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TAILORING POINT COUNTS FOR INFERENCE ABOUT AVIAN DENSITY: DEALING WITH NONDETECTION AND AVAILABILITY
Authors:FRED A. JOHNSON  ROBERT M. DORAZIO  TRACI D. CASTELLÓN  JULIEN MARTIN  JAY O. GARCIA  JAMES D. NICHOLS
Affiliation:1. Southeast Ecological Science Center, U.S. Geological Survey, , Gainesville, FL 32653;2. Archibold Biological Station, , Venus, FL 33960;3. Fish and Wildlife Research Institute, Florida Fish and Wildlife Conservation Commission, , St. Petersburg, FL 33701;4. Ocala National Forest, U.S. Forest Service, , Umatilla, FL 32784;5. Patuxent Wildlife Research Center, U.S. Geological Survey, , Laurel, MD 20708
Abstract:Point counts are commonly used for bird surveys, but interpretation is ambiguous unless there is an accounting for the imperfect detection of individuals. We show how repeated point counts, supplemented by observation distances, can account for two aspects of the counting process: (1) detection of birds conditional on being available for observation and (2) the availability of birds for detection given presence. We propose a hierarchical model that permits the radius in which birds are available for detection to vary with forest stand age (or other relevant habitat features), so that the number of birds available at each location is described by a Poisson‐gamma mixture. Conditional on availability, the number of birds detected at each location is modeled by a beta‐binomial distribution. We fit this model to repeated point count data of Florida scrub‐jays and found evidence that the area in which birds were available for detection decreased with increasing stand age. Estimated density was 0.083 (95%CI: 0.060–0.113) scrub‐jays/ha. Point counts of birds have a number of appealing features. Based on our findings, however, an accounting for both components of the counting process may be necessary to ensure that abundance estimates are comparable across time and space. Our approach could easily be adapted to other species and habitats.
Keywords:Abundance  availability  beta‐binomial mixture  detection probability  Florida scrub‐jay  hierarchical model  N‐mixture model  Poisson‐gamma mixture  point count
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