Do community-level models describe community variation effectively?
The aim of community-level modelling is to improve the performance of species distributional models by taking patterns of co-occurrence among species into account. Here, we test this expectation by examining how well three community-level modelling strategies (‘assemble first, predict later’, ‘predict first, assemble later’, and ‘assemble and predict together’) spatially project the observed composition of species assemblages. Location
Variation in the composition of European tree assemblages and its spatial and environmental correlates were examined with cluster analysis and constrained analysis of principal coordinates. Results were used to benchmark spatial projections from three community-based strategies: (1) assemble first, predict later (cluster analysis first, then generalized linear models, GLMs); (2) predict first, assemble later (GLMs first, then cluster analysis); and (3) assemble and predict together (constrained quadratic ordination). Results
None of the community-level modelling strategies was able to accurately model the observed distribution of tree assemblages in Europe. Uncertainty was particularly high in southern Europe, where modelled assemblages were markedly different from observed ones. Assembling first and predicting later led to distribution models with the simultaneous occurrence of several types of assemblages in southern Europe that do not co-occur, and the remaining strategies yielded models with the presence of non-analogue assemblages that presently do not exist and that are much more strongly correlated with environmental gradients than with the real assemblages. Main conclusions
Community-level models were unable to characterize the distribution of European tree assemblages effectively. Models accounting for co-occurrence patterns along environmental gradients did not outperform methods that assume individual responses of species to climate. Unrealistic assemblages were generated because of the models’ inability to capture fundamental processes causing patterns of covariation among species. The usefulness of these forms of community-based models thus remains uncertain and further research is required to demonstrate their utility.