Dataset Information

Testing the Effectiveness of Environmental Variables to Explain European Terrestrial Vertebrate Species Richness across Biogeographical Scales.

ABSTRACT: We compared the effectiveness of environmental variables, and in particular of land-use indicators, to explain species richness patterns across taxonomic groups and biogeographical scales (i.e. overall pan-Europe and ecoregions within pan-Europe). Using boosted regression trees that handle non-linear relationships, we compared the relative influence (as a measure of effectiveness) of environmental variables related to climate, landscape (or habitat heterogeneity), land-use intensity or energy availability to explain European vertebrate species richness (birds, amphibians, and mammals) at the continental and ecoregion scales. We found that dominant land cover and actual evapotranspiration that relate to energy availability were the main correlates of vertebrate species richness over Europe. At the ecoregion scale, we identified four distinct groups of ecoregions where species richness was essentially associated to (i) seasonality of temperature, (ii) actual evapotranspiration and/or mean annual temperature, (iii) seasonality of precipitation, actual evapotranspiration and land cover) and (iv) and an even combination of the environmental variables. This typology of ecoregions remained valid for total vertebrate richness and the three vertebrate groups taken separately. Despite the overwhelming influence of land cover and actual evapotranspiration to explain vertebrate species richness patterns at European scale, the ranking of the main correlates of species richness varied between regions. Interestingly, landscape and land-use indicators did not stand out at the continental scale but their influence greatly increased in southern ecoregions, revealing the long-lasting human footprint on land-use-land-cover changes. Our study provides one of the first multi-scale descriptions of the variability in the ranking of correlates across several taxa.

SUBMITTER: Mouchet M

PROVIDER: S-EPMC4498906 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Testing the Effectiveness of Environmental Variables to Explain European Terrestrial Vertebrate Species Richness across Biogeographical Scales.

Mouchet Maud M Levers Christian C Zupan Laure L Kuemmerle Tobias T Plutzar Christoph C Erb Karlheinz K Lavorel Sandra S Thuiller Wilfried W Haberl Helmut H

PloS one 20150710 7

We compared the effectiveness of environmental variables, and in particular of land-use indicators, to explain species richness patterns across taxonomic groups and biogeographical scales (i.e. overall pan-Europe and ecoregions within pan-Europe). Using boosted regression trees that handle non-linear relationships, we compared the relative influence (as a measure of effectiveness) of environmental variables related to climate, landscape (or habitat heterogeneity), land-use intensity or energy av ...[more]

PMID: 26161981

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Project description:BackgroundWhy biodiversity is not uniformly distributed on the Earth is a major research question of biogeography. One of the most striking patterns of disparity in species distribution are the biodiversity hotspots, which generally do not fit with the distribution of relevant components of the Neotropical biota. In this study, we assess the proximal causes of the species-richness pattern of one of the most conspicuous groups of Neotropical mammals, the New World monkeys the Platyrrhini. We test two complementary hypotheses: (1) there is a historical source-sink dynamic (addressed using macroevolutionary and macroecological approaches); (2) the large number of species in the Amazon basin is due to the constraints imposed by environmental variables occurring outside this area.MethodsWe first characterize spatial patterns of species richness and biodiversity hotspots using a new, objective protocol based on probabilities. Then we evaluate the source-sink hypothesis using BioGeoBEARS analysis and nestedness analysis of species richness patterns. Complementarily, to measure how often different species pairs appear in the same sites, we used null models to estimate the checkerboard score index (C-score). Finally, we evaluate the relationship between several climatic variables and species richness through ordinary least squares (OLS) and spatial autoregressive (SAR) models, and the potential environmental constraints on the pattern.ResultsWe found one significant cluster of high values for species richness in the Amazon basin. Most dispersal events occurred from the Amazonian subregion to other Neotropical areas. Temperature (T), discrepancy (BR), and NODF indexes show a significant nesting in the matrix ordered by species richness and available energy. The C-score observed was significantly smaller than the null expectation for all sites in the Neotropics where there are records of platyrrhine species. Ten climatic variables comprised the best-fitting model that explains species richness. OLS and SAR models show that this set of variables explains 69.9% and 64.2% of species richness, respectively. Potential of evapotranspiration is the most important variable within this model, showing a linear positive relationship with species richness, and clear lower and upper limits to the species richness distribution.DiscussionWe suggest that New World monkeys historically migrated from their biodiversity hotspot (energetically optimal areas for most platyrrine species) to adjacent, energetically suboptimal areas, and that the different dispersal abilities of these species, the lack of competitive interactions at a macroecological scale, and environmental constraints (i.e., energy availability, seasonality) are key elements which explain the non-uniform pattern of species richness for this clade.

Dataset Information

Testing the Effectiveness of Environmental Variables to Explain European Terrestrial Vertebrate Species Richness across Biogeographical Scales.

Publications

Testing the Effectiveness of Environmental Variables to Explain European Terrestrial Vertebrate Species Richness across Biogeographical Scales.

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