Résumé: AimTo assess contemporary and historical determinants of taxonomic and ecological trait turnover in birds worldwide. We tested whether taxonomic and trait turnover (1) are structured by regional bioclimatic conditions, (2) increase in relationship with topographic heterogeneity and environmental turnover and change according to current and historical environmental conditions, and (3) decrease with human impact. Major TaxaBirds. LocationGlobal. MethodsWe used computationally efficient algorithms to map the taxonomic and trait turnover of 8,040 terrestrial bird assemblages worldwide, based on a grid with 110km x 110 km resolution overlaid on the extent-of-occurrence maps of 7,964 bird species, and nine ecological traits reflecting six key aspects of bird ecology (diet, habitat use, thermal preference, migration, dispersal and body size). We used quantile regression and model selection to quantify the influence of biomes, environment (temperature, precipitation, altitudinal range, net primary productivity, Quaternary temperature and precipitation change) and human impact (human influence index) on bird turnover. ResultsBird taxonomic and trait turnover were highest in the north African deserts and boreal biomes. In the tropics, taxonomic turnover tended to be higher, but trait turnover was lower than in other biomes. Taxonomic and trait turnover exhibited markedly different or even opposing relationships with climatic and topographic gradients, but at their upper quantiles both types of turnover decreased with increasing human influence. Main conclusionsThe influence of regional, environmental and anthropogenic factors differ between bird taxonomic and trait turnover, consistent with an imprint of niche conservatism, environmental filtering and topographic barriers on bird regional assemblages. Human influence on these patterns is pervasive and demonstrates global biotic homogenization at a macroecological scale.

Résumé: Taxonomic nestedness, the degree to which the taxonomic composition of species-poor assemblages represents a subset of richer sites, commonly occurs in habitat fragments and islands differing in size and isolation from a source pool. However, species are not ecologically equivalent and the extent to which nestedness is observed in terms of functional trait composition of assemblages still remains poorly known. Here, using an extensive database on the functional traits and the distributions of 6316 tropical reef fish species across 169 sites, we assessed the levels of taxonomical vs functional nestedness of reef fish assemblages at the global scale. Functional nestedness was considerably more common than taxonomic nestedness, and generally associated with geographical isolation, where nested subsets are gradually more isolated from surrounding reef areas and from the center of biodiversity. Because a nested pattern in functional composition implies that certain combinations of traits may be represented by few species, we identified these groups of low redundancy that include large herbivore-detritivores and omnivores, small piscivores, and macro-algal herbivores. The identified patterns of nestedness may be an outcome of the interaction between species dispersal capabilities, resource requirements, and gradients of isolation among habitats. The importance of isolation in generating the observed pattern of functional nestedness within biogeographic regions may indicate that disturbance in depauperate and isolated sites can have disproportionate effects on the functional structure of their reef fish assemblages.

Résumé: Local species richness (SR) is a key characteristic affecting ecosystem functioning. Yet, the mechanisms regulating phytoplankton diversity in freshwater ecosystems are not fully understood, especially in peri-urban environments where anthropogenic pressures strongly impact the quality of aquatic ecosystems. To address this issue, we sampled the phytoplankton communities of 50 lakes in the Paris area (France) characterized by a large gradient of physico-chemical and catchment-scale characteristics. We used large phytoplankton datasets to describe phytoplankton diversity patterns and applied a machine-learning algorithm to test the degree to which species richness patterns are potentially controlled by environmental factors. Selected environmental factors were studied at two scales: the lake-scale (e.g. nutrients concentrations, water temperature, lake depth) and the catchment-scale (e.g. catchment, landscape and climate variables). Then, we used a variance partitioning approach to evaluate the interaction between lake-scale and catchment-scale variables in explaining local species richness. Finally, we analysed the residuals of predictive models to identify potential vectors of improvement of phytoplankton species richness predictive models. Lake-scale and catchment-scale drivers provided similar predictive accuracy of local species richness (R2 = 0.458 and 0.424, respectively). Both models suggested that seasonal temperature variations and nutrient supply strongly modulate local species richness. Integrating lake- and catchment-scale predictors in a single predictive model did not provide increased predictive accuracy; therefore suggesting that the catchment-scale model probably explains observed species richness variations through the impact of catchment-scale variables on in-lake water quality characteristics. Models based on catchment characteristics, which include simple and easy to obtain variables, provide a meaningful way of predicting phytoplankton species richness in temperate lakes. This approach may prove useful and cost-effective for the management and conservation of aquatic ecosystems.