Assessing metacommunity processes through signatures in spatiotemporal turnover of community composition

Abstract

Although metacommunity ecology has been a major field of research in the last decades, with both conceptual and empirical outputs, the analysis of the temporal dynamics of metacommunities has only emerged recently and consists mostly of repeated static analyses. Here we propose a novel analytical framework to assess metacommunity processes using path analyses of spatial and temporal diversity turnovers. We detail the principles and practical aspects of this framework and apply it to simulated datasets to illustrate its ability to decipher the respective contributions of entangled drivers of metacommunity dynamics. We then apply it to four empirical datasets. Empirical results support the view that metacommunity dynamics may be generally shaped by multiple ecological processes acting in concert, with environmental filtering being variable across both space and time. These results reinforce our call to go beyond static analyses of metacommunities that are blind to the temporal part of environmental variability.

Fragmentation promotes the role of dispersal in determining 10 intermittent headwater stream metacommunities

“…Such temporal changes in metacommunity processes in highly dynamic ecosystems have been conceptualised and ever more studies are indicating that shifts in metacommunity processes occur through time (e.g. Crabot, Clappe, et al, 2019;Jabot et al, 2020;Sarremejane, Cañedo-Argüelles, et al, 2017).…”

“…Such temporal changes in metacommunity processes in highly dynamic ecosystems have been conceptualised (Datry, Bonada, et al, 2016) and ever more studies are indicating that shifts in metacommunity processes occur through time (e.g. Crabot, Clappe, et al, 2019; Jabot et al., 2020; Sarremejane, Cañedo‐Argüelles, et al, 2017). Although beyond the scope of the present study, the discrepancies in metacommunity dynamics before and after the drying period call for a better understanding of how assembly processes are alternating in time in highly dynamic ecosystems.…”

“…Downes & Lancaster, 2018; Downes, Lancaster, Glaister, Bovill, & Strecker, 2017). However, research is still scarce in non‐perennial rivers fragmented by drying, possibly due to the inherent difficulties in assessing dispersal abilities for many organisms (Cañedo‐Argüelles et al., 2015; Heino et al., 2017; Sarremejane et al., 2019) and to the limitations of existing statistical tools (Crabot, Clappe, Dray, Datry, & McCrea, 2019; Jabot et al., 2020).…”

Joint species distributions reveal the combined effects of host plants, abiotic factors and species competition as drivers of species abundances in fruit flies

“…Community structure can be determined by several factors such as environmental filtering, interspecific interactions, regional species pool and dispersal (Müller et al 2011, D'Amen et al 2018, Nakadai et al 2018, Jabot et al 2020. Despite decades of research, estimating the relative importance of these processes on species distributions has proven particularly complex (Pollock et al 2014).…”

Deterministic processes drive functional and phylogenetic temporal changes of woody species in temperate forests in Northeast China

“…With longitudinal data, quantifying the functional or phylogenetic temporal change relative to species change provides important insights into two basic types of mechanisms: deterministic and stochastic processes (Cadotte et al 2011;Gianuca et al 2017;Stegen et al 2013;Swenson 2013). Stochastic processes entail random temporal change patterns, while deterministic, niche-based processes can constrain functional and phylogenetic change patterns to be nonrandom (Adler et al 2013;Götzenberger et al 2012;Jabot et al 2018;Letten et al 2014). Along ecological succession, communities undergo a joint influence of deterministic and stochastic processes, thus providing an ideal context to investigate the mechanisms underlying community temporal change (Connell and Slatyer 1977;Lohbeck et al 2014;Meiners et al 2015).…”