Integrating Occupancy Modeling and Camera-Trap Data to Estimate Medium and Large Mammal Detection and Richness in a Central American Biological Corridor

Abstract

Noninvasive camera-traps are commonly used to survey mammal communities in the Neotropics. This study used camera-traps to survey medium and large mammal diversity in the San Juan – La Selva Biological Corridor, Costa Rica. The connectivity of the corridor is affected by the spread of large-scale agriculture, cattle ranching, and a growing human presence. An occupancy modeling approach was used to estimate corridor species richness and species-specific detection probabilities in 16 forested sites within four different matrix-use categories: eco-lodge reserves, tree plantations/general reforestation, cattle ranches, and pineapple/agricultural plantations. Rarity had a highly negative effect (β = −1.96 ± 0.65 SE) on the ability to detect species presence. Corridor richness was estimated at 20.4 ± 0.66 species and was lower than that observed in protected areas in the Neotropics. Forest cover was significantly less at pineapple plantations than other land-use matrices. Richness estimates for different land-use matrices were highly variable with no significant differences; however, pineapple plantations exhibited the highest observed richness. Given the limited forest cover at those sites, we believe that this reflects the concentrated occurrence of medium and large mammals in small forest patches, particularly because the majority of pineapple plantation communities were generalist mesopredators. Fragmentation and connectivity will need to be addressed with reforestation and limitations on pineapple production for the region to function as an effective corridor. Occupancy modeling has only recently been applied to camera-trap data and our results suggest that this approach provides robust richness and detection probability estimates and should be further explored.