Community composition exceeds area as a predictor of long-term conservation value

• Published in: PLoS computational biology Vol. 19; no. 1; p. e1010804
• Main Authors: O'Sullivan, Jacob D, Terry, J Christopher D, Wilson, Ramesh, Rossberg, Axel G
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 01-01-2023; Public Library of Science (PLoS)
• Subjects: Biodiversity; Biological diversity; Biology and Life Sciences; Biomass; Community composition; Conservation; Conservation of Natural Resources; Cost analysis; Datasets; Ecology and Environmental Sciences; Ecosystem; Empirical analysis; Endangered & extinct species; Extinction; Habitat loss; Habitats; Impact prediction; Methods; Nature conservation; Perturbation; Protection and preservation; Research and Analysis Methods; Variables; Wildlife conservation; United Kingdom
• ISSN: 1553-7358; 1553-734X; 1553-7358
• DOI: 10.1371/journal.pcbi.1010804

Conserving biodiversity often requires deciding which sites to prioritise for protection. Predicting the impact of habitat loss is a major challenge, however, since impacts can be distant from the perturbation in both space and time. Here we study the long-term impacts of habitat loss in a mechanistic metacommunity model. We find that site area is a poor predictor of long-term, regional-scale extinctions following localised perturbation. Knowledge of the compositional distinctness (average between-site Bray-Curtis dissimilarity) of the removed community can markedly improve the prediction of impacts on regional assemblages, even when biotic responses play out at substantial spatial or temporal distance from the initial perturbation. Fitting the model to two empirical datasets, we show that this conclusions holds in the empirically relevant parameter range. Our results robustly demonstrate that site area alone is not sufficient to gauge conservation priorities; analysis of compositional distinctness permits improved prioritisation at low cost.