Aurèle Toussaint
Chargé de recherche (CR) / Researcher
My research sits at the interface of macroecology, functional ecology, and conservation biology, with a focus on understanding how the functional diversity of vertebrates and plants is distributed across the globe, what processes generate and maintain these patterns, and how anthropogenic pressures are reshaping them.
A central theme of my work is the functional diversity of freshwater fishes. During my PhD and subsequent projects, I built one of the largest morphological trait databases for freshwater fishes, covering more than 9,000 species across more than 1,000 river basins worldwide. This work revealed that functional diversity is highly concentrated in the Neotropics — which host more than 75% of global functional diversity — and is only weakly correlated with species richness at macroecological scales. I showed that the introduction of non-native species has fundamentally restructured the functional composition of fish assemblages worldwide, increasing functional diversity by up to 150% on average while simultaneously driving taxonomic homogenization through the dominance of a few widespread invasive species.
A second major axis of my research concerns the consequences of biodiversity loss for functional diversity. I have demonstrated that the extinction of threatened vertebrates will not lead to uniform losses of functional diversity, but rather to idiosyncratic changes that vary substantially across biogeographic realms and taxonomic groups. In birds, I showed that non-native species will not compensate for the functional and phylogenetic diversity lost following the extinction of threatened species, highlighting the irreplaceable role of native biodiversity in sustaining ecosystem functioning.
More recently, I have been investigating intraspecific trait variability as a neglected but critical component of functional diversity. The INTRAIT project aims to quantify morphological variation within freshwater fish species in French Guiana and to assess how ignoring this variability biases community-level estimates of functional diversity.
Across all these research axes, I employ a combination of large-scale trait databases, multivariate statistics, and simulation approaches implemented in R. My work has been published in leading international journals: