Disentangling the interactive effects of anthropogenic disturbances on biodiversity

TL;DR

This paper presents a unified theoretical model integrating multiple coexistence mechanisms to better understand how anthropogenic disturbances affect biodiversity patterns and species coexistence.

Contribution

It introduces a novel method to incorporate habitat autocorrelation into differential equations, revealing complex interactions influencing biodiversity under disturbance.

Findings

Interactions between mechanisms are crucial for species coexistence.

Biodiversity patterns can shift from unimodal to bimodal along disturbance gradients.

Habitat loss has a stronger impact than habitat autocorrelation in highly disturbed scenarios.

Abstract

Anthropogenic activity threatens biodiversity through climate change, habitat fragmentation, and increasing frequency and scale of disturbance. Various theoretical studies have sought to shed light on how these factors could promote or hinder the coexistence of species. However, our understanding of the relative importance of, and interactions between, these factors remains limited. In this study, we employ a theoretical approach integrating three commonly cited coexistence mechanisms -- the competition-colonisation trade-off, the intermediate disturbance hypothesis, and spatial heterogeneity -- into a unified model. We implement a novel method to integrate habitat autocorrelation into a system of differential equations, to create a simple and flexible model that can be used to investigate coexistence of multiple species arranged in a competitive hierarchy under different disturbance and habitat structure scenarios. Using this model, we find that considering interactions between different mechanisms is crucial for explaining the coexistence of species. Biodiversity patterns alternative to the uni-peak curve predicted by the intermediate disturbance hypothesis (e.g., bimodal) emerge along disturbance gradients as habitat fragmentation increases. Furthermore, habitat loss outweighs habitat autocorrelation effects in highly disturbed scenarios, yet autocorrelation can shape species coexistence under low disturbance. These findings underscore the need to integrate spatial and temporal mechanisms in biodiversity management.