A mesoscale approach to extinction risk in fragmented habitats

• Published in: Nature (London) Vol. 400; no. 6744; pp. 560 - 562
• Main Authors: Casagrandi, Renato, Gatto, Marino
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 05.08.1999; Nature Publishing; Nature Publishing Group
• Subjects: Animal, plant and microbial ecology; Biological and medical sciences; Ecology; Endangered species; Environment; Extinction; Fundamental and applied biological sciences. Psychology; General aspects. Techniques; Habitat fragmentation; Habitats; Humanities and Social Sciences; letter; Methods and techniques (sampling, tagging, trapping, modelling...); multidisciplinary; Science; Science (multidisciplinary); Stochastic model; Metapopulation; Population extinction; Risk; Population dynamics; Habitat; Fragmentation
• ISSN: 0028-0836; 1476-4687
• DOI: 10.1038/23020

Assessing the fate of species endangered by habitat fragmentation 1 , 2 , 3 using spatially explicit and individual-based models 4 , 5 , 6 , 7 can be cumbersome and requires detailed ecological information that is often unavailable. Conversely, Levins-like 8 macroscale models 9 , 10 neglect data on the distribution of local numbers, which are frequently collected by field ecologists 11 , 12 , 13 . Here we present an alternative, mesoscale approach for metapopulations that are subject to demographic stochasticity, environmental catastrophes and habitat loss. Starting from a model that accounts for discrete individuals in each patch and assumes a birth–death stochastic process with global dispersal 14 , 15 , we use a negative-binomial approximation 16 to derive equations for the probability of patch occupancy and the mean and variance of abundance in each occupied patch 17 . A simple bifurcation analysis 18 can be run to assess extinction risk. Comparison with both the original model and a spatially explicit model with local dispersal proves that our approximation is very satisfactory. We determine the sensitivity of metapopulation persistence to patch size, catastrophe frequency and habitat loss, and show that good dispersers are affected more by habitat destruction than by environmental disasters.