Density of ocelots in a semiarid environment in northeastern Brazil

Spatial capture-recapture and LiDAR-derived vegetation metrics reveal high densities of ocelots on Texas ranchlands

Reliable estimates of population density and size are crucial to wildlife conservation, particularly in the context of the Endangered Species Act. In the United States, ocelots (Leopardus pardalis pardalis) were listed as endangered in 1982, and to date, only one population density estimate has been reported in Texas. In this study, we integrated vegetation metrics derived from LiDAR and spatial capture-recapture models to discern factors of ocelot encounter rates and estimated localized population estimates on private ranchlands in coastal southern Texas. From September 2020 to May 2021, we conducted a camera trap study across 42 camera stations on the East Foundation’s El Sauz Ranch, which was positioned within a larger region of highly suitable woody and herbaceous cover for ocelots. We observed a high density of ocelots (17.6 ocelots/100 km2) and a population size of 36.3 ocelots (95% CI: 26.1–58.6) with the 206.25 km2 state space area of habitat. The encounter probability of ocelots increased with greater canopy cover at 1-2 m height and decreasing proximity to woody cover. These results suggest that the incorporation of LiDAR-derived vegetative canopy metrics allowed us to understand where ocelots are likely to be detected, which may aid in current and future population monitoring efforts. These population estimates reflect the first spatially explicit and most recent estimates in a portion of the northernmost population of ocelots in southern Texas. This study further demonstrates the importance of private working lands for the recovery of ocelots in Texas.

The role of unprotected and privately protected areas for ocelot conservation: densities in Colombia and Brazil

The ocelot (Leopardus pardalis) is a widely distributed, medium-sized felid in the Americas with declining population size. We estimated ocelot densities and home ranges in one agricultural area in the Magdalena River valley in Colombia, a private reserve and cattle ranch in the Colombian Llanos, and a private reserve in the Serra do Amolar in the Brazilian Pantanal. We used camera trapping (39–52 stations) and spatially explicit capture-recapture (SECR) models. Density estimates (individuals/100 km2) were 11.0 ± 2.7 (SE) in the Magdalena River valley; 13.2 ± 3.2 (SE) in the Llanos, and 10.3 ± 2.9 (SE) in the Serra do Amolar. Overall, despite an impact of agriculture and human disturbance, our results highlight the importance of unprotected areas and privately protected ranching areas for ocelot conservation. As agriculture continues to expand across the tropics causing habitat loss, and negatively affecting ocelot densities, we recommend land use planning and best agricultural practices to maintain natural habitats, thereby limiting human impacts on ocelot conservation.

Habitat use of the ocelot (Leopardus pardalis) in Brazilian Amazon

Amazonia forest plays a major role in providing ecosystem services for human and sanctuaries for wildlife. However, ongoing deforestation and habitat fragmentation in the Brazilian Amazon has threatened both. The ocelot is an ecologically important mesopredator and a potential conservation ambassador species, yet there are no previous studies on its habitat preference and spatial patterns in this biome. From 2010 to 2017, twelve sites were surveyed, totaling 899 camera trap stations, the largest known dataset for this species. Using occupancy modeling incorporating spatial autocorrelation, we assessed habitat use for ocelot populations across the Brazilian Amazon. Our results revealed a positive sigmoidal correlation between remote-sensing derived metrics of forest cover, disjunct core area density, elevation, distance to roads, distance to settlements and habitat use, and that habitat use by ocelots was negatively associated with slope and distance to river/lake. These findings shed light on the regional scale habitat use of ocelots and indicate important species-habitat relationships, thus providing valuable information for conservation management and land-use planning.