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首页> 外文期刊>Proceedings of the National Academy of Sciences of the United States of America. >Evolution of stochastic demography with life history tradeoffs in density-dependent age-structured populations
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Evolution of stochastic demography with life history tradeoffs in density-dependent age-structured populations

机译：Evolution of stochastic demography with life history tradeoffs in density-dependent age-structured populations

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摘要

We analyze the stochastic demography and evolution of a density-dependent age- (or stage-) structured population in a fluctuating environment. A positive linear combination of age classes (e.g., weighted by body mass) is assumed to act as the single variable of population size, N, exerting density dependence on age-specific vital rates through an increasing function of population size. The environment fluctuates in a stationary distribution with no autocorrelation. We show by analysis and simulation of age structure, under assumptions often met by vertebrate populations, that the stochastic dynamics of population size can be accurately approximated by a univariate model governed by three key demographic parameters: the intrinsic rate of increase and carrying capacity in the average environment, r(0) and K, and the environmental variance in population growth rate, sigma(2)(e). Allowing these parameters to be genetically variable and to evolve, but assuming that a fourth parameter, theta, measuring the nonlinearity of density dependence, remains constant, the expected evolution maximizes EN-theta = 1 - sigma(2)(e)/(2r(0))K-theta. This shows that the magnitude of environmental stochasticity governs the classical trade-off between selection for higher r(0) versus higher K. However, selection also acts to decrease sigma(2)(e) so the simple life-history trade-off between r- and K -selection may be obscured by additional trade-offs between them and sigma(2)(e) Under the classical logistic model of population growth with linear density dependence (theta = 1), life-history evolution in a fluctuating environment tends to maximize the average population size.

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