Open AccessAd hoc smoothing parameter performance in kernel estimates of GPS‐derived home ranges
Author(s) -
Schuler Krysten L.,
Schroeder Greg M.,
Jenks Jonathan A.,
Kie John G.
Publication year - 2014
Publication title -
wildlife biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.566
H-Index - 52
eISSN - 1903-220X
pISSN - 0909-6396
DOI - 10.2981/wlb.12117
Subject(s) - smoothing , home range , statistics , range (aeronautics) , odocoileus , global positioning system , sample size determination , mathematics , sample (material) , post hoc , kernel (algebra) , geography , computer science , ecology , biology , habitat , medicine , telecommunications , materials science , dentistry , combinatorics , composite material , chemistry , chromatography
Accuracy of home‐range estimates in animals is influenced by a variety of factors, such as method of analysis and number of locations, but animal space use is less often considered and frequently over‐generalized through simulations. Our objective was to assess effect of an ad hoc (h_ad hoc) smoothing parameter in kernel analysis from two species that were predicted to have different patterns of utilization distributions across a range of sample sizes. We evaluated variation in home‐range estimates with location data collected from GPS collars on two species: mule deer Odocoileus hemionus and coyotes Canis latrans. We calculated home ranges using 95% and 50% kernel contours using reference (h_ref and h ad hoc smoothing parameters. To evaluate the influence of sample size, we calculated home ranges using both smoothing parameters for random subsamples of 5, 10, 25 and 50% of GPS locations and compared area estimates to estimates for 100% of GPS locations. On mule deer, we also conducted visual relocations using conventional radiotelemetry, which resulted in fewer locations than GPS collars. Area was overestimated at smaller sample sizes, but an interesting pattern was noted with higher relative bias at 60–100 locations than at sample sizes < 50 locations. Relative bias was most likely due to increased smoothing of outer data points. Subsampling allowed us to examine relative bias across a range of samples sizes for the two smoothing parameters. Minimum number of points to obtain a consistent home range estimates varied by smoothing method, species, study duration, and volume contour (95% or 50%). While h_ad hoc performed consistently better over most sample sizes, there may not be a universal recommendation for all studies and species. Behavioral traits resulting in concentrated or disparate space use complicates comparisons among and between species. We suggest researchers examine their point distribution, justify their choice of smoothing parameter, and report their choices for home‐range analysis based on their study objectives.