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Resource selection by animals varies depending on spatial and temporal context, thus it is important to account for these factors when conducting studies that examine this behavior relative to the availability and distribution of resources. Many resource selection studies combine fine‐scale animal location data obtained using global positioning system (GPS) technology and coarse‐scale, remotely sensed, spatial layers. Fewer studies combine fine‐scale animal location data with vegetation data collected in the field, which can identify important fine‐scale drivers of resource selection. Understanding fine‐scale resource selection of ungulates inhabiting regions dominated by closed‐canopy forests may provide important information regarding management actions that improve habitat quality. From April 2021 to August 2022, we conducted vegetation surveys at locations (n = 1294) used by 39 GPS‐collared elk Cervus canadensis and at paired random locations (n = 2509) available to elk. We used conditional logistic regressions to compare seasonal (spring, summer, fall, winter) vegetation characteristics between used and available locations. We also conducted a species indicator analysis to compare plant species found at used and available locations during peak foraging periods (dawn/dusk). Regardless of season, the probability of use by elk increased as tree basal area (m2/ha) decreased, and the presence of herbaceous plants increased. Clovers (Trifolium spp.) were indicators of locations used by elk during primary foraging periods regardless of season. Other plants that were indicators of locations used by elk during at least one season included purple‐crown vetch Securigera varia, bird's foot trefoil Lotus corniculatus, and black medick Medicago lupulina. This research highlights the importance of managed openings, ecotones, and other communities characterized by reduced tree cover and increased herbaceous plants to meet the foraging needs of elk in landscapes dominated by closed‐canopy forests. Creating and maintaining managed herbaceous openings and restoring open‐forest communities will likely facilitate elk population growth and expansion.
Resource selection by animals varies depending on spatial and temporal context, thus it is important to account for these factors when conducting studies that examine this behavior relative to the availability and distribution of resources. Many resource selection studies combine fine‐scale animal location data obtained using global positioning system (GPS) technology and coarse‐scale, remotely sensed, spatial layers. Fewer studies combine fine‐scale animal location data with vegetation data collected in the field, which can identify important fine‐scale drivers of resource selection. Understanding fine‐scale resource selection of ungulates inhabiting regions dominated by closed‐canopy forests may provide important information regarding management actions that improve habitat quality. From April 2021 to August 2022, we conducted vegetation surveys at locations (n = 1294) used by 39 GPS‐collared elk Cervus canadensis and at paired random locations (n = 2509) available to elk. We used conditional logistic regressions to compare seasonal (spring, summer, fall, winter) vegetation characteristics between used and available locations. We also conducted a species indicator analysis to compare plant species found at used and available locations during peak foraging periods (dawn/dusk). Regardless of season, the probability of use by elk increased as tree basal area (m2/ha) decreased, and the presence of herbaceous plants increased. Clovers (Trifolium spp.) were indicators of locations used by elk during primary foraging periods regardless of season. Other plants that were indicators of locations used by elk during at least one season included purple‐crown vetch Securigera varia, bird's foot trefoil Lotus corniculatus, and black medick Medicago lupulina. This research highlights the importance of managed openings, ecotones, and other communities characterized by reduced tree cover and increased herbaceous plants to meet the foraging needs of elk in landscapes dominated by closed‐canopy forests. Creating and maintaining managed herbaceous openings and restoring open‐forest communities will likely facilitate elk population growth and expansion.
Context There is a growing appreciation that wildlife behavioral responses to environmental conditions are scale-dependent and that identifying the scale where the effect of an environmental variable on a behavior is the strongest (i.e., scale of effect) can reveal how animals perceive and respond to their environment. In South Texas, brush management often optimizes agricultural and wildlife management objectives through the precise interspersion of vegetation types creating novel environments which likely affect animal behavior at multiple scales. There is a lack of understanding of how and at what scales this management regime and associated landscape patterns influence wildlife. Objectives Our objective was to examine the scale at which landscape patterns had the strongest effect on wildlife behavior. Bobcats (Lynx rufus) our model species, are one of the largest obligated carnivores in the system, and have strong associations with vegetation structure and prey density, two aspects likely to influenced by landscape patterns. We conducted a multiscale resource selection analysis to identify the characteristic scale where landscape patterns had the strongest effect on resource selection. Methods We examined resource selection within the home range for 9 bobcats monitored from 2021 to 2022 by fitting resource selection functions which included variables representing landcover, water, energy infrastructure, and landscape metrics (edge density, patch density, and contagion). We fit models using landscape metrics calculated at 10 different scales and compared model performance to identify the scale of effect of landscape metrics on resource selection. Results The scale of effect of landscape metrics occurred at finer scales. The characteristic scale for edge density and patch density was 30 m (the finest scale examined), and the characteristic scale for contagion occurred at 100 m. Bobcats avoided locations with high woody patch density and selected for greater woody edge density and contagion. Bobcats selected areas closer to woody vegetation and water bodies while avoiding herbaceous cover and energy development infrastructure. Conclusions A key step in understanding the effect of human development and associated landscape patterns on animal behavior is the identifying the scale of effect. We found support for our hypothesis that resource selection would be most strongly affected by landscape configuration at finer scales. Our study demonstrates the importance of cross-scale comparisons when examining the effects of landscape attributes on animal behavior.
Outbreaks of COVID-19 in humans, Dutch elm disease in forests, and highly pathogenic avian influenza in wild birds and poultry highlight the disruptive impacts of infectious diseases on public health, ecosystems and economies. Infectious disease dynamics often depend on environmental conditions that drive occurrence, transmission and outbreaks. Remote sensing can contribute to infectious disease research and management by providing standardized environmental data across broad spatial and temporal extents, often at no cost to the user. Here, we (i) conduct a review of primary literature to quantify current uses of remote sensing in disease ecology; and (ii) synthesize qualitative information to identify opportunities for further integration of remote sensing into disease ecology. We identify that modern advances in airborne remote sensing are enabling early detection of forest pathogens and that satellite data are most commonly used to study geographically widespread human diseases. Opportunities remain for increased use of data products that characterize vegetation, surface water and soil; provide data at high spatio-temporal and spectral resolutions; and quantify uncertainty in measurements. Additionally, combining remote sensing with animal telemetry can support decision-making for disease management by providing insights into wildlife disease dynamics. Integrating these opportunities will advance both research and management of infectious diseases.
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