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Modelling and analyzing density‐dependent population processes: Comparison between wild and laboratory strains of the bean weevil, Callosobruchus chinensis (L.)
Author(s) -
Kuno Eizi,
Kozai Yoshitake,
Kubotsu Koji
Publication year - 1995
Publication title -
population ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.819
H-Index - 59
eISSN - 1438-390X
pISSN - 1438-3896
DOI - 10.1007/bf02515817
Subject(s) - biology , callosobruchus chinensis , population , selection (genetic algorithm) , domestication , adaptation (eye) , statistics , ecology , zoology , mathematics , demography , sociology , computer science , artificial intelligence , neuroscience
Three models were constructed for analyzing the population characteristics of C. chinensis on stored beans; model A describing the whole reproductive process with a single equation, model B describing the three age‐specific processes (oviposition, egg survival and larval survival) with separate equations, and model C which describes all these processes not for the whole habitat but for the individual beans comprizing it. The logit equation was employed here as a common basis to describe the density‐response relationship involved. All three models showed very good fit to the experimental data obtained for both laboratory and wild strains of the weevil. The parameter values characterizing the population dynamics were, however, widely different between the two strains; the laboratory one which had been reared for some 500 generations showed significantly higher reproductive capacity, less sensitive and gentler response to crowding in both adult and egg stages, and more uniform egg distribution among individual beans, as compared with the wild strain newly introduced. Sensitivity analyses using these models suggested that these changes in population characteristics have been attained by the process of domestication or adaptation to stable laboratory conditions through a long period of time. This process seemed in effect to have optimized the population's performances in the laboratory environment. Evolutionary significance of such optimization was discussed with reference to the selection pressure which may have acted upon individuals.

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