Ungulate mortality from capture‐related injuries is a recurring concern for researchers and game managers throughout North America and elsewhere. We evaluated effects of 7 variables to determine whether ungulate mortality could be reduced by modifying capture and handling procedures during helicopter net‐gunning. During winter 2001–2006, we captured 208 white‐tailed deer (Odocoileus virginianus) and 281 pronghorn (Antilocapra Americana) by helicopter net‐gunning throughout the Northern Great Plains. Of 281 pronghorn, 25 (8.9%) died from capture‐related injuries; 12 were from direct injuries during capture, and 13 occurred postrelease. Of 208 deer, 3 (1.4%) died from injuries sustained during helicopter captures, with no mortalities documented postrelease. We used logistic regression to evaluate the probability that ungulates would die of injuries associated with helicopter net‐gun captures by analyzing effects of snow depth, transport distance, ambient and rectal temperatures, pursuit and handling times, and whether individuals were transported to processing sites. The probability of capture‐related mortality postrelease decreased 58% when transport distance was reduced from 14.5 km to 0 km and by 69% when pursuit time decreased from 9 minutes to <1 minute. Wildlife managers and researchers using helicopter capture services in landscapes of the Midwest should limit pursuit time and eliminate animal transport during pronghorn and white‐tailed deer capture operations to minimize mortality rates postrelease.

Wildlife managers need empirical data about pronghorn (Antilocapra americana) movements in North Dakota to assess whether mid‐summer surveys represent occupancy of pronghorn in hunting units during the fall hunting season. Using data from 121 radiocollared pronghorn we evaluated patterns of pronghorn migrations in southwestern North Dakota from 2004 to 2007. Pronghorn exhibited 2 primary movement patterns between summer and winter ranges: migrations >15 km (45%) and movement <15 km (55%). Most migratory pronghorn moved northeast or east in the spring and southwest or west in the fall. Average distance moved for migratory pronghorn was 70.6 km (range = 17.4–253 km). Mean date of pronghorn migration in spring was 20 March (SD = 20 days) and in fall was 22 October (SD = 17 days). Nearly all migratory pronghorn (97%) returned to within 15 km of their previous summer range, whereas only 61% of pronghorn returned to within 15 km of their previous winter range. Most pronghorn moved across hunting and survey unit boundaries; however, only 7 fall migrations occurred between the aerial survey and the hunting season. During years of our study, the mid‐summer survey provided representative information about hunting unit occupancy of radiocollared pronghorn for the fall hunting season. © 2011 The Wildlife Society

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Wildlife population dynamics are modulated by abiotic and biotic factors, typically climate, resource availability, density-dependent effects, and predator-prey interactions. Understanding if human-caused disturbances shape these processes is needed for the conservation and management of ecological communtiies within increasingly human-dominated landscapes. Garnering this understanding is difficult due to lack of long-term longitudinal data on wildlife populations, human-mediated disturbances, climate and predator density on ungulate population dynamics has been under-studied. Using a 50-year time series (1962-2012) on mule deer (Odocoileus hemionus) demographics, seasonal weather, predator density, oil and gas development patterns from the North Dakota Badlands to investigate long-term effects of landscape-level disturbance. We aimed to evaluate if harsh weather conditions in-combination with energy development and predators affected fall mule deer recruitment. We found that density-dependent effects and harsh seasonal weather primarily drove recruitment in the North Dakota Badlands. Recruitment was further shaped by interacting effects of harsh seasonal weather and predator presence in the form of high coyote density. Additionally, we found that fall recruitment was subtly modulated by interactions between seasonal weather and energy development (i.e., lower recruitment when harsher weather was combined with higher density of active oil and gas wells), and that the combined effect of predator density and energy development was not interactive but rather additive. Our analysis demonstrates the effect of energy development by modulating mule deer recruitment fluctuations concurrent with main recruitment drivers being biotic (density-dependency, habitat, predation) and abiotic (harsh seasonal weather, woody vegetation encroachment). A pattern emerges of density dependence, presumably due to limited quality habitat, being the primary factor influencing fall fawn recruitment in mule deer. Secondarily, stochastic weather events periodically cause dramatic declines in recruitment. Finally, the interactions between human disturbance and predation can be additive to the aforementioned drivers of recruitment and subsequently cause further declines.

Wildlife population dynamics are modulated by abiotic and biotic factors, typically climate, resource availability, density‐dependent effects, and predator–prey interactions. Understanding whether and how human‐caused disturbances shape these ecological processes is helpful for the conservation and management of wildlife and their habitats within increasingly human‐dominated landscapes. However, many jurisdictions lack either long‐term longitudinal data on wildlife populations or measures of the interplay between human‐mediated disturbance, climate, and predator density. Here, we use a 50‐year time series (1962–2012) on mule deer (Odocoileus hemionus) demographics, seasonal weather, predator density, and oil and gas development patterns from the North Dakota Badlands, USA, to investigate long‐term effects of landscape‐level disturbance on mule deer fawn fall recruitment, which has declined precipitously over the last number of decades. Mule deer fawn fall recruitment in this study represents the number of fawns per female (fawn:female ratio) that survive through the summer to October. We used this fawn recruitment index to evaluate the composite effects of interannual extreme weather conditions, energy development, and predator density. We found that density‐dependent effects and harsh seasonal weather were the main drivers of fawn fall recruitment in the North Dakota Badlands. These effects were further shaped by the interaction between harsh seasonal weather and predator density (i.e., lower fawn fall recruitment when harsh weather was combined with higher predator density). Additionally, we found that fawn fall recruitment was modulated by interactions between seasonal weather and energy development (i.e., lower fawn fall recruitment when harsh weather was combined with higher density of active oil and gas wells). Interestingly, we found that the combined effect of predator density and energy development was not interactive but rather additive. Our analysis demonstrates how energy development may modulate fluctuations in mule deer fawn fall recruitment concurrent with biotic (density‐dependency, habitat, predation, woody vegetation encroachment) and abiotic (harsh seasonal weather) drivers. Density‐dependent patterns emerge, presumably due to limited quality habitat, being the primary factor influencing fall fawn recruitment in mule deer. Secondarily, stochastic weather events periodically cause dramatic declines in recruitment. And finally, the additive effects of human disturbance and predation can induce fluctuations in fawn fall recruitment. Here we make the case for using long‐term datasets for setting long‐term wildlife management goals that decision makers and the public can understand and support.