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INFLUENCES OF AVAILABILITY ON PARAMETER ESTIMATES FROM SITE OCCUPANCY MODELS WITH APPLICATION TO SUBMERSED AQUATIC VEGETATION
Authors:BRIAN R GRAY  MARK D HOLLAND  FENG YI  LEIGH ANN HARROD STARCEVICH
Institution:1. Upper Midwest Environmental Sciences Center, U.S. Geological Survey, , La Crosse, WI, 54603;2. School of Statistics, University of Minnesota, , Minneapolis, MN, 55455;3. Department of Statistics, Oregon State University Corvallis, , OR, 97339
Abstract:Site occupancy models are commonly used by ecologists to estimate the probabilities of species site occupancy and of species detection. This study addresses the influence on site occupancy and detection estimates of variation in species availability among surveys within sites. Such variation in availability may result from temporary emigration, nonavailability of the species for detection, and sampling sites spatially when species presence is not uniform within sites. We demonstrate, using Monte Carlo simulations and aquatic vegetation data, that variation in availability and heterogeneity in the probability of availability may yield biases in the expected values of the site occupancy and detection estimates that have traditionally been associated with low‐detection probabilities and heterogeneity in those probabilities. These findings confirm that the effects of availability may be important for ecologists and managers, and that where such effects are expected, modification of sampling designs and/or analytical methods should be considered. Failure to limit the effects of availability may preclude reliable estimation of the probability of site occupancy.
Keywords:Availability  bias  detection probability  local occupancy  site occupancy  submersed aquatic vegetation  temporary emigration  zero‐inflated binomial model
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