<p>Groups have been constructed using the correlation coefficients between layers. Models in the same group indicate that their predictions are highly correlated. This table may help researchers to select the GCMs for constructing their ecological niche models, to generate a more complete picture of the potential variability of the species ranges. Researchers should choose at least one model from each different group for each variable used for constructing their ecological niche models.</p><p>Results from the hierarchical clustering analysis (k = 4) identifying the groups of general circulation models (GCMs) that have similar predictions for each variable at a global scale.</p
A multivariate statistical clustering technique— based on the iterative k-means algorithm of Hartiga...
Variation in the abundance of species in space and/or time can be caused by a wide range of underlyi...
Species distribution models have many applications in conservation and ecology, and climate data are...
<p>Hierarchical cluster grouping the nine GCMs by the correlation of their predictions for all 19 bi...
<div><p>Ensemble forecasting is advocated as a way of reducing uncertainty in species distribution m...
Ensemble forecasting is advocated as a way of reducing uncertainty in species distribution modeling ...
Understanding the causes of spatial variation in species richness is a major research focus of bioge...
<p>Maps show differences between the projected climatic habitat distributions (2071–2100) obtained u...
<p>The graphs show the mean and 95% confidence intervals across clades of the 2A) mean within clade ...
Although biogeographic patterns are the product of complex ecological processes, the increasing comp...
Aim Community ecologists often compare assemblages. Alternatively, one may compare species distribut...
Variation in the abundance of species in space and/or time can be caused by a wide range of underlyi...
International audienceEcological Niche Models (ENMs) are increasingly used by ecologists to project ...
<p>Colors with higher values show areas with more suitable predicted conditions. ENM for the total, ...
<p>We added five new species to the dataset and preformed hierarchical clustering with the establish...
A multivariate statistical clustering technique— based on the iterative k-means algorithm of Hartiga...
Variation in the abundance of species in space and/or time can be caused by a wide range of underlyi...
Species distribution models have many applications in conservation and ecology, and climate data are...
<p>Hierarchical cluster grouping the nine GCMs by the correlation of their predictions for all 19 bi...
<div><p>Ensemble forecasting is advocated as a way of reducing uncertainty in species distribution m...
Ensemble forecasting is advocated as a way of reducing uncertainty in species distribution modeling ...
Understanding the causes of spatial variation in species richness is a major research focus of bioge...
<p>Maps show differences between the projected climatic habitat distributions (2071–2100) obtained u...
<p>The graphs show the mean and 95% confidence intervals across clades of the 2A) mean within clade ...
Although biogeographic patterns are the product of complex ecological processes, the increasing comp...
Aim Community ecologists often compare assemblages. Alternatively, one may compare species distribut...
Variation in the abundance of species in space and/or time can be caused by a wide range of underlyi...
International audienceEcological Niche Models (ENMs) are increasingly used by ecologists to project ...
<p>Colors with higher values show areas with more suitable predicted conditions. ENM for the total, ...
<p>We added five new species to the dataset and preformed hierarchical clustering with the establish...
A multivariate statistical clustering technique— based on the iterative k-means algorithm of Hartiga...
Variation in the abundance of species in space and/or time can be caused by a wide range of underlyi...
Species distribution models have many applications in conservation and ecology, and climate data are...