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New tools for population viability analyses
 
 Oenothera glaziovianaSince three decades, the toolbox of biologists to assess conservation status of endangered species and take actions to improve their long-term viability includes the very popular matrix population models. For this range of models where populations are divided into discrete stages, a solid mathematical framework is available (e.g., Caswell Matrix population models 2001). In addition, softwares such as RAMAS or demogR allow to implement these models in real ecological situations. Unfortunately, not all populations of plants and animals can be divided into discrete categories without loss of significant biological information because individuals often differ for continuous traits such as body size, body condition or growth potential. Continuously structured populations can be described using integral projection models (IPMs), a mathematical framework first introduced by Stephen Ellner and collaborators (Easterling et al. Ecology 2000) and now more and more popular among population ecologists (Coulson Oikos 2012). Although the IPM is efficient with small data sets (Ramula et al. Journal of Applied Ecology 2009), it has not yet been used for real life population viability analyses. In this article, we present for the first time population viability analyses of animal and plant species using the stochastic IPM recently developed by Vindenes and collaborators (Ecology 2011). We show how to construct the stochastic IPM, demonstrate how to calculate and decompose deterministic and stochastic components of the population growth rate, and show results of sensitivity analyses. In addition, we compare results of a diffusion approximation with individual based simulations.
 
 
Photograph: Populations of Oenothera glazioviana, an evening primrose with a semelparous reproduction and size-structured populations were modelled in this study (photograph by Bernd Sauerwein on Wiki Commons)
 
Jaffré, M. and J.-F. Le Galliard. 2016. Population viability analyses of plant and animal populations with stochastic integral projection models. Oecologia 182(4):1031-1043.
 
Integral projection models (IPM) make it possible to study populations structured by continuous traits. Recently, Vindenes et al. (2011) proposed an extended IPM to analyse the dynamics of small populations in stochastic environments, but this model has not yet been used to conduct population viability analyses. Here, we used the extended IPM to analyse the stochastic dynamics of IPM of small size-structured populations in one plant and one animal species (evening primrose and common lizard) including demographic stochasticity in both cases and environmental stochasticity in the lizard model. We also tested the accuracy of a diffusion approximation of the IPM for the two empirical systems. In both species, the elasticity for λ was higher with respect to parameters linked to body growth and size-dependent reproduction rather than survival. An analytical approach made it possible to quantify demographic and environmental variance in order to calculate the average stochastic growth rate. Demographic variance was further decomposed to gain insights into the most important size classes and demographic components. A diffusion approximation provided a remarkable fit to the stochastic dynamics and cumulative extinction risk, except for very small populations where stochastic growth rate was biased upward or downward depending on the model. These results confirm that the extended IPM provides a powerful tool to assess the conservation status and compare the stochastic demography of size-structured species, but should be complemented with individual based models to obtain unbiased estimates for very small populations of conservation concern.
Last Updated ( jeudi, 08 décembre 2016 )