DUGi

Environmental filtering determines metacommunity structure in wetland microcrustaceans

http://dugi.udg.edu/item/http:@@@@hdl.handle.net@@2072@@299516

Metacommunity approaches are becoming popular when analyzing factors driving species distribution at the regional scale. However, until the popularization of the variation partitioning technique it was difficult to assess the main drivers of the observed patterns (spatial or environmental). Here we propose a new framework linking the emergence of different metacommunity structures (e.g., nested, Gleasonian, Clementsian) to spatial and environmental filters. This is a novel approach that provides a more profound analysis of how both drivers could lead to similar metacommunity structures. We tested this framework on 110 sites covering a strong environmental gradient (i.e., microcrustacean assemblages organized along a salinity gradient, from freshwater to brackish water wetlands). First we identified the metacommunity structure that better fitted these microcrustacean assemblages. Then, we used hierarchical variation partitioning to quantify the relative influences of environmental filters and the distance among wetlands on the identified structure. Our results showed that under strong environmental filtering metacommunity structures were non-random. We also noted that even passive dispersers, that are supposed to be poorly spatially filtered, showed spatial signals at a large geographical scale. However, some difficulties arose when inferring biotic interactions at finer-scale spatial signals. Overall, our study shows the potential of elements of metacommunity structure combined with variation partition techniques to detect environmental drivers and broadscale patterns of metacommunity structure, and that some caution is needed when interpreting finer-scale spatial signals

This work was financially supported by the Catalan Water Agency, the Ministerio de Ciencia e Innovación (CGL2011-23907), and the Generalitat de Catalunya (ref. 2014 SGR 484).

Springer Verlag