Spatial structure of woody cover affects habitat use patterns of ocelots in Texas

Abstract

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.

Factors influencing the habitat use by ocelots in one of the last large Atlantic Forest remnants in southeastern Brazil

“…Because our sampling design covered the entire RDSP area, we believe that our ocelot occupancy estimate reflected the real occupancy estimate for the species in the Park. When compared to estimates found in human-altered environments or nonprotected areas (Cruz et al, 2018;Lombardi et al, 2020), our occupancy estimate was considerably higher. It is worth noting that RDSP is one of the largest Atlantic Forest remnants in Brazil; hence, the ocelot occupancy estimate found in this study might reflect a positive scenario for the species in the biome.…”

“…Based on ground-truthing, our map´s accuracy was >95%. For each station, we selected a concentric circle (buffer) of 500-m radius (Figure A2 in Appendix) (Lombardi et al, 2020). This extent covers 78.5 ha and is equivalent to the smallest home range size ever recorded for ocelots (76 ha; Crawshaw & Quigley, 1989).…”

Effects of Scarification, Phytohormones, Soil Type, and Warming on the Germination and/or Seedling Performance of Three Tamaulipan Thornscrub Forest Species

“…Principal among these functions are wildlife habitat, which supports a hundred-million-dollar regional ecotourism industry based largely around bird- and butterfly-watching, and carbon sequestration [ 11 , 12 , 13 ]. These dense and well-armed forests provide a short, thick canopy preferred by many native reptiles and mammals, including endangered ocelots ( Leopardus pardalis ) that depend on closed-canopy thornforests with >95% cover [ 14 , 15 , 16 ]. Thornscrub forests also provide forage and habitat for a particularly high diversity and abundance of bees, beetles, resident and migratory birds and butterflies, and many other organisms [ 17 ].…”

If you build it, will they come? A comparative landscape analysis of ocelot roadkill locations and crossing structures

“…We calculated seven class-level landscape metrics ( Table 1 ): percent land cover (PLAND, %), patch density (PD, patches/ha), largest patch index (LPI, %), edge density (ED, m/ha), mean patch area (MPA, ha), mean nearest neighbor (ENN, m), and aggregation index (AI, %). These metrics described the amount and spatial distribution of land cover features within each extent and have been used to analyze habitat features of endangered felids [ 42 – 44 ]. Landscape metrics were calculated using FRAGSTATS 4.2 [ 45 ].…”