Positive interactions and the emergence of community structure in metacommunities

TL;DR

This study uses a spatially explicit metacommunity model to explore how local dispersal influences community structure, diversity, and interactions, revealing phase transitions and contrasting effects of connectivity on stability and biodiversity.

Contribution

It introduces a model analyzing the impact of spatial dispersal on community structure with multiple interaction types, highlighting phase transitions and the role of spatial interconnectedness.

Findings

Low dispersal promotes mutualistic, stable communities.

High dispersal enhances local biodiversity but reduces stability.

Community structure undergoes phase transitions with dispersal rate.

Abstract

The significant role of space in maintaining species coexistence and determining community structure and function is well established. However, community ecology studies have mainly focused on simple competition and predation systems, and the relative impact of positive interspecific interactions in shaping communities in a spatial context is not well understood. Here we employ a spatially explicit metacommunity model to investigate the effect of local dispersal on the structure and function of communities in which species are linked through an interaction web comprising mutualism, competition and exploitation. Our results show that function, diversity and interspecific interactions of locally linked communities undergo a phase transition with changes in the rate of species dispersal. We find that low spatial interconnectedness favors the spontaneous emergence of strongly mutualistic communities which are more stable but less productive and diverse. On the other hand, high spatial interconnectedness promotes local biodiversity at the expense of local stability and supports communities with a wide range of interspecific interactions. We argue that investigations of the relationship between spatial processes and the self-organization of complex interaction webs are critical to understanding the geographic structure of interactions in real landscapes.