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Keywords:

  • Beta diversity;
  • community assembly;
  • eastern North America;
  • environmental filtering;
  • functional traits;
  • species turnover;
  • temperate forest;
  • trees

Abstract

Aim

Determining the relative influence of niche-based and neutral processes in driving the spatial turnover of community composition is a central challenge in community ecology. Spatial patterns of functional turnover, or functional beta diversity, may capture important signals of niche-based assembly processes, but these patterns have not been quantified for communities across broad geographic and environmental gradients. Here, we analyse continental-scale patterns of species and functional beta diversity in relation to space and the environment to assess the relative importance of niche-based and neutral community assembly mechanisms.

Location

Eastern North America.

Methods

We use a continental-scale forest plot dataset and functional trait data to quantify spatial patterns of species and functional beta diversity. We use redundancy analysis-based variance partitioning to evaluate the influence of space, soil and climate on beta-diversity metrics. We use a null model approach to test for non-random functional beta diversity given the observed patterns of species turnover across spatial scales.

Results

Species and functional beta diversity increased with increasing geographic distance (i.e. distance decay of community similarity). Results of variance partitioning analysis show that species and functional beta diversity were spatially structured and significantly related to environmental, particularly climatic, variation. Results of null model analysis show that functional beta diversity was lower than expected based on species turnover at fine scales (< 600 km) and higher than expected at broad scales (> 1800 km).

Main conclusions

The observed patterns of functional beta diversity support a niche-based model of community assembly, driven by the deterministic filtering of species across environmental gradients based on their functional traits.