Journal
ECOLOGICAL APPLICATIONS
Volume 29, Issue 5, Pages -Publisher
WILEY
DOI: 10.1002/eap.1910
Keywords
agro-ecology; avian habitat; countryside biogeography; deforestation; environmental gradient; fragmentation; habitat loss; landscape context; N-mixture model; tropical bird communities
Categories
Funding
- National Geographic Exploration Grant [9977-16]
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Ecologists are increasingly exploring methods for preserving biodiversity in agricultural landscapes. Yet because species vary in how they respond to habitat conversion, ecological communities in agriculture and more natural habitats are often distinct. Unpacking the heterogeneity in species responses to habitat conversion will be essential for predicting and mitigating community shifts. Here, we analyze two years of bird censuses at 150 sites across gradients of local land cover, landscape forest amount and configuration, and regional precipitation in Costa Rica to holistically characterize species responses to habitat conversion. Specifically, we used Poisson-binomial mixture models to (1) delineate groups of species that respond similarly to environmental gradients, (2) explore the relative importance of local vs. landscape-level habitat conversion, and (3) determine how landscape context influences species' local habitat preferences. We found that species fell into six groups: habitat generalists, abundant and rare forest specialists, and three groups of agricultural specialists that differed in their responses to landscape forest cover, fragmentation, and regional precipitation. Birds were most sensitive to local forest cover, but responses were contingent on landscape context. Specifically, forest specialists benefitted most when local forest cover increased in forested landscapes, while habitat generalists exhibited compensatory dynamics, peaking at sites with either local or landscape-level forest, but not both. Our study demonstrates that species responses to habitat conversion are complex but predictable. Characterizing species-level responses to environmental gradients represents a viable approach for forecasting the winners and losers of global change and designing interventions to minimize the ongoing restructuring of Earth's biota.
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