Evaluating temporal trends in habitat and behavioral responses is critical for conservation, yet long‐term monitoring studies are rare. We used a 35‐year dataset (1982–2017) to assess multiscale habitat use and selection by an endangered carnivore, the ocelot (Leopardus pardalis), in South Texas, USA. We used a time series of remotely sensed imagery to map changes in availability of woody cover, habitat critical to ocelots that has diminished due to anthropogenic development and increased road infrastructure. Our objectives were to characterize habitat relationships, predict high‐quality habitat, and assess behavior with changing environmental conditions. We fit functional response (third order) and individual‐specific resource selection (second order) functions to assess multiscale habitat use of vegetation cover and roads. Within home ranges, ocelots used woody cover greater than availability. Ocelots used areas near roads in proportion to availability, with minor exceptions. We observed changes in habitat use by ocelots across time with higher proportions of woody and non‐woody cover used in later time periods. Average availability of woody cover decreased in the study area between the 1980s and 2010s (0.44 in 1985 to 0.39 in 2015, p < 0.001), and ocelots used areas with a higher proportion of woody cover (≥0.48) farther from high‐traffic roads compared to availability. High‐quality ocelot habitat was consistently predicted in areas with high proportions of woody cover, while areas closer to high‐traffic roads were consistently predicted as non‐habitat. The extent of predicted habitat never exceeded 47% (1515 km2) of the study area, illustrating the confined nature of ocelot habitat. Our assessment of multiscale habitat use demonstrated that higher order selection processes likely truncate resource gradients within home ranges. Ocelots did not avoid roads as expected within home ranges, which is a likely mechanism for vehicle‐induced mortality. Private lands contained ≥79% of predicted high‐quality habitat over time. Therefore, the future of ocelots in the United States relies on private land stewardship. Insights gained from these analyses can advance habitat conservation and mitigation of road mortality for ocelot populations.
Wildlife-vehicle collisions can have a substantial influence on the mortality rates of many wildlife populations. Crossing structures are designed to mitigate the impact of road mortality by allowing safe passage of wildlife above or below roads, and connect to suitable areas on both sides of the road. Ocelots (Leopardus pardalis) are a federally endangered felid in the United States, with remnant populations of <80 individuals remaining in the Lower Rio Grande Valley of South Texas. Vehicle collisions are the greatest known source of mortality for ocelots in Texas. Crossing structures designed for ocelot use have been implemented throughout South Texas since the 1990s, however, ocelots rarely use them. We compared landscape characteristics between ocelot crossing structures and ocelot-vehicle collision sites. We quantified the spatial distribution of woody and herbaceous cover types surrounding ocelot crossing structures (n = 56) and ocelot-vehicle collision sites (n = 26) at multiple spatial extents and compared landscape metrics between these location types. The landscape surrounding ocelot crossing structures had 17–22% more open herbaceous cover >1,050 m from the road, and 1.2–5.8 ha larger herbaceous patches >450 m from the road compared to ocelot-vehicle collision sites. Additionally, many crossing structures installed during the 1990’s are situated >100 km away from an extant ocelot population. Results from this study can guide conservation planners to place future road crossing structures in areas more likely to be used by ocelots. Our results also emphasize that reliable scientific data must be used for effective mitigation efforts. In the absence of data, post-installation assessments can improve the placement of future structures.
Assessment of locations where wildlife species cross highways is a key question in mitigating future wildlife-vehicle mortality. Examination of the spatial structure, complexities, and patterns of vegetation or other land-use types (i.e., cropland, urban areas) near roadways allows scientists to identify any thresholds that influence where animals are likely to die or successfully cross the roadway. We used a historic 1982 to 2017 dataset of ocelot (Leopardus pardalis pardalis) mortality locations and approximate road crossing locations of telemetered ocelots in the Lower Rio Grande Valley in Texas to examine the spatial structure of woody vegetation within a hypothesized road effect zone. We determined if there were differences in the spatial structure of woody cover within a 1050 m buffer of each successful crossing and roadkill location using PERMANOVA and principal component analyses. We used a similarity percentages analysis to determine the relative contribution of each aspect of spatial structure on differences in successful crossing and roadkill locations. We found statistically significant differences in spatial attributes of patches at the locations of successful crossing versus roadkill locations of ocelots at the 150 m spatial extent (pseudo-F1,41 = 4.85, P(perm) = 0.008, permutations = 9949). Largest patch index contributed most to the differences between successful crossing and roadkill locations (15.94%), followed by mean patch area (15.44%), percent woody cover (15.18%), aggregation indices (14.53%), Euclidean nearest neighbor (13.47%), edge (13.08%) and patch densities (12.36%). Roadkill locations were clustered in locations with lower-quality woody cover within 300 m of the highway. This suggests areas immediately surrounding roads need to contain woody patches that are larger and closer together to reduce the barrier-effects of roads. Such information is important for informing highway planners about where to encourage crossings or to build wildlife crossing structures to promote movement across the highway.
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