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Estimating population density from indirect sign: track counts and the Formozov–Malyshev–Pereleshin formula
Author(s) -
Stephens P. A.,
Zaumyslova O. Yu.,
Miquelle D. G.,
Myslenkov A. I.,
Hayward G. D.
Publication year - 2006
Publication title -
animal conservation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.111
H-Index - 85
eISSN - 1469-1795
pISSN - 1367-9430
DOI - 10.1111/j.1469-1795.2006.00044.x
Subject(s) - bootstrapping (finance) , range (aeronautics) , statistics , ungulate , population , kernel density estimation , sign (mathematics) , econometrics , nonparametric statistics , distance sampling , confidence interval , calibration , density dependence , mathematics , estimator , demography , mathematical analysis , materials science , sociology , composite material
For many purposes it is often desirable to estimate animal population densities over large areas. Where total counts are not possible and sightings are relatively rare, a range of methods exists to estimate densities from indirect sign. Such methods are frequently unreliable and usually require independent calibration or confirmation. We present an analytical method for estimating population density from track counts. The method, widely known in the Russian Federation but not in the English language scientific literature, requires counts of tracks of known age, together with estimates of animal daily travel distances. We use simulations to verify the theoretical basis of the approach and to indicate potential precision that may be achieved. We illustrate application of the approach using a large data set on ungulate track counts in the Russian Far East. We suggest that under most circumstances, nonparametric bootstrapping will be the most appropriate method for deriving estimates of confidence intervals about density estimates. As with other approaches to estimating density from indirect sign, the method that we discuss is vulnerable to violations of an array of underlying assumptions. However, it is easily applied and could represent an important method by which the relationship between indices of abundance and absolute density can be understood.