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

Annika Vilmi,Konsta Happonen,Corentin Gibert,Gilles Escarguel,Félix Picazo,Janne Soininen,Aurélien Jamoneau,Jianjun Wang,Sophia I Passy,Jani Heino,Juliette Tison‐Rosebery

doi:10.1111/ecog.05356

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.

Highlights

Understanding how biological communities are assembled is one of the main goals of community ecology, macroecology and biogeography
We developed a novel quantitative index, dispersal–niche continuum index (DNCI), to disentangle the importance of niche and dispersal processes in community assembly, with distinct advantages over existing methods, including earlier null model approaches (Chase et al 2011), variance partitioning in constrained ordination (Borcard et al 1992) and PER-SIMPER’s original qualitative inference procedure (Gibert and Escarguel 2019)
The DNCI allows evaluating whether the dominant assembly mechanism and its strength vary across different datasets

Summary

Introduction

Understanding how biological communities are assembled is one of the main goals of community ecology, macroecology and biogeography. Variation partitioning in constrained ordination (Borcard et al 1992) is another widely implemented method It assesses the effects of environmental conditions (a proxy for niche processes) and space (a proxy for dispersal) on community assembly, and it relies on detailed data on community composition, environmental factors and geographic locations. PER-SIMPER utilizes sites-by-taxa community matrices, generating three distinct null models, constraining rows (‘niche assembly’), columns (‘dispersal assembly’) or both during permutations It uses the SIMPER (Clarke 1993) method to model the original community matrix compositional similarity pattern and to detect the empirical model profile, which is compared to the three null distribution profiles (hereafter called ‘null PER-SIMPER profiles’, Fig. 1). We discussed the strengths and weaknesses of the DNCI in inferring community assembly processes and suggested potential research avenues

Material and methods

Results

Discussion

Findings

Data availability statement