Dispersal–niche continuum index: a new quantitative metric for assessing the relative importance of dispersal versus niche processes in community assembly

Abstract

Patterns in community composition are scale‐dependent and generally difficult to distinguish. Therefore, quantifying the main assembly processes in various systems and across different datasets has remained challenging. Building on the PER‐SIMPER method, we propose a new metric, the dispersal–niche continuum index (DNCI), which estimates whether dispersal or niche processes dominate community assembly and facilitates the comparisons of processes among datasets. The DNCI was tested for robustness using simulations and applied to observational datasets comprising organismal groups with different trophic level and dispersal potential. Based on the robustness tests, the DNCI discriminated the respective contribution of niche and dispersal processes in pairwise comparisons of site groups with less than 40% and 30% differences in their taxa and site numbers, respectively. In the observational datasets, the DNCI suggested that dispersal rather than niche assembly was the dominant assembly process which, however, varied in intensity among organismal groups and study contexts, including spatial scale and ecosystem types. The proposed DNCI measures the relative strength of community assembly processes in a way that is simple, easily quantifiable and comparable across datasets. We discuss the strengths and weaknesses of the DNCI and provide perspectives for future research.

Divergent assembly processes? A comparison of the plant and soil microbiome with plant communities in a glacier forefield

“…Depending on the scale and the organisms under consideration, dispersal filters, environmental filters and/or interaction filters are the dominant processes explaining the composition and diversity of local plant or animal communities (Vellend 2010 ; Vilmi et al . 2021 ), which may be modulated by evolutionary and metacommunity dynamics (Mittelbach and Schemske 2015 ). This line of research aiming at identifying the mechanisms underlying species co-occurrence and local diversity is central to ecological theory and nature conservation (HilleRisLambers et al .…”

Improved detection of mass effect species assembly for applied metacommunity thinking

“…We can test this pure spatial to joint process continuum using the dispersal-niche continuum index (DNCI; Vilmi et al, 2021). The DNCI derives from a similarity percentage (SIMPER) analysis combined with three forms of occurrence matrix permutation (PER-SIMPER; to zero suggesting greater joint contribution (Vilmi et al, 2021).…”

“…The four watersheds provided natural site groups for determining each species' empirical profile, that is, per cent contribution to between-group overall average taxonomic dissimilarity (Gibert & Escarguel, 2019). Given the wide range in sample size (73 to 404 sites) among watersheds, and the simulation results in Vilmi et al (2021), we randomly subsampled each watershed to the smallest site group 100 times to eliminate potential group size bias. We analysed presence/absence data consistent with the species distribution modelling in Leboucher et al (2020).…”

“…We suggest using a niche width analysis (e.g. Fridley et al, 2007) or raw occupancy and abundance patterns for identifying generalists; the DNCI (Vilmi et al, 2021) to test for dispersal signal; probabilistic co-occurrence modelling to check for low rates of negative co-occurrence and rule out dispersal limitation (as in Leboucher et al, 2020); and null models of metacommunity coherence (Leibold & Mikkelson, 2002) to evaluate stochastic influences-removal of vagrant species and nonbreeding occurrences should mitigate stochastic effects (Bried et al, 2016) but users should bear in mind that mass effects involve source(breeding)-sink(nonbreeding) interactions (Leibold & Chase, 2018).…”

“…Mass effects involve local and regional processes that depending on scale and environmental heterogeneity range from surplus dispersal rates swamping out local niche differences to strong combined niche and dispersal influences (Heino et al, 2015; Leibold & Chase, 2018). We can test this pure spatial to joint process continuum using the dispersal–niche continuum index (DNCI; Vilmi et al, 2021). The DNCI derives from a similarity percentage (SIMPER) analysis combined with three forms of occurrence matrix permutation (PER‐SIMPER; Gibert & Escarguel, 2019).…”