A quantitative framework to estimate the relative importance of environment, spatial variation and patch connectivity in driving community composition. (March 2017)

• Record Type: Journal Article
• Authors: Monteiro, Viviane F.; Paiva, Paulo C.; Peres‐Neto, Pedro R.
• Editors: Webb, Tom
• Is Part Of: Journal of animal ecology. Volume 86:Number 2(2017:Mar.)
• Page Start: 316
• Page End: 326
• Publication Date: 2017-03
• Subjects: canonical analysis -- connectivity -- metacommunity ecology -- polychaete -- spatial autocorrelation -- species distributions -- variation partitioning; Animal ecology -- Periodicals; 591.7
• DOI: 10.1111/1365-2656.12619
• Languages: English
• ISSNs: 0021-8790

Abstract

Summary: Perhaps the most widely used quantitative approach in metacommunity ecology is the estimation of the importance of local environment vs. spatial structuring using the variation partitioning framework. Contrary to metapopulation models, however, current empirical studies of metacommunity structure using variation partitioning assume a space‐for‐dispersal substitution due to the lack of analytical frameworks that incorporate patch connectivity predictors of dispersal dynamics. Here, a method is presented that allows estimating the relative importance of environment, spatial variation and patch connectivity in driving community composition variation within metacommunities. The proposed approach is illustrated by a study designed to understand the factors driving the structure of a soft‐bottom marine polychaete metacommunity. Using a standard variation partitioning scheme (i.e. where only environmental and spatial predictors are used), only about 13% of the variation in metacommunity structure was explained. With the connectivity set of predictors, the total amount of explained variation increased up to 51% of the variation. These results highlight the importance of considering predictors of patch connectivity rather than just spatial predictors. Given that information on connectivity can be estimated by commonly available data on species distributions for a number of taxa, the framework presented here can be readily applied to past studies as well, facilitating a more robust evaluation of the factors contributing to metacommunity structure. Abstract : In this study, for the first time, the authors extended the metapopulation style of modelling to metacommunities within the variation partitioning framework to estimate the relative contributions of dispersal and environment in determining variation in community composition across patches.