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The costs of reproduction in evolutionary demography : an application of Multitrait Population Projection Matrix models

Abstract : Costs of reproduction are pervasive in life history theory. Through this constraint, the reproductive effort of an organism at a given time negatively affects its later survival and fertility. For life historians, they correspond mostly to a physiological trade-off that stems from an allocative process, occurring at each time-step, at the level of the individual. For evolutionary demographers, they are essentially about genetic trade-offs, arising from a genetic variance in a pleiotropic gene acting antagonistically on early-age and late-age fitness components. The study, from an evolutionary demographic standpoint, of these mechanisms and of the relative, cross and joint effects of physiological and genetic costs, is the aim of this thesis. The close examination of Williams (1966)’s original definition of the physiological costs of reproduction led us to produce a theoretical design of their apparatus that accounts for both their mechanistic and evolutionary mechanisms. This design allowed us to make predictions with regards to the strength of costs of reproduction for various positions of organisms on three life-history spectra: slow-fast, income-capital breeders and quality-quantity. From Stearns (1989b)’s tryptic architecture of life history trade-offs –that divides their structure into the genotypic level, the intermediate structure and the phenotypic level – we devised a general framework, which models the possible cohabitation of both physiological and genetic costs. From this, we inferred differing detectability patterns of both types of costs according to the environmental conditions, their variance and individual stochasticity. We could also establish that both costs buffer environmental variations, but with varying time windows of effect. Their dissimilarity emerges also from the differences between mathematical projection models specific to each cost. A new family of evolutionary models is therefore required to implement both physiological and genetic trade-offs. We then describe the vector-based construction method for such a model which we call Multitrait Population Projection Matrix (MPPM) and which allows incorporating both types of costs by embedding them as traits into the matrix. We extend the classical sensitivity analysis techniques of evolutionary demography to MPPMs. Most importantly, we present a new analysis tool for both life history and evolutionary demography: the Trait Level Analysis. It consists in comparing pairs of models that share the same asymptotic properties. Such ergodic equivalent matrices are produced by folding, an operation that consists in reducing the number of traits of a multi-trait model, by averaging transitions for the traits folded upon, whilst still preserving the asymptotic flows. The Trait Level Analysis therefore allows, for example, to measure the evolutionary importance of costs of reproduction by comparing models incorporating them with folded versions of these models from which the costs are absent. Using classical and new methods to compute fitness moments – selection gradient, variance in reproductive success, environmental variance - in models with and without the costs, we can show their effects on various demographic and evolutionary measures. We reveal, in this way, the combined effects of genetic and physiological costs on the vital rates of an age-structured population. We also demonstrate how physiological costs affect both components of effective selection, as they flatten the slope of selection gradients and increase the effective size of a population. Finally, we show how their buffering of environmental and demographic variance confer greater resilience to populations experiencing physiological costs of reproduction
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Submitted on : Monday, June 24, 2019 - 11:49:30 AM
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Christophe Coste. The costs of reproduction in evolutionary demography : an application of Multitrait Population Projection Matrix models. Other [q-bio.OT]. Université Sorbonne Paris Cité, 2017. English. ⟨NNT : 2017USPCC259⟩. ⟨tel-02163377⟩



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