,  Eight  Engraulidae,  families  Gadidae,  (Clupeidae,  Pleuronectidae,  Salmonidae, Scombridae, Scorpaenidae) with sample s i z e s larger  than  11 were analyzed. The r e s u l t s are shown i n  F i g u r e 6. In these from  10.88%  eight  (cv)  families,  of  variations  Engraulidae  to  Salmonidae. Scombridae has the l a r g e s t LH followed  by Gadidae (39.12 cm),  Cyprinidae  (30.34  Clupeidae at  (19.32 cm).  first  maturity  f i s h e s ; Sgualidae among  all  between (n=12)  cm),  Clupeidae it  is  (24.48  and  (n=5)  LM  has  Engraulidae;  30. 86.  cm), size  In other f a m i l i e s o f  has t h e l a r g e s t  f i s h e s ; Osmeridae  cm),  has the s m a l l e s t  cm).  of cm),  Salmonidae {32.64  Engraulidae  (n=6)  76.85? (62.02  Scorpaenidae  (12.24  range  a LM for  The s i z e a t f i r s t  (81.1  cm)  (15.80  cm)  Sciaenidae maturity i s a  very s t a b l e c h a r a c t e r .  e.  TM  i s the age  length  at  LH.  first  Four  maturity  families  18 were analyzed.  7. In these (cv)  for  sample  fish  has  Osmeridae,  sizes  larger  r e s u l t s are shown i n F i g u r e  four f a m i l i e s , v a r i a t i o n s range from 36.74% Cyprinidae  Cyprinidae  has  Pleuronectidae Scombridae families  The  which  (Cyprinidae,  P l e u r o n e c t i d a e , Scombridae) with than  at  has of  to  59.43%  for  Scombridae.  the highest TH  (5.7 y e a r s ) , f o l l o w e d  (5.6  yrs),  Osmeridae  the  youngest  fishes  ;  TH  Engraulidae  (2.8  (2.7 y r s ) . In {n=12)  has  by  yrs). other the  ErGFRAULIDAir  QJLPeiOAE  11 i  °*  1 -  5^ 5  <T7.  4.5^  B.  8. U>.  A. 12. 13. 14. 13. ]£. 17. jla, JJJ,  species i  I CYPRINIQAE  GADIOAIT •  Z  e.  3.  SPECIES I  Figure  6.1  o-  i.  e.  3.  a-  G.  7.  tl.  D. 10. 11. 12. 13. 14. IS-  axcics i  Mean v a l u e s , 95% confidence limits, ranges, and sample sizes among s p e c i e s w i t h i n f a m i l i e s f o r t h e f i r s t m a t u r i t y s i z e (LM) (species index refer to Table 1)  16. 17.  cn  PLE1PCNECTI0AE SCCVeRIDAE  1  2 -J  72-  D  ro.  I 24.  O.  I. 2. 3. 4. 3- 6. 7. B- 3. 10. 11. 12. 13- 14. 13. 1£. 17. IB. 13. a> 21. 22.  0 . 1. 2. 3 . 4. S . 6. 7. 0- B-10.ll.12.l3-14.lS.lj5.17.ia.ia.a3.21.22.23.24. 25-yS-27.2B-29*  SPECIES I  £FECIE5 I  SALMQMICAE SCCRPAENIOAE  e •  _i  -J  2D.  G  17-  £  1310-  0.  1.  e.  3.  Figure  4.  3.  G  .  sprits i  7.  B* SPECIES I  6.2 Mean values, 95% c o n f i d e n c e limits, r a n g e s , and sample s i z e s among s p e c i e s w i t h i n f a m i l i e s for the first maturity size ( L H ) (species index r e f e r to T a b l e 1)  CYPRINIQAE  PLELRQVJECT I D A E  B-6  7t 6-7 , 3-7 4-G >a 2-a  2 • 2 •  i-a 1.0 o-oL 0.  SPECIES I  1.  2.  3.  3.  6- 7. 8'  e> 10. U . 12. 13. 14. 13. i £ . SFECICS I  17. IB. 13. 20. 21. 22.  CS/6RinAE SCOMBRIDAE '5,  E-0  6-7,  5-4.  C.Q.  4-Q  s-e  4-E  4-i  2-2 1-i p-a 0-G  SPECIES I  1. 2. 3. 4. 5. 6. 7- B- 9'l^-ll-l2.0.1<.15.1fi.l7.1B.l£i.£0.fcl.E2.E3.i STOCS I  Figure  7.  Mean v a l u e s , 95? . . confidence limits, r a n g e s , . and sample sizes among s p e c i e s w i t h i n f a m i l i e s f o r t h * f i r s t m a t u r i t y age (TH) (species index refer to T a b l e 1)  c o  59  youngest TH  f.  TH  (1.0 y r s ) . Sgualidae  (n=8)  has the  oldest  (18.8 yrs) among a l l the f i s h e s .  The  l e n g t h of f i s h  which  fish  families  can  at age grow  during  {Clupeidae,  Scombridae)  with  1 (L1)  shows the  first  Cyprinidae,  sample  sizes  the  speed year.  families,  variations  Four  Pleuronectidae,  larger  than  analyzed. The r e s u l t s are shown i n F i g u r e 8. four  at  range from  21 were In  these  32.37% (cv) f o r  C y p r i n i d a e to 42.99% f o r Clupeidae. Scombridae has largest  L1  (14.84 cm), (7.39  (47.34  cm),  Pleuronectidae  cm).  (n=7)  g.  size  In  other  has the second  ovoviviparous;  for  for  (n=9)  Engraulidae  followed  (8.4  cm),  families  l a r g e s t L1  (3 6. 56 cm)  Sciaenidae  Scombridae  least  h.  T95,  cm;  the  weight-length  (n=34) ] with l a r g e enough sample s i z e s were  data  families).  fishes  is  f a m i l i e s f P l e u r o n e c t i d a e (n=11),  were found  however, the most s t a b l e the  since i t  cm.  analysed. The r e s u l t s are shown i n F i g u r e the  Cyprinidae  (n=14) i t i s 21.71  i t i s 12.70  Only two  and  Clupeidae  of f i s h e s ; Sgualidae  b i s the e x p o n e n t i a l c o e f f i c i e n t of relationship.  by  the  It  one  9.  Although  f o r t h i s parameter. I t i s , (cv l e s s than  fluctuates  10% f o r a l l  around 3 f o r a l l of the  analysed.  as an index of • l i f e span*,  is  the  hypothetical  B  <;  w  a  Q  3 z  -Q C M  -a  CD  co  9B w  (V  0>  a  <U T l rt 3"  ro  OJ rt  P  3 CD  R  H> 3  C  <  W PJ HC N <D iD W  K-  OJ  ?' B-  (fl  ^  OJ 3 O 3  LH  -Q f —^  t/i  n >D o n  "O  PAFW.CTER L l  fD  "o (/> a, ro ru n *: 3 H" H- n 0) n- r D W  3"  H3  3  CL r t i  P  6  S  8  4  B  8  8  «  3 rt I — 01  H '  § O )>» ft) u) Ik u  g  P  8  w 0  M H-  (5  PARAMETER L l  <6  n (-"• fD H rti f D fD CA f"! n a*  H „ M K  rt  3 r-h . Q  O  O  rD  H OJ tT  rt  PJ  H" 3 "  3  ©  U)  P 5 P' K  ? G ?•  P  09  a  y  A  —•—.•  61 PLEIJRCNETTIDAE 3-G. 3-3 e.a 2-6 E-E  S i  i.a. 1-5 1-1. 0.7. 0.4.. 0.0 0. 1. 2. 3. 4. 5- G. 7. 8- Q. iO- i i . 12. 13. 14. 15. 1G- 17. IB. 13. 20. Hi- 22-  SPECIES I SCOMBRIDAE 3-e 3-4. + 3-Q  2  T  2 X  3  I  E  I  £•3. i-a. --•s. i-t. o-a. 0.4. .  -4 1- - 4 — i — i — ^ E. 3- 4. 5. 6. 7. B. a.iO.l'l. 12.13.14.l!s.lS.17.1fl.i3.i.2i.s.s.24.25.BS.27.i.29. SPECIES I  Figure  9.  Mean v a l u e s , 95% c o n f i d e n c e limits, ranges, and sample sizes among s p e c i e s w i t h i n f a m i l i e s f o r thf» weight-length exponential c o e f f i c i e n t (b) (sp—ies index r e f e r to Table 1)  62  age  of  Eight  f i s h on r e a c h i n g 95% of i t s asymptotic families  Gadidae,  (Clupeidae,  Pleuronectidae,  Cyprinidae,  Engraulidae,  Salmonidae,  Scombridae,  Scorpaenidae) with sample s i z e s analysed.  The  larger  than  r e s u l t s are shown i n Figure  19  were  10. In  these  e i g h t f a m i l i e s , v a r i a t i o n ranges from -44.95% Clupeidae  t o 141%  l a r g e s t T95 (32.29 yrs),  y r s ) , Cyprinidae  Clupeidae  (cv)  by  (28.58 y r s ) , Salmonidae  (24.00  (16.82 y r s ) , Scombridae {14.64 y r s ) ,  (8.29  (n=10)  Sciaenidae  (n=15) T95  it  character  is has  and  y r s ) . Engraulidae has the youngest  Sgualidae  has  i s 9.144  27.51 the  the o l d e s t T95  while  for  Sparidae  G e n e r a l l y speaking,  largest  T95  (57.77 yrs) ; f o r  y e a r s ; and  years.  the  Pleuronectidae  (only 2.359 yrs) of the other f a m i l i e s of f i s h e s  (n=11)  for  f o r Scombridae. Scorpaenidae has  {41.25 y e a r s ) , f o l l o w e d  Gadidae  length.  variation  of  all  this the  parameters.  In  summary,  the weight-length  exponential  appears to be the most s t a b l e c h a r a c t e r . The LM, are  a l s o s t a b l e c h a r a c t e r s . The  are f a i r l y s t a b l e because of the natural T95,  mortality  coefficient  a t h e o r e t i c a l age,  variation  among  has  species  the  Sciaenidae.  TH,  growth parameters large (M)  sample  L1  (K, LINF)  sizes.  variation.  i s d i s p l a y e d by c e r t a i n  The suggested  and  The  shows l a r g e v a r i a t i o n .  greatest  Engraulidae, C l u p e i d a e , C y p r i n i d a e , and  coefficient  Gadidae,  less  families:  Scorpaenidae,  means and standard  e r r o r s of  cLipeioAH  ENGRAULIDAE  6.7, 6.0,  . IA  J.  01  I  o-  i.  a.  s.  I-  4-S.  f  3-0.  *  4.  s.  6.  8-  B- !£>•.11.  li?. 13- 14. IS.  1£. 17. 16• l a .  STXIES I  STCICS  CYPRIMIQAE  I  GADIDAE  SBIA (-  C  33-  S3-  s  SB-,  •  J7-.  I  10  T  I SRXIES I  Figure  10.1  0.  1*  2«  3.  4.  5. .  6*  7.  B.  3.  lO*  11-  13-  14.  13-  16-  17.  5PECTC5 I  Mean values, 95X confidence limits, r a n g e s , and sample s i z e s among s p e c i e s w i t h i n f a m i l i e s f o r the • l i f e s p a n ' (T95) ( s p e c i e s i n d e x r e f e r t o T a b l e 1)  OJ  PLEXROECTIDAE-  St OOP I DAE  1 B04-I  IA  1A I-  70.  U3J  sa..  I • O-  ..  £• 3-  i.  G. 7. U.  0. 1. £. 3. 4. 5' 6* 7. B. 9.10.11.li!.l3.14.1i.lC.17.1B.13.aD.cn-a?.E3.e4.Zi.ai.E7.aB-i  3. ID. I t . IT. 13. 14. 15- UG- 17. l f l . 13.  aracs i  SPECIES I SCORPAENIDAE  SALMONIDAE ISO-,  13S-,  120.J  Ul CI  £  CG-  E.  srccics I  Figure 10.2  3-  SPECIES I  Mean v a l u e s , 95" c o n f i d e n c e l i m i t s , ranqes, and sample s i z e s among s p e c i e s w i t h i n f a m i l i e s f o r the • l i f e span' (T95) (species index r e f e r to T a b l e 1)  means f o r i n d i v i d u a l parameters of summarized i n Table  Relative  15  major  3.  5  relative  characters  (ratios),  TM/T95, T50/T95, the sample s i z e s are 88, data  records  respectively  M/K,  213,  LM/1INF,  175, 45,  a.  The  1 f o r s p e c i e s index  M/K  ratio  families  shows  analysed. four  The  variation.  Gadidae, sizes  Only  Pleuronectidae,  r e s u l t s are shown i n F i g u r e 11. In  these  range  than  and were  variations  larger  four  from  50.46%  for  t o 123.4% f o r P l e u r o n e c t i d a e . Salmonidae has (4.708), f o l l o w e d  Gadidae  other f a m i l i e s Scombridae  great  11  the h i g h e s t r a t i o (3.018),  a  sample  families,  Clupeidae  Refer  number.  (Clupeidae,  Salmonidae) with  15  ranges  r e l a t i v e c h a r a c t e r s among s p e c i e s within f a m i l i e s .  to Table  and  (Table 2). F i g u r e s 11 to  show sample s i z e s , means, 95% confidence l i m i t s , and of  are  Characterg  For  402  families  of  (n=4) ;  by  Pleuronectidae  (1. 686),  and  Clupeidae  fishes,  the  ratio  Percidae  (n=4)  has  is  (0.937). In 1.348  a ratio  for  (1.818)  s i m i l a r t o Gadidae.  b.  The  LM/LINF r a t i o i s a  families  very  stable  character.  Eight  (Clupeidae, C y p r i n i d a e , E n g r a u l i d a e , Gadidae,  P l e u r o n e c t i d a e , Salmonidae, Scombridae, and  Sciaenidae)  T a b l e 3.1 Summary t a b l e of mean v a l u e s , sample s i z e s , s t a n d a r d e r r o r s , and c o e f f i c i e n t s o f v a r i a t i o n f o r p o p u l a t i o n parameters (M, K, L I N F , LB) i n f a m i l i e s a n a l y s e d  i  """" 1  a j  Family  1 1  K  1  LM •  —'"i  Hean  N  IClupeidae  i 0. 330 17 0. 068 85.45 0. 431 20 0 . 024 45. 99 28.88 82 0. 879 2 7 . 57| 19. 32  £2  1Cyprinidae  1 0. 625  (Gadidae  | 0. 354  Mean  SE  }.  1  LINF  i t)  i  cv  | Hean  H  SE  cv  Hean  H  SE  cv -  2 0. 475 107.5 0. 216  22  I P l e u r o n e c t i d a e ! 0. 222 l i  0. 084 125.3 0. 24 3  51 10 1.6 101 . 5 35. 62 2§- 4 . 750 70.551  6 0. 122 62.51  IBotbidae  j 0. 300  2  IEngraulidae  1  0  1. 654 20 0. 155 42. 26 16.15 21 0. 492 13. 94j 12. 24  IHiodontidae  1  0  0. 266 • 6 0. 062 57. 48 40.87  IOsmeridae  |  0  0. 409 10 0. 145 111 .8 31.19  (Salmonidae  | 0. 755  (Sciaenidae  1  0  IScorpaenidae  1 0. 200  2  IPercidae  | 0. 295 74 0. 057 38.81 0. 179  ISparidae  |  (Sgualidae  |  t.  -  L  0. 781 31.821  11 0. 026 7 1 . 80 75.72 56. 4. 271 42. 21 39. 12 2S- 4. 026 52.481  1 0. 478  0. 347 26 0. 033 56. 54 1 52.7 6.0 12 .14 61. 59 62. 02 0. 300  |  r  IScombridae  0  cv  ±1 0. 027 84. 68 173.34 51 6. 397 6 2 . 28 30. 34 33 1. 409 28.621  0. 014 23.32 0. 207 38 0. 030 90. 37 178. 18  0  SE  2  0  0  4 11 .96 53. 65 33. 50  44.60  6 2. 657 15. 98: 10 7. 161 72. 60  32  6. 089 55.54|  2 14 .50 61.211  12  0. 305 10.88)  0 15. 80  1  5 1. 497 2 1 . 1 8 |  11 0 . 092 52.88 0. 329 2§ 0. 042 68. 25 6 1.35 23 7. 940 68. 48 32. 64 21 5. 474 76.851 0. 345 16 0. 027 31. 30 65.37 0  0  17 6. 548 4 1 . 07 | 30. 86 12 3. 281 36.831  0. 107 29 ?• 009 44. 47 43.02 13 1. 999 26. 70] 24. 48  12  1. 830 25.901 1  .7 0 . 028 40. 67 56.74  7 11 .36 52. 97  0  0  0. 111 11 0 . 005 15. 36 78.44  11 4. 104 17. 35  0  0  0. 071 13 0. 014 72. 75 124.3  13 11 .11  6 6. 319 19.091  L  ii  .  N : sample s i z e (with u n d e r s c o r i n g shows t h e r e i s SE : s t a n d a r d e r r o r o f mean c v : c o e f f i c i e n t of v a r i a t i o n  32. 23 81. 10  j  — i  a corresponding  !  figure)  T a b l e 3.2 summary t a b l e of mean v a l u e s , sample s i z e s , s t a n d a r d e r r o r s , and c o e f f i c i e n t s o f v a r i a t i o n f o r p o p u l a t i o n paramentrs (TH, L l , b, T95) i n f a m i l i e s a n a l y z e d 4-  1  f  I  L1  T8  I  I  I  I Family I I I I IClupeidae I ICyprinidae I |Gadidae I |Pleuronectidae I )Scombridae I 1Bothidae I IEngraulidae I IHiodontidae I |Osmeridae I ISalmonidae t ISciaenidae I IScorpaen i d a e I |Percidae I ISparidae I ISqualidae I  i  ,i  [lean  1.B33  SE  N  9 0.221  cv  | Bean  N  SE  I | Bean I  N  6E  cv  Bean  N  SE  4 0.096  6.07  8.29 70 0.445  39 0.383 32.37|3.266  4 0.125  7.64  |29.58 47 4.685  15 0.442 49.90|18.78  8 1.385  20.86)2.987  5 0.035  2.61  16.82 45- 1. 424  15.605 19 0.635 49.36)8.400  31 0.523  34.64|3.201  11 0.081  8.43  32.29 36 7.119  39.19|3.014 34 0.045  8.70  14.64 3.2 3.658  3.427  2.700  19 09368 59.43|47.34 34 3.181 0  1.000  12 0.000 0  0  I 17.55  2 0.95  7.66|  0  9.98  |12.70  9 0.409  9.68|  b  2.35 20 0.367  I 11 .50  4 2.661  46.28|  13.74  0  (2.848 23 0.333 56.13|5.720 10 6.456 25.21|3.330  2 0.080  i 3.500  4 0. 141 9. 43  2 0.500 20.201 0  13.000  3.40  14.69 24.00  32.25|3.112  2 0.071  3.20  9.14  3 0.677 2 0 . 0 9 ) 3 . 1 8 5  2 0.066  2.90  41.25  121.71 14 1.872  7.617 12 0.896 40.76)5.833  18.88  0  2  I |  I  111.67  3 2.404  35.69|  0  19.54  0  112.43  8 1.493  33.991  0  27.51 11  8 3.492 52.33136.56  7 2.125  15.38| L  N : sample s i z e {with u n d e r s c o r i n g shows t h e r e i s SE : s t a n d a r d e r r o r of mean cv : c o e f f i c i e n t of v a r i a t i o n  0  I 44.951  I  108.61 I 56.791 I 132.31 I 141.3| I 0 I  I  6 2. 522 69.481 I 10 4.273 44.98| I 23 6.244 91.981 I 15 0.764 137.71 I 22 7.290 32.361 I 7 3.284 95.17|  0  _J  cv  4  42.99|3.176  36.08|14.84 22 1.360  5.694 35 0.354 36.74)7.390  cv  T95  I  1.442 44.451 I I57.77 13 10.31 17.381 I 64.331 I a corresponding fiqure)  fLELRdrcCTIDA£  CLLPEIDAE  1,a  =  IS..  r  1-7  14.  t>5  12-  t-4  ii.  2  i.e.  o  9  l-o.  e<  0-0  E.  0-£ 0-4 O-E o-oj O. 1.  E-  5- 4. 5- 6-  e.  a.  ID.  ii. iB.  is.  i4.  IJ.  ]!e.  jj7.  jig. 1a.  gTTTTS I  GADIDAE  0. 1. e. 3. 4.  s. C.  7.  B. B.  lO. U. 12. 13. 14. 13. IE. 17. JFECIES j  IB.  13. BO. a . E>.  SALMDNiOAE  8-0. 4- 5 4* 5- 5  5-Q  3 5  3  8-3 B-Q 1-5 1-Q  o-oj  O-  1.  £.  3-  4. 5. 6. 7. B. 9- 10- 11. 12. 13. 14. IS. 16. 17; STCIES  I  s.  s-  CTi  Figure  11.  Mean values, 95%, c o n f i d e n c e limits, r a n g e s , and sample s i z e s among s p e c i e s w i t h i n f a m i l i e s f o r the r a t i o M/K ( s p e c i e s i n d e x r e f e r t o T a b l e 1)  CO  69  with sample s i z e s l a r g e r  than  results  Figure  are  shown  in  9  were 12.  analyzed. In  these  f a m i l i e s , v a r i a t i o n ranges from 12.17% f o r to  41.95%  ratio  f o r S c i a e n i d a e . Engraulidae  (0.766),  Scombridae  followed  (0.629),  the  lowest  of  highest  (0.88); Sgualidae  The grow  value  fishes,  highest (0. 707),  (0.590),  Gadidae  Sciaenidae  (0.513).  Osmeridae (n=6)  (0.110). In  (n=3)  has  also  L1/LINF r a t i o shows the amount t h a t during  its  first  year  with sample s i z e s l a r g e r results  has a high  of  than  11  the  life.  were  fish  Four  and  ranges  Cyprinidae.  from  (0.456),  followed  by  (0.323).  Cyprinidae  has  the  Sciaenidae has  the  families  analyzed.  28.521 f o r Clupeidae  Clupeidae  Squalidae  d.  The life  highest (n=7)  value  The  families, to 58.91%  highest  ratio  (0.364), Scombridae  lowest  L1/LINF  ratio  (0.112); In other f a m i l i e s o f f i s h e s , E n g r a u l i d a e the  can  Scombridae)  are shown i n F i g u r e 13. In these four  variation  has  the  (0.77) s i n c e i t i s o v o v i v i p a r o u s .  (Clupeidae, C y p r i n i d a e , P l e u r o n e c t i d a e ,  for  has the  IM/LINF r a t i o  other f a m i l i e s  ratio  c.  has  (0.57a),  eight  Engraulidae  Clupeidae  Salmonidae  (0.588), P l e u r o n e c t i d a e Cyprinidae  by  The  |n=9)  (0.831) among a l l f i s h e s ; f o r  i t i s (0.314).  TH/T95 r a t i o i n d i c a t e s prior to a t t a i n i n g  the p r o p o r t i o n of the  its  maturity.  fish's  Cyprinidae  and  COPeiDAE  ENGRAULIDAE  0-B5. 0.7C . 0.O1  4-4  O.S3 0-S1  3 3-a  0-42  S  2-7.  0-34  o-a  i.e. l-l  C17  o-on  C  11  I  0-5  X' •*• S-  *•  5-  &*  ?•  6'  e.  10. U -  12- 13. 14. 13. 16• 17.  is.  J-Oj IS* bHO-lLb I  CYPRINIDAE  • GADIDAE  CS7  0.T7 CSS  0.45  0.61 .  C O  Z  e  x  0.34 O'ER  0-54  5  0-4S  3  0-33  O-Q  C31  0-17.  0-23.  CU.  0-1S  o-osi  O-CQ  -o-cc.  3-  4.  -o.ccj  •I  3.  4.  S.  6-  7'  6.  9.  10. 11. 12. 13. 14. 15-  1£> 17.  SPECIES I  Figure  12.1  Mean values, 95% c o n f i d e n c e limits, ranges, and sample s i z e s among s p e c i e s w i t h i n f a m i l i e s f o r the r a t i o LM/LINF { s p e c i e s i n d e x r e f e r t o T a b l e 1)  o  PLEURONECTIDAE  SCIAENIDAE  era.  0.7SL 0.71.  0.70  e  0-E3  e  0-5S  C54i  0.47  a  0-33 ,  0-3E CEV O.lfi o.oa 0-  1.  P*  3-  4. 5 .  6.  7.  B.  B. to- 11- 12. 13. 1 « - IS. IB- 17. 10- 13- 2D- E l . E2» SFECIES  cooJ  a-  I  3. i r t i m  SALMXTQAE  i  'SCO.GRIDAE  O.B7 0-7B. 0-70. 0-81 .  0.3S. o.aa.  0-17. o.oai.  o.oa  a.  e.  0. 1* 2. 3* 4- 5' T . 7- 0.  9.10.11.ie.l3.14.15.1£.17.10-13-a3.E1.2D.e3.24.25.EG-B'.ffl.ai.  SPC:IES i  Figure  12.2  Wean values, 9 5% confidence limits, r a n g e s , and sample s i z e s among s p e c i e s w i t h i n f a m i l i e s for the r a t i o LM/LINF ( s p e c i e s i n d e x r e f e r t o T a b l e 1)  CLUPEIDAE  PLEURONECTIDAE  0.72^  0-43 0.S7,  0-33  0-50.  J  O - O  5  o-aa  S  o  £•  0-23  0-33  o  0-22.  0-14  0-14  o-oa o-os O.  1-  2.  3-  S. 6-  ?•  B'  o-co,O-  B« lO. 11. J2. .13. 14. 13- IS. 17. IB. 13.  1. 2. 3. 4. 3- b- 7. S. 9. JO. 11- 12- 13- 14. 15. IS. 17. Ifl. 13. 20. CISPECIES I  SPECIES t 5CQUGRIDAE  CYPRINIDAE  0-23 2  T  0-21  e -J s  U  o  0.401  0-201  0-0& 0-03 S. £. 7. B. B-10.11-J2-1314.15-16-17-13-liCD-2l-ti. 2)-24.2i.tC-e7.r3-23.  -o-ooi.  ,  SPECIES I  Figure 13.  Mean v a l u e s , 95% c o n f i d e n c e l i m i t s , ranges, and sample s i z e s among s p e c i e s w i t h i n f a m i l i e s f o r the r a t i o L1/LINF (species index r e f e r to Table 1)  73  Engraulidae  with  sample  sizes  larger  than  analyzed. The r e s u l t s are shown i n F i g u r e 14, ranges from 16.85% f o r Sgualidae Osmeridae ratio  (n=7).  (0.649),  Osmeridae  Engraulidae followed  (0. 249).  TM/T95 r a t i o  by  (n=8) (n=10)  Gadidae  Variation  59.09% f o r  (0.426)  (n=8) (n=6)  were  has the h i g h e s t  Sgualidae  Cyprinidae  (0.190).  to  7  has  has  and  the lowest  a  ratio  of  0.222.  e.  The  T50/T95  ratio  is  a  very s t a b l e  c h a r a c t e r . This  shows how much time t h e f i s h needs t c grow t o its  asymptotic  its  full  of  l e n g t h r e l a t i v e t o the time t c grow to  length.  Cyprinidae)  half  Two  with  sample  families sizes  (Clupeidae,  larger  than  and  46 were  analyzed. The r e s u l t s are shown i n F i g u r e 15. The r a t i o i s around 0.23 f o r a l l f i s h e s except the Sgualidae  (0.145).  ovoviviparous  T h i s means most of the f i s h e s need  l e s s than one g u a r t e r of t h e i r l i f e  span  to  grow  to  h a l f of t h e i r u l t i m a t e s i z e .  In  summary, the T50/T95 r a t i o has the l e a s t  although the  LH/LINF  ratio  significance  because  of  f i s h e s f o r growth and/or L1/LINF suggested  and  the  TM/T95  has  the  greatest  the energy-spending for  variation, biological  strategies of  reproduction.  The fl/K, the  r a t i o s show large  v a r i a t i o n s . The  means and standard e r r o r s o f  means  for  relative  74 CYPMNICAE  ENGRAU.IOAE  o.»[  ©•E7,  0.31 3  0*30  o.«  a cu]  0-31 0-13  o-ea 0-1T,  o.in  o.tr  o.ia  e.oa  coo.  EPfXIES I  Figure  14.  SFVTJCS i  Mean values, 95$ confidence limits, r a n g e s , and sample s i z e s among s p e c i e s w i t h i n f a m i l i e s f o r the r a t i o TM/T95 ( s p e c i e s i n d e x r e f e r t o T a b l e 1)  CYPRINIDAE  cupeirjAE CHL 0-31  c-er,  cm °'  E<  ca «? »  •  •  I  I  »I 0-17.  o-v  B o-i-4  I  civ O'Ul  o-co  O'CP  0-CG  0-CQ  O-ce  CCQ  l*  r> j .  tf  *• V. '«. o.ID. U> UB« 13* 14. IS- Ii. 17- i j . ia.  o-co SPECIES I  Figure  15.  Mean values, 95« confidence limits, r a n g e s , and sample s i z e s among s p e c i e s w i t h i n f a m i l i e s for thr a t i o T50/T95 ( s p e c i e s i n d e x r e f e r t o T a b l e 1)  75  characters  (ratios)  of 15 f a m i l i e s are summarized i n Table  4.  3. . C o r r e l a t i v e  Characters  Five c o r r e l a t i v e c h a r a c t e r s 11—LINF, analysis.  1/.H—T95)  were  (H—K,  examined  Nine f a m i l i e s : Clupeidae,  1/K--LINF, L H — L I N F , by  linear  Cyprinidae,  regression Engraulidae,  Gadidae, P l e u r o n e c t i d a e , Salmonidae, S c i a e n i d a e , and  a.  Scombridae,  Scorpaenidae were analyzed.  For  the  M—K  correlation,  four f a m i l i e s  Gadidae, p l e u r o n e c t i d a e , Salmonidae) with larger  than  F i g u r e 16. families  11 were analysed.  Except  The  (Clupeidae, sample  r e s u l t s are shown i n  f o r P l e u r o n e c t i d a e , the  ether  three  show a s i g n i f i c a n t l i n e a r c o r r e l a t i o n between  M--K.  The s l o p e o f these r e g r e s s i o n l i n e s i s  from  the  coresponding  of the r e g r e s s i o n  Clupeidae  Dl i s about 1.66 4 times K and M  is  2.454  Salmonidae M i s 1.047  different  r a t i o s . Without c o n s i d e r i n g the  intercept  Gadidae  size  times  line  K  on  and  times K and H/K  the K/K H/K  M-axis,  in  i s 0.937; i n i s 1.686; i n  i s 4.7  (refer  to  Table 4) .  b.  For  the  correlation  (Clupeidae,  between 1/K—LINF, nine  Cyprinidae,  Engraulidae,  families Gadidae,  P l e u r o n e c t i d a e , Salmonidae, S c i a e n i d a e , Scombridae, and  and  i—  Table 4 Summary t a b l e o f mean v a l u e s , sample s i z e s , s t a n d a r d e r r o r s , c o e f f i c i e n t s of v a r i a t i o n f o r r e l a t i v e characters i n f a m i l i e s analysed  f  1  T  H/K 1  Family  LH/LIHF  L1/LINF  f. I Bean  1  T  !  TB/T95  | Bean  N  J  N  SE  cv  Bean  N  SE  IClu p e i d a e  }o.937 1 2 0. 137 50. 46 0. 707 51 0.014  ICyprinidae  I 1.322  1Gadidae  I 1.686 20 0. 270 71.63 0. 588 20 0.021  cv  I Mean  N  14. 38 10. 456 2 2  SE  cv  0. 028 28.521  0  2 0. 678 72.55 0. 410 1 2 0.033 25. 29 10. 112 29 0. 012 58.9110.190 16.24 1 o .383  SE  7 0. 090 62.3510.222  IScombridae  I 1.348  4 0. 362 53.65 0. 629 1 2 0.036 25.01 t o . 323 2 2 0. 029 46.56|0.047  2 0.000  IBothidae  | 1.000  2 0. 000  0  IEngraulidae  0  IHiodontidae  0  IOsmeridae  0  0  10. 345  I 1.870  2 0. 130  |Percidae  I 1.818  4 0. 445 08. 89  ISparldae  0  ISqualidae  0  cv  |  0,218 2 2 0.006 22.581 0. 002  5.521  12.44 0.236 36 0.008  19.421  0.04 0.234 33 0. 008 18.701 0.231  I  0. 756 11 0.023 12. 17 10. 831 79 0. 030 10.9310.649 1 2 0.073 35.43 0.231 20 0. 000  0  I  4 0.069 51.911  0  7 0.059 74.8210.249  7 0.056 59.09 0.222 10 0. 012 17.11)  0  1  0  0.231 28 0. 000  0.06)  0. 513 11 0.065 4 1. 95 10. 364 12 0. 040 38.18|  0  0.231  1.94)  0. 888  1Scorpaenidae  SE  0  0  0  N  2 0. 000  3 0.009  0. 267 1 .84 0. 208  I 4.708 11 1. 189 110.0 0.590 2 1 0.034 26.65  ISciaenidae  2 0. 137 56.27|  Bean  6 0.026 29. 16 0.202 45 0. 010 34.62J 2 0.036  0  cv  8 0.028 42. 19 0.234 ±1  I p l e u r o n e c t i d a e 13.018 14 0. 995 123.4 0. 574 2 2 0.022 20. 15 |0. 181 30 0. 017 51.27|0.409  ISalmonidae  T50/T95  9.87 0. 447  0.218 76 0.027. 30.67]  15 0. 001  4 0.034. 15.'09 0. 170  3 0.039 39.781  •' 0  0  t o . 139  3 0. 035 44. 191  0  0.236  7 0. 004  4.541  0  t o . 152  8 0. 017 30.361  0  0.225 1 1 0. 004  6.26|  10. 314  7 0. 049 41.0810.426  8 0.025 16.85 0. 145 13 0. 007 17.871  0. 770 6 0.014  N : sample s i z e (with u n d e r s c o r i n g SE : s t a n d a r d e r r o r o f mean cv : c o e f f i c i e n t o f v a r i a t i o n  4.50  shows t h e r e  i s a corresponding  fiqure)  0.226 29 0.012 27.31)  77  FLOJRON'ECTIOAE M 0-SC8 • 0<O37K (N* 15) PRCO OF ELCP EETING ZERO IS O-IOCE 01  CLLPCIOAE "  FPOQ OT 3-OPE BEING ZERO IS 0.73SE-O3  »i  ©-?  tvt,  0-1-.  ••5 • M O-l  . o-erj  e-i  •-oat  0-00  0-0*  C  L 0-21  o-eo  0-31  0-42  0--4  0O(.  0-61  GADIDAE M o -0.182 • CN= 50) PRCS CF SLOP ECIN3 2EFQ IS 0-OOCG 00  o c o  o - u >  o-i3  Figure  o - a  16.  0 - 3 3  o - < j  £ M  OSD  T  i  C-OQ c e o  o o .  o - i 2  o - i ?  c - r j  O-LQ  o - : n  o - « i  o - - i >  o - u  o - u .  SALWONIOAE • M e 0.125 * l.o<C K 'N= IS) «\ PR03.CF SLOPS BEIN3 ZERD IS 0.337E>CH  F  "  Linear regression families  o-ol J U >  j - a i  c - i i  c - i 3  <..JO  . - . j i  a n a l y s i s betw-en 1  oT5  £aj  ^ 7 1  /M--T95 within  78  Scorpaenidae)  with  sample  sizes  larger  analyzed. The r e s u l t s are shown i n F i g u r e  than 14 sere 17. .  ftll  the  other e i g h t f a m i l i e s except Sciaenidae show s i g n i f i c a n t linear  correlations  the higher the K  between  value,  1/K—LIHF, This shows t h a t  the  smaller  the  asymptotic  length.  c.  For  the  correlation  (Clupeidae,  Cyprinidae,  Salmonidae,  TH/T95,  Gadidae,  correlations  Lfl—LINF.  Clupeidae,  Salmonidae,  families  The r e s u l t s are  18. A l l of them show s i g n i f i c a n t l i n e a r  between  in  six  Pleuronectidae,  Scombridae) were analysed.  shown i n F i g u r e  lines  between  and  corresponding  Slopes  Gadidae,  Scombridae 1H/LINF  are  of  regression  Pleuronectidae, similar  ratios.  to  the  Cyprinidae  show  i n c o n s i s t e n c y between the slope of 0.16 6 and the  ratio  of 0.410.  d.  For  the  correlation  between  L1—LINF,  (Clupeidae,  Cyprinidae,  Engraulidae,  Sciaenidae,  Scombridae) were analysed.  shown i n Figure 19. Only two  families  Scombridae)  show  correlations this, has  out  cf  six  between L1--LINF. Hy  six families  Pleuronectidae, The r e s u l t s are (Clupeidae  significant  and  linear  rationalization  for  not having good l i n e a r r e g r e s s i o n , i s because L1 large  similar  to  variation. the  For  Cyprinidae  the  slope  is  L1/LIHF r a t i o , but f o r Scombridae the  I  79  I  I  Q-lPEIOAE  e . c o s  ENGRAULIDAE  1/K = 0"D3 * 0-O33 LXfF tN* 70) .r. FR33 OF SLOPE EEIN3 ZERO 15 O-ISCE-CS  1/K * o.ira.iNF < N , S O t.» PROB Q- ELCP EEIN3 ZLK) IS 0-2CGE-O3  «-<4  it  »•» i*r »-c  ••5  »•* 6-C . ••  CYPRINIDAE i/K -4-033 • O-aCGLlNF i[N= -17) PRCS DF SLOPE EEIN3 ZEFO IS 0«S2GE-Q7  Figure  17.1  linear regression tarailres  lO-  IJ.  is.  GADIDAE 1/K  •=  1.553 •  0«CS3 LINF  PRCS O F SLOP B E I N G ZERO I S  analysis  between  1/K—LINF  CN= -45) .  within  80 SCOvBRIOAE  PLEIJFOCCTIOAE ^  Cf HUP ^  TS*  G  ^  JVK -1-EG7 • O'CCQLINF <N» 33) PRD3 CF SUP EEIN3 ZERO IS 0-2Q7E-O3  IS o.OOaf CO  100'  R3.  eo«  ^ 0-897 * C H S LI>T (N=20) RR03 DF ELCPE EEIK3 2ER0 IS O-IEBE-Ol c  17.2  a^>  »v j .  na.  3^4-  <n.  *o*  SCORPAENIDAE:  SALWCNIDAZ  Figure  uc.  Linear regression families  ^ " -3-108 • 0-534 LINT tN= 29) PRD3 DF EIXFE EEIN3 ZERO IS O-UEET-OI e  x  a n a l y s i s between  1/K—LINF  within  81 PLEURONECTIDAE:  QJLFEIOAE LM  t>>  a  4*  O-OIO *  ••  12.  0-7CG LTtF  Hi.  139.  XI-  CN" 51)  V*  31.  33.  3Q-  CYPRINIDAE: LM 1G-EE2 * O-IOGLIN^ CN= 10) PRCQ CF SLEFEEEIN3 ZERO IS 0-1SQE-01  tv  co>  o-  co»  ea*  joi.  ibi»  O  W.  7i->  V3.  ICO.  SALMDNIDAE LM = -1-303 +  nn. eoi.  1^*  JD'  ft*.  0-335LrN="  O-  COO.  LINF  5G*  -C«  SCCVBRIQAE LM 14-612 •  GADIDAE: LM a O'D-VB • 0-5S2 LIN=- <N= 50) [ FTOO Or SLCP EEirc 2ERQ is O-COOZ 00  0*  UO.  (N= 21)  TO.  tU.  uiV>  I'C*  CNa IS)  * x  to.  Figure  18.  uo.  L i n e a r r e g r e s s i o n a n a l y s i s between families  lO-  uo. pjo-  LH—LINF  within  CLUPEIDAE U-  8-E33  Ll  -1-73S *  c  82  PLEURONECTIDAE 0-505 LINF  (Na 2 2 )  *  -O.0O4Jt>F  CN* 3 0 )  P H 0 3 O F S L O P E E I N 3 ZERO I S O - I O O E 0 1  F R D 3 O F S L O P E : E E I N 3 ZERO I S 0 - 8 3 C G . - C 3  —  -TTK  X  .  30-  o.  o.  un>  CYPRINIDAE =  U.  8-'tis *  -0-014 LINT  PROB O F S L O P E E O N S  SCIAENIDAE Ll «= 1 5 - 1 2 9 *  (N= S 3 )  ZERO I S 0 - 1 0 C E 0 0  °RCB O F  X  •*  lc.  -a-  to.  i a j -  129.  i i i -  172.  i v * .  e i s .  10-843  io-  0-100  LI>F .CN=  12)  BEING ZERO I S 0 - 1 O X 0 1  11.  <a>  n-  c  ?!'  EC*  B>-  fXO  SCOMBRIDAE  ENGRAULIDAE L l  o*  aXPC  216.  *  C121LINF  Ll  9)  CN*  30-655 *  0-073LIN?  (N= 27)  PRD3 O F S L O P B E I N G ZERO I S 0 - 3 7 C G - 0 3  ^1 F T O 0 O F S L O P E E I N G ZERO I S 0 - 1 0 C E 0 1  X  X  X  o*  i*  Figure  ».  19.  »-  • •  10*  « •  M '  13*  S7-  Linear regression families  01.  *  *  i x .  i u . - »  n y .  c v j .  j t o .  a n a l y s i s between L 1 — L I N F  •co.  ca.  within  83  slope  e.  For  (0.073) i s much s m a l l e r than the r a t i o  the  correlation  families  between  (Clupeidae,  Scombridae) were analyzed Figure  20.  None  of  1/M--T95,  Gadidae, and  them  (0.323).  only  four  Pleuronectidae,  the r e s u l t s are shown shows a s i g n i f i c a n t  in  linear  c o r r e l a t i o n between 1/M-—T95.  In c o n c l u s i o n , there are s i g n i f i c a n t l i n e a r relationships  (slope  between H—K,  b  regression  i s s i g n i f i c a n t l y d i f f e r e n t from  beween 1/K—LINF, and  0)  between L H — L I N F i n most  of the f a m i l i e s analysed  except  show  a l a r g e r LINF a l s o have a l a r g e r LM  that  fish  having  Sciaenidae.  and lower K and H v a l u e s . A l l these  results  sample s i z e s are summarized i n T a b l e  5.  Combining  the data records from the  a c o r r e l a t i o n matrix correlation  was  between  calculated  characters.  The  to  These  together  coefficient  a s m a l l e r LINF.  with  15 major f a m i l i e s , show  the  overall  r e s u l t s are shown i n  Table 6. Once a g a i n , i t suggests t h a t f i s h having mortality  results  a  higher  have a higher K value, a lower LH  and  84  CLLFEIOAE: 1/M a 1-3CG » 0-307 T033 CN» IH) PTC33 C T E L C F G GEIfGLZOTa IS 0-&VE-01  PLEIJRONECTIOAE JVM. ,5  t  '.•-••CM *  O-OOHTCQS  n o 3 or txxr> c o r e  Z E R O  I S  CN" 13)  o-iocr: 01  7.4  •«  11 t.5  • •7  GADIQAE = *''TFR33  C T  2»73S * S U P  0 - 0 3 4  EEIN3 Z E R O  T O S S I S  CN=  0-175E  S O ) C O  f  SALMONIDAE ^ J-^M = 1.543 • 0-021 T035 CN= 13) " R 0 8 C F EUPE EEIN3 ZERO IS 0.531E-01 C  ..cl  *-? 4.7.  o.q »•!  1-3 ••7  .... 13S.  F i g u r e 20.  Linear regression fa rallies  a n a l y s i s between  1/M—T95  within  85  Table 5 Summary t a b l e o f l i n e a r r e q r e s s i o n a n a l y s e s for 5 correlative characters within families (sample s i z e s w i t h i n b r a c k e t )  Families  -  Clupeidae  M—  **  (12) Cyprinidae Engraulidae Gadidae Pleuronectidae Salmonidae  —  —  K  1/K--LINF  *#  LM—LINF  **  *  (Hi)  (10)  ns (29)  **  — —  **  **  (45)  (20)  ns (15)  **  **  (36)  (27)  —  Scombridae  —  Scorpaenidae  —  ns (12)  **  **  Sciaenidae  **  (22)  (15)  **  1/M—T9'5  (51)  (70)  (20)  (15)  L1—LINF  * (28) ns (15)  **  ns (9)  ns (30) —  n s (12)  **  **  **  (33)  (19)  (27)  *  —  —  _  ns (20)  (21) —  —  —  ns (13) ns (19) _  _  —  _  —  (29)  ** : 1% l e v e l f o r l i n e a r r e g r e s s i o n c o e f f i c i e n t b w i t h 0 * : 5% l e v e l f o r l i n e a r r e g r e s s i o n c o e f f i c i e n t b w i t h 0 ns : no s i g n i f i c a n t d i f f e r e n c e between b and 0 — : s a m p l e s i z e l e s s t h a n 10  Table  W I T H I N GROUPS  6.  CORRELATION  VARI&SIFS GROUP VARIABLE GROUP  M K  LINF LM TM Ll B  1-0000 0.0 0.0 0.0 0.0 0.0 0.0 0-0  The correlation combined d a t a o f 15  matrix between families  parameters  for  MATRIX  M  1. 0 0 0 0 0.22293 -0.12545 - 0 . 9 6 6 2 0 E - 01 0 . 3 6 3 4 1 E - 02 0. 8 4 0 3 4 E - 05 0. 1 5 3 4 3 E -02  K  1.0000 -0.20974 -0.33286E-0.45981E0.21794E-0.40492E-  LINF  1.0000 01 0.41971 0. 12797 01 01 0. 1 6 4 6 6 02 - 0 . 5 3 2 9 3 E - 0 2  LM  2.. 0 0 0 0 0. 23572* 0. 1 0 6 4 4 - 0 . 2 69 52E  TM  Ll  1.0000  - 0 . 18712E-01 -0.42299E-02  1.0000 0.26381E-02  1.0000  oo CTl  87  I I POPULATION PATTERNS  1.. Ccmjgarison  between F a m i l i e s  The comparisons of standard of T95,  the  four  and  parameters  LH)  families:  between  Osmeridae,  were  Cyprinidae,  Pleuronectidae,  Scombridae, Scorpaenidae,  mean  with l a r g e sample s i z e s families  Clupeidae,  d e v i a t i o n s and  (K, LINF,  conducted  for  Engraulidae,  Salmonidae,  and S g u a l i d a e . By  values  11  Gadidae,  Sciaenidae, using the F - t e s t  and the a p p r o p r i a t e t - t e s t , s i g n i f i c a n t d i f f e r e n c e s between 1  f a m i l i e s were found families  was  i n most of the cases.  rearranged  using  the  The  methods  seguence of  numerical  taxonomy i n order to b r i n g s i m i l a r f a m i l i e s adjacent other and the r e s u l t s are shown i n Table 7. Each in  Table  7  f a m i l i e s . The  to each  small  box  d i s p l a y s the r e s u l t s cf comparison between first  two  t - t e s t . The  two  columns show the r e s u l t s from the  t e s t and the next two columns appropriate  of  show  the  results  from  the  four rows i n t h e s m a l l box i n d i c a t e  f o u r parmeters (K, LINF, T95,  and  LH)  on which analyses  were  based. The attempt to group f a m i l i e s i n t o p a t t e r n s f a i l e d t h i s method. But t h i s c o n f i r m s that  significant  F-  that one  differences  exist  of  my  from  by  hypotheses, phylogeretic  If a significant d i f f e r e n c e was shown from F v a l u e , the Welch s approximation method was u t i l i z e d i n s t e a d of the Student t-test. 1  t  88  Enqraulidae  Table 7 The F - t e s t and t h e a p p r o p r i a t e t - t e s t between families  i ~x  Clupeidae  Osmeridae  1****1 1****1 I * * !  |**  |Clupeidae  r  +~ | j  |***|**  |  I  r  H  rK I LINF|  4  i  1  **|** *|  I****I****I  1****1****1 * j 1****1****1  1Cyprinidae  I* * * * j * * * | * *  j**  I* * * * | * * * | I *j** * |  I * I **  |****|  |  *** j **  j * * * * j * ***I  | Salmonidae  — i  **j  * *| **** |  1****1  I  Gadidae  +  +  H  |  (Gadidae +  I  * *j * * |  * j* * * * |  1****1****1**  |****|****|****|****|****| |****|**  1****1****1 * * * | * * I**  i**  *|  1  1****1 * * | * * l****j****l  1****1**  |  I ***|****|  Squalidae  H  I** | j** *|  |** | * * * * j * * * | ****j ****| I* * | * 1 j * * * * j sciaenidae  1****1**  1****1****1**  Scombridae  j  |****j *|** | **|* j* * * * j * * * * | **| I I  Scorpaenidae  JPleur onectidae  | ** | ** j****l****l****l** I****I****I** | * * * I** I * *j**** j I * * *|  i Sciaenidae  I **  **j**  : *\% l e v e l : 5% l e v e l : sample s i z e l e s s t h a n 10  I I  Pleuronectidae|****|****| * ) * *  j  i ** * —  ** j  1****1****| * * * |  Salmcnidae  T95| LM I  |Osmeridae  1****1 Cyprinidae  -i  j **j ** j** | ** I  F t  | *|**  | **|  *j****|****|****j  I  1****1****1  |** * ] * * * * )  I  **|  *j  *  |scorpaenidae  1****1  ***|****|****|****|****|****|****j  | * | * * |** * | * * | 1****1 1****1 * * | **| * * * | * * * | * * * * | s c o m b r i d a e  1****1 * * * | * * * | * * * | * * * * j * * * * j * * * | ***| * * | **** 1****1****1 **|****| * * j * * * | * * * * | ***!****! j* * * * j * * * * j I **** 1****1****1****1****1 * * * | * I I -I I I  89  considerations, i s true.  Comparison among F a m i l i e s The is  mean and i t s 95% c o n f i d e n c e l i m i t f o r each  shown (a) i n F i g u r e 21 and 22 f o r each parameter, (b) i n  F i g u r e 23 and 24 f o r each r e l a t i v e c h a r a c t e r . Fig.  family  23  show the r e s u l t s  21  and  from group I : 5 f a m i l i e s ; F i g . 22  and F i g . 24 show the r e s u l t from Together  (Fig.  group  II:  10  families).  with Tables 3 and 4, which show the standard e r r o r  of the mean and t h e c o e f f i c i e n t o f v a r i a t i o n , these permitted  the  grouping  of  fishes  into  four  figures different  c a t e g o r i e s by comparing the four s t a b l e c h a r a c t e r s  such  as  K, LINF, LIS, and the r a t i o LM/LINF, as f o l l o w s :  A)  Engraulidae, highest K  Clupeidae,  (1.-6  and  Osmeridae. They have the  f o r Engraulidae,  over  0.4  f o r the  o t h e r s ) , the s m a l l e s t LINF, LM, and a very high LK/LINF ratio of  (over 0.7). Common c h a r a c t e r i s t i c s of t h i s group  fishes  schocling  B)  Scombridae  are  small  size,  pelagic  habitat,  K  (around  and  behavior.  has  fairly  high  value  0.35),  although i t i s lower than p e l a g i c s h o a l i n g f i s h e s . T h i s f a m i l y has t h e l a r g e s t LINF cm).  Salmonidae  and  (152.7 cm)  Sciaenidae  and  L1  (47.34  seem t o show s i m i l a r  characteristics, especially for their K  values  (0.329  e-a.  M. t-o. t.s.  a.  1.4,  1-1 O-B,  ©•7 .  o-a.  Cypri  Clupe  Gadid  Pleuro  Scombr  Clupe  Cypri  Scombr  Clupe  Cypri  Gadid  Pleuro  Scombr  Pleuro  Scombr  o-a 0-7 .  0-6.  o-a. 0-4. O.E  CI.  0-OL  Clupe  Cypri  Figure 21.1  Gadid  Pleuro  Gadid  Mean v a l u e s , 95£ c o n f i d e n c e limits, ranges and sample sizes of i n d i v i d u a l parameters among 5 f a m i l i e s (group I)  o  i.e.  u.v E.G. •°  e.a.  C  i-n.  £  i.s.  o.a 0.4  -o-oj  Clupe  Cypri.  Gadid  Pleuro  Clupe  Scombr  Cypri  Gadid  Cypri  Gadid  Pleuro  Scombr  eo. To-  o. Iin  D  U3'  £  01.  ED  «•  il T  70  0.  Clupe  Cypri  Gadid  Figure 2 1 . 2  Pleuro  Scombr  —t—  Clupe  Pleuro  Mean v a l u e s , 95% c o n f i d e n c e l i m i t s , ranges and sample sizes of i n d i v i d u a l parameters among 5 f a m i l i e s (group I)  Scombr  t—*  1>s  r  1-8  1-0.  173-  o-a, o-a 0-6  IS?.  -I  130.  W  0-3.  £  o-«.  ic0  '  B7ss.  e  0-3  U.  B  0-1  El  a  0-OL  Both  Engr  Hiod^ Salm . Scor Spar Osme Scia Perc Squa  B  o  p  t  h  K  v „ „  Engr  i o d  o  Osme  Salrn  . Scor Spar Scia Perc Squa F  e-ay  i-a J.-S.  i-e.  O.E 0-K •  e  u  •a Both  Engr  Hiod ^ SalirT . S c o r Spar Osme Scia Perc Squa  F i g u r e 22.1  p  Both  Engr  Hiod „ Salm . Scor Spar Osme Scia Perc Squa  Wean values. 95% confidence l i m i t s , ranges and sample sizes of i n d i v i d u a l parameters among 10 f a m i l i e s (group I I )  p  3  '\  f i  I E7-.  10-1  1-Q.  7-.  0-7 .  3-J  0-3.  13 B  -O'OL  Both  Engr  Hiod  Osme  Salm  . Scor Spar Scia Perc Squa  Both  Engr  Hiod^ Salm. . Scor Osme Scia Perc  Spar  Squa  1E3. l-O.  83.  50.  13-i  13 w  * Both  Engr  Hiod^ Salin . Scor Spar Osme Scia Perc Squa  F i g u r e 22.2  Both. Hiod^ Salin . Scor Spar Engr Osme Scia Perc Squa  Mean v a l u e s , 95? c o n f i d e n c e limits, ranges and sample sizes of i n d i v i d u a l parameters among 10 f a m i l i e s (group II)  RATIO M/K  RATIO l_M/Ca> A  o  fj  p  o  o  o  p  o  y  o  ft  o g  o P  o P  o ,*  5  P  o  o  d  d •x+x «K TJCD  CD 03 d n to  01 g H- CD N 0) CD 3 01 ' < O OJ Hi M d o ro o 01 K l-«  fD  M Ul 0) o\P ft O < O CD 3 Hi O H-  «B  —x  TJ.  o  o  0). fi.  «8  P>  «8  HTJ I—' CD d O  TJ hCD , d H O  cn o o  cn o o  1  «3  'to  RATIO  0) CD  K. 3 OJ O O CD r+ CD H 01 3 H0) rt 3 . 01 o 02 M  n  o TJ  o P  o d TJCD  o E  o P  P  o P  o f  r  TM/T95  o F  '  o r  o '  .  to p  -  o p  RATIO Ll/Uo  o* .  O  p  3  pi  p  }  JK  o (-• c TJ CD  0)  ui 3 . 0} Hi CD OJ 01  TJ  3  H- (1)  H- Cu CD 01 01  O OJ  •Q) — 3 iQ ' 0  O CD d H  TJ • H H-  ,0>  HTJ H CD d n o cn o o  fr6  O  Di TJ hCD d n o 1  cn o o  X  1  K  i  g  iL  t  IB  ie-  0-£H  12'  C7S,  13-  z o  0.66.  12  u.  CSS.  8-  iS.  ;>.. 5  s-  C37.  o.sa.  «..  o.ia  e.  3  0-OQ  Both  coo.  ' Hiod ^ Salm . Scor Spar < Engr Osme Scia Perc Squa  Both  P  S.S.  Hiod^ Salm ."Scor Osme Scia Perc  Engr  Soar P  Squa  O-tlT.  4.a.  o.oa.  •»•«  0-7B.  a-a  H|  ?  fi  S  8  RAT  fl'  o  O-EQ.  C<1.  0.33. 1-6  o-aa.  .1 IT  0-5  t I  o-ia.  0.10..  t>*0  O'CO. B  ° t h  Engr  Hiod  F i g u r e 24.  Osme  Salm  Scor •• q n s r Scia Perc ° Squa b C O r  P  a  r  B  O  T  H  T T ^ V  Engr  H  i  o  d  r >  .• Osme  Salm,, . S c o r Spar Scia Perc Squa F  Mean v a l u e s , 95% confidence l i m i t s , ranges, and sample s i z e s o f c o r r e l a t i v e c h a r a c t e r s among 10 f a m i l i e s (group I I )  «>  96  for  Salmonidae, 0.345 f o r S c i a e n i d a e ) . These f i s h e s are  l a r g e , p e l a g i c , and migratory.  C)  Gadidae,  Pleuronectidae,  Scorpaenidae,  Sparidae e t c .  They have lower  K values | l e s s than 0.25), i n t e r m e d i a t e  1IHF,  LH/LINF r a t i o s  and lower  fishes  ( l e s s than  0.6).  These  l i v e on or c l o s e t o the c o n t i n e n t a l s h e l f , have  a longer l i f e  span and a l a r g e asymptotic  length,  but  are slow growing.  D)  Freshwater  fish  -  Cyprinidae  has  K and LIWF v a l u e s  which a r e s i m i l a r t o those o f the group C has  a  smaller  (0.4) and TM/T95  fishes,  but  LH and, e s p e c i a l l y , the lowest LM/1IFF (0.2) r a t i o . They  start  reproduction  e a r l y and have a high m o r t a l i t y r a t e (0.625, the second highest among 15 f a m i l i e s , next t o Salmonidae),  The  r e s u l t s of c a l c u l a t i o n s f o r t h e other 28 f a m i l i e s ,  i n s u f f i c i e n t data support, are l i s t e d i n appendix 1 and 2.  with  97  C l a s s i f y i n g Families For  7  (Discriminant  v a r i a b l e s (M,  discriminant analysis  K,  not  Ana3.ysis)  LINF, LH, TM,  only  L1 , b) , stepwise  elegantly  guantifies  means of d i f f e r e n t groups by a set of d i s c r i m i n a n t according  to t h e i r underlying  groups d i f f e r Figure I  in a  functions  a f f i n i t i e s but a l s o shows  multi-dimensional  space.  Table  8  and  (among 5 f a m i l i e s , which have very l a r g e sample s i z e s ) 93.291  of  independently,  the  families  432  cases,  which  of  have  analysis fairly  188  the  are shown i n Table  of  the  620  (15  groups.  classified  classification  II  (among  Further,  F i g u r e 27 of group I  altogether)  in  cases  which These  classified  into  into  function  10,  12.2051  Pleuronectidae. for  15  families  11. Table  of  Scorpaenidae  The  calculated  based  12 presents  on  seven  a summary  r e s u l t s of the d i s c r i m i n a n t a n a l y s i s by l i s t i n g  canonical roots  (eigen-values), canonical v a r i a b l e s  vectors) ,  the  and  10  sample s i z e s ) i n which  10 and  of  Figure  Thus, they i n d i c a t e the s i m i l a r i t y among  v a r i a b l e s , i s shown i n Table the  9 and  cases were c o r r e c t l y c l a s s i f i e d .  groups. For example, i n Table were  group  families  t a b l e s a l s o show the percentage different  Table  in  considered  cases were c o r r e c t l y c l a s s i f i e d .  group I I combined  90.48^  in  large  90.963? of the results  when  were c o r r e c t l y c l a s s i f i e d .  26 show the r e s u l t s  and  how  25 show the r e s u l t of d i s c r i m i n a n t a n a l y s i s i n group  which  of  the  the  (eigen-  group means (based on eigen-values)  for  I  i  98  I Table  8.  Discriminant  OBSERVED KLUPEI CYPRIN CADI DA PLEURO SCOMPR  a n a l y s i s i n 5 f a m i l i e s (cjroup I)  93.29% CF THE CASFS HERE CORRECTLY CLASSIFIED NUMBER OF CASES CLASSIFIED INTO GROUP PREDJCTFD KLUPEI CYPRIN GADIDA PL.SURO SCOMBR TOTAL 57 3  3  5 0  I 85 1 0 0  1 0 63 3 8  0 1 1 6? 0  I 0  100  0 96  ' 70 104  89 69  1  I OF CASES CLASSIFIED INTO EACH GROUP • PREOICTEC KLUPEI CYPRIM GADIDA PLEURO SCOMPR IBSFRVF.D KLUPFI 97.00 1.00 1.00 0.0 1.00 CYPRIN 3.37 95.51 0.0 1.12 0.0 GADIGA 4.35 1.45 91.3 0 1.4 5 1.4 5 PLEURO 7.14 0.0 4.29 88.57 0.0 SCOMBR 0.0 0.0 7.69 0.0 92.31  Table  OBSERVED 6B0THI 7ENGRA 8HIJOO 90SHER OS ALMO 1SCIAF  2SC0RP 3°ERCI 4SPARI 5S0U4L  9.  Discriminant  a n a l y s i s i n 10 f a m i l i e s ( q r o u p I I )  90.56? OF THF CASES WERF CORRECTLY CLASSIFIED NU^eSR OF CASES CLASSIFIED INTO GROUP PREDICTED 6E0THI 7ENGRA 8HI0DC 9QSMER OSALMO 1SCIAE 2SC0RP 3PERCI 4 SPAR I 5SCUAL TOTAL c  0 0 0 3 5 0 C 0 0  0 20 0 0 0 0 0 0 0 0  0 2 6 0 2 0 0 0 0 0  0 0 0 30 0 0 0 0 0 0  1 Of- CASES CLASSIFIED INTO EACH GROUP PPEDICTFQ 6B01HI 7ENGRA 8HI0DO 9OSMER OBSERVFO 630THI 1C0.0C 0.0 0.0 0.0 7ENGPA 0.0 90.91 9.09 0.0 0.0 0.0 100.00 0.0 8HIOD0 CO CC 0.0 ICO.CO 90SHER OSALMO 5.C5 CO 6.06 O.C 0.0 0.0 0.0 1SCIAE 26.32 2SC0PP CO 0.0 0.0 CC 3PERCI 0.0 0.0 0.0 0.0 4SPARI CC CO 0.0 O.C 5S0UAL 0.0 0.0 0.0 0.0  0 0 0 0 24 0 0 0 0 0  0 0 0 0 0 13 0 0 0 0  0 0 0 a 0  c  41 0 0 0  0 0 0 0 3 1 0 7 0 0  0 0 0 0 1 0 0 0 12 0  0 0 0 0 0 0 0 0 . 0 13  OSALMO 1SCIAE 2SC0RP 3PFRCI 4SPARI 5SQUAL 0.0 0.0 0.0 0.0 72.73 0.0 0.0 0.0 0.0 0.0  0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 O.C 0.0 68. 42 CO 0.0 100.00 CC CO 0.0 0.0 0.0 CO  0.0 0.0 0.0 CO 9.05 5.26 0.0  100.oc CO 0.0  0.0 CC 0.0 0.0 0.0 0.0 0.0 0.0 3.03 0.0 0.0 O.C 0.0 0.0 0.0 0.0 100.00 CC 0.0 100.00  5 22 6 30 33 19 41 7 12 13  99  8.000 7.667 7.333 7.000 6.667 6.333 6.000 5.667 5.333 5.000 4.667 4.33? 4.000 3.667 3.333 3.0CC 2.667 2.333 2.000 1.667 1.333 1.000 0.667 0.333 -0.000 -0.333 -0.667 -1.000 -1.333 -1.667 -2.000 -2.333 -2.667 -3.000 -3.333 -3.667 -4.0C0 -4.333  • •  S.000 7.667 7.333 7.000 6.667 6.333 6.000 5.667 5.333 5.000 4.667 4.333 4.000 3.667 3.333 •3.000 2.667 2.333 2.000 1.667 1.333 1.000 0.667 0.333 -0.000 -0.333 -0.667 -1.000 -1.333 -1.667 -2.000 -2.333 -2.667 -3.000 -3.333 - 3 . 667 -4.000 -4.333 -4.667 -5.000 -5.333 -5.667 -6.000 -6.333 -6.667 -7.000 -7.333 -7.667 -8.000 -8.333 -3.667 -5.000 -9.333 -0.667 -!0.000  • a  #  •  *  / s / sss SS 5 / s s SS Is s s s sss /  •  \  #  s  \s  a  s  •  -<i.667  -5.000 -5.333 • -5.667 -6.000 -6.3?2 -6.667 -7.000 -7.333 * -7.667 -8.000 -a.333 -8.667 -9.0CO -9.333 -9.667 -10.000 • -4.000  -8.COO -10.000  Figure  -2.000  -6.000  25.  Discriminant  K C G P S  : : : : :  -0.000  analysis  2.000  in 5 families  Clupeidae Cyprinidae Gadidae Pleuronectidae Scombridae  8.000  4.000  6.000  (group I)  100  13. 12. 12. 11. 11 10. 10.  13.;  2CC  7C0 200 7CC . 200 700 20C •>•. 700 s . 200 8, 700 8. 200 7, 7C0 7. 200 6. 700 6c 200 5. 700 5. 2CC <t. 700 <• . 200 3, 70C 3. 200 2. 700 2. 2C0 1 •700 1. 20C 0, 700 0 . 200 30C - 0 . BOO - 0 . 3C0 - 1 . 800 - 1 . 300 -2. 800 -2 . 300 -3, 800 - 3 . 300 -•». 800 -<i , 300 -5. BOO -5 .,?00 - O ,800 -6 ,300 -7 ,800 - 7 ,3CC -8 ,800 -6 ,300 -i ,800 -4 .300 -10 ,800 - 1 0 .300 - l i ,800 .300 -11  12. 12. 11. 11. 10. 10. 9.  S. 8. 8. 7. 7.  6. 6. 5. 5. 4. 4. 3. 3. 2. 2.  1. 1. 0. 0.  - c .  -0.  -1. -1. -2. -2. -3. -3.  -<.. -1.  -5. -5. -6. -6. -7. -7. -8. -8. -9. -5. -10. -IC. -11. -11. -12. -12. -13. -13.  -12 - ! 2 ,noo -!-> ,3CC -13 .300  -13.800  -1C.800  F i g u r e 26.  800  •7.8C0  -1.8C0  1.200  Discriminant analysis  6 7 8 9 0  : : : : :  Bothidae Engraulidae Hiodont idae O s m e r i d ae Salmonidae  7.200 *.2C0  1 2 3 4 5  i n 10 f a m i l i e s  : : : : :  Scia enidae S c o r paen i d a e Percidae Sparidae Sgualidae  10.200  13.200  (group I I )  Table 10.  D i s c r i m i n a n t a n a l y s i s i n 15 f a m i l i e s (group I and group I I combined)  90.16? OF THE CASES WERE CCRRECTLY CLASSIFIED NUMBER OF CASES CLASSIFIED INTO GROUP PREDICTED KLUPEI CYPRIN GADIDA PLEUNC SCOMBR 6B0THI 7ENGRA 8HIO0O 90SMER OSALMO 1SCIAE OBSERVED KLLPEI CYPR IN GADIDA PLEUNC SCOMBR 6ROT HI 7ENGRA 8HI0D0 90SMER OSALMO 1SCIA? 2SCORP 3PERCI 4SPARI 5SCUAL  97 C 0 C 0 0 1 0 0 0 5 C 0 C 0  0 83 0 1 0 0 0 0 0 0 0 0 0 0 0  1 0 62 0 3 0 1 0 0 7 1 0 0 0 0  0 5 0 66 0 0 0 3 4 0 0 5 4 0 0  2 0 2 0 95 0 0 0 0 1 1 0 0 0 0  0 0 0 0 0 3 0 0 0 0 0 0 0 0 0  0 0 0 0 0 0 20 0 0 0 0 c 0 0 0  c 0 c 0 0 0 0 3 0 c 0 0 0 0 0  S OF CASES CLASSIFIED INTO EACH GRCUP PRECICTEC KLUPEI CYPRIN GADICA PLEUNC SCOMBR 6B0THI 7ENGRA 8HI0D0 OBSERVED KLUPEI 97.OC 1.00 0.0 0.0 2.0C C. C CO CC CYPRIN 0.0 93.26 0.0 5.62 0.0 0.0 0.0 CO 0.0 0.0 GADIDA 89.86 2.90 0. c 0.0 0.0 0.0 94.29 PLEUNC 0.0 0.0 0.0 O.C CO c. c 1 .43 SCOMBR 0. 0 2.88 CO 95.19 0.0 CO CO CO 6B0IHI 0.0 0.0 0.0 60. CO CO 0.0 CO 0.0 7ENGRA CO 4.55 CO 4.55 0.0 0.0 50.91 0.0 0. 0 8HIODO 0.0 0.0 0. 0 50. CC 0.0 0.0 50.00 90 SH ER 0.0 0.0 • 0.0 0.0 CO 0. 0 13.33 O.C 0.0 0.0 21.21 0.0 3.03 0.0 0.0 CO OSALMO 1SCIAE 5.26 O.C 0.0 5.26 CO CO c. 0 26 .32 0.0 0.0 0.0 12.20 0.0 2SC0RP 0.0 0.0 CC 57. 14 0.0 0.0 3PFRCI CC CO 0.0 0. c 0.0 4SPARI 0.0 0.0 0.0 0.0 0.0 O.C CO CO 0.0 0.0 0.0 5SQJ AL O.C 0.0 0.0 0.0 0.0  c 1 0 0 0 c 0 c 26 0 0 0 0 0 0  0 0 5 1 0 2 0 0 0 25 0 0 0 1 0  C 0 C 0 1 c 0 c 0 0 12 0 c 0 0  90SMER OSALMO 1SCIAE  0.0  0.0 0. C 7.25 1.43 0.0 40.00 0. C 0.0  86.67  0.0  0.0  75. 76  0.0 1.12 0.0 0. 0 0.0 0.0  CO  CO CO o.o •  0.0  0.0 0.0  8.33 C. C  CO 0.0  2SC0RP  3PERCI 4SPARI  0 0 0 1 0 0 0 0 0 0 0 36 0 0 0  0 0 0 1 0 0 0 0 0 0 C 0 3 0 0  0 0 0 0 0 0 0 0 0 • 0 0 0 0 11 0  5S0UAL  •  0 0 0 C 1 C 0  100 89 69 70 104 5 22  0 0 0 0 0 0 0 13  6 30 33 19 41 7 12 13  2SC0RP  3PERCI 4S PAR I 5 SOUAL  0.0 CO 0.0  0.0 0. 0  0.0  1.43 0. 0 0.0 C. 0  0.0 0.0 0.0 1.43 0.0 0.0  0.96 0.0  0. C  0.0  0.0 0.0 0.0  0.0  63 .16 CO  0.0  CO CO 87. 30  0.0 0.0  0.0 0.0  CO  CO  0.0  0.0 0.0 0.0 0.0  CO 42.96 0 .0 0.0  TOTAL  0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0. 0 0.96 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 O.C 0. 0 O.C 0.0 0.0 0.0 O.C CO 91 .67 0.0 O.C ICO.00  102  SOC  -6.900  -12.900  -3.SCO  •9.SCO  Figure 27.  K C G P S  : : : : :  -C.9C0  ...»  5.ICO 2.100  S.100  11.100  D i s c r i m i n a n t a n a l y s i s i n 15 f a m i l i e s (group T and group i i )  Clupeidae Cyprinidae Gadidae Pleuronectidae Scombridae  6 7 8 9 0  : : : : :  Bothidae Engraulidae Hiodontidae Osmeridae Salmonidae  1 2 3 4 5  : : : : :  Sciaenidae Scorpaenidae Percidae Sparidae Sgualidae  Table 11.  Classification function families i n discriminant  CLASSIFICATION FUNCTION FOR EACH GROUP KLUPEI CYPRIN GAOIDA PLEUNC  VARIABLE M 16.811 K 11.686 LINF 0.11014E-02 LM 0.20755 TM 0.70422 Ll 0.55912 B 536.02 .CNSTANT 866.C8  -  37.310 4.4406 C.27205E-01 0.22790 2.4101 0.20869 551.32 -927.17  2C.958 6.6172 0.99545E-02 0.259C6 1.2445 0.70223 504.54 -775.77 .  12.700 7.466C 0.12221E-01 0.25642 2.3852 C. 26260 540.49 -882.62  CLASSIFICATION FUNCTION FOR EACH GROUP OSALMO 1SCIAE 2 SCORP  VARIABLE M 44.534 K 5.5853 LINF 0.15026E-01 LM 0.27710 TM 1.2849 Ll C.564C5 B 506.57 »ONSTANT  - 791.92  16.699 11.084 9.6869 4.2365 0.11456E-01 -0.23150E-C3 C.27C36 0.16440 0.12965 3.5925 0.82627 C.2C306 525.30 53 7.4 5 -637.70  -876.07  SCOMBR  -813.60  6B0THI  29.167 16.620 8.5276 8.1035 0.3C012E-01 -0.7589 1F-02 0.4C226 0.28995 0.65046 1.1265 1.8851 0.67281 505.42 519.59 -839  3PFRCI  16.566 5.4356 0.20C32F-01 C. 11062 2.2735 0.43634 519.CO  with 7 variables analysis  .40 4SPARI  -818.06  f o r 15  7ENGRA  8HIO0O  11.062 23.666 48.885 6.4889 0.33069E -01 - 0. 55370E-C2 0.19807 0.27299 0.4C951 2.0388 0.39242 0.41766 519.71 519.60 -349.56  -819.55  90SMER 22.088 11.104 0.13379E-01 0.17933 1.1929 0.15457 56 1.92 •548.  5SCUAL  24.791 25.028 2.6624 2.2282 0.38354!!-01 -0. 24 25Cli 0.7 1506F-01 0.38277 2.2535 8.8680 0.46032 1.5457 446.74 520.32 -610  .06  -934.43  O co  Table 12.  Summary families  table  of  discriminant  analysis  for  15  EIGENVALUES 10.93254  4.61658  1.77785  CUMULATIVE PROPORTION OF TOTAL DISPERSION 0.53340 0.75e64 0.84538  1.66485  1.21548  0.18683  0.10185  C.92661  0.98592  0.99503  1.00000  0.79041  0.74070  0.39676  0.30403  CANONICAL CORRELATIONS 0.55718  0.90662  C.800C1  COEFFICIENTS FOR CANONICAL VARIABLE STANDARDIZED VARIABLE •0.22035 0.67732 M -0.15938 0.33379 K -0.24347E-01 0.86798 LINF -0.84822E-C1 C.52660E 01 - 0.136C0 •0.16636 0.29306 LM -0.43159 -1.8741 0.56'+19 TM C.4344C -0.41136 0.46582 Ll -2.6811 •0.60580E-01 -1.62C4 B 0.62483 CONSTANT  66.854  14.264  31. 554  -C.86523 1.2811 -0.14040 , 0. 10140 0.86 129 0.73039 0.75413 -12.712  -1.0685 -0.21184 -0.94059 0. 2475C -0.30161 0.64078 0. 15624!-01 1.1389 -0.55722 -0.47681 -1.3784 0.51212 -0.54456E-01 0.34618 13.909  GROUP CANONICAL VARIABLES EVALU4T ED AT GROUP M<=ANS KLUPEI 1.CC71 1.7959 -0.189C9 0.24561 0.77437 CYPRIN 2.7153 -1.2023 -1.7239 -C.76C55 -1 .1287 GADIJA -0.76258 0.23073 1.3697 -C.53035 0.36086 PLEUNC 2.4642 -C.78368 0.223eo 0.66685 0.96300 SC0M3R -6.5213 -C.60642E-01 -0.76132 0. 18788 0.18429 6B0THI -C.22874E-01 C.68154 0.74728 -C. 1A-880 0.88781 7ENGKA 0.77563 5.4761 1.£239 3.7654 -3.2186 8HIODO 1.2355 -C.44997 0.85978 -0.56214 -0. 1 2325 90S ME R 3.41 62 1.2700 -1.6668 C. 393? 8 0.24279 OSALMO -0.30077 0.833595-01 0.2C453 -2.3853 -2.C293 ISC IA E -C.66736 1.9537 -0.7E917E -01 -0.20364 1 .2204 2SC0RP 3.4244 -2.0745 1.C268 0.72173 1.0139 3PERC I 1.6371 -C.33334 1.3727 -0.49515 0.65750 4 S AR I -0.39766 -C.499 1 2 5.5098 -3.4647 -0.8 703 3 5S0UAL -2.4350 -10.130 1.4804 3.7218 -1.5787 0  0.16588 -0.17855 -1.4764 1.3506 -0.27383 -0.85485E -0.63832E  -60.155  63. 476  -0. 58817 0.12142 C.43853 0.75983 0. 50755E-01 -0. 14207E-01 C.3011 9 C.30979E-C1 -0. 28903 -0. 13422 -0. 44330E-02 -0. 28201 -C. 7195 7 -0. 51134 -0. 76065  0.17730 -0.19832 0.33232 -0.35517E -01 -0.18380 0 .68485 -0.15014 0.7 1820 -0 .13423 0.56171 0.80640E -01 -0.22519 -0.34442  -1 . 1490 0.5t249  105  each of the The  f a m i l i e s w h i c h make up  analyses  Gadidae  Scombridae 23.08?  27.  were a l s o c o n d u c t e d among s p e c i e s w i t h i n 5  major f a m i l i e s [ C l u p e i d a e (n=89) ,  Figure  {sample  (n=69),  (n=104)].  (Scombridae  n=100) ,  Pleuronectidae  Correct 28  size  (n=70) ,  and  ranged  from  classification  species,)  Cyprinidae  t o 76.40% ( C y p r i n i d a e , 5  species) .  Classifying Families Cooley above  and  method  ( C c o l e y and  Lohnes n o r m a l i z e to  the c a n o n i c a l r o o t s of  the  u n i t m a g n i t u d e . T h i s method p r o v i d e d  more  successful classifications. cases  were  Table  correctly classified  93.62% of t h e c a s e s Further,  L o h n e s ' Method},  Table  13  shows  96.761?  i n group I . Table  were c o r r e c t l y c l a s s i f i e d  15 shows 9 0 . 1 6 % o f t h e c a s e s  in  Table  i n Appendix species Gadidae,  3.  within  group  shows II.  group I I .  A  o f t h e c a l c u l a t i o n f o r 15 f a m i l i e s i s l i s t e d The 5  analyses major  ranged  were  families  Pleuronectidae,  classification  14  the  were c o r r e c t e d  c l a s s i f i e d f o r t h e c o m b i n e d d a t a o f g r o u p I and summary  of  conducted  among  (Clupeidae, Cyprinidae,  and  f r o m 58.6%  also  Scombridae).  Correct  (Pleuronectidae) to  87.6%  (Cyprinidae) .  Besults for classifying  f a m i l i e s are  summarized  in  Table  j Table  106 13.  Cooley and Lo families (group  lines'  classification  method  i n  5  1)  9 6 . 7 6 * OF THF CAS^S WERF C 0 P R C T L Y CLASSIFIED NUMBER OF C A S E S C L A S S I F I E D INTO GROUP PREOICTED c  KLUPEI  CYPRIN  GAOIGrA  95 1 C 0 0  1 87 0 0 0  0 0 66 1 3  OBSERVFD KLUPEI CYPRIN GAOIQ4 PLEURO SCCMBR  PLEURO SCOMRR 3J. 0 69 0  TOTAL 100 89 69 70 104  1 0 3 0 101  :  OF C A S E S C L A S S I F I E D INTO E A C H GR?UP PREC IC TED K L U P E I C Y P R I N GADI'DA PLFIJQQ S C 0 « 3 R IBSGRVHD KLUPEI 95.OC 1 .00 0.0 3.00 1.00 CYPRIN 1.12 97.75 0.0 0.0 1.12 0.0 GACIDA 0.0 95.65 0.0 4.35 PLEURO 0.0 0.0 9 8 . 57 1 .43 0.0 SCOMBR O.C 0. 0 2.83 0.0 9 7 . 12  T a b l e 14.  Cooley and Lohnes' f a m i l i es (group I I )  c l a ss i f i c a t i o n  9 3 . 6 2 ? OF THE CA,ScS WERff C 3 R R E C T L Y C L A S S I F I E D NUMBER OF C A S E S C L A S S I F I E D INTO GROUP PREDICTED 6 E 0 T H I 7ENGRA 8HI0DC 9CSMER OSALMO 1SCIA E 2SC0RP OBSERVED 6B0THI 7ENGRA 8HIO0O 90SMER 0S/1LH0 1SCIAE 2SC0PP 3P&RCI 4S PAR I 5SQUAL  3  .  0 0 C  c  0 0  c  0 0  0 21 0 0 0 0 0 0 0 0  1 0 4 0 0 0 0 0 0 0  0  1 1  0 0 30 0 0  0 0 33 2 1  0 0 0 ,  1 2 1 0  0 0 1 0 0 17 0 0 0 0  C 0 0 C 0  c  39 0 0 0  3PFRCI 0 0 1 0 0 0 0 5 0 0  method  i n  4 SP AR I  5S0UAL  0 C 0 0 0 .0 0 0 11 0  0 0 0 0 0 0 0 0 0 13  % Of- C A S E S C L A S S I F I E D INTO EACH GROUP PRECICTEC 6 BOTH I 7ENGRA 8 H I 0 D 0 9'0SMFR OSAIMC 1 S C I A E 2SC0RP 3PE.RCI 4 S P A R I 5S0UAL OBSERVED 690TH1 60.00 0.0 20.00 0.0 20.00 O.C CO CC CC 0.0 7EN6RA 0. 0 95.45 CO 0.0 4.55 0.0 CO CO 0.0 0.0 0.0 8HIGD0 0.0 66.67 0.0 0.0 16.67 CO 16.67 0.0 CO 9CSKER CO 0.0 0.0 ICO.00 CO 0.0 CO O.C 0.0 CC 0.0 OSALHO CO CO 0.0 100.00 C O CO CO 0.0 0.0 1SCIAE O.C CO 0.0 0.0 10.53 89.47 CO O.C CO CO CO 2SC0RP CC 0.0 2.44 2.44 0.0 95.12 CO CO 0.0 0.0 0.0 0.0 C O 2 8 . 57 C C CO 3PERCI 71.43 CO 0.0 0.0 4 S PARI CO 91.67 0.0 0.0 0.0 8.33 0.0 0.0 CO CC 5S0UAL 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.00  TO  TOTAL 5 22 6 30 33 19 41 7 12 13  T a b l e 15.  Cooley and L o h n e s classification method i n 15 families (group I I and group I I ) and C o o l e y a n d L o h n e s ' c l a s s i f i c a t i o n method 1  9 0 . 4 8 V 0 F T H E C A S E S WERE C O R R E C T L Y CLASSIFIED NUMBER O F C A S E S C L A S S I F I E D I N T O GROUP PREDICTED KLUPEI CYPRIN GADICA P L E U N C SCOMBR 6 B 0 T H I 7 E N G R A OBSERVED KLLPFI CYPRIN G40IDA PLEUNC SCCMBR 6R0THI 7ENGRA 8HIODO 90SMER OSALMO ISCI«E 2SC0RP  55 0 C 2  0  c 4  0  c  0 3 2  0 0 0  3 P EKCI 4 SPAR I 5S0UAL *  OF  0  CASES  1  CLASSIFIED  1 0 57 0 0 0 0 0 0 0 0 0 0 0  1  6 0 0 0 0 2 0 0 0 0 0 INTO  i  0  0 60  85 0 0 0 C 0 0 0 0 C 0 0 0 0  EACH  0 0 0 95 0 C 0 0 0 0 0 0 0 1  0 0 3 0 0 5 0 0  18 0  0 2 0 0 0 0 0  1 0 0 0 0 0 0  8HICDO 0  1 0 0 0 0 0  1 0 1 0 0 0 6 0 0 0 0 0 0 0  90SMER  OSALMO  0 2 0 2 0 0 0 0 28 0 0 0 0 0 0  2 0 4 0 0 0 0 0 0 26 0 0 0 0 0  90SMER  OSALMO  ISCIAF 0 0 2 0 2 0 0 C 0 0 16 0 C 0 0  2SCORP  3PERCI  4 S PAR I  0  0 0 0 6 0 0 0 0 1 0 0 39 0 0 0  5SOUAL  0 0  0 0 0 0 0 0 0 0 2 0 0 7 0 0  0 0 0 0 0 0 0 0  0 1 1 0 0 0 0 1 0 0 0 12 0  0 0 C 0 0 0 12  4S PARI  5S0UAL  TOTAL 100 89 69 70 104 5 22 6 30 33 19 41 7 12 13  GRCUP  PREC ICTFD SC0M3R OBSERVED KLUPEI CYPKIN G4CICA PLEUNC SCOMBR 6B0THI 7ENGRA 8HI0D0 9GSMER OS A L MQ ISCIAE 2SCJRP 3°ERCI 4 S PAR I 5SQJAL  95.00 0.0 0.0 2.86 0.0 0.0 18.18 0.0 0.0 O.C 15.79 4.68 0.0 0.0 C C  0.0 95.51 0.0 0.0 0.0  C O 0.0 0.0 0.0 0.0 C O  1.00 0.0 86.96 1.43 5.77 0.0 C O C O 0.0 6. 0 6 0.0 0.0 0.0 0.0 0.0  C O 1.12 0.0 81.43  l.CC C O 0.0 C O 91.35  6B0THI  7ENGRA  8HI0D0  0. 0  l.OC C O C O C O  C. C 1.12 0.0 1.43 0 0 0 0 0 0  0.0 4.35 0.0 0. 0 1 0 0 . 00 0. 0 0. 0. 0  c  6. C6  0.0  0.0  C O  C O  0.0 0.0  0.0 0.0  0. 0 0. 0 0. 0 C O  C O  7.69  O.C  0.0 C O 81.32 C O 2.33  0.0  00 C C 0.0 C. 0 CO 0.0 O.C 0.0  100  0.0 2.25 0.0 2.86 0.0 0.0 0.0 0.0 53.33 0 .0 C O 0.0 0.0 0.0 0.0  2.00 0. C 5.80 O.C 0 0 0 0 C C 0 0 0 70 79 0 0 O.C 0.0 0.0 0.0  c  1SCIAE C O 0. 0 2.90 0.0 1 .92 C O 0.0  0. 0 0. 0 0. 0 84. 21  0. C 0. 0 0. 0 0. 0  2SCORP C O C O 0.0 8. 5 7 C O 0.0 0. 0 0.0 3. 3 3 0.0 0.0 9 5 . 12 0.0 C O 0. 0  3PCRCI  0.0 C O 0.0 0.0 0.0 0.0 0.0 0.0 C O 6.06 0.0 0.0 100.00 0.0 C O  0.0 0. 0 0.0 1.43 0.56 0.0 0. 0 0.0 0.0 3.03 0. 0 0. 0 0. 0 ICO. 00 0. C  0.0 C O 0.0 0.0 0.0 0.0 C O 0.0 0.0 C O 0.0 0. 0 0.0 0.0 92.31  o  108  T a b l e 16 Summary t a b l e o f t h e r e s u l t s from t h e d i s c r i m i n a n t a n a l y s i s and C o o l e y and L o h n e s * c l a s s i f i c a t i o n method (The % o f c a s e s were c o r r e c t l y c l a s s i f i e d )  Cases  Discriminan t Method  C c c l e y and L o h n e s ' Classification  G r o u p I (5 f a m i l i e s )  432  93.2 9%  96.76%  Group I I (10 f a m i l i e s )  188  90.96%  9 3.62%  Group I and I I (15 f a m i l i e s )  620  90.4  90. 16%  Data  1  +  _  Clupeidae (1*3 s p e c i e s )  100  73.0 0f  6  80.00%  Cyprinidae (5 s p e c i e s )  89  76.4 0%  87.64%  Ga d i d a e (16 s p e c i e s )  69  44.93%  68. 12%  Pleuronectidae (22 s p e c i e s )  70  24.2 9%  58.57%  +  + Sccmbridae (28 s p e c i e s )  104  23.08%  68.27%  j Group I : C l u p e i d a e , C y p r i n i d a e , G a d i d a e , P l e u r c n e c t i d a e , Sccrabridae. Group I I : B o t h i d a e , E n q r a u l i d a e , H i o d o n t i d a e , Osmeridae, S a l m o n i d a e , S c i a e n i d a e , S c o r p a e n i d a e , P e r c i d a e , S p a r i d a e , and S g u a l i d a e .  109  16.  5._ C l o s e n e s s among F a m i l i e s ( C l u s t e r Analy.sisX Dendrograph  relationships  among  15  families  have  been  examined using c l u s t e r a n a l y s i s . T h i s method c l u s t e r s cases t h a t have the l e a s t d i s t a n c e between together  are  amalgamated  and  turn c l u s t e r e d with o t h e r s . The values  of  Hiodontidae, sizes,  all  Scorpaenidae Sciaenidae  7  them.  The  two  cases  closest  t r e a t e d as one case and then, i n a n a l y s e s were based  on  average  v a r i a b l e s i n 15 f a m i l i e s . In Table 17, except f o r Bothidae, other  fishes  relates with  Percidae,  with Scombridae. The  result  have  show t h e i r b i o l o g i c a l  closely  Gadidae;  which  with  Clupeidae shows  smaller  relationships.  Pleuronectidae; with Osmeridae; the  sample  ecological  between f a m i l i e s r a t h e r than the systemic r e l a t e d n e s s .  similarly Sgualidae affinities  110  Table 17.  Dendroqraphic r e l a t i o n s h i p s among 15 f a m i l i e s  C N 0  A  •  S L  A B E L  AMALf>. DISTANCE  2 4  3  fi  s  C c P & H P S L S c L 0 I E c I U M 0 £ T 0 P E R U H D C A E R P R I 0 I E I I A 0 D N P N D D N N A T A I E I E D A A I  G A D I D A E  e  *  0.701 1.125 1.138 1 .1 50 1.133 1 .419 1.8 61 1.7 30 1.923 2.460 2.761 ft .064 4. 300 4 .6 50  i i. 3 1 3  1  1  I  *  *  I  I  *  *  I  - +-  I  I  I I I -+- 1 1 I - -  +  *  7 5 5  sS c E  s  A D I  I  p A A M R 0 I N 0 I  S Y N Q c P G U 0 R I? A M I A L B N U I R L D  E 0 D I A D  *  *  *  *  *  #  *  T T T TI I T \ T T I I I T -+- T T T T I T I I y T I I T I J T I I I I I T T T T T I T I TIT I T T T TT I I I I T I I ! I JI -- I I T  T  T  T  -  T  —  T  _  +  — -  #  T  T T  T I -+-  I  *  i  i 0  +  T  -  - +  f  .'- +  + -  -  T  +  +  -  111  I I I GENERAL DISCOSSION  Comments on Comparative Ihile relation (e.g.  gross to  Studies  comparisons,  systematic  clupeoids  such as t o t a l stock s i z e i n  classification,  seem  to  have  larger  p e r c i f o r m s ) , " d i s s e c t i o n " o f the more  same way  t h a t i n t e r n a l anatomy i s  to  is  in  comparing  population  more  useful  than  likely  than  to  recruitment  for  size,  rates.  mortality,  it  Thus,  s t u d i e s are only a t o o l .  gross  i n d i v i d u a l organisms. However, to maturity  and  w i l l be n e c e s s a r y t o make  comparisons between these parameters and s p e c i f i c and  useful  u s e f u l r e s u l t s and be l e s s m i s l e a d i n g , i n the  e v e n t u a l l y r e l a t e parameters growth  be  populations  population  produce  morphology  might  comparative f i s h  fecundity population  Methods of a n a l y s i s p r o v i d e us with  a more p r a c t i c a l common b a s i s . The p o p u l a t i o n correlative  parameters,  characters  were  relative  chosen  characters,  mainly because  and  either  they were v a r i a b l e s i n t h e Beverton-Holt y i e l d model or they were of b i o l o g i c a l s i g n i f i c a n c e and were r e a d i l y This  does not mean that I am f u l l y convinced by the r e a l i t y  of parameters used i n the useful  for  comparative  models  have  studies  can  but  purposes.  study i s to re-examine these they  available.  been  used  for  be  used  to  the  One  population such display  a  parameters  are  of my aims i n t h i s parameters,  since  long time. Comparative the  variabilities  of  112  population  parameters  t h e i r usage i n y i e l d direction  and  a l s o t o d e t e c t the r e a l i t i e s o f  models i n order t o determine  improvement  should be pursued  randomly d i r e c t e d t r i e s .  summaries  of  which  so as t o e l i m i n a t e  In other words, I  the r e s u l t s o f these comparative  in  only  feel  that  s t u d i e s provide d e s c r i p t i v e  data r a t h e r than laws of nature, although the  r e s u l t s might i n d i c a t e o f the l a t t e r . There a r e , however, t h r e e q u a l i f i c a t i o n s which must made.  One a r i s e s out of the dependence upon published  A c o n s i d e r a b l e element o f p e r s o n a l judgement and  interpretation  e s p e c i a l l y as original  of  the  true  context  was  maturity d e t e r m i n a t i o n size),  the  body l e n g t h s  original  meaning not  parameters  qualification  in  their  f o r example,  maturity  or  critical  ( t o t a l l e n g t h , f o r k l e n g t h , o r standard  length) and the problem f o r e s t i m a t i o n second  i n evaluation  defined;  ( s i z e at f i r s t  data.  papers was necessary,  of  fully  be  i s that  examples has been unavoidable  of  parameters.  The  some degree of s e l e c t i o n o f  although I have kept t h i s to a  minimum. For example, most o f t h e r e f e r e n c e s  used  studies  i n English,i n  are  mainly  based  on  the  papers  in  this  Chinese, and i n Japanese. S i n c e one o f the p r a c t i c a l o b j e c t s i s t o make p r e d i c t i o n s , based on many a r e a s , to f i s h in  other  areas f o r which data a r e l a c k i n g , r e f e r e n c e s from  a l l over the world taken  into  (i.e. in  consideration.  languages l i s t e d agriculture  stocks  in  the  Organization  other  languages)  Therefore,  publications  have  t c be  r e f e r e n c e s i n ether from  the  of the United Nations  Food  and  (e.g. c i t e d  113  in t h e f i s h e r i e s scholars of  synopsis)  were c o n s i d e r e d .  a v a i l a b l e data which  biology  studies.  economically  or  important,  by  the  well-known  The t h i r d i s a r e s u l t o f the fcias  are  These  cited  taken  data  mainly  tend  to  large fishes  from  be  than  fisheries  based on  more on  the  smaller  r e p r e s e n t a t i v e s o f t h e f a m i l y . Therefore, the c a l c u l a t i o n o f mean  value  f o r each  f a m i l y i s l a r g e r than the mean value  would be. For example, the asymptotic  length  in  calculated  Cyprinidae  mean  value  (estimated  difficulties  c r e a t e d by t h e personal  data s e l e c t i o n , and  biased  hamper attempts t o formulate a  samples  ocly 7  from  species) i s much t o o l a r g e f o r most o f the s t t a l l These  of t h e  cyprinids.  interpretation,  should  not, however,  hypotheses which may u n i t e i n t o  s i n g l e e n t i t y the c o n s i d e r a b l e volume of accumulated  pertaining to f i s h  populations.  Organizing t h e data r e q u i r e d t o t e s t massive  project  data  -  and  i t i s only  hypotheses  the  is a  great amount o f  a v a i l a b l e data p e c u l i a r t o  fisheries  possible  of comparative methods. T h i s , i n  the  utilization  i t s e l f , i s an i n d i c a t i o n o f t h e reguired population specimens  to  compile  parameter by  biology  large  amount  which  of  research  and  analyze the banks o f data.  was  estimated  different  authors,  from  and  Bakes  Every  thousands  about  of  one thousand  d i f f e r e n t papers were u t i l i z e d . T h e r e f o r e , t h i s r e s e a r c h based  on  information  from  millions  of  specimens  is  which  comprise many f i s h s t o c k s i n v a r i o u s areas o f the world.  114  li  2i££JissioB of the J e s u i t s  1. P o p u l a t i o n  parameters:  A major concern to  determine,  of p o p u l a t i o n  by  experiment  parameters  of  populations  mortality,  so  as  populations  to  to  be  and  dealing able  increase  c o n s i d e r i n g biomass and Therefore,  dynamics has  those  natality  assess  numerically  yield,  been  observation, with  to  always  and  the c a p a c i t y of  with  time.  growth i s brought i n t o  By  focus.  the p o p u l a t i o n parameters are d i v i d e d i n t o  three  groups f o r d i s c u s s i o n :  §1 M o r t a l i t y  M:  Present  estimations  coefficient properly  are  the  imprecise  natural to be  evalulating  this  important  dynamics.  Host  authors  population range o f  too  of  sampling  error  as  to  mortality  satisfactory in component  give  make  of  such a wide  their  results  u s e l e s s . A l s o , r e s u l t s are f r e g u e n t l y i n c o n s i s t e n t with information  from o t h e r sources or s i m i l a r  An a l t e r n a t i v e method, using an (e.g. T95) be  or a function  found to estimate  populations.  Especially  alternative  (by adding  adeguately in  populations. parameter  o t h e r f a c t o r s ) must  the death r a t e of  short-lived  species,  fish a  115  constant  mortality  rate  i s not a p a r t i c u l a r l y  useful  measure where m o r t a l i t y i s h i g h l y a g e - s p e c i f i c . only  satisfactory  in  species  It is  with l o n g e r l i f e  spans  which have a n e a r l y l i n e a r s u r v i v a l curve.  T95: T95, as an index o f ' l i f e (1959)  i s the  age  at  span*,  suggested  by  Taylor  which f i s h reach 95% of t h e i r  asymptotic l e n g t h . The reason f o r using t h i s i n s t e a d o f the r e a l l i f e span i s because the maximum age i s h i g h l y dependent on the sample s i z e Different  sample  sizes  tend  maximum ages. TS5 ( c a l c u l a t e d  to  from K  t h e o r e t i c a l age, f o r comparative life  span  i s determined  for  Sgualidae  has  and  different  LINF)  is a  T95  (2.4  years)  t h e l o n g e s t T95 (57.8 y e a r s ) . But,  24  (e.g.  unrealistic)  so we must a l s o take f e c u n d i t y i n f o r m a t i o n order  -  to  which  T95 i s  to  "life  years  Salmonidae,  calculated  into consideration i n  bl  provide  1963).  by m o r t a l i t y , not the r a t e of  c e r t a i n kinds of f i s h e s be  (Beverton  purposes, although the  growth. Engraulidae has t h e s h o r t e s t and  recorded  better  i s obviously  estimate  the  span*.  growth The  reason f o r choosing growth parameters  B e r t a l a n f f y growth eguation i n s t e a d eguations  [although  some  of  from  from the von other  growth  s h o r t - l i v e d f i s h e s show a growth  pattern as d e s c r i b e d by Parker and Larkin  (1959) '], i s mainly  116  because i t i s most widely used especially for  for  comparative  in fish  population  purposes.  studies,  This situation  calls  the need to develop a more g e n e r a l i z e d e q u a t i o n , using a  more widely a p p l i c a b l e form of the growth curve. Length  i s used as the measure of body s i z e r a t h e r  weight  because  simple  curve  contents  growth  in  without  and  an  gonad  length  v a r i a t i o n i n the e s t i m a t i o n o f  K:  The  growth  character.  parameter The  n e a r l y always f o l l o w s a  inflection.  maturation  Besides,  contribute  greater  relatively  stable  weight.  K  is  a  higher the K value, the sooner the implies  (1.6) ,  followed  has  by  an  extremely  high  (0.347).  It  Salmonidae  seems  that  (0.3 29)  that  (below  Sciaenidae  fishes  0.3).  have  largest  length i s a size  families,  Scombridae  (0.345)  and  that  a  lower  K  In p a r t i c u l a r , the c a r t i l a g i n o u s (0.07).  theoretical  fish  value  showing  a f i s h can a t t a i n . T h i s has a  r e l a t i v e l y l a r g e r v a r i a t i o n but i s within  (both are  relatively  Sgualidae have the lowest K v a l u e  The asymptotic  value  are s i m i l a r t o l a r g e p e l a g i c f i s h .  Host of the demersal values  K  Clupeidae and Osmeridae  over 0.4), and then, the l a r g e p e l a g i c f i s h :  the  fish  f i s h has a s h o r t l i f e - s p a n , among s h o a l i n g p e l a g i c  f i s h e s , Engraulidae  LINF:  stcBach  to  reach t h e i r asymptotic l e n g t h . T h i s a l s o the  than  with  a  still longer  very LINF  stable (e.g.  117  Scombridae) has a f a s t e r has  a  growth r a t e o n l y  l a r g e r K v a l u e . Sgualidae has a very l a r g e IINF  but a very low K v a l u e . Engraulidae high  i f i t also  has  an  K value but the lowest LINF, so t h a t they are not  the f a s t growing f i s h e s . The growth r a t e on  both  K  and  LINF,  as  shown  by  mathematical e x p r e s s i o n , a f t e r G u l l a n d dl — = K (LINF - 1) dt  The  extremely  is  dependent  the  following  (1969),  where 1 i s the l e n g t h o f f i s h  l e n g t h o f a f i s h a t age 1 i s used t o i l l u s t r a t e t h e  speed a t which f i s h can grow Part  of  the  during  reason f o r choosing  the  first  year.  t h i s character i s to  i n d i c a t e p a r t i a l l y the f i s h a b l e s i z e of f i s h . L1 fairly  stable  character.  My  rationalization for i t s  v a r i a t i o n i s t h a t f i s h e s spawn a t the  exponential  coefficient  r e l a t i o n s h i p i s the there  are  the  most  least  proportional  to  of  stable  data f o r i t .  growth eguation assumes t h a t the  surface  area  weight, but i n not  hold.  or  weight  practice This  to  the  times  of  of  weight-length  parameter,  although  The von B e r t a l a n f f y  catabolic  a n a b o l i c processes are assumed t o  does  different  year.  The  the  is a  the be  processes fish,  are  whereas  proportional  to  the two t h i r d s power o f the  this  relatonship  freguently  can be shown by the f a c t t h a t b  118  values f l u c t u a t e around the  weight  3. Marr  (1960)  indicated  of f i s h at a g i v e n l e n g t h v a r i e s  that  inversely  with stock s i z e . I f t h i s i s a r e s u l t of c o m p e t i t i o n f o r food i t can be proved by i n d u c t i o n of  changes  weight-length  the  relation  by  altering  in  diet  the i n an  experiment.  In  other s t u d i e s o f f i s h  (1940) found a c o r r e l a t i o n season  growth,  Eddy  and  Carlander  between the l e n g t h of the growing  and the growth r a t e f o r a number of s p e c i e s . Gerking  (1966) i n v e s t i g a t e d p o p u l a t i o n s of b l u e g i l l s u n f i s h i n eight Indiana l a k e s and found season  that  the  length  of  the  growing  v a r i e d between the d i f f e r e n t l a k e s and that the most  r a p i d l y growing f i s h  occurred i n the l a k e s w i t h  the  longer  growing seasons. I n v e s t i g a t i o n s have a l s o shown t h a t both o f the  von B e r t a l a n f f y c o e f f i c i e n t s , K and LINF, are i n f l u e n c e d  by temperature. For example, cod growth parameters have been determined  throughout  their  c o r r e l a t e d with s u r f a c e water Holt  (1959b)  then  logarithmically decrease  slowly  that  temperature,  with  K  He  kept  varied  with  to  that  temperature. Kinne  and  (1558). increase  LINF  should  (1960) d i d a more  temperature  on  fish  f i s h a t d i f f e r e n t temperatures i n a g u a r i a  and h i s r e s u l t s show how fish  ought  and  d i r e c t i n v e s t i g a t i o n o f the e f f e c t of growth.  range,  temperature by T a y l o r  suggested  with  geographical  the length  temperature.  The  at  age  of  individual  growth parameters  l i n e a r l y r e l a t e d to temperature, but only w i t h i n  a  are  certain  119  range, when p l o t t e d on a s e m i - l o g a r i t h m i c b a s i s . all  these  findings  highly c o r r e l a t e d with  with  suggest  that  environmental  growth  of f i s h i s  factors,  especially  water temperature. Eddy and Carlander  (1940)  that h e r e d i t y could account f o r d i f f e r e n c e s i n between  growth  rate  s p e c i e s and races but t h a t w i t h i n s p e c i e s i t i s the  environment t h a t i s important Therefore, the  suggested  one  of my f u r t u r e approaches w i l l be t o  correlation  temperature  between  in  add another  i n determing the growth  growth  parameters  rate. analyse  and  water  d i f f e r e n t f i s h e s . In so doing, I hope I can  v a r i a b l e , the water temperature, i n t o the growth  eguation.  £l maturity.  K  f e c u n d i t y , and  recruitment  In a study o f the n a t u r a l r e g u l a t i o n of animal Lack  (1946)  determined  concluded by  that  the  reproductive  rate  offspring  per  female  that  survive u n t i l  f i s h e s , the same r e s u l t i s g e n e r a l l y achieved fecundity. Information biggest  problems  r e g a r d i n g recruitment  i n f i s h e r i e s b i o l o g y . The  stock and  r e c r u i t m e n t s t a r t e d with  followed  by  Bicker  (1964), Cushing Larkin  (1973).  variable,  and  was  n a t u r a l s e l e c t i o n ; i n p a r t i c u l a r , the c l u t c h  s i z e that i s s e l e c t e d i s the one which maximizes the of  numbers.  Bicker's  m a t u r i t y . In  with very i s one  However, s i n c e i t may  because  high  of  formal study (1954)  (1958), L a r k i n , B a l e i g h , and  (1971, 1973), Cushing and  number  the of  paper,  Wilimcvsky  H a r r i s (1973), and  recruitment  is  highly  take a c o n s i d e r a b l e time to show  120  that the downward t r e n d i s a r e s u l t of o v e r f i s h i n g , be  too  Cushing that  late  for  decisive  (1977) suggested  management  recruitment To  estimate  failure,  best  be taken. Even so, it  may  appear  on the growth model were  whereas  those  based  y i e l d s from multi-aged  desirable  relationships progress has  to  with  cn  a  a  combine  stocks i t i s  stock-recruitment  yield-per-recruit  analysis.  been made i n t h i s d i r e c t i o n . Beverton  Some  and  Holt  proposed a " s e l f - r e g e n e r a t i n g " model t h a t combines a  recruitment curve Halters  (1969)  growth,  and  with  any  he  pattern, rate.  used very much  analysis.  an a n a l y t i c a l combination  developed  curve  and  any  a  fish  model  type  the corresponding  (1967,1969) developed  with an analog  mortality  yield-per-recruit  recruitment  also  programs. S i l l i m a n  growth  their  formulated  that can handle  model  based  may  model were l e s s accurate but more h e l p f u l .  obviously  (1957)  to  t h a t i n the f u t u r e  decisions  p r e c i s e but prone to  action  it  of  computer  population  computer program which c o n s i s t s of the  stock-recruitment  relationship,  and  None o f these p r o p o s a l s , however, has been with  actual  stocks.  Thus,  there  are  no  a v a i l a b l e p o p u l a t i o n parameters f o r recruitment which can universally  applied., Larkin  recruitment  information  comparative  fish  should  population  parameters o f recruitment  (pers. comm.) be  studies.  suggests  considered Not  highly v a r i a b l e ,  s i z e s f o r these parameters are very l i m i t e d .  only but  be  more  in  the  are  the  the  Although  sample I have  c o l l e c t e d some f e c u n d i t y data, u s e f u l a n a l y s i s of these  data  121  is  complicated  by the v a r i a t i o n between f i s h e s i n spawning  freguency. T h e r e f o r e , I  could  parameters  the s i z e a t f i r s t maturity  other  the age at f i r s t  LM:  than  not  maturity s i z e  find  (TM)  any  reproduction  f o r comparative  The s i z e at f i r s t maturity i s a very s t a b l e Its  (LM)  and  studies.  parameter.  v a r i a t i o n i s p a r t l y due to the i n a c c u r a c y of quoted  maturity  sizes  of the f i s h attained factor  ( e i t h e r the c r i t i c a l s i z e at which  have reached  when  first  maturity or  spawning  the  mean  50%  length  b e g i n s ) . Maturity i s a  l i k e l y t o i n f l u e n c e f i s h growth, because,  after  the onset o f maturity, energy that might have been used for  growth w i l l  some  be r e q u i r e d f o r gonad maturation  cases, f o r making spawning m i g r a t i o n s . Growth can  be expected maturity  t o be  than  more  it  reduced  otherwise  after  an  unknown  quantity.  freguency  is  also  method might be to compare values b e f o r e and different of  K  onset  of  in  reproduction  Not only i s i t d i f f i c u l t to  estimate the f e c u n d i t y of f i s h , but spawning  the  would have been. However,  the amount of energy the f i s h expends is  and i n  the  information  reguired.  An  difference  a f t e r the s i z e at f i r s t  alterative of  the  maturity.  values w i l l i n d i c a t e d i f f e r e n t  f i s h e s i n u t i l i s i n g t h e i r energy f o r  about  K The  strategies  growth  and/or  reproduction.  TM:  The  age  at f i r s t  maturity has more v a r i a t i o n than  LM.  122  T h i s may  be a t t r i b u t e d t o fewer samples. A few  determined without  TM by d e t e c t i n g *spawning checks' on s c a l e s  even knowing the s i z e at f i r s t  maturity.  In c o n c l u s i o n , the most complete i n f o r m a t i o n for  growth.  Improvement  of  factors  such  environmental  c o n s i d e r a t i o n . The  the  of  as  only s t a b l e and  n a t a l i t y i s the s i z e at f i r s t development  techniques  would  short-lived The  similarly  water  temperature  suggested mean and  the  2.  as  to b e t t e r estimate  affected,  of any  The  estimation  cf  p a r t i c u l a r l y f o r the  limit  out  by  Holt  wider  (1959a),  p a r t i c u l a r parameter estimate  each  than  can are the  because the  i s rather  lew.  (ratios):  M/K  r a t i o , a most important  has  been s t r o n g l y recommended by H o l t  c h a r a c t e r and (196 2),  because of i t s e v o l u t i o n a r y meaning but necessary  for  other f i s h s t o c k s where data  The  is  the  the f e c u n d i t y of  i t s 95% confidence  for  pointed  Belative characters  M/K  into  f a m i l i e s are l i s t e d i n T a b l e 3. T h i s  information  ranges,  accuracy  the  have t o emphasize  l a c k i n g . These v a r i a t i o n s are always c e r t a i n l y true  take  species.  parameter f o r d i f f e r e n t provide  available  r e l i a b l e parameter r e l a t e d t o  maturity. He  be  is  growth model should  f i s h , e s p e c i a l l y with r e s p e c t to r e c r u i t m e n t . mortality  authors  one  which  not  only  a l s o because i t  f o r the s i m p l i f i c a t i o n of c a l c u l a t i o n i n  123  the y i e l d This  e q u a t i o n , shows a g r e a t  large  variation  i s due  uncertainties i n the value of variation  than  either  deal  M  to  M.  or  of  inaccuracies  That  M/K  h a s n o t been shown by my r e s u l t s .  trends  are  H i s nearly egual t o  about  times  K;  further  by H o l t  But  K;  certain  f o r Gadidae  H i s  K f o r S a l m o n i d a e . These  confirmed  Beverton  and H o l t ' s  suggestions  t h a t " t h e r e l a t i o n b e t w e e n H and K  to  from  differ  less  f o r P l e u r o n e c t i d a e M i t i s about 3  t i m e s K, and a b o u t 5 t i m e s ratios  or  i n the four f a m i l i e s analysed: f o r  Clupeidae 2  has  K, a s s u g g e s t e d  (1962),  evident  variation.  one  group  of  fish  (1959) appears  to another; f o r  c l u p e o i d s , fl i s g e n e r a l l y between one a n d two t i m e s for  gadiforms  M  T h u s i t becomes stock  assessment  separate  L8/LINF  i s b e t w e e n two a n d t h r e e t i m e s  theoretically  This  of  this  after  ( L M ) . The  (Scorpaenidae)  be  least  partly  K. . M  undertake without  about  variation  indicates  a  range  that 0.6  The  of the  the energy higher  t h e more e n e r g y t h e f i s h i t reaches of  mean  t o 0.89 ( O s m e r i d a e ) .  (1959b) s u g g e s t i o n could  groups  f o r reproduction. ratio,  for reproduction size  the  character  spent by t h e f i s h value  to  K,  e s t i m a t i o n o f M and K.  The r a t i o LM/LINF shows ratios.  possible  f o r taxonomic  M/K  the to  0.7  ratio  i t s first values  the  spends  maturity  i s f r o m 0,41  These r e f u t e H o l t ' s f o r many  (i.e.  two  species  thirds  of  124  asymptotic l e n g t h ) . that  short-lived  Beverton and  Clupeidae,  Holt  (1962)  LM/LINF  but  also  and  K,  found t o be t r u e f o r E n g r a u l i d a e  not  f o r Salmonidae and  suggested v i z . that  a  size  which  more  gradually  from my  calculations  linear  relationship  linear relationship 4,  and  should  rapidly  (high K value) mature  of f i s h which approach  relatively  between  grow  which i s l a r g e r , r e l a t i v e l y to that  than that  3,  Sciaenidae.  correlation  fish  towards t h e i r asymptotic s i z e a  suggested  f i s h a l s o have a higher LM/LINF v a l u e .  In the study, t h i s was and  Holt (1959)  the  (low  i n s p i t e of  an  between K and  asymptote,  asymptotic  K value).  size  This i s true  apparent LINF and  a  inverse positive  between LM—-LINF. (Refer to  5). The  at  Tables  r e l a t i o n s h i p between LM/LINF and  be  investigated  underlying  biological  in  order  meaning  to of  expose energy  K the  spend  strategies.  L1/LINF  The  r a t i o L1/LINF shows a great d e a l of v a r i a t i o n .  i s due  to the  chosing  large  this  v a r i a t i o n of  character  is  L1.  y i e l d c a l c u l a t i o n . Thus, i f  fishable  size,  L1/LINF  This also indicates example:  the  Engraulidae  will  for  to  the  f o r s i m p l i f i c a t i o n of L1  be  is the  growth s t r a t e g y grow  reason  to p a r t i a l l y i n d i c a t e  l c / L I N F r a t i o , which i s necessary the  The  This  four  egual same as of fifths  to  the  lc/LINF.  fish. of  For their  maximum s i z e during t h e i r f i r s t year but C y p r i n i d a e  can  125  only grow to one  TM/T95 The  tenth of t h e i r maximum s i z e .  r a t i o TM/T95 a l s o  absence  of  worthwhile  due  to i n s u f f i c e n t TM  of  time remaining  T50/T95  For  a  great  variation.  data. The smaller the  fish  has  spent  in  a l l fishes  most  fish  one  m a t u r i t y , the  here.,  quarter  of  Sgualidae)  indicates  grow to h a l f t h e i r asymptotic  they have reached  proportion  (except o v o v i v i p a r o u s  the r a t i o T50/T95 i s around 0,23.,This  be  reproduction,  Engraulidae has the h i g h e s t r a t i o  almost  The  r e s u l t s from t h i s r a t i o may  a f t e r the f i s h reaches  g r e a t e r energy the figain,  shows  their  that  length b e f o r e entire  life  span. The biological example,  relative  c h a r a c t e r s sometimes d i s p l a y r a t h e r more  meaning  than  compared  with  r e l a t i v e l y high TM  (5.69  the other  fishes,  y r s ) , but  (0.19). T h i s e x p l a i n s why life  individual  parameters. Cyprinidae  a very low  has  TM/T95  c a r p s only take one f i f t h  For a  ratio  of t h e i r  span to reach maturity i n order to s u s t a i n the s p e c i e s  i n the u n s t a b l e freshwater  environment. The  suggested  mean  and standard e r r o r s of the means f o r each r a t i o i n d i f f e r e n t families  3.  are  listed  in  T a b l e «|. T h i s t a b l e s u p p l i e s very  u s e f u l i n f o r m a t i o n when these  values  the s i m p l i f i e d  (equation 20  y i e l d equation  Correlative characters:  are  substituted p.13)  into  126  There  are  s i g n i f i c a n t linear regression r e l a t i o n s h i p s  i n a l l of the f a m i l i e s LINF,  between  (except  LM—LINF,  Sciaenidae)  between  and between M—K.  T h i s means that  f i s h having a l a r g e r LINF a l s o have a l a r g e r LM, and  M values.  suggestion  This  that  with both a low relation  a  fish  Beverton  with a high  maximum l e n g t h and  holds  comparisons.  supports  for  One  both  a  and  and  lower K  Hclt*s  (1959)  K value i s a s s o c i a t e d high  intra-family  particular  mortality.  difficulty  in  interpreting  tend  vice  versa.  K i s that i n  these parameters from curves, a chance r o t a t i o n  of the r e g r e s s i o n l i n e of lt+1 on I t (Walford would  This  and i n t e r - f a m i l i e s  apparent i n v e r s e r e l a t i o n s h i p s between LINF and determining  1/K—  to  relationships  increase The  which  K would always decrease LINF,  intra-species  and  i n d i c a t e d above could not,  generated i n t h i s  method)  inter-species  however, have teen  way.  My r a t i o n a l i z a t i o n f o r the d i f f e r e n c e between the of the r e g r e s s i o n l i n e  (Figure  16  to  20)  and  the  slope ratio  (Table 4) t h a t the s l o p e may  show the c h a r a c t e r i s t i c s of  whole  ratio  family  while  the  c h a r a c t e r i s t i c s of the s p e c i e s greater  the  difference  v a r i a t i o n f o r the It  i s very  and  among  represents  the  average  i n the f a m i l y . T h e r e f o r e , species  the  the  larger  the the  family. d i s a p p o i n t i n g that the r e s u l t s d i d not show  a s i g n i f i c a n t l i n e a r c o r r e l a t i o n between 1/M—T95 because i t could reasonably be expected that f i s h span  (T95),  having a longer  would a l s o have a lower n a t u r a l m o r t a l i t y  life rate  127  (M). The  of using T95  Idea  instead  of  m o r t a l i t y r a t e has not been shown t o be  Osing  the  indicate  that  there  are  significant  that  differences  exist  time, although  it  differences one o f my from  is  between  hypotheses, phylogenetic  c o n s i d e r a t i o n s . S i n c e t h i s method only takes one a  the  feasible.  e r r o r s o f the means  f a m i l i e s i n most cases. T h i s confirmed namely,  to  P - t e s t and the a p p r o p r i a t e t - t e s t as a b a s i s f o r  comparison o f means and standard evident  M  variable at  four c h a r a c t e r s were considered  (Table 7 ) ,  the attempt to group f a m i l i e s i n t o p a t t e r n s f a i l e d  by  this  method.  I t would appear t h a t by comparing the more s t a b l e c h a r a c t e r s such  as  growth  parameters  (K,  LINF),  LM,  and  the  ratio  LM/LINF, the f a m i l i e s can be d i v i d e d i n t o groups as f o l l o w s :  A)  Shoaling p e l a g i c f i s h e s - E n g r a u l i d a e , Osmeridae.  Clupeidae,  and  These f i s h e s have the highest K values  (1,6  f o r E n g r a u l i d a e , over LINF and  LM,  0.4  f o r the o t h e r s ) , the s m a l l e s t  as w e l l as a very high LM/LINF r a t i o  0.7). They reach t h e i r asymptotic and  length  Large p e l a g i c f i s h e s - Sccobridae value  quickly  a l s o spend a qreat deal o f energy i n r e p r o d u c t i o n .  T h i s r e s u l t s i n t h e i r lower LM and LINF  B)  very  (over  (around  0.35)  values,  have a f a i r l y high  K  and the l a r g e s t LINF. These f i s h  128  reach t h e i r asymptotic grow  to  a  very  length  large  relatively  s i z e . T h i s kind of f i s h  c o n s t i t u t e t h e most v a l u a b l e f i s h  C)  Demersal  fishes  Scorpaenidae,  -  Sparidae  fishes,  and would  p r o t e i n resource.  Gadidae,  Pleuronectidae,  e t c . They have lower K values  ( l e s s than 0.25), i n t e r m e d i a t e LINF pelagic  quickly  but  bigger  (smaller than  than  f i s h e s ) , and lower LM/LINF r a t i o s  shoaling  large  pelagic  ( l e s s than 0.6). They  have r e l a t i v e l y longer l i f e spans. They grow s l o w l y and spend  less  energy,  but  over  a  longer  period, i n  reproduction.  D)  Freshwater which  f i s h e s - C y p r i n i d a e have K and  are  close  and  values  t o these of the demersal f i s h e s , but  have a s m a l l e r LM and, e s p e c i a l l y , t h e (0.4)  LINF  TM/T95  (0.2) r a t i o s .  lowest  The  fish  LM/LINF starts  r e p r o d u c t i o n a t a very e a r l y s t a g e . Due t o t h e u n s t a b l e freshwater environment, have  a  the  freshwater  to  Salmonidae).  order t o s u s t a i n the s p e c i e s , the f i s h has t o s t a r t  r e p r o d u c t i o n at a very e a r l y stage. T h i s shows lowest  6.  would  high m o r t a l i t y r a t e (0.625 f o r C y p r i n i d a e , t h e  second h i g h e s t among 15 f a m i l i e s next In  fishes  i n the  LM/LINF and TM/T95 r a t i o s .  Classification  methods make i t p o s s i b l e f o r r e s e a r c h e r s who  have data based on common measurements from many p o p u l a t i o n s  129  to  demonstrate  the  validity  of  the  measurements  for  p r e d i c t i n g membership i n the populations. T h i s g i v e s r i s e discriminant find cases  analysis,  the  r u l e s of behaviour  in  to predetermined  classification predetermined  general the  function classes.  in The  assignment  of  individual  Table larger  11 the  defines  the  a b s o l u t e value of  f o r the p o p u l a t i o n  parameter,  g r e a t e r the i n f l u e n c e of c l a s s i f i c a t i o n . T h e r e f o r e ,  most u s e f u l c h a r a c t e r s f o r  classification  are, i n decending order, L1, TH, The  families  (n=5), Hiodontidae hard  o b j e c t of which i s to  c l a s s e s with optimal p r o p e r t i e s . The  c a n o n i c a l v a r i a b l e (Table 12) the  b, K,  in  M, LM,  15 and  LINF.  with s m a l l sample s i z e s such as (n=6), and  Percidae  t o i n t e r p r e t . T h i s again  (n=7)  f a m i l i e s shown i n Table  the number  of  classification  species  in  power.  There  Bothidae  made  results  shows the importance of l a r g e  normalized  classification  canonical method  the  families,  are  the  differences  method emphasises one  variables  (appendix  5  15, i t seems t h a t the g r e a t e r lower  the  between the  c a n o n i c a l v a r i a b l e s i n d i s c r i n i n a n t a n a l y s i s (Table 12) the  the  families  sample s i z e s i n these kinds o f comparative s t u d i e s , among major  to  i n c o o l e y and  2). I t seems that the  parameter a t a time, while the  and  Lohnes* fcrmer latter  method c o n s i d e r parameters more evenly.  Dendrograph  r e l a t i o n s h i p s based on 7 p o p u l a t i o n parameters  among 15 f a m i l i e s have been surveyed S t r i c t l y speaking,  this result  using c l u s t e r a n a l y s i s .  i s not p r e c i s e enough to show  130  p o p u l a t i o n p a t t e r n s . The main reason only  the  mean  value  for  each  f o r t h i s i s the use o f  group  without  v a r i a t i o n of parameters i n t o c o n s i d e r a t i o n . The  taking the program  of  UBC BHD P 2 H cannot handle such a l a r g e sample i f i t i s based on i n d i v i d u a l cases  In  conclusion,  i n s t e a d o f groups  comparative  (families).  p o p u l a t i o n s t u d i e s are h i q h l y  dependent on sample s i z e s . The r e s u l t s c f the species  within  families  r e q u i r e d . T h i s being and  estimate  show  that  more  the case, i f we want t o  comparison  supportive better  among data i s  understand  p o p u l a t i o n s i z e , more a t t e n t i o n should be paid t o  the p o p u l a t i o n l e v e l , e s p e c i a l l y n a t a l i t y and m o r t a l i t y . I t can not be s a i d which parameter i s best when based on single with or  analysis.  Population  parameters have d i f f e r e n t  d i f f e r e n t a n a l y s e s . For example, i f we reliability,  K,  LINF,  and  LH are very  e s p e c i a l l y by using them t c group f i s h p a t t e r n s . But, i n terras of c l a s s i f y i n g groups,  L1  and  TH  have  comparative f i s h p o p u l a t i o n sizes,  but  also  rely  parameters employed.  on  consider  a  weights  stability  useful characters,  into different ecological fishes  into  systematic  more s i g n i f i c a n t meaning.  Therefore,  s t u d i e s not only  on  the  depend  sample  number and kinds of p o p u l a t i o n  131  future  My  Studies  f i n d i n g s suggest  obtained  from  undertake sexes,  a  t h a t more worthwhile r e s u l t s are greater  comparison  and  volume  among  comparison  of  data.  species,  among  In  to  be  order  to  comparison  between  d i f f e r e n t s t o c k s of the same  s p e c i e s , the c o l l e c t i o n o f data  then,  is  an  ongoing  and  necessary e x e r c i s e . For example, only by having enough data, can  one  prove  or disprove Holt*s  (1959a) suggestions  "In most f i s h e s , i t seems t h a t when there are sexual d i f f e r e n c e s , these are t h a t K and  M  that  intra-specific is  higher  and  LINF i s lower  i n males than  i n females".  Modification  of the s i n g l e s p e c i e s model to a m u l t i - s p e c i e s  •family* y i e l d model based on f a m i l y undertaken.  Also,  introduction  parameters i n t o the y i e l d order  to  detect  the  model  statistics  the should  sensitivity  of  should  variation be  of  be  these  considered  in  the  model  to such  characters  very  likely  variation.  The  cause  encompasses temperature. do  not  for  variation  of  environmental But,  mention  factors,  particularly  t h i s approach i s hampered as  most  water papers  v e r t i c a l d i s t r i b u t i o n s of f i s h e s . I t seems  the only a l t e r n a t i v e  i s t o use  surface  water  temperature.  132  However  it  would  be  of  great  endeavoured t o o b t a i n data on collecting  Aside for  value  vertical  i f a l l workers  distributions  information.  from  surface  water temperature, an a d d i t o n a l method  examination o f t h e f a u n a l p a t t e r n i s the  geographical suitable  variations  with  species  comparison  cf  f o r which there are  data.  Eoth growth parameters maturity  (LH)  are  m o r t a l i t y , maturity population between  size,  these  recruitment  (K  fairly and  i t will  LINF)  stable.  growth  parameters  rates.  and  spending  and  size  at  first  However, t o r e l a t e the  be necessary  eventually  to  t o make comparisons  specific  fecundity  These can serve as indexes f o r different  and  grouping  strategies  t h e i r energy i n growth and/or r e p r o d u c t i o n . I  w i l l endeavour t o employ a d d i t i o n a l datermine  and  parameters  f i s h e s i n t o d i f f e r e n t c a t e g o r i e s with for  when  the  patterns  analytical  methods  to  f o r d i f f e r e n t s t r a t e g i e s of energy  ultilization.  I t w i l l be e a s i e r t o f i n d p o p u l a t i o n most  stable  characters.  p a t t e r n s by  But, i n terms  of  using  the  a p p l y i n g the  r e s u l t s t o f i s h e r i e s models, t h e i n t e r r e l a t i o n s h i p s between (or  among)  though Perhaps  they by  parameters show  great  still  need  variation  t o be e s t a b l i s h e d even (e.g. M,  T95,  etc.).  o b t a i n i n g l a r g e r sample s i z e s t h e v a r i a t i o n can  133  be  neutralized.  characteristics  Once of  this  i s done,  population  example,  maturity  by  predaticn,  induce  mathematical  f o r the M/K r a t i o s u f f i c i e n t  f o r s u r v i v a l of the  determined  can  the  parameters and, a t the same  time, deduce b i o l o g i c a l meaning with For  I  population.  the  fish  fish  Even  should  support. must reach  i f M  sere  have a high K  value, which i s a r e s u l t o f n a t u r a l s e l e c t i o n , i n  order  to  reach the breeding s t a t e .  The and  best r e s u l t s I can o b t a i n are from growth they do e x i h i b i t s i g n i f i c a n t  T h i s being the case, different selection.  population  parameteters,  d i f f e r e n c e s among f a m i l i e s .  i t may be p o s s i b l e t o c o n s i d e r a p p l y i n g growth  strategies  of  r  and  K  134  VIII CONCLUSIONS  For  individual  coefficient first  parameters,  maturity  fairly  (LM), the  (M)  the  The  maturity  size  at  (TH), the  characters.  and  The  natural  mortality  the age on reaching 95% of asymptotic  (T95, as an index o f l i f e span) show l a r g e v a r i a t i o n .  The suggested in  age a t f i r s t  exponential  (K and LINF) , and the l e n g t h at age 1 (L1)  stable  coefficient length  weight-length  <b) i s the most s t a b l e c h a r a c t e r .  growth parameters are  the  15  means and standard  major  e r r o r s f o r each  f a m i l i e s are l i s t e d  information  f o r other  fish  parameter  i n Table 3. T h i s stocks  where  provides data  are  lacking.  For  relative  characters  s t a b l e c h a r a c t e r although variation. TM/T95  The  show  standard  other  large  ( r a t i o s ) , the LM/LINF i s the most the T50/T95 r a t i o shows t h e  three  least  c h a r a c t e r s : M/K, L1/LINF, and  variation.  The  suggested  means  and  e r r o r s f o r each r a t i o i n 15 f a m i l i e s are l i s t e d i n  Table 4.  For c o r r e l a t i v e c h a r a c t e r s , regression  relationships  there (between  LINF, and between  M—K)  in  Sciaenidae.  means  that  This  are  significant  linear  1/K—LINF, between  a l l of a fish  the  families  LM—  except  having a g r e a t e r LINF  a l s o has a l a r g e r LM, a lower K and a lower M. There are  no  s i g n i f i c a n t l i n e a r c o r r e l a t i o n s between L 1 — L I N F and between  135  1/M--T95.  By  comparing  and  LM/LINF) I can d i v i d e the f a m i l i e s i n t o groups:  A)  f o u r s t a b l e c h a r a c t e r s together  Shoaling p e l a g i c f i s h e s - E n g r a u l i d a e , have  Clupeidae,  They  the  highest  K  (1.6 f o r  Engraulidae,  over 0.4 f o r the  others),  the  smallest  Large  pelagic  value  C)  (around  Demersal  fishes  (over 0.7).  - Scombridae, has f a i r l y  fishes  -  Gadidae,  Pleuronectidae,  Sparidae  e t c . They  have lower K value  ( l e s s than 0.25), i n t e r m e d i a t e LINF s i z e LM/LINF r a t i o s  Freshwater  high K  0.35) and the l a r g e s t LINF.  Scorpaenidae,  D)  and  Osmeridae.  LINF, LM, and a very high LM/LINF r a t i o  B)  (K, LINF, LM,  ,  and  lower  has K and LINF  values  ( l e s s than 0.6).  fishes  -  Cyprinidae  which a r e s i m i l a r to those of the demersal f i s h e s , has (0.4)  a  smaller  LM and, e s p e c i a l l y , the lowest LS/LINF  and TM/T95 (0.2) r a t i o s .  By u s i n g the F - t e s t and the a p p r o p r i a t e t - t e s t for four  but  comparison population  of  the mean and t h e standard  parameters  (K,  LINF,  as  a  basis  d e v i a t i o n , of  T95,  and  LM) ,  136  significant  differences  are found between f a m i l i e s i n most  cases. Although the attempt t o group f a m i l i e s i n t o  patterns  by t h i s method f a i l e d , i t does confirm one of my hypotheses; namely  that  population  differences  between  parameters,  exist  families,  as  from  shown  by  phylogenetic  considerations.  6.  Stepwise  discriminant  analysis  parameters  (M, K, LINF, LH, TH, L1, and b) were conducted i n  group I (among 5 f a m i l i e s , sizes), sample (15  which  based  have  on  7  very  population  large  sample  group I I (among 10 f a m i l i e s which have f a i r l y s i z e s ) , and a l s o with group I and group  families  altogether).  Over  90%  of  II  the  combined  cases  considered i n d e p e n d e n t l y were c o r r e c t l y c l a s s i f i e d  large  when  i n a l l of  the a n a l y s e s .  7.  Cooley and Lohnes* c l a s s i f i c a t i o n method was  also  utilized  and i t gave even b e t t e r r e s u l t s . The a n a l y s e s were conducted among  species  Cyprinidae,  within  Gadidae,  5  major  families  Pleuronectidae,  and  C o r r e c t c l a s s i f i c a t i o n ranged from 58.6% 87.6%  8.  A  (Clupeidae, Scombridae).  (Pleuronectidae) t o  (Cyprinidae).  dendrograph  families  based  using  relationship  to  on  cluster be  7  p o p u l a t i o n parameters among 15  analysis  shows  more s i g n i f i c a n t  r e l a t i o n s h i p among f a m i l i e s .  the  ecological  than the p h y l o g e n e t i c  137 IX  LITERATURE  laser), O. 1952. F i s k e r i d i r . S k r . Havundersok. 10 (2) . Beverton and H o l t 1959)  (quoted  in  Aasen, 0. 1961. 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I n Proc. w o r l d s c i . m e e t i n g on t h e b i o l . o f sarine and r e l a t e d s p e c i e s . FAO F i s h . S y n . No. 52. Yoshiike, N. . 1962. F i s h e r y b i o l o g y o f H i p p o g l o s s o i d e s d u b i u s i n Hakasa Bay. .Dept. F i s h . F a c . A g r . , K y o t o U n i v . Spec. Publ. 24p. ( i n J a p a n e s e ) Y u e n , H. S. H. 1955. M a t u r i t y and f e c u n d i t y o f b i g e y e t u n a i n t h e P a c i f i c . S p e c . s c i . Bep. 0. S. F i s h . W i l d l . S e r v . - F i s h . 150, 30p. Zawisza, J. 1951. The g r o w t h r a t e o f bream, b a r b e l , Vimba yjmba and w h i t e - b r e a m i n t h e m i d d l e r e a c h e s c f t h e Vistula near Sarsan. (Polish, En and Ru summary). Bocz. Nauk r o l n . 57:237-271. Z h u k c v , P. I . 1958. SSR, 191pp.  Ryby b a s s e i n a Nemana. M i n s k ,  Izda  Eeloruskoi  179  Zukowski, C. 1972. G r o w t h ana m o r t a l i t y o f a t l a n t i c a r g e n t i n e , A r g e n t i n a s i I u s A s c a n i u s , on t h e Nova S c o t i a Banks. ICNAF Bes. B u l l . 9:109-115.  X APPENDICES CO o  Appendix 1.  Mean v a l u e s , 95% confidence l i m i t s , ranges and sample s i z e s of i n d i v i d u a l parameters among 28 f a m i l i e s (group I I I )  1: A c i p e n s e r i d a e 2 : Ammodytidae 3: A n g u i l l i d a e 4: A p l o c h i t o n i d a e 5 : Argentinidae 6 : Atherinidae 7: Blennidae 8: Callionymidae 9 : Carangidae 10 : C i c h l i d a e  11: 12: 13: 14: 15: 16: 17: 18: 19: 20:  Cottidae Dasyatidae Drepanidae Embiotocidae Gasterosteidae Hexagrammidae Ictaluridae Istiophoridae Lujanidae Nemipteridae  21: P o e c i l i d a e 22 : Polynemidae 23: Pomacentridae 24: S i l l a g i n i d a e 25: S o l e i d a e 26 : S t i c h a e i d a e 27: Syngrathidae 28: T r a c h i p t e r i d a e  18  si 8 a a i i •Ma i  a a a 3  B  &  S  s  2  a  8  Q  ° W1 >Qi3tVWd  fl ' ru  0  (a a a a a a  a  j5  a I •a " a 2  i  i  <s  ?  ru  a Fi fl •8 •a 3 •a •a •a  ?5  •a  182  8  I s  ii  K  6  i  i  a  a  a  3  ?«  -j  a  ?s  ?S ?!  ?! a a  a  a  -5)—r-  CM  X  •rH  G CD Ci  I  3.o  era,. CS7  e.«  est.  CI  J  i-a  Y N  r S  1-5  t  \  0-3Q.  D  o-3a,  M  o-a.  o-ia.  0-6.  o-ia.  ca.  COG  O.Q C  O-CO,  1. E . 3. 4. S- B. 7 . 6- 9-10-11.12.l3.i«.i5.1fi.i7-lB.ia.eb.Ei.S.S-E4.3-ai-E7.Sa.  FAMILY  0. 1. t - 3. 4 . S. 6. 7. 6 .  I  FAMILY  O.BCL  I  O-SO.  0-77  o-sa.  CBa.  0.4Q ,  0-60  s •J-  S.10.11.1E-13-14.1S.16-17.IB.13.20-21.E2.23.24.2S.2S.27.2a.  §  0-42.  p  0-3S  S 51  nl  5-3  3-EGl  o.aa. 0-B4 .  cia. o-ia.  j-cal  cos.  o-oo 1  *'  B  >  3  " *• " s  c  *  8. a - i o . i l .  12.13-14.15.lfi-I7.i.i.20.21.£E.E3.24.E5.eri.27.a3.  -o-oa_ U  E  ' " *' 3- 6. >. 3  B- C 1 0 . 1 1 . i 2 . i 3 . 1 4 . 1 S . 1 6 . 1 7 . i B . j l 3 . i . i . 2 2 . S 3 . 2 4 . E 3 . 2 S . i l  FAMILY  Appendix 2.  I  Mean v a l u e s , 95% confidence l i m i t s , ranges and sample s i z e s o f c o r r e l a t i v e c h a r a c t e r s among 2 8 f a m i l i e s (group I I I )  184  Appendix  3.  Summary t a b l e o f C o o l e y c l a s s i f i c a t i o n method  and L o h n e s '  C O O L t Y £ L C H N E S C A L L Tt-E C A N C M C A L V A R I A B L E S D I S C R I M I N A N T FUNCTIONS. HEY PPRFPR TC NflRM AL I ZF T H E S E E I G L N - V E C T O R S TO U N I T MAGNITUDE. AN A R B I T R A R Y - 1 . 0 IS I N C L U D E D I N T H E R F N O R M A L I Z A T ION T  ORIGINAL I VARIABLE M C. K 0. LINF 0. LM C. T v. - 0 . 0. Ll -0. B  :  2  3  18486 0. 37618 1 7 C 2 4 F - C 1 - c . 892 28 3 4 1 8 5 5 - C3 - 0 . 5 4 9 6 4 F - 0 3 4 9 2 Z C E - C2 c. 2 7 9 2 4 ^ - 0 2 2 1 7 2 3 E - CI c. 2 0 1 4 4 CI 0. 93569= -02 98122 c. 1 4 C 9 5  I GROUP KLUPc I -2.3667 CYPRIN -2.7652 GADIDA - 1.9738 PLEUNC -2.7267 SCOMciR - C . 6 3 0 2 2 6Q0THI -2.1464 7ENGRA -2.3336 8HICJ0 -2.44C1 ^OSMiR -2.9468 OSALMO -2.C816 1SCIAE -1.9494 2SCQRP -2.9507 -2.5337 3PERC I 4 SPAR I -2.0590 5SQUAL -1.5837  0. -0. 0. 0. -0. 0. 0.  29384 87294E205C0 125COE15410F26925F9 5 1 73 C  2  3  0.73347 1.7630 1.2709 1.6192 1.3710 1.1161 -C.53024 1.5047 C.91404 1.3 215 C.69617 2.0625 1.4835 1.5215 4.8285  3 . 1241 3. 2580 2. 9861 3 0861 • 3. 1740 — * C424 2. 9484 3. C326 3. 2530 3 . C897 •5 — . 1145 3. 0180 2. 9878 2. 6 2 6 9 2. 9 7 8 4 #  01 03 02 01 02  ERRATA No data has been entered i n Table 1 f o r s p e c i e s no. (Gadus c a l l a r i a s ) as i t i s a synonym f o r s p e c i e s no. (Gadus morhua).  

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