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Girard-Tercieux, C.

Publications and source records attributed to Girard-Tercieux, C..

3 recordsLinked to original sources

Strong Selection, but low repeatability: Temperature-specific effects on genomic predictions of adaptation

Climate warming is threatening biodiversity by increasing temperatures beyond the optima of many ectotherms. Due to the inherent non-linear relationship between temperature and the rate of cellular processes, such shifts towards hot temperature are predicted to impose stronger selection compared to corresponding shifts toward cold temperature. This suggests that when adaptation to warming occurs, it should be relatively rapid and predictable. Here, we tested this hypothesis from the level of single-nucleotide polymorphisms to life-history traits, by conducting an evolve-and-resequence experiment on three genetic backgrounds of the beetle, Callosobruchus maculatus. Indeed, phenotypic evolution was faster and more repeatable at hot, relative to cold, temperature. However, at the genomic level, adaptation to heat was less repeatable when compared across genetic backgrounds. As a result, genomic predictions of phenotypic adaptation in populations exposed to hot temperature were accurate within, but not between, backgrounds. These results seem best explained by genetic redundancy and an increased importance of epistasis during adaptation to heat, and imply that the same mechanisms that exert strong selection and increase repeatability of phenotypic evolution at hot temperature, reduce repeatability at the genomic level. Thus, predictions of adaptation in key phenotypes from genomic data may become increasingly difficult as climates warm.

evolutionary biology↗

Beyond variance: simple random distributions are not a good proxy for intraspecific variability in systems with environmental structure

The role of intraspecific variability (IV) in shaping community dynamics and species coexistence has been intensively discussed over the past decade and modelling studies have played an important role in that respect. However, these studies often implicitly assume that IV can be represented by independent random draws around speciesspecific mean parameters. This major assumption has largely remained undiscussed, although a great part of observed IV is structured in space or time, in particular when environmental dimensions that influence individual performance are imperfectly characterised or unobserved in the field. To test the impact of this strong assumption on the outcome of community dynamics models, we designed a simulation experiment where we varied the level of knowledge of the environment in virtual communities, resulting in different relative importance of explained vs unexplained spatial individual variation in performance. We used a community dynamics simulator to generate communities where the unexplained individual variation is, or is not, added as an unstructured random noise. Communities simulated with unstructured IV never reached the community diversity and composition of those where all the variation was explained and structured (perfect knowledge model). This highlights that incorporating unstructured IV (i.e. a random noise) to account for unexplained (but structured) variation can lead to incorrect simulations of community dynamics. In addition, the effects of unstructured IV on community diversity and composition depended on the relative importance of structured vs unstructured IV, i.e. on the level of knowledge of the environment, which may partly explain the contrasting results of previous studies on the effect of IV on species coexistence. In particular, the effect of unstructured IV on community diversity was positive when the proportion of structured IV vs unstructured IV in the model was low, but negative when this proportion was high. This is because unstructured random noise can either limit the competitive exclusion of inferior competitors in low dimensions or destabilise tight niche partitioning in high dimension. Our study suggests that it is crucial to account for the sources and structure of observed IV in real communities to better understand its effect on community assembly and properly include it in community dynamics models.

ecology↗

Rethinking the role of intraspecific variability in species coexistence

ContextIntraspecific variability (IV) has been proposed to explain species coexistence in diverse communities. Assuming, sometimes implicitly, that conspecific individuals can perform differently in the same environment and that IV blurs species differences, previous studies have found contrasting results regarding the effect of IV on species coexistence. ObjectiveWe aim at showing that the large IV observed in data does not mean that conspecific individuals are necessarily different in their response to the environment and that the role of high-dimensional environmental variation in determining IV has been largely underestimated in forest plant communities. Methods and ResultsWe first used a simulation experiment where an individual attribute is derived from a high-dimensional model, representing "perfect knowledge" of individual response to the environment, to illustrate how a large observed IV can result from "imperfect knowledge" of the environment. Second, using growth data from clonal Eucalyptus plantations in Brazil, we estimated a major contribution of the environment in determining individual growth. Third, using tree growth data from long-term tropical forest inventories in French Guiana, Panama and India, we showed that tree growth in tropical forests is structured spatially and that despite a large observed IV at the population level, conspecific individuals perform more similarly locally than compared with heterospecific individuals. SynthesisAs the number of environmental dimensions that are typically quantified is generally much lower than the actual number of environmental dimensions influencing individual attributes, a great part of observed IV might be misinterpreted as random variation across individuals when in fact it is environmentally-driven. This mis-representation has important consequences for inference about community dynamics. We emphasize that observed IV does not necessarily impact species coexistence per se but can reveal species response to high-dimensional environment, which is consistent with niche theory and the observation of the many differences between species in nature.

ecology↗