About 80% of the known breeding population of ocelots (Leopardus pardalis) in the USA occurs exclusively on private ranches in northern Willacy and Kenedy counties in South Texas. These private ranches support several large contiguous undisturbed patches of thornscrub, which is preferred by ocelots. Past studies have indicated ocelots in South Texas select for woody patches that contain extremely dense thornscrub (i.e., 95% canopy cover and 85% vertical cover) and require large patches of woody cover to survive. Landscape metrics have been used to explain ocelot habitat use in fragmented areas, but their application in less-fragmented rangelands is lacking. From 2011 to 2018, we used camera traps on the East Foundation’s El Sauz Ranch to assess seasonal habitat use of ocelots relative to landscape structure, configuration, and complexity and other site-level factors in South Texas. Seasonal habitat use and detection were positively influenced by larger mean patch area and lower landscape shape index values. We also observed ocelots were less likely to be detected during periods of drought and exhibited a seasonal trend in detection. Ocelots used woody patches that were larger and more regularly shaped, indicating a preference for areas with a lower degree of fragmentation across the study area. As patches become larger, they will coalesce over time and form larger woody aggregates, which will promote ocelot habitat use. Brush management needs to be strategic as patch area and shape index are a limiting factor to promote ocelot habitat use on working rangelands in South Texas. These results demonstrate the ability to use landscape metrics to discern the effects of spatial structure of vegetation communities relative to ocelot occupancy parameters.

Interspecific competition among carnivores has been linked to differences in behavior, morphology, and resource use. Insights into these interactions can enhance understanding of local ecological processes that can have impacts on the recovery of endangered species, such as the ocelot (Leopardus pardalis). Ocelots, bobcats (Lynx rufus), and coyotes (Canis latrans) share a small geographic range overlap from South Texas to south‐central Mexico but relationships among the three are poorly understood. From May 2011 to March 2018, we conducted a camera trap study to examine co‐occurrence patterns among ocelots, bobcats, and coyotes on the East Foundation's El Sauz Ranch in South Texas. We used a novel multiseason extension to multispecies occupancy models with ≥2 interacting species to conduct an exploratory analysis to examine interspecific interactions and examine the potential effects of patch‐level and landscape‐level metrics relative to the occurrence of these carnivores. We found strong evidence of seasonal mutual coexistence among all three species and observed a species‐specific seasonal trend in detection. Seasonal coexistence patterns were also explained by increasing distance from a high‐speed roadway. However, these results have important ecological implications for planning ocelot recovery in the rangelands of South Texas. This study suggests a coexistence among ocelots, bobcats, and coyotes under the environmental conditions on the El Sauz Ranch. Further research would provide a better understanding of the ecological mechanisms that facilitate coexistence within this community. As road networks in the region expand over the next few decades, large private working ranches will be needed to provide important habitat for ocelots and other carnivore species.

Introduction: Tanglehead is a grass native to southwestern US rangelands; however, its prevalence as a native invasive on South Texas rangelands has increased rapidly during the last decade. Large areas of monotypic stands have emerged in Jim Hogg, Duval, Brooks, and Kleberg counties. The aim of this research is to understand the spatial and temporal dynamics of these invasions as a model for the assessment of native invasive species. Our specific objectives were to (1) evaluate the feasibility of classifying tanglehead using 1-m resolution imagery data, (2) assess the spatial and temporal distribution of tanglehead in relation to soil type and distance from roads, and (3) quantify the temporal and spatial distribution of tanglehead on our study sites. We combined remote sensing approaches with landscape metrics to quantify the spatial and temporal distribution of tanglehead in five locations across our study area. We calculated the normalized difference vegetation index and combined it with the original aerial imagery to conduct an unsupervised classification with the following land cover classes: woody vegetation, tanglehead, non-tanglehead herbaceous, and bare ground. Soil type and the distance from roads were assessed to determine the relationship between these factors and tanglehead spatial distribution. Results: We were able to successfully map tanglehead using the 1-m imagery. Our image classification approach resulted in accuracies greater than 85% for all sites. Tanglehead occurred in sandy, loamy sand, and sandy loam soils. Over 70% of tanglehead cover occurred within the first 150 m from the edge of roads. This cover increased from 7.1% (SE = 1.1%) in 2008 to 17.8% (SE = 5.4%) in 2014. Once established, small patches of tanglehead began aggregating or coalescing with existing stands, thereby creating larger patches over larger areas. Conclusions: Our study has shown the value of analyzing spatiotemporal dynamics of tanglehead with remote sensing techniques and landscape metrics to improve our understanding of establishment and dispersal processes of a native invasive. This study provides useful information to improve rangeland management decisions as well as assessing native invasive dynamics with potential applications for assessing its effects on wildlife habitat, livestock operations, and habitat restoration strategies.