A family of null models to distinguish between environmental filtering and biotic interactions in functional diversity patterns

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Traditional null models used to reveal assembly processes from functional diversity patterns are not tailored for comparing different spatial and evolutionary scales. In this study, we present and explore a family of null models that can help disentangling assembly processes at their appropriate scales and thereby elucidate the ecological drivers of community assembly.


French Alps.


Our approach gradually constrains null models by: (1) filtering out species not able to survive in the regional conditions in order to reduce the spatial scale, and (2) shuffling species only within lineages of different ages to reduce the evolutionary scale of the analysis. We first tested and validated this approach using simulated communities. We then applied it to study the functional diversity patterns of the leaf–height–seed strategy of plant communities in the French Alps.


Using simulations, we found that reducing the spatial scale correctly detected a signature of competition (functional divergence) even when environmental filtering produced an overlaying signal of functional convergence. However, constraining the evolutionary scale did not change the identified functional diversity patterns. In the case study of alpine plant communities, investigating scale effects revealed that environmental filtering had a strong influence at larger spatial and evolutionary scales and that neutral processes were more important at smaller scales. In contrast to the simulation study results, decreasing the evolutionary scale tended to increase patterns of functional divergence.


We argue that the traditional null model approach can only identify a single main process at a time and suggest to rather use a family of null models to disentangle intertwined assembly processes acting across spatial and evolutionary scales.

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