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Jaguars (Panthera onca) and pumas (Puma concolor) coexist throughout the Neotropics. Using camera trapping in four Brazilian biomes, we compare the daily activity patterns of the jaguar and puma, and their relationships with their main prey species. We used a kernel density method to quantify daily activity patterns and to investigate overlap between these predators and their main prey. Both cats showed intensive nocturnal and crepuscular activity (0.69 and 0.14 kernel density, respectively, for jaguars; 0.68 and 0.19 kernel density, respectively, for pumas). Only in the Pantanal did we observe a pattern of concentrated diurnal activity for both species. We found little temporal segregation between jaguars and pumas, as they showed similar activity patterns with high coefficients of overlapping (average ∆1 = 0.86; SE = 0.15). We also observed a significant overlap between the activity patterns of the predators and their main prey species, suggesting that both predators adjust their activity to reduce their foraging energy expenditure. Our findings suggest that temporal partitioning is probably not a generalized mechanism of coexistence between jaguars and pumas; instead, the partitioning of habitat/space use and food resources may play a larger role in mediating top predator coexistence. Knowledge about these behavior aspects is crucial to elucidating the factors that enable coexistence of jaguars and pumas. Furthermore, an understanding of their respective activity periods is relevant to management and associated research efforts.

Aim  To test the prediction that environmental suitability derived from species distribution modelling (SDM) could be a surrogate for jaguar local population density estimates. Location  Americas. Methods  We used 1409 occurrence records of jaguars to model the distribution of the species using 11 SDM methods. We tested whether models’ suitability is linearly correlated with jaguar population densities estimated from 37 different locations. We evaluated whether the relationship between density and suitability forms a constraint envelope, in which higher densities are found mainly in regions with high suitability, whereas low densities can occur in regions with variable suitability. We tested this using heteroscedasticity test and quantile regressions. Results  A positive linear relationship between suitability and jaguar density was found only for four methods [bioclimatic envelope (BIOCLIM), genetic algorithm for rule set production (GARP), maximum entropy (Maxent) and generalized boosting models (GBM)], but with weak explanatory power. BIOCLIM showed the strongest relationship. Variance of suitability for lower densities values was larger than for higher values for many of the SDM models used, but the quantile regression was significantly positive only for BIOCLIM and random forests (RF). RF and GBM provided the most accurate models when measured with the standard SDM evaluation metrics, but possess poor relationship with local density estimates. Main conclusions  Results indicate that the relationship between density and suitability could be better described as a triangular constraint envelope than by a straight positive relationship, and some of the SDM methods tested here were able to discriminate regions with high or low local population densities. Low jaguar densities can occur in areas with low or high suitability, whereas high values are restricted to areas where the suitability is greater. In high suitability areas but with low jaguar density estimates, we discuss how extrinsic factors driving abundance could act at local scales and then prevent higher densities that would be expected by the favourable regional environmental conditions.

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