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Gervais, L.

Publications and source records attributed to Gervais, L..

3 recordsLinked to original sources

Thermal performance in fishes varies systematically across latitude, habitat, and biological organization

Thermal performance curves are widely used to understand how ectotherms respond to anthropogenic climate change, yet comparable data remain fragmented for fishes despite their predicted sensitivity to warming. Here we introduce FishTherm, a compilation of 457 thermal responses from 107 wild fish species, spanning diverse performance metrics and temperatures. With this dataset, we estimated thermal optima, performance breadth, tolerance breadth, and activation energies, and tested how these thermal traits vary geographically, across latitude and habitat, and by type and functional context of performance. Thermal optima increase toward lower latitudes and warmer waters, consistent with established biogeographic patterns. We also found that responses measured at lower levels of biological organization exhibit higher thermal optima than population-level responses, supporting complexity constraints on thermal performance curves. Activation energies broadly matched predictions from the Metabolic Theory of Ecology, and we further found systematic variation of lower values in negatively-motivated responses, and associated with narrower thermal performance breadths, in line with theory. Our results provide supporting evidence for several unifying principles that advance our understanding of constraints and variation in thermal performance. FishTherm is a new resource for comparative thermal ecology and for improving our understanding of fish vulnerability under climate warming.

ecology↗

Tit wit: environmental and genetic drivers of cognitive variation along an urbanization gradient

Cognitive abilities can promote acclimation and adaptation to life in cities. However, the genetic versus environmental drivers of cognition have rarely been studied in the wild and there exists a major gap concerning the role of cognition in adaptation to novel urban contexts. To address this, we evaluate cognitive variation in wild great tits (Parus major; N = 393) along an urban gradient, and decipher the genetic basis of this variation using a combination of a common garden experiment, quantitative genetic analyses, and genome-wide association studies. Specifically, we measure inhibitory control abilities which affect how animals respond to novel resources and challenges. We find that wild urban and forest tits do not clearly differ in inhibitory control performance (number of errors or the latency to escape) during a motor detour task; a result that was consistent in birds from urban and forest origins reared in a common garden (N = 73). Cognitive performance was repeatable (R = 0.35 - 0.38) and showed low to moderate heritability in the wild (h2= 0.16 - 0.28 using social and genomic pedigrees). We identified five SNPs that were significantly associated with the number of errors during the task, explaining 21% of the cognitive variation. These SNPs are linked to genes related to serotonergic and dopaminergic systems that are known to play important roles in cognition. Altogether, our study finds limited evidence that inhibitory control abilities have evolved under novel urban contexts, yet reveals a genetic basis of this cognitive trait in great tits.

animal behavior and cognition↗

RAD-sequencing for estimating GRM-based heritability in the wild: a case study in roe deer

Estimating the evolutionary potential of quantitative traits and reliably predicting responses to selection in wild populations are important challenges in evolutionary biology. The genomic revolution has opened up opportunities for measuring relatedness among individuals with precision, enabling pedigree-free estimation of trait heritabilities in wild populations. However, until now, most quantitative genetic studies based on a genomic relatedness matrix (GRM) have focused on long-term monitored populations for which traditional pedigrees were also available, and have often had access to knowledge of genome sequence and variability. Here, we investigated the potential of RAD-sequencing for estimating heritability in a free-ranging roe deer population for which no prior genomic resources were available. We propose a step-by-step analytical framework to optimize the quality and quantity of the genomic data and explore the impact of the SNP calling and filtering processes on the GRM structure and GRM-based heritability estimates. As expected, our results show that sequence coverage strongly affects the number of recovered loci, the genotyping error rate and the amount of missing data. Ultimately, this had little effect on heritability estimates and their standard errors, provided that the GRM was built from a minimum number of loci (above 7000). GRM-based heritability estimates thus appear robust to a moderate level of genotyping errors in the SNP dataset. We also showed that quality filters, such as the removal of low-frequency variants, affect the relatedness structure of the GRM, generating lower h2 estimates. Our work illustrates the huge potential of RAD-sequencing for estimating GRM-based heritability in virtually any natural population.

genomics↗