Wolf (Canis spp.) predations on livestock and domestic dogs in Upper Michigan : characterizing prior attacks and predicting future risk
(Book - Regular Print)

Thesis,MSES,Green Mountain College,2010

Includes bibliographical references.

Wolves (Canis spp.) have recolonized the Great Lakes region (GLR) and expanded into agricultural areas, resulting in an increase in predations on livestock and domestic dogs (n = 121), seasonality of predations on livestock, and the association between previous winter severity and predations on livestock, and the association between previous winter severity and predations on livestock, in the Upper Peninsula of Michigan, U.S.A., between 15 April 1996 and 14 April 2009. Additionally, I applied and refined a predictive spatial model for livestock predations by wolves, developed by Treves et al. (2004; hereafter "2004 model"), to the UP. Annual number of predations on livestock increased with wolf abundance and was greatest between July and September. Overall, predations on cattle and calves increased during typical calving season. I observed a direct relationship between annual number of predations on livestock and previous winter severity. No relationship was observed between annual number of domestic dogs killed by wolves and wolf abundance. The 2004 model did not satisfactorily discriminate townships (61.4% overall; affected and unaffected; with and without predations, respectively) in the UP. Consequently, I refined the 2004 model based on deer density and spatial data derived from the UP, which discriminated 70% of townships in my sample (n = 70). Affected townships in the UP displayed a consistent set of landscape variables, including relatively higher proportions of pasture/hayfield and crops, and relatively lower proportions of coniferous forest. As conflicts between wolves and humans becomes more common, a better understanding of previous sites of wolf predations on domestic animals and development of spatial models for predicting predations by wolves will assist managers in limiting the number of conflicts, as well as reducing costs of control and compensation.