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National Quail Symposium Proceedings

Abstract

Home-range area curves are used to estimate the number of locations needed to accurately estimate home range size based on the asymptote of the curve. However, the current methodology used to identify asymptotes for home-range area curves is largely subjective and varies between studies. Our objective was to evaluate the use of exponential, Gompertz, logistic, and reciprocal function models as a means for identifying asymptotes of home-range area curves. We radio monitored northern bobwhite (Colinus virginianus) coveys during mid-September through November 2001-2002 in Jim Hogg County, Texas. We calculated home-range size of radiomarked coveys using the 95% fixed kernel with least squares cross validation and minimum convex polygon estimators. We fitted area observations and coefficient of variation to the number of locations using exponential, Gompertz, logistic, and reciprocal function models to estimate the minimum number of locations necessary to obtain a representative home range size for each home range estimator. The various function models consistently provided a relatively good fit for home range area curves and coefficient of variation curves (0.58 ≤ R2 0.99; P < 0.05) for both home range estimators. We used an information-theoretic framework (AICC) to select the best model to estimate area-curve asymptotes. The use of function models appears to provide a structured and useful approach for calculating area-curve asymptotes. We propose that researchers consider the use of such models when determining asymptotes for home-range area curves and that more research be conducted to validate the strength of this method.

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