Using occupancy models of forest breeding birds to prioritize conservation planning

• Published in: Biological conservation 2009-05, Vol.142 (5), p.982-991
• Main Authors: De Wan, Amielle A., Sullivan, Patrick J., Lembo, Arthur J., Smith, Charles R., Maerz, John C., Lassoie, James P., Richmond, Milo E.
• Format: Article
• Language: English
• Subjects: Animal, plant and microbial ecology; Applied ecology; Biodiversity; Biological and medical sciences; Conservation planning; Conservation, protection and management of environment and wildlife; Detection probability; Forest breeding birds; Forestry; Fundamental and applied biological sciences. Psychology; General forest ecology; Generalities. Production, biomass. Quality of wood and forest products. General forest ecology; Parks, reserves, wildlife conservation. Endangered species: population survey and restocking; Urban-sensitive
• ISSN: 0006-3207; 1873-2917
• DOI: 10.1016/j.biocon.2008.12.032

As urban development continues to encroach on the natural and rural landscape, land-use planners struggle to identify high priority conservation areas for protection. Although knowing where urban-sensitive species may be occurring on the landscape would facilitate conservation planning, research efforts are often not sufficiently designed to make quality predictions at unknown locations. Recent advances in occupancy modeling allow for more precise estimates of occupancy by accounting for differences in detectability. We applied these techniques to produce robust estimates of habitat occupancy for a subset of forest breeding birds, a group that has been shown to be sensitive to urbanization, in a rapidly urbanizing yet biological diverse region of New York State. We found that detection probability ranged widely across species, from 0.05 to 0.8. Our models suggest that detection probability declined with increasing forest fragmentation. We also found that the probability of occupancy of forest breeding birds is negatively influenced by increasing perimeter–area ratio of forest fragments and urbanization in the surrounding habitat matrix. We capitalized on our random sampling design to produce spatially explicit models that predict high priority conservation areas across the entire region, where interior-species were most likely to occur. Finally, we use our predictive maps to demonstrate how a strict sampling design coupled with occupancy modeling can be a valuable tool for prioritizing biodiversity conservation in land-use planning.