A Bayesian approach to line-transect analysis for estimating abundance |
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| Authors: | Tomoharu Eguchi Tim Gerrodette |
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| Institution: | 1. Mosquito-Borne Disease Control, Environmental Health Hazards Unit, Department of Health, P.O. Box 8172 Perth Business Centre, Perth, Western Australia 6849, Australia;2. Naturhistorisches Museum, Augustinergasse 2, CH-4001 Basel, Switzerland;3. Biosciences Research Branch, Department of Economic Development, Jobs, Transport & Resources, La Trobe University, Bundoora, AgriBio, 5 Ring Road, Melbourne Victoria 3083, Australia;4. School of Applied Systems Biology, La Trobe University, Bundoora, Melbourne, Victoria 3086, Australia;1. U.S. Geological Survey, Alabama Cooperative Fish and Wildlife Research Unit, School of Forestry and Wildlife Sciences, Auburn University, Auburn, AL 36845, United States;2. U.S. Geological Survey, Leetown Science Center, Kearneysville, WV 25430, United States;3. U.S. Geological Survey, Patuxent Wildlife Research Center, 12100 Beech Forest Rd., Laurel, MD 20708, United States;4. U.S. Fish and Wildlife Service, Division of Migratory Bird Management, Patuxent Wildlife Research Center, 11510 American Holly Drive, Laurel, MD 20708, United States;5. U.S. Fish and wildlife Service, Northeast Fishery Center, P.O. Box 75, Lamar, PA 16848, United States;6. Delaware Department of Natural Resources and Environmental Control, Delaware Division of Fish and Wildlife, Smyrna, DE 19977, United States;7. Conserve Wildlife Foundation of New Jersey, Bordenton, NJ, 08505, United States;8. New Jersey Department of Environmental Protection, Division of Fish and Wildlife, Port Republic, NJ 08241, United States;9. Virginia Tech University, Department of Fisheries and Wildlife Sciences, Blacksburg, VA 24061, United States;10. Atlantic States Marine Fisheries Commission, Washington D.C. 20005, United States |
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| Abstract: | Line-transect analysis is a widely used method of estimating plant and animal density and abundance. A Bayesian approach to a basic line-transect analysis is developed for a half-normal detection function. We extend the model of Karunamuni and Quinn Karunamuni, R.J., Quinn II, T.J., 1995. Bayesian estimation of animal abundance for line-transect sampling. Biometrics 51, 1325–1337] by including a binomial likelihood function for the number of objects detected. The method computes a joint posterior distribution on the effective strip width and the density of objects in the sampled area. Analytical and computational methods for binned and unbinned perpendicular distance data are provided. Existing information about effective strip width and density can be brought into the analysis via prior distributions. The Bayesian approach is compared to a standard line-transect analysis using both real and simulated data. Results of the Bayesian and non-Bayesian analyses are similar when there are no prior data on effective strip width or density, but the Bayesian approach performs better when such data are available from previous or related studies. Practical methods for including prior data on effective strip width and density are suggested. A numerical example shows how the Bayesian approach can provide valid estimates when the sample size is too small for the standard approach to work reliably. The proposed Bayesian approach can form the basis for developing more advanced analyses. |
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