Towards a multi‐trophic extension of metacommunity ecology

Abstract

Metacommunity theory provides an understanding of how spatial processes determine the structure and function of communities at local and regional scales. Although metacommunity theory has considered trophic dynamics in the past, it has been performed idiosyncratically with a wide selection of possible dynamics. Trophic metacommunity theory needs a synthesis of a few influential axis to simplify future predictions and tests. We propose an extension of metacommunity ecology that addresses these shortcomings by incorporating variability among trophic levels in ‘spatial use properties’. We define ‘spatial use properties’ as a set of traits (dispersal, migration, foraging and spatial information processing) that set the spatial and temporal scales of organismal movement, and thus scales of interspecific interactions. Progress towards a synthetic predictive framework can be made by (1) documenting patterns of spatial use properties in natural food webs and (2) using theory and experiments to test how trophic structure in spatial use properties affects metacommunity dynamics.

Top predator introduction changes the effects of spatial isolation on freshwater community structure

“…Our results are more aligned with multi-trophic metacommunities that consider interspecific variation in dispersal rates ( i.e. Vellend et al 2014; Guzman et al 2019). Because the species in our communities have different dispersal rates, isolation was not only a process that increases stochasticity in the frequency of species arrival ( i.e.…”

“…More importantly, the effects of fish and isolation are highly dependent on each other in ways that differ from those expected by classic metacommunity models ( e.g. Mouquet & Loreau 2003; Leibold et al 2004; Leibold & Chase 2018), but similar to what would be expected for multitrophic metacommunities with variable dispersal rates among species (Vellend et al 2014; Guzman et al 2019).…”

“…Thus, niche selection processes are more likely to shape community structure in intermediate levels of dispersal rate or intermediate levels of connectivity. However, it is also important to incorporate interspecific variation in dispersal rates and not only mean dispersal rates (Levins & Culver 1971; Finlay et al 2002; McCann et al 2005; Shurin et al 2009; Astorga et al 2012; Vellend et al 2014; Guzman et al 2019). Vellend et al (2014), for example, suggested that variation in dispersal rates can reduce the effect of stochasticity because species with higher dispersal rates would always colonize a patch first, leaving less room for the establishment of different community structures.…”

“…Freshwater pond species can vary substantially in dispersal and colonization rates (Bilton et al 2001; Shulman & Chase 2007; Chase & Shulman 2009; Shurin et al 2009; Guzman et al 2019) and such rates can vary with trophic level among invertebrates. For example, predatory insects tend to have larger body sizes than consumers, and thus higher locomotory ability (McCann et al 2005).…”

Spatial insurance in multi‐trophic metacommunities

“…Empirical studies have found that the buffering capacity of dispersal depends on the stressor and the ecosystem metric (Thompson & Shurin ; Symons & Arnott ) and varies widely among studies (Eggers et al ; Lindo et al ; Thompson & Shurin ; Symons & Arnott ; de Boer et al ). Part of this complexity likely stems from environmental change and dispersal having differential effects on different groups of organisms (Voigt et al ; De Bie et al ; Guzman et al ). Consequently, the capacity of dispersal to mitigate effects of environmental change could vary among functional and trophic groups.…”