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Contrasting effects of anthropogenic disturbance on the interaction among sympatric carnivores


Penjor, Ugyen (2022), Contrasting effects of anthropogenic disturbance on the interaction among sympatric carnivores, Dryad, Dataset,


Interaction among species is central to the stability of community structure. However, anthropogenic pressures alter interactions, disrupt trophic levels, and threaten ecosystem stability. Understanding interactions across human land-use gradients is fundamental to mitigating anthropogenic threats effectively and better managing threatened species. Using data from a large-scale camera trap survey, we developed a multispecies occupancy model for a carnivore guild comprising tiger, leopard, and dhole to investigate the effects of environmental (forest and prey abundance) and anthropogenic (settlement) variables on the interspecific interaction. Human settlement density had a strong but contrasting effect on interaction: as settlement density increased, tigers and leopards were less likely to coexist whereas leopards and dholes were more likely to occur together. Tiger and dhole occupancy was negatively associated with settlement density whereas, the leopard was positively associated. Per cent forest cover and large prey abundance had ubiquitous positive effects on carnivore occupancy. Our results indicate that human presence alters available niche space and spatial overlap among predators affecting interactions. The duality in the effect of the settlement on interacting pairs suggests that humans create a landscape of fear for apex predators but promotes coexistence between subordinate species partially supporting the intermediate disturbance hypothesis.


We used camera traps to collect the data. A total of 1129 unbaited camera stations were established. We placed a pair of infrared motion-triggered camera traps in each grid cell along human or animal trails (except in absence of trails, when cameras were placed randomly) at a height of ~45 cm above the ground. For logistical convenience, the country was divided into two blocks and camera traps were deployed during the dry season. Data were processed in MS Excel spreadsheet and R programming language. We provide more details in the paper that used this dataset. Please follow the link to the paper.

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