Comparison of species richness and detection between line transects, ground camera traps, and arboreal camera traps

Monitoring trends in the occurrence of species over time is important for informing conservation plans and concurrent management actions. Understanding the effectiveness of field methodologies for collecting accurate and precise data is crucial for optimizing allocation of sampling effort and resources. In this study, we compared mammalian species richness and detection probabilities between three field methodologies: line transects, ground camera traps and arboreal camera traps in Nyungwe National Park, Rwanda. Arboreal camera traps may be suitable for monitoring mammal communities with arboreal species, but their relative effectiveness compared to the more common field methods, line transects and ground camera traps, is relatively unknown. Using single-season occupancy models with multi-species data and single-species multi-method occupancy models, we estimated mammalian species richness and detection probability for each method and combination of methods. In addition, we estimated single-species occupancy and detection probability by method for six diurnal primate species. And, we tested for the effect of height on a tree on estimated occupancy probability and detection probability for arboreal camera traps. Overall, for all species the combination of ground and arboreal cameras was the most effective methodology in terms of highest estimates of occupancy and detection coupled with highest precision. However, for the six primate species the most effective method differed between species. The height of the arboreal camera trap in the tree did not significantly affect estimates of occupancy or detection. We suggest using all three field methods concurrently to maximize detection of all species; however, if only two methods can be deployed combining arboreal and ground cameras provided the highest and most precise estimates of occupancy and detection. The addition of arboreal camera traps could improve detection of species and improve future species monitoring programs.