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SeMoVi - April 13th, 2011

SeMoVi

 

Hal Caswell, Woods Hole Oceanographic Institution
Beyond R_0: Demographic models for variability of lifetime reproductive output

The net reproductive rate, R_0, measures the expected lifetime reproductive output of an individual, and plays an important role in demography, ecology, evolution, and epidemiology. Well-established methods exist to calculate it from age- or stage-classified demographic data. Because it is an expected value, however, R_0 provides no information on variability. Many empirical measurements of lifetime reproduction have revealed high levels of variability, and often positive skewness. This is often interpreted as evidence of heterogeneity, and thus of an opportunity for natural selection. However, variability provides evidence of heterogeneity only if it exceeds the level of variability that would be expected in a cohort of identical individuals all experiencing the same vital rates. Such comparisons require a way to calculate the statistics (variance, coefficient of variation, skewness) of lifetime reproduction from demographic data. These calculations have not been possible; here, I present a new approach, using the theory of Markov chains with rewards, that gives all the moments of the distribution of lifetime reproduction. The approach applies to age- or stage-classified models, to constant, periodic, or stochastic environments, and to any kind of reproductive schedule. As examples, I analyze data from several empirical studies of a variety of animal and plant taxa.

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Arnaud Chaumot, Cemagref
Jumping from toxicological to eco-toxicological effects: how matrix population models can help to assess population sensitivity to contaminants in ecosystems

The retrospective and prospective assessment of contaminant impacts at higher levels of biological organization (populations, communities) is today constrained by the difficulty to observe, detect and assess chemical effects directly at these integrated levels. This is because of both practical issues (time and spatial scale, extinction) and intrinsic properties of such complex biological systems (integration of multiple environmental influences, adaptability, stochasticity). To gain in sensitivity and specificity, the assessment of toxicity in the lab and in the field is thus performed considering effects on organisms (survival, fertility, growth, &) or sub-organism responses (biomarkers). The extrapolation from such lower tier toxicity tests to sensitivity of higher biological levels is therefore required to ensure the ecological relevance of toxicity assessment. In this framework, population modelling is proposed in order to bridge the gap between the alterations of individual performance traits and the potential impairment of population dynamics. In ecotoxicology, this mechanistic demographic modelling approach revealed, theoretically and experimentally, how toxic population impacts are deeply modulated by population life history. In this presentation based on examples from aquatic ecotoxicology, I will illustrate how perturbation analysis of matrix population models allows one to disclose key demographic transitions for population fitness and to recognize the interplay between these demographic sensitivities and the toxicological sensitivities in the response of populations to chemical perturbations. I will discuss how these modelling tools lead us to consider that between and within species differences in life history are key determinants of chemical effects on the ecosystems.

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Jean-Michel Gaillard, LBBE
Demographic analyses of vertebrate populations: when demography meets evolution?

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