Hostname: page-component-586b7cd67f-tf8b9 Total loading time: 0 Render date: 2024-12-01T03:58:29.091Z Has data issue: false hasContentIssue false

Improving studies of resource selection by understanding resource use

Published online by Cambridge University Press:  01 November 2010

BRIAN N. KERTSON
Affiliation:
School of Forest Resources, University of Washington, Seattle, WA 98195, USA
JOHN M. MARZLUFF*
Affiliation:
School of Forest Resources, University of Washington, Seattle, WA 98195, USA
*
*Correspondence: Dr John Marzluff e-mail: [email protected]

Summary

Understanding the resource needs of animals is critical to their management and conservation. Resource utilization functions (RUFs) provide a framework to investigate animal-resource relationships by characterizing variation in the amount of resource use. In this context a ‘resource’ is any aspect of a species' fundamental niche that can be mapped throughout the area of investigation (such as study area or home range). Extensive global positioning system (GPS) data from 17 cougars (Puma concolor) demonstrate the utility and potential challenges of estimating RUFs within the home range for far-ranging species. Ninety-nine per cent utilization distributions (UDs) estimated using bivariate plug in, univariate least-squares cross-validation and reference bandwidth selection methods were compared. Distance to water, per cent clear-cut and regenerating forest, and slope were used to estimate cougar RUFs. UDs derived from GPS data were more refined, and plug-in UDs were least similar to UDs derived from other bandwidths. RUFs were resilient to variation in the smoothing parameter, with all methods yielding coefficients that largely reflected observations of foraging ecology and behaviour. Cougars were individualistic, but use was generally positively associated with the presence of regenerating forest and inversely associated with steep slopes. Advances in technology allow for greater accuracy and resolution of the UD, but software improvements and spatially explicit information on animal behaviour are needed to better understand resource use.

Type
Papers
Copyright
Copyright © Foundation for Environmental Conservation 2010

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Altendorf, K., Laundre, J., LopezGonzalez, C. Gonzalez, C. & Brown, J. (2001) Assessing effects of predation risk on foraging behavior of mule deer. Journal of Mammalogy 82: 430439.2.0.CO;2>CrossRefGoogle Scholar
Beyer, H. (2004) Hawth's Analysis Tools for ArcGIS [www document]. URL http://www.spatialecology.com/htoolsGoogle Scholar
Bluff, L. & Rutz, C. (2008) A quick guide to video-tracking birds. Biology Letters 4: 319322.CrossRefGoogle ScholarPubMed
Cain, J., Krausman, P., Jansen, B., Morgart, J. & Krausman, T. (2005) Influence of topography and GPS fix interval on GPS collar performance. Wildlife Society Bulletin 33: 926934.CrossRefGoogle Scholar
Clark, J., Dunn, J. & Smith, K. (1993) A multivariate model of female black bear habitat use for a geographic information-system. Journal of Wildlife Management 57: 519526.CrossRefGoogle Scholar
Cooper, A. & Millspaugh, J. (1999) The application of discrete choice models to wildlife resource selection studies. Ecology 80: 566575.CrossRefGoogle Scholar
DeCesare, N., Squires, J. & Kolbe, J. (2005) Effect of forest canopy on GPS-based movement data. Wildlife Society Bulletin 33: 935941.CrossRefGoogle Scholar
D'Eon, R. & Delparte, D. (2005) Effects of radio-collar position and orientation on GPS radio-collar performance, and the implications of PDOP in data screening. Journal of Applied Ecology 42: 383388.CrossRefGoogle Scholar
Dickson, B. & Beier, P. (2002) Home range and habitat selection by adult cougars in southern California. Journal of Wildlife Management 66: 12351245.CrossRefGoogle Scholar
Dickson, B., Jenness, J. & Beier, P. (2005) Influence of vegetation, topography, and roads on cougar movement in southern California. Journal of Wildlife Management 69: 264276.2.0.CO;2>CrossRefGoogle Scholar
Frair, J., Nielsen, S., Merrill, E., Lele, S., Boyce, M., Munro, R., Stenhouse, G. & Beyer, H. (2004) Removing GPS collar bias in habitat selection studies. Journal of Applied Ecology 41: 201212.CrossRefGoogle Scholar
Gitzen, R., Millspaugh, J. & Kernohan, B. (2006) Bandwidth selection for fixed-kernel analysis of animal utilization distributions. Journal of Wildlife Management 70: 13341344.CrossRefGoogle Scholar
Goh, K. (2000) Macrohabitat selection by Vancouver Island cougar. M.Sc. thesis, University of British Columbia, Vancouver, British Columbia, Canada.Google Scholar
Hepinstall, J., Alberti, M. & Marzluff, J. (2008 a) Predicting land cover change and avian community responses in rapidly urbanizing environments. Landscape Ecology 23: 12571276.CrossRefGoogle Scholar
Hepinstall, J., Marzluff, J. & Alberti, M. (2008 b) Modeling the responses of birds to predicted changes in land cover in an urbanizing region. In: Models for Planning Wildlife Conservation in Large Landscapes, ed. Millspaugh, J.J. & Thompson III, F.R., pp. 625659. San Diego, CA, USA: Elsevier Science.Google Scholar
Hepinstall, J., Marzluff, J., Handcock, M. & Hurvitz, P. (2005) Incorporating utilization distributions into the study of resource selection: dealing with spatial autocorrelation. In: Resource Selection Methods and Applications, ed. Huzurbazar, S., pp. 1219. Madison, WI, USA: Omnipress.Google Scholar
Hooge, P. & Eichenlaub, P. (1997) Animal movement extension to ArcView ver 1.1. Alaska Science Center-Biological Science Office, Anchorage, AK, USA: US Geological Survey.Google Scholar
Johnson, C., Nielsen, S., Merrill, E., McDonald, T. & Boyce, M. (2006) Resource selection functions based on use-availability data: theoretical motivation and evaluation methods. Journal of Wildlife Management 70: 347357.CrossRefGoogle Scholar
Johnson, D. (1980) The comparison of usage and availability measurements for evaluating resource preference. Ecology 61: 6571.CrossRefGoogle Scholar
Kernohan, B., Gitzen, R. & Millspaugh, J. (2001) Analysis of animal space use and movements. In: Radiotelemetry and Animal Populations, ed. Millspaugh, J. & Marzluff, J., pp. 125166. London, UK: Academic Press.CrossRefGoogle Scholar
Kertson, B. (2010) Cougar ecology, behavior, and interactions with people in a wildland-urban environment in western Washington. Dissertation, University of Washington, Seattle, WA, USA.Google Scholar
Koehler, G. & Hornocker, M. (1991) Seasonal resource use among mountain lions, bobcats, and coyotes. Journal of Mammalogy 72: 391396.CrossRefGoogle Scholar
Koehler, G. & Pierce, D. (2003) Black bear home-range sizes in Washington: climatic, vegetative, and social influences. Journal of Mammalogy 84: 8191.2.0.CO;2>CrossRefGoogle Scholar
Lele, S. (2009) A new method for estimation of resource selection probability function. Journal of Wildlife Management 73: 122127.CrossRefGoogle Scholar
Lewis, J., Rachlow, J., Garton, E. & Vierling, L. (2007) Effects on habitat on GPS collar performance: using data screening to reduce location error. Journal of Applied Ecology 44: 663671.CrossRefGoogle Scholar
Long, R., Muir, J., Rachlow, J. & Kie, J. (2009) A comparison of two modeling approaches for evaluating wildlife-habitat relationships. Journal of Wildlife Management 73: 294302.CrossRefGoogle Scholar
Manly, B., McDonald, L., Thomas, D., McDonald, T. & Erickson, W. (2002) Resource Selection by Animals, Statistical Design and Analysis for Field Studies, Second edition. Dordrecht, the Netherlands: Kluwer Academic Publishers.Google Scholar
Marzluff, J., Knick, S. & Millspaugh, J. (2001) High-tech behavioral ecology: modeling the distribution of animal activities to better understand wildlife space use and resource selection. In: Radiotelemetry and Animal Populations, ed. Millspaugh, J. & Marzluff, J., pp. 309326. London, UK: Academic Press.CrossRefGoogle Scholar
Marzluff, J., Millspaugh, J., Hurvitz, P. & Handcock, M. (2004) Relating resources to a probabilistic measure of space use: forest fragments and Steller's jays. Ecology 85:14111427.CrossRefGoogle Scholar
Mech, L. (1983) Handbook of Animal Radio-Tracking. Minneapolis, Minnesota, USA: University of Minnesota Press.Google Scholar
Millspaugh, J., Nielson, R., McDonald, L., Marzluff, J., Gitzen, R., Rittenhouse, C., Hubbard, M. & Sheriff, S. (2006) Analysis of resource selection using utilization distributions. Journal of Wildlife Management 70: 384395.CrossRefGoogle Scholar
Moll, R., Millspaugh, J., Beringer, J., Sartwell, J. & He, Z. (2007) A new ‘view’ of ecology and conservation through animal-bonre video systems. Trends in Ecology and Evolution 22: 660668.CrossRefGoogle ScholarPubMed
Morrison, M. (2002) Wildlife Restoration.Washington, DC, USA: Island Press.Google Scholar
Neatherlin, E. & Marzluff, J. (2004) Campgrounds enable American crows to colonize remote native forests. Journal of Wildlife Management 68:708718.CrossRefGoogle Scholar
Otis, D. & White, G. (1999) Autocorrelation of location estimates and the analysis of radiotracking data. Journal of Wildlife Management 63:10391044.CrossRefGoogle Scholar
Raphael, M., Evans, D., Marzluff, J. & Luginbuhl, J. (2002) Effects of forest fragmentation on populations of the marbled murrelet. Studies in Avian Biology 25: 221235.Google Scholar
Rodgers, A., Carr, A., Beyer, H., Smith, L. & Kie, J. (2007) HRT: Home Range Tools for ArcGIS. Ontario Ministry of Natural Resources, Centre for Northern Forest Ecosystem Research, Thunder Bay, Ontario, Canada.Google Scholar
Samuel, M. & Garton, E. (1987) Home range: a weighted normal estimate and tests of underlying assumptions. Journal of Wildlife Management 49: 513519.CrossRefGoogle Scholar
Seidensticker, J., Hornocker, M., Wiles, W. & Messick, J. (1973) Mountain lion social organization in the Idaho Primitive Area. Wildlife Monographs Number 35. The Wildlife Society.Google Scholar
Silverman, B. (1986) Density Estimation for Statistics and Data Analysis. First edition. London, UK: Chapman & Hall.Google Scholar
Spencer, R., Pierce, D., Schirato, G., Dixon, K. & Richards, C. (2001) Mountain lion home range, dispersal, mortality and survival in the western Cascade Mountains of Washington. Washington Department of Fish and Wildlife. Olympia, Washington, USA.Google Scholar
Van Winkle, W. (1975) Comparison of several probabilistic home-range models. Journal of Wildlife Management 39:118123.CrossRefGoogle Scholar
Wand, M. (2006) KernSmooth: functions for kernel smoothing for Wand and Jones (1995). R package version 2.22–19. R port by Brian Ripley [www document]. URL http://cran.r-project.org/web/packages/KernSmooth/KernSmooth.pdfGoogle Scholar
Wand, M. & Jones, M. (1995) Kernel Smoothing. First edition. London, UK: Chapman & Hall.CrossRefGoogle Scholar
Western Region Climate Center (2009) Washington. [www document]. URL http.//www.wrcc.dri.edu/summary/Climsmwa.htmlGoogle Scholar
Whittaker, K. & Marzluff, J. (2009) Species-specific survival and relative habitat use in an urban landscape during the postfledging period. Auk (in press).CrossRefGoogle Scholar
Williams, J., McCarthy, J. & Picton, H. (1995) Cougar habitat use and food habits on the Montana Rocky Mountain front. Intermountain Journal of Sciences 1: 1628.Google Scholar
Withey, J. & Marzluff, J. (2009) Multi-scale use of lands providing anthropogenic resources by American Crows in an urbanizing landscape. Landscape Ecology (in press).CrossRefGoogle Scholar
Worton, B. (1989) Kernel methods for estimating the utilization distribution in home-range studies. Ecology 70: 164168.CrossRefGoogle Scholar
Zar, J. (1999) Biostatistical Analysis, Fourth edition. Englewood Cliffs, NJ, USA: Prentice-Hall.Google Scholar