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USGS2018

Weekly summer diet of gray wolves (Canis lupus) in northeastern Minnesota

Wolves ( Canis lupus ) are opportunistic predators and will capitalize on available abundant food sources. However, wolf diet has primarily been examined at monthly, seasonal, or annual scales, which can obscure short-term responses to available food. We examined weekly wolf diet from late June to early October by collecting scats from a single wolf pack in northeastern Minnesota. During our 15 week study, nonungulate food types constituted 58% of diet biomass. Deer ( Odocoileus virginianus ) fawns were a major food item until mid-July after which berries (primarily Vaccinium and Rubus spp.) composed 56–83% of weekly diet biomass until mid-August. After mid-August, snowshoe hares ( Lepus americanus ) and adult deer were the primary prey. Weekly diet diversity approximately doubled from June to October as wolves began using several food types in similar proportions as the summer transitioned into fall. Recreational hunting of black bears ( Ursus americanus ) contributed to weekly wolf diet in the fall as wolves consumed foods from bear bait piles and from gut piles/carcasses of successfully harvested or fatally wounded bears. To our knowledge, we are the first to examine wolf diet via scat analysis at weekly intervals, which enabled us to provide a detailed description of diet plasticity of this wolf pack, as well as the rapidity with which wolves can respond to new available food sources.

Minnesota↗

USGS2013

Fall survival of American woodcock in the western Great Lakes Region

We estimated fall (10 Sep–8 Nov) survival rates, cause-specific mortality rates, and determined the magnitude and sources of mortality of 1,035 radio-marked American woodcock ( Scolopax minor ) in Michigan, Minnesota, and Wisconsin during 2001–2004. In all 3 states, we radio-marked woodcock on paired study areas; 1 of which was open to hunting and expected to receive moderate to high hunter use and the other of which was either closed to hunting (Michigan and Minnesota) or was relatively inaccessible to hunters (Wisconsin). We used Program MARK to estimate fall survival rates, to evaluate a set of candidate models to examine the effects of hunting and several covariates (sex, age, year, state) on survival, and to examine the relationship between survival rates and kill rates due to hunting. Hunting accounted for 70% of the 86 woodcock deaths in the hunted areas, followed by predation (20%) and various other sources of mortality (10%). Woodcock deaths that occurred in the non-hunted and lightly hunted areas ( n  = 50) were caused by predators (46%), hunting (32%), and various other sources (22%). Based on small-sample corrected Akaike's Information Criterion values, variation in fall survival of woodcock was best explained by treatment (i.e., hunted vs. non-hunted), year, and period (pre-hunting season intervals vs. hunting season intervals). The average fall survival estimate from our best model for woodcock in the non-hunted areas (0.893, 95% CI = 0.864–0.923) was greater than the average for the hunted areas (0.820, 95% CI = 0.786–0.854 [this estimate includes data from the lightly hunted area in Wisconsin]), and the average treatment effect (i.e., greater survival rates in non-hunted areas) was 0.074 (95% CI = 0.018–0.129). The kill rate due to hunting was 0.120 (95% CI = 0.090–0.151) when data were pooled among states and years. We detected a negative relationship between hunting kill rates and survival in our hunted areas, which suggests that hunting mortality was at least partially additive during fall. Our results illustrate the influence of hunting relative to other sources of mortality in Michigan, Minnesota, and Wisconsin, and indicate that managers may be able to influence fall survival rates by manipulating hunting regulations or access on public land.

Michigan, Minnesota, Wisconsin↗