Seeing the Canopies for the Forest: Habitat Utilization Mapping Using Habitat Structure and Composition
Joseph J Erinjery1,2, Mewa Singh3, Olatunji Johnson4
1Department of Geography and Environment, Bar-Ilan University, Ramat-Gan, Israel.
Abstract:
Mapping habitat utilization at fine spatio-temporal scales is essential for understanding various aspects of animal ecology, and for the conservation and management of animal species. A unified approach incorporating habitat structure, composition, and animal activities is necessary for such fine-scale assessments. Here, we introduce a unified activity-based habitat utilization model based on simulations of habitat structure and composition, and map the fine-scale spatio-temporal habitat utilization of an endangered canopy dwelling primate inhabiting the Western Ghats, the lion-tailed macaque (Macaca silenus). From our simulations, we found that habitat utilization predictions will be enhanced when tree distribution and abundance are combined with height utilization data, compared to when they were assessed independently. This simulation study indicates that for all activities, primary forests provide more suitable habitats for lion-tailed macaques than plantations. Seasonal variation was observed in habitat suitability due to seasonality in the fruiting of trees, as plantations provided more suitable habitats during monsoon, while primary forests provided more suitable habitats in post monsoon and summer. We observed no locomotion routes with contiguous canopy connectivity in plantations, whereas such routes were common in forests. Our simulation-based model has implications for understanding many aspects of arboreal ecology, as it incorporates habitat structure and composition. Overall, our simulations reveal that incorporating habitat structure and composition is important for understanding fine-scale spatio-temporal habitat utilization of arboreal species, and it can be utilized for the conservation of primates inhabiting tropical habitats, where the collection of field data on trees for large areas can be demanding.
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