Landscape structure of woody communities for ocelots in southern Texas: Implications for translocation and road mitigation

Jason V. Lombardi, Humberto L. Perotto-Baldivieso, Maksim Sergeyev, Amanda M. Veals and Michael E. Tewes, Caesar Kleberg Wildlife Research Institute, Texas A&M University-Kingsville, Kingsville, TX, Landon Schofield, East Foundation, Kingsville, TX, John H. Young Jr., Texas Department of Transportation, Austin, TX

Background/Question/Methods
Landscape-based models have traditionally used different types of frameworks to describe the patterns and processes that govern ecological processes that drive animal-habitat relationships. Recent advancements in remote sensing and landscape ecological concepts now allow the examination of the full range of conditions along a continuum of metrics perceived usable by a species of interest. Identification of such conditions can influence conservation strategies of endangered species, such as the ocelot (Leopardus pardalis) in the United States. Our objectives were to (i) identify the range of cover metrics associated with woody vegetation used by endangered ocelots, and (ii) quantify the potential distribution of suitable woody cover patches for ocelots across southern Texas. We used the gradient concept of landscape ecology and the concept of slack combined with GPS data from 10 ocelots caught from 2016 to 2020 to identify the range of the spatial structure of woody cover in South Texas.
Results/Conclusions
The spatial distribution of optimal woody cover is comprised of large woody patches, with low shape-indices (1.07–2.25), and low patch (27.2–72.5 patches/100 ha), and edge densities (0–191.5 m/ha). Model verification indicated percentages of expected relocations and observed historic relocations were not statistically different among years, except for 2014 (χ2 = 38.6, α = 0.05; df = 3; Table 3). Our results indicate there is 28.1% optimal cover in the eight-county study area and there are large areas in the western and northeastern regions that are suitable for translocation measures. Our study illustrates that the range of landscape structural metrics important for ocelots is composed of large, regularly shaped patches in low densities in high aggregations, an indication of a forest-dependent species. This strengthens growing support for use of landscape metrics in defining the range of landscape metrics perceived usable for ocelots in Texas and its importance in defining ocelot cover. We observed more optimal cover in southern Texas that may be usable by ocelots than previously believed. The results indicate a model based on the gradient concept of landscape structure and the concept of slack is transferable across time and space and can be used in the future to predict suitable cover for ocelots in Texas. These results will aid in the further fine-scale evaluation of potential recovery areas for translocation and identification of locations for wildlife crossing structures in southern Texas.