Reconceptualising the beta diversity‐environmental heterogeneity relationship in running water systems

Abstract

Summary Beta diversity modelling has received increased interest recently. There are multiple definitions of beta diversity, but here, we focus on variability in species composition among sampling units within a given area. This facet can be described using various approaches. Some approaches ignore the spatial scale of the area considered (i.e. region limits), while some consider different region limits as a starting point for the analysis of beta diversity. We focused specifically on the beta diversity–environmental heterogeneity relationship in running waters. First, we present two conceptual models, which assume either (1) strong environmental control among localities (riffle sites in our case) within each region unit (a region unit encompasses a species pool and can be a stream or a basin or an ecoregion) or (2) that the spatial level of a region unit affects the relative importance of mechanisms affecting variability in species composition among localities (i.e. among riffle sites) within each region unit. Second, we compared three recent studies that used similar methods to examine the beta diversity–environmental heterogeneity relationship, but which were based on different region units, comprising sets of streams or sets of basins or sets of ecoregions. Our conceptual framework assumes that environmental control is not likely to be the sole mechanism affecting variability in community composition among localities within each region unit, but it is likely to be most important when dispersal rates are intermediate (i.e. among localities within a basin). In contrast, if dispersal rates are very high (i.e. among localities within a stream) or very low (i.e. among localities within an ecoregion), environmental control is in part masked by high dispersal rates or is prevented from occurring because not all species can reach all localities, respectively. Such scale dependency in the relative strength of environmental control might therefore transcend spatial scales from individual region units to the strength of the beta diversity–environmental heterogeneity relationship. We emphasise that the beta diversity–environmental heterogeneity relationship can only be tested across multiple region units. The results of three case studies are consistent with these predictions. Specifically, the beta diversity–environmental heterogeneity regression was highly significant across multiple basins, but not across multiple streams or across multiple ecoregions. We suggest that researchers take spatial scale and region unit level explicitly into account when inferring the mechanisms structuring ecological communities and mapping variation in beta diversity. We also propose a unified terminology for studies examining the beta diversity–environmental heterogeneity relationship in running waters because inconsistent terminology is likely to hamper the progress of our science.

Context dependency in biodiversity patterns of central German stream metacommunities

“…Disentangling metacommunity patterns and underlying processes requires an understanding of not only local environmental influences (i.e. Given the strong ties between the theoretical foundations of meta-community ecology and the drivers of beta diversity, understanding beta diversity patterns also necessitates hypotheses developed in the context of metacommunity theory (Heino, Melo & Bini, 2015a). Given the strong ties between the theoretical foundations of meta-community ecology and the drivers of beta diversity, understanding beta diversity patterns also necessitates hypotheses developed in the context of metacommunity theory (Heino, Melo & Bini, 2015a).…”

Simulating the role of connectivity in shaping stream insect metacommunities under colonization cycle dynamics

“…from the perspective of multiple communities connected by dispersing organisms that are subject to the combined effects of environmental filtering and dispersal limitation (Leibold et al, 2004;Winegardner et al, 2012). As a consequence, the role of habitat connectivity has received attention from both scientists and managers (e.g., in aquatic ecology, Auerbach and Poff, 2011;Brown et al, 2011;Campbell Grant et al, 2007;Carrara et al, 2014;Heino et al, 2015a;Lowe and Bolger, 2002). Connectivity can be defined as "the degree to which the landscape facilitates or impedes movement among resource patches" (Taylor et al, 1993).…”

“…However, the role of connectivity in shaping metacommunities may depend on various factors driving spatial variation in a given metacommunity. Studies on metacommunity ecology have shown that niche and dispersalassembly processes cannot be viewed independently of each other, but as two extremes of a continuum (Gravel et al, 2006;Heino et al, 2015a;Logue et al, 2011;Winegardner et al, 2012). At the niche-assembly extreme, metacommunity structure is determined by organisms' responses to environmental factors, whereas at the more neutral, dispersal-assembly extreme, metacommunity structure is mainly a result of dispersal limitation, speciation and ecological drift, rather than on the ecological differences between species (Hubbell, 2001).…”

Temporal and spatial dynamics of fish community structure during watershed alteration in two Ouachita River systems

“…Beta diversity (β-diversity), the degree of variation in community composition among sampling sites within a given area (i.e., region unit; Heino, Melo, & Bini, 2015), can be compared across samples taken at different times and used to reveal whether communities have become more similar through time (i.e., biotic homogenisation).…”