QUANTIFYING HOME-RANGE OVERLAP: THE IMPORTANCE OF THE UTILIZATION DISTRIBUTION

Abstract The concept of an animal's home range has evolved over time, as have methods for estimating home-range size and shape. Recently, home-range estimation methods have focused on estimating an animal's utilization distribution (UD; i.e., the probability distribution defining the animal's use of space). We illustrate the importance of the utilization distribution in characterizing the degree of overlap between home ranges (e.g., when assessing site fidelity or space-use sharing among individuals). We compare several different statistics for their ability to accurately rank paired examples in terms of their degree of overlap. These examples illustrate limitations of indices commonly used to quantify home-range overlap and suggest that new overlap indices that are a function of the UD are likely to be more informative. We suggest 2 new statistics for measuring home-range overlap: (1) for a measure of space-use sharing, we suggest a generalization of Hurlbert's (1978) E/Euniform statistic, which we term the utilization distribution overlap index (UDOI), and (2) for a general measure of similarity between UD estimates, we suggest Bhattacharyya's affinity (BA; Bhattacharyya 1943). Using a short simulation study, we found that overlap indices can accurately rank pairs of UDs in terms of the extent of overlap, but estimates of overlap indices are likely to be biased. The extent of the bias depended on sample size and the degree of overlap (UDs with a high degree of overlap resulted in statistics that were more biased [low]), suggesting that comparisons across studies may be problematic. We illustrate the use of overlap indices to quantify the degree of similarity among UD estimates obtained using 2 different data collection methods (Global Positioning Systems [GPS] and very high frequency [VHF] radiotelemetry) for an adult female northern white-tailed deer (Odocoileus virginianus) in north-central Minnesota.

[1]  Paul W. Mielke,et al.  Permutation Techniques Based on Euclidean Analysis Spaces: A New and Powerful Statistical Method for Ecological Research , 1991 .

[2]  W. V. Winkle.  COMPARISON OF SEVERAL PROBABILISTIC HOME-RANGE MODELS' , 1975 .

[3]  F. Stephen Dobson,et al.  A technique for evaluation of spatial data using asymmetrical weighted overlap values , 1994, Animal Behaviour.

[4]  Kenneth J. Berry,et al.  An extended class of permutation techniques for matched pairs , 1982 .

[5]  Joshua J. Millspaugh,et al.  Comparison of least-squares cross-validation bandwidth options for kernel home-range estimation , 2003 .

[6]  Joshua J. Millspaugh,et al.  RELATING RESOURCES TO A PROBABILISTIC MEASURE OF SPACE USE: FOREST FRAGMENTS AND STELLER'S JAYS , 2004 .

[7]  Richard S. Ostfeld,et al.  Territoriality and mating system of California voles , 1986 .

[8]  S. Hurlbert.  The Measurement of Niche Overlap and Some Relatives , 1978 .

[9]  Joshua J. Millspaugh,et al.  Elk and hunter space-use sharing in South Dakota. , 2000 .

[10]  Joshua J. Millspaugh,et al.  Validation tests of a spatially explicit habitat effectiveness model for Rocky Mountain elk , 2001 .

[11]  Edward O. Garton,et al.  Experimental Design for Radiotelemetry Studies , 2001 .

[12]  Robert A. Gitzen,et al.  Analysis of Animal Space Use and Movements , 2001 .

[13]  W. H. Burt.  Territoriality and Home Range Concepts as Applied to Mammals , 1943 .

[14]  Calyampudi R. Rao.  Diversity and dissimilarity coefficients: A unified approach☆ , 1982 .

[15]  Joshua J. Millspaugh,et al.  Effects of sample size on kernel home range estimates , 1999 .

[16]  Anne Lohrli.  Chapman and Hall , 1985 .

[17]  D. W. Macdonald,et al.  The Evaluation of Home Range Size and Configuration Using Radio Tracking Data , 1980 .

[18]  Joshua J. Millspaugh,et al.  Comparability of three analytical techniques to assess joint space use , 2004 .

[19]  Anthony C. Davison,et al.  Bootstrap Methods and Their Application , 1998 .

[20]  B. Worton.  Kernel methods for estimating the utilization distribution in home-range studies , 1989 .

[21]  M. C. Jones,et al.  A reliable data-based bandwidth selection method for kernel density estimation , 1991 .

[22]  D R Rasmussen.  Clumping and consistency in primates' patterns of range use: definitions, sampling, assessment and applications. , 1980, Folia primatologica; international journal of primatology.

[23]  Joshua J. Millspaugh,et al.  High-Tech Behavioral Ecology: Modeling the Distribution of Animal Activities to Better Understand Wildlife Space Use and Resource Selection , 2001 .

[24]  B. Worton.  Using Monte Carlo simulation to evaluate kernel-based home range estimators , 1995 .

[25]  Wojtek J. Krzanowski,et al.  Non-parametric estimation of distance between groups , 2003 .

[26]  P. A. Jewell,et al.  Home-range and movements of leopards ( Panthera pardus ) on a livestock ranch in Kenya , 1998 .

[27]  K. Matusita.  DISCRIMINATION AND THE AFFINITY OF DISTRIBUTIONS , 1973 .

[28]  Joshua J. Millspaugh,et al.  Value and structure of research experiences for undergraduate wildlife students , 2004 .