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bioRxiv · 10.1101/588947

Taxonomic and functional anuran beta diversity of the subtropical metacommunity respond differentially to environmental and spatial predictors

Dalmolin, D. A.·Ramos Pereira, M. J. V. d. C.·Tozetti, A. M.
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Abstract

The relative contributions of environmental and spatial predictors in the patterns of taxonomic and functional anuran beta diversity were examined in 33 ponds of a metacommunity along the coast of south Brazil. Anurans exhibit limited dispersion ability and have physiological and behavioural characteristics that narrow their relationships with both environmental and spatial predictors. So, we expected that neutral processes and, in particular, niche-based processes could have similar influence on the taxonomic and functional beta diversity patterns. Variation partitioning and distance-based methods (db-RDA) were conducted with presence/absence and abundance data to examine taxonomic and functional facets and components (total, turnover and nestedness-resultant) in relation to environmental and spatial predictors. Processes determining metacommunity structure were similar between the components of beta diversity but differed among taxonomic and functional diversity. While taxonomic beta diversity was further accounted by environmental predictors, functional beta diversity responded more strongly to spatial predictors. These patterns were more evident when assessed through abundance data. These opposing patterns were contrary to what we had predicted, suggesting that while there is a taxonomic turnover mediated by environmental filters, the spatial distance promotes the trait dissimilarity between sites. Our results reinforce the idea that studies aiming to evaluate the patterns of structure in metacommunities should include different facets of diversity so that better interpretations can be achieved.

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Dalmolin, D. A., Ramos Pereira, M. J. V. d. C., Tozetti, A. M.. 2019-03-25. Taxonomic and functional anuran beta diversity of the subtropical metacommunity respond differentially to environmental and spatial predictors. https://doi.org/10.1101/588947

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