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Phenotypic variance of bilateral characters as an indicator of genetic and environmental conditions in bream Abramis brama (L.) (Pisces, Cyprinidae) populations
Author(s) -
Kozhara A. V.
Publication year - 1994
Publication title -
journal of applied ichthyology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.392
H-Index - 62
eISSN - 1439-0426
pISSN - 0175-8659
DOI - 10.1111/j.1439-0426.1994.tb00156.x
Subject(s) - meristics , biology , cyprinidae , fluctuating asymmetry , range (aeronautics) , ecology , variance (accounting) , population , zoology , fishery , fish <actinopterygii> , demography , materials science , accounting , sociology , business , composite material
Summary The expressions of factorial (s̀ 2 s ) and stochastic (s̀ 2 s ) components of henotypic variance of bilateral characters are given, regarding simple connection of the latter to the fluctuating asymmetry indicator, being traditionally used for assessment of developmental stability. The values of both components were calculated for 5 meristic characters in 172 samples of bream collected over most of its geographic range. The s̀ 2 s values were to indicate possible effects of genetic disbalance and to measure environmental stress, while s̀ 2 s was regarded as a rough estimate of the genetical heterogeneity. It was found that s̀ 2 s values tended to grow in following situations: a) zones of interpopulational contacts or in populations with unusual morphology; b) zones of increased anthropogeneous pollution, in particular In the lower parts of the artificial reservoirs as compared to the upper arts and the majority of rivers and lakes. On the other hand, s̀ 2 f values in lakes appeared to be lower than in rivers, probably due to comparatively low genetic heterogeneity of the lake populations. The whole set of samples exhibits another clear trend: negative correlation between s̀ 2 s and s̀ 2 f , which seems to illustrate a well‐known connection between developmental homeostasis and heterozygosity. A conclusion may be made that the phenotypic variance components are useful in ecological and genetical monitoring of large population systems, although the data are often difficult to interpret properly for separate populations.