Margay (Leopardus wiedii) in the southernmost Atlantic Forest: Density and activity patterns under different levels of anthropogenic disturbance

Abstract

The margay (Leopardus wiedii) is a small Neotropical arboreal wild cat. This species is thought to be forest-dependent, although few studies so far have directly evaluated the relationships between spatiotemporal aspects of its ecology and landscape characteristics. The aim of this study was to estimate margay population density and activity patterns in six areas with different habitat types and levels of anthropogenic disturbance in the southernmost Atlantic Forest of Brazil. Our working hypothesis was that density and activity patterns differed between areas in response to differences in forest cover and anthropogenic disturbance. Margay records were obtained using camera trapping, during spring and summer from 2017 to 2019. In all areas, the sampling scheme consisted of 20 un-baited stations, set 1km apart, each containing two paired cameras. We assessed the potential effects of environmental variables, including anthropogenic factors, on margay density, rate of detection and space use by comparing nine spatial capture-recapture (SCR) models. Activity patterns of the margay, its potential prey, and competitors were described and compared using the date and time of the records. We obtained 66 records of margay. Two of the six sampled areas were excluded from subsequent analyses due to the small number of records. The density estimated by the top-ranked model varied from 9.6±6.4 individuals/100km 2 in the area with the highest human disturbance to 37.4±15.1 individuals/100km 2 in a less disturbed area. Margay densities responded positively to vegetation cover, supporting the hypothesis of forest dependence by the species. Both the margay and their potential prey (small rodents and marsupials) were found to be mostly nocturnal. Margay activity also overlapped with that of the ocelot, Leopardus pardalis, and with mammals associated with human

Long-term monitoring of margays (Leopardus wiedii): Implications for understanding low detection rates

“…Spatial recaptures were rare, especially for the surveys designed for large cats (>1.5 km between stations), but increased with camera density (shorter trap spacing). We are aware of only two other camera trap studies which report on the recapture rates of margays: in the Atlantic forest, Brazil, the individual encounter frequencies ranged from 1 to 6 detections at the same location over 60 sampling days [ 12 ]; and in forest of the eastern slopes of the Andes in Ecuador, nine out of 10 margays were recaptured over 19 months, with an average of 7.5 detections per individual (range = 1 to 17), at an average of 4.5 locations per individual (range = 1 to 9 locations, with cameras spaced 200–500 m apart [ 14 ], Vanderhoff pers comm).…”

“…Given these range sizes, we suggest that detection rates might be improved if trap spacing does not exceed 1 km (e.g. [ 12 , 26 , 30 ]).…”

“…Although wide dirt roads are attractive travel routes for large cats like jaguars [ 4 ], we detected no margays here. Indeed, margays are more likely to be detected on narrow trails (0.5–1.5 m) than wide trails (> 1.5m) or dirt roads, and prefer to walk under vegetation cover than in the open [ 12 , 30 , 36 ]. In our study, the trails were on average 1.7 m wide [ 4 ].…”

“…Compared with other neotropical cats, the scientific community knows relatively little about margays [ 10 ]. They are associated with mature moist broadleaf forest, suggesting that they do well in protected forest interiors [ 11 , 12 ]. Margays are well known for their climbing abilities, and evidence of arboreal hunting can be found in their diet [ 11 ].…”

“…However, we expect that short-term surveys for jaguars are sub-optimal for sampling margays for population assessment, as the cameras are primarily deployed along trails, spaced widely compared to the margay home range [ 11 ], and under these sub-optimal sampling conditions are not run for long enough to amass sufficient captures and spatial recaptures to estimate population size [ 19 ]. Methods for assessing population status from camera data range from density estimation by mark-recapture analysis [ 12 , 20 ], spatial distribution from occupancy modelling [ 21 , 22 ], or at the simplest level, use of relative abundance indices (RAI) based on raw detections and trap effort [ 23 , 24 ]. The more robust analyses, such as mark-recapture or occupancy modelling tend to be data hungry and so may be unsuitable for use with sparse ‘by-catch’ data, leaving only RAIs for making weak inferences about the population.…”