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Density estimation in wildlife surveysAuthor(s): Jonathan Bart; Sam Droege; Paul Geissler; Bruce Peterjohn; C. John Ralph
Source: Wildlife Society Bulletin 32(4): 1242-1247
Publication Series: Miscellaneous Publication
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DescriptionSeveral authors have recently discussed the problems with using index methods to estimate trends in population size. Some have expressed the view that index methods should virtually never be used. Others have responded by defending index methods and questioning whether better alternatives exist. We suggest that index methods are often a costeffective component of valid wildlife monitoring but that double-sampling or another procedure that corrects for bias or establishes bounds on bias is essential. The common assertion that index methods require constant detection rates for trend estimation is mathematically incorrect; the requirement is no long-term trend in detection "ratios" (index resultlparameter of interest), a requirement that is probably approximately met by many well-designed index surveys. We urge that more attention be given to defining bird density rigorously and in ways useful to managers. Once this is done, 4 sources of bias in density estimates may be distinguished: coverage, closure, surplus birds, and detection rates. Distance, double-observer, and removal methods do not reduce bias due to coverage, closure, or surplus birds. These methods may yield unbiased estimates of the number of birds present at the time of the survey, but only if their required assumptions are met, which we doubt occurs very often in practice. Double-sampling, in contrast, produces unbiased density estimates if the plots are randomly selected and estimates on the intensive surveys are unbiased. More work is needed, however, to determine the feasibility of double-sampling in different populations and habitats. We believe the tension that has developed over appropriate survey methods can best be resolved through increased appreciation of the mathematical aspects of indices, especially the effects of bias, and through studies in which candidate methods are evaluated against known numbers determined through intensive surveys.
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CitationBart, Jonathan; Droege, Sam; Geissler, Paul; Peterjohn, Bruce; Ralph, C. John. 2004. Density estimation in wildlife surveys. Wildlife Society Bulletin 32(4): 1242-1247
Keywordsbias, density estimation, distance methods, double-observer, double-sampling, estimation, indices, surveys, trends
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