Among numerous anthropogenic impacts on terrestrial landscapes, expanding transportation networks represent one of the primary challenges to wildlife conservation worldwide. Larger mammals may be particularly vulnerable because of typically low densities, low reproductive rates, and extensive movements. Although numerous studies have been conducted to document impacts of road networks on wildlife, inference has been limited because of experimental design limitations. During the last decade, the North Carolina Department of Transportation (NCDOT) rerouted and upgraded sections of United States Highway 64 between Raleigh and the Outer Banks to a 4-lane, divided highway. A new route was selected for a 24.1-km section in Washington County. The new section of highway included 3 wildlife underpasses with adjacent wildlife fencing to mitigate the effects of the highway on wildlife, particularly American black bears (Ursus americanus). We assessed the short-term impacts of the new highway on spatial ecology, population size, survival, occupancy, and gene flow of black bears. We tested our research hypotheses using a before-after control-impact (BACI) study design. We collected data during 2000-2001 (preconstruction phase) and 2006-2007 (postconstruction phase) in the highway project area and a nearby control area (each approx. 11,000 ha), resulting in 4 groups of data (i.e., pre-or postconstruction study phase, treatment or control area). We captured and radiocollared 57 bears and collected 5,775 hourly locations and 4,998 daily locations. Using mixed-model analysis of variance and logistic regression, we detected no differences in home ranges, movement characteristics, proximity to the highway alignment, or habitat use between the 2 study phases, although minimum detectable effect sizes were large for several tests. However, after completion of the new highway, bears on the treatment area became less inactive in morning, when highway traffic was low, compared with bears on the control area (F 1, 43 ¼ 6.05, P ¼ 0.018). We used DNA from hair samples to determine if population size and site occupancy decreased following highway construction. For each study phase, we collected black bear hair from 70 hair snares on each study area during 7 weekly sampling periods and generated genotypes using 10 microsatellite loci. We used the multilocus genotypes to obtain capture histories for 226 different bears and used capture-mark-recapture models to estimate population size. Model-averaged estimates of population size decreased on the treatment area from 87.7 bears before construction to 31.6 bears after construction (64% reduction) and on the control area from 163.6 bears to 108.2 bears (34% reduction). Permutation procedures indicated this reduction was proportionally greater for the treatment area (P ¼ 0.086). We also applied a spatially explicit capture-recapture technique to test our research hypothesis. The model with the most support indicated a greater change in density on the treatment area (69% reduction) compared with the...
Determining impacts of anthropogenic landscape changes on wildlife populations is difficult. Besides the challenges of designing field studies to document conditions before and after landscape changes occur, assessment of population responses (e.g. changes in population density) often provide poor inference because of sampling limitations. Estimation of occupancy, however, only requires data on detection or non-detection of a species and might provide better inference. To demonstrate the utility of occupancy models, we used data from an American black bear (Ursus americanus Pallas) population in North Carolina, USA to test our research hypothesis that documented declines in site occupancy of black bears would be greater near a new four-lane highway. We used multi-season occupancy models to estimate site occupancy based on bear visitation to survey sites before and after completion of the new highway and as a function of distance to the highway. Site occupancy declined from 0.81 to 0.35 between the two study phases, but was not a function of distance to the highway. Therefore, the impact of the new highway on occupancy extended to the entire study area. Our case study demonstrates that occupancy models can provide powerful inference regarding the potential impacts of landscape changes on species occupancy. As urban areas and transportation infrastructure are rapidly expanding in developing regions of the world, the need to determine how these changes affect mammal populations and how they might be mitigated increases accordingly. Because field sampling for occupancy models only requires detection data, surveys can be conducted for extensive geographic areas, thus making these surveys particularly applicable to studies of large mammals.
Understanding the density‐dependent processes that drive population demography in a changing world is critical in ecology, yet measuring performance–density relationships in long‐lived mammalian species demands long‐term data, limiting scientists' ability to observe such mechanisms. We tested performance–density relationships for an opportunistic omnivore, grizzly bears (Ursus arctos, Linnaeus, 1758) in the Greater Yellowstone Ecosystem, with estimates of body composition (lean body mass and percent body fat) serving as indicators of individual performance over two decades (2000–2020) during which time pronounced environmental changes have occurred. Several high‐calorie foods for grizzly bears have mostly declined in recent decades (e.g., whitebark pine [Pinus albicaulis, Engelm, 1863]), while increasing human impacts from recreation, development, and long‐term shifts in temperatures and precipitation are altering the ecosystem. We hypothesized that individual lean body mass declines as population density increases (H1), and that this effect would be more pronounced among growing individuals (H2). We also hypothesized that omnivory helps grizzly bears buffer energy intake from changing foods, with body fat levels being independent from population density and environmental changes (H3). Our analyses showed that individual lean body mass was negatively related to population density, particularly among growing‐age females, supporting H1 and partially H2. In contrast, population density or sex had little effect on body fat levels and rate of accumulation, indicating that sufficient food resources were available on the landscape to accommodate successful use of shifting food sources, supporting H3. Our results offer important insights into ecological feedback mechanisms driving individual performances within a population undergoing demographic and ecosystem‐level changes. However, synergistic effects of continued climate change and increased human impacts could lead to more extreme changes in food availability and affect observed population resilience mechanisms. Our findings underscore the importance of long‐term studies in protected areas when investigating complex ecological relationships in an increasingly anthropogenic world.
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