Spatial Characteristics of Wolf Depredation Sites in Northwest Wyoming: A Comparison between Areas with Migratory and Resident Elk

The Wildlife Society, Hawaii 2011The Wildlife Society, 18th Annual Conference,  05-10 November 2011, Waikoloa, Hawaii

Abigail Nelson, Matthew J. Kauffman, Arthur Middleton, Doug McWhirter, Mike Jimenez, and Ken Gerow

“As large carnivores recover in many wilderness areas and mixed-use landscapes, wildlife management agencies must seek ways to minimize private property damage while maintaining viable populations. Although much is known about carnivore-livestock conflicts, drivers of these processes in the Northern Rocky Mountains are still emerging amid the dynamic conditions of recovering predator populations (gray wolves [Canis lupus] and grizzly bears [Ursus arctos horribilis]), declining elk productivity, and the re-distribution of migratory and resident elk subpopulations. There has been little research to date that examines the influence of fine-scale elk distribution and movements on patterns of livestock depredation. In this study, we analyze four years of cattle depredation data, two years of summer and fall wolf predation data (n = 4 wolves), and three years of elk movement data (n = 70 elk) to assess the influence of migratory and resident prey on the location and occurrence of wolf depredations on cattle. Wolves living in migratory elk areas face low densities of their preferred prey in summer, when elk depart for higher elevations inside Yellowstone National Park (YNP), while wolves living in the resident elk area have access to abundant elk year-round. Wolves living in both areas have the potential to interact with several thousand head of cattle. We used logistic regression to compare the relative influence of landscape features on the risk of livestock depredation in the migratory and resident elk areas. Wolf-killed cattle locations showed differences between the migratory elk area and the resident elk area. Depredation sites in the resident elk area were associated with habitats closer to roads and with high elk density, while depredation sites in the migratory elk area were associated with dens, streams, and open habitat away from the forest edge. Our findings indicate that knowledge of ungulate distributions and migration patterns can help understand and predict hotspots of wolf conflict with livestock.”

Spatial Analysis by Distance Indices: An Alternative Local Clustering Index for Studying Spatial Patterns

Methods in Ecology and EvolutionMethods in Ecology and Evolution, published online 11 November 2011

Baohua Li, Laurence V. Madden, and Xiangming Xu

“The spatial analysis by distance indices (SADIE) methodology for data analysis is valuable for quantifying spatial patterns of organisms in terms of patches and gaps. Previous research showed that the calculation of the local clustering indices, key SADIE statistics, does not adequately adjust for the absolute location or the magnitude of the counts.

“We present a new definition of a local clustering index, which overcomes the problem associated with the original cluster indices related to sampling position and count size. The new index is calculated without breaking the link between the observed count and its original position and quantifies the contribution of an observed count at this particular position to the local gaps or patches for the observed pattern relative to the expected under the assumption of spatial independence amongst observed counts. Randomisation-based testing for statistical significance of an individual local clustering index follows naturally from the definition of the new index.

“New indices, calculated for several simulated and observed data sets, showed that the original indices overestimated the number of points (sites, locations) contributing to the gaps/patches in a spatial grid. Results indicate that the significance (or interpretation) of individual local clustering indices cannot be made based on its magnitude only and needs to be supported by statistical testing.

“The newly developed index will provide a valuable tool for quantifying the local pattern and testing for its significance and enhance the value of SADIE methodology in analysing spatial patterns. It can also be used in conjunction with other approaches that test for global clustering.”