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Keywords:

  • AUC;
  • bioclimate envelope model;
  • climate change;
  • ecological niche factor;
  • Great Britain;
  • multivariate statistics;
  • ordination

Abstract

Aim  Species distribution models are increasingly used to predict the impacts of global change on whole ecological communities by modelling the individualistic niche responses of large numbers of species. However, it is not clear whether this single-species ensemble approach is preferable to community-wide strategies that represent interspecific associations or shared responses to environmental gradients. Here, we test the performance of two multi-species modelling approaches against equivalent single-species models.

Location  Great Britain.

Methods  Single- and multi-species distribution models were fitted for 701 native British plant species at a 10-km grid scale. Two machine learning methods were used – classification and regression trees (CARTs) and artificial neural networks (ANNs). The single-species versions are widely used in ecology but their multivariate extensions are less well known and have not previously been evaluated against one another. We compared their abilities to predict species distributions, community compositions and species richness in an independent geographical region reserved from model-fitting.

Results  The single- and multi-species models performed similarly, although the community models gave slightly poorer predictive accuracy by all measures. However, from the point of view of the whole community they were much simpler than the array of single-species models, involving orders of magnitude fewer parameters. Multi-species approaches also left greater residual spatial autocorrelation than the individualistic models and, contrary to expectation, were relatively less accurate for rarer species. However, the fitted multi-species response curves had lower tendency for pronounced discontinuities that are unlikely to be a feature of realized niche responses.

Main conclusions  Although community distribution models were slightly less accurate than single-species models, they offered a highly simplified way of modelling spatial patterns in British plant diversity. Moreover, an advantage of the multi-species approach was that the modelling of shared environmental responses resolved more realistic response curves. However, there was a slight tendency for community models to predict rare species less accurately, which is potentially disadvantageous for conservation applications. We conclude that multi-species distribution models may have potential for understanding and predicting the structure of ecological communities, but were slightly inferior to single-species ensembles for our data.