Fig 1.
Atlantic Forest reserves sampled for ocelot populations in State of Minas Gerais (MG), southeastern Brazil.
FM = Fazenda Macedônia Reserve; FMA = Feliciano Miguel Abdala Reserve; MS = Mata do Sossego Reserve; SB = Serra do Brigadeiro State Park; SS = Sete Salões State Park; RD = Rio Doce State Park. The current distribution of Atlantic Forest remnants are shown in the insert (grey area) as defined by the SOS Mata Atlântica Foundation [47]. The state divisions are from the Brazilian Institute of Geography and Statistics [48].
Table 1.
Area covered by camera traps (minimum convex polygon—MCP—area), buffer area and effective trapping areas (ETA) based on two distances (MMDM = 2,718.61 m and ½ MMDM = 1,359.31 m) derived from camera traps in six Atlantic Forest reserves in southeastern Brazil.
Table 2.
List of covariates used to model the variation in detection probability of ocelots among reserves, specifically the percentage of land covered by road networks and Forest Area, percentage of cameras installed on unpaved roads, the number of dogs detected in the reserve, reserve size and the presence of both Top Predators.
Forest Area, Number of Dogs, Reserve size and Presence of both Top Predators were also used to model the process variance in abundance estimates of ocelot populations in six Atlantic Forest reserves in southeastern Brazil.
Table 3.
Abundance and density estimates for ocelots derived from camera-trap studies conducted in six Atlantic forest reserves, southeastern Brazil.
Table 4.
The percent of biological process variation in ocelot abundance explained by four reserve variables among six Atlantic Forest reserves in southeastern Brazil.
Negative process variances were considered zero. See Methods for details.
Fig 2.
Model-averaged estimates of ocelot detection probabilities (p; ± 95% CI) in six Atlantic Forest reserves, southeastern Brazil.
FM = Fazenda Macedônia Reserve; FMA = Feliciano Miguel Abdala Reserve; MS = Mata do Sossego Reserve; SB = Serra do Brigadeiro State Park; SS = Sete Salões State Park; RD = Rio Doce State Park.
Table 5.
Model selection results for variables expected to influence ocelot detection probability in six Atlantic Forest reserves in southeastern Brazil.
Only models with an AICc weights ≥ 0.01 are presented here.
Table 6.
Cumulative AICc weights for variables used to model ocelot detection probabilities in six Atlantic Forest reserves in southeastern Brazil.
Table 7.
Abundance and density estimates for ocelots derived from camera-trap studies conducted in Atlantic forest sites.
Estimates are provided for two levels of buffers (MMDM, ½MMDM) according to their availability in each study. Ninety-five percent confidence intervals (95% CI) are presented, unless not included in a study.