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UBC Theses and Dissertations

Comparative fish population studies Ni, I-hsun

Abstract

This project was designed to study the patterns of variability in fish populations. My hypothesis is that specific population patterns should be related to evolutionary concepts (phylogenetic patterns} , zoogeographic considerations (faunal patterns), and their vertical distributions. These patterns should be detected by comparing certain population parameters [growth parameters (K, LINF), the natural mortality coefficient (M) size at first maturity (LM), age at first maturity (TM), size at age 1 (L1) , the weight-length exponential coefficient (b) , and life span (T95)] which are intrinsic biological features of the population. Comparative methods were used to analyze data from published fish population studies by comparing fish population parameters, individually, in pairs (ratio or linear regression), or grouped together (discriminant analysis or Cooley and Lohnes' classification method), in order to find the similarities or differences among different categories, and then to group these into patterns. Published data provided 682 parameter records from 43 families (171 species) of fishes. My findings suggested that more satisfactory results would be obtained from a greater volume of data. Therefore, all the analyses were based mainly on 15 families with large sample sizes (Bothidae, Clupeidae, Cyprinidae, Engraulidae, Gadidae, Hiodontidae, Osmeridae, Percidae, Pleuronectidae, Salmonidae, Sciaenidae, Scombridae, Scorpaenidae, Sparidae, and Sgualidae). Sample sizes, mean values, standard errors, and coefficients of variation for population parameters and relative characters of the 15 families of fishes are listed in the summary table. These data would enable the extrapolation of results based on many areas for management of other fish stocks where data are lacking. In the majority of families significant linear regression relationships were found between 1/K--LINF, between LM--LINF, and between M--K. This means that fish having a greater asymptotic length (LINF) also have a larger size at first maturity (LM), a lower natural mortality coefficient (M), and a lower rate (K) at which the asymptotic length is reached. Using the F-test and the appropriate t-test as a basis for comparison of variances and means of individual parameters, it is evident that in most cases there are significant differences between families. This confirms one of my hypothesis; namely that differences between families, as shown by population parameters, exist from phylogenetic considerations. By comparing the four characters (K, LINF, LM, and LH/LINF) the fish families can be divided into the following groups: A) Shoaling pelagic fishes - Engraulidae, Clupeidae, and Osmeridae. These families have the highest K values (1.6 for Engraulidae, over 0.4 for the others), the smallest LINF, LM, and a very high LM/LINF ratio (over 0.7). B) Large pelagic fishes - Scombridae. This family has a moderately high K value (around 0.35) and the largest LINF. C) Demersal fishes - Gadidae, Pleuronectidae, Scorpaenidae, Sparidae etc. These families have low K values (less than 0.25), intermediate LINF size, and lower LM/LINF ratios (less than 0.6). D) Freshwater fish - Cyprinidae. This family has K and LINF values which are similar to those of the demersal fishes, but has a smaller LM length and, especially, the lowest LK/LINF (0.4) and TH/T95 (0.2) ratios. Stepwise discriminant analysis based on 7 variables in the 15 families showed that over 90% of the 620 cases considered independently could be correctly classified into the right families. Cooley and Lohnes' classification method was also utilized among species within 5 major families (Clupeidae, Cyprinidae, Gadidae, Pleuronectidae, and Scombridae). Correct classification ranged from 5 8.6% (Pleuronectidae) to 87.6% (Cyprinidae). These results further confirmed the existence of population patterns by examination of population parameters. Cluster analysis based on 7 population parameters displayed the closeness among the 15 families. Dendrograph relationships brought out the ecological, rather than the systematic, affinities between families.

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