Study Designs and Tests for Comparing Resource Use and Availability

Thomas, Dana L.; Taylor, Eric J.

doi:10.2307/3809050

Cited by 312 publications

(232 citation statements)

References 15 publications

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“…I employed a logistic regression -resource selection function (RSF) approach to assess factors that influence caribou distribution during winter (Manley et al, 2002). I selected Thomas and Taylor's (1990) Design II, where the locations of individually marked animals are pooled to study population level patterns. Selection or avoidance by caribou was rela¬ tive to the random locations.…”

Section: Data Acquisition and Derivationmentioning

confidence: 99%

Modeling influences on winter distribution of caribou in northwestern Alaska through use of satellite telemetry

Joly

2011

Ran

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I hypothesize that the distribution of barren-ground caribou (Rangifer tarandus granti) is affected by multiple, interrelated factors. These factors include, but are not limited to, terrain and snow characteristics as well as predation pressure and habitat. To test this hypothesis, I attributed caribou locations derived from satellite telemetry over a 6 year period with terrain (elevation, slope, aspect, and ruggedness), habitat characteristics, and moose density -potentially an index of wolf predation pressure. These locations were compared to random locations, attributed using the same data layers, using logistic regression techniques to develop resource selection functions (RSFs). I found that caribou moved significantly less during mid-winter than early-or late-winter and that cows moved significantly more in April than bulls due to their earlier departure on their spring migration. Distribution was different between cows and bulls. Terrain variables were important factors but were scale-dependent. Cows avoided forested areas, highlighting the importance of tundra habitats, and selected for dwarf shrub, with relatively high lichen cover, and sedge habitat types. Bulls selected for dryas, coniferous forest and dwarf shrub habitats but against lowland sedge, upland shrub and burned tundra. Cow distribution was negatively correlated with moose density at the scale of the Seward Peninsula. My results support the hypothesis that caribou distribution during winter in northwest Alaska is affected by multiple, interrelated factors. These results may be useful for researchers to track and/or model changes in future patterns of range use over winter.

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Section: Data Acquisition and Derivationmentioning

confidence: 99%

Modeling influences on winter distribution of caribou in northwestern Alaska through use of satellite telemetry

Joly

2011

Ran

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“…Under this concept, our data described second-(i.e., home range selection within the study area) and third-order (i.e., cover selected within a home range) selection (Table 2) for deer. We then applied study designs 1-3 of Thomas and Taylor (1990) to Johnson's (1980) hierarchal selection process to describe cover selection processes of deer and the magnitude of their differences at different spatial scales. We assumed, for example, that if a cover type dominated the selection process at multiple spatial scales, then its relative importance to deer was higher than a cover type selected at 1 spatial scale.…”

Section: Cover Selectionmentioning

confidence: 99%

“…Both use and availability are defined at the individual level with design 3 (Thomas and Taylor 1990), which describes third-order selection by Johnson (1980; Table 2). We defined use as the proportion of location estimates of an individual within each cover type, and availability as the proportional area of each cover type within the 95% kernel home range of that individual.…”

Section: Cover Selectionmentioning

confidence: 99%

“…We assumed, for example, that if a cover type dominated the selection process at multiple spatial scales, then its relative importance to deer was higher than a cover type selected at 1 spatial scale. Finally, we applied Ivlev's (1961) electivity index to quantify selection based on these varying definitions of use and availability under Thomas and Taylor (1990).…”

Section: Cover Selectionmentioning

confidence: 99%

“…The use of confidence limits is advantageous in that an estimate of effect size and a measure of uncertainty are provided (Johnson 1999 Landscape-scale selection. We used design 1 of Thomas and Taylor (1990) to describe second-order selection (Johnson 1980), where both use and availability are defined at the population level (Table 2). We quantified use and availability using Euclidean distances of location estimates to nearest cover types within the study area.…”

Section: Cover Selectionmentioning

confidence: 99%

See 2 more Smart Citations

Multi-scale Cover Selection by White-tailed Deer, <em>Odocoileus virginianus</em>, in an Agro-forested Landscape

2009

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Resource selection studies are commonly conducted at a single spatial scale, but this likely does not fully or accurately assess the hierarchical selection process used by animals. We used a multi-spatial scale approach to quantify White-tailed Deer (Odocoileus virginianus) cover selection in south-central Michigan during [2004][2005][2006] by varying definitions of use and availability and ranking the relative importance of cover types under each study design. The number of cover types assigned as selected (proportional use > proportional availability) decreased from coarse (landscape level) to fine (within home range) scales, although at finer scales, selection seemed to be more consistent. Although the relative importance changed substantially across spatial scales, two cover types (conifers, upland deciduous forests) were consistently ranked as the two most important, providing strong evidence of their value to deer in the study area. Testing for resource selection patterns using a multi-spatial scale approach would provide additional insight into the ecology and behavior of a particular species.

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