Visibility bias in aerial surveys a review of estimation procedures

Aerial surveys, often used to estimate the density of wildlife populations, commonly underestimate population density because of animals being missed. This visibility bias can be serious. Methods of estimating visibility bias based on comparison with ground counts, use of a subpopulation of marked animals, mapping with multiple observers, line transect sampling, and multiple counts on the same area are reviewed. All of the methods are model based and the various model assumptions are discussed and compared. J. WILDL. MANAGE. 51(2):502-510 Aerial surveys are used to estimate the population size of many large birds (Caughley and Grice 1982), large terrestrial mammals (Rice and Harder 1977), and marine mammals (Burnham et al. 1980:76). They are used in conjunction with other methods of estimation or by themselves, either by choice or necessity. "Visibility bias" results from animals being missed and is exacerbated by factors such as dense vegetation, bad weather conditions, and observer fatigue. Beyond the logistics and dangers of flying surveys precisely, the principal difficulty in aerial censuses lies in estimating the visibility bias to establish a correction factor. Caughley (1977: 35) presents a table showing the visibility bias in a wide range of aerial surveys. Biologists tempted to minimize this problem should study this table where the visibility bias is often in the range of 30-50% animals missed! If absolute density estimates are to be reported there will always be the need for a correction factor. Here we review the various methods of estimating visibility bias from an applied statistician's perspective. Neither of us claim to be experts in the practicalities of running aerial

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