3 years ago

Evolution of stochastic demography with life history tradeoffs in density-dependent age-structured populations [Population Biology]

Evolution of stochastic demography with life history tradeoffs in density-dependent age-structured populations [Population Biology]
Russell Lande, Bernt–Erik Sather, Steinar Engen

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, NN, 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, r0r0 and KK, and the environmental variance in population growth rate, σe2σe2. Allowing these parameters to be genetically variable and to evolve, but assuming that a fourth parameter, θθ, measuring the nonlinearity of density dependence, remains constant, the expected evolution maximizes E[Nθ]=[1σe2/(2r0)]KθE[Nθ]=[1−σe2/(2r0)]Kθ. This shows that the magnitude of environmental stochasticity governs the classical trade-off between selection for higher r0r0 versus higher KK. However, selection also acts to decrease σe2σe2, so the simple life-history trade-off between rr- and KK-selection may be obscured by additional trade-offs be

-Abstract Truncated-

You might also like
Discover & Discuss Important Research

Keeping up-to-date with research can feel impossible, with papers being published faster than you'll ever be able to read them. That's where Researcher comes in: we're simplifying discovery and making important discussions happen. With over 19,000 sources, including peer-reviewed journals, preprints, blogs, universities, podcasts and Live events across 10 research areas, you'll never miss what's important to you. It's like social media, but better. Oh, and we should mention - it's free.

  • Download from Google Play
  • Download from App Store
  • Download from AppInChina

Researcher displays publicly available abstracts and doesn’t host any full article content. If the content is open access, we will direct clicks from the abstracts to the publisher website and display the PDF copy on our platform. Clicks to view the full text will be directed to the publisher website, where only users with subscriptions or access through their institution are able to view the full article.