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Carnivore extinctions frequently have cascading impacts through an ecosystem, so effective management of ecological communities requires an understanding of carnivore vulnerability. This has been hindered by the elusive nature of many carnivores, as well as a disproportionate focus on large-bodied species and particular geographic regions. We use multiple survey methods and a hierarchical multi-species occupancy model accounting for imperfect detection to assess extinction risk across the entire carnivore community in Ghana’s Mole National Park, a poorly studied West African savanna ecosystem. Only 9 of 16 historically occurring carnivore species were detected in a camera-trap survey covering 253 stations deployed for 5469 trap days between October 2006 and January 2009, and our occupancy model indicated low overall likelihoods of false absence despite low per-survey probabilities of detection. Concurrent sign, call-in, and village surveys, as well as long-term law enforcement patrol records, provided more equivocal evidence of carnivore occurrence but supported the conclusion that many carnivores have declined and are likely functionally or fully extirpated from the park, including the top predator, lion (Panthera leo). Contrary to expectation, variation in carnivore persistence was not explained by ecological or life-history traits such as body size, home range size or fecundity, thus raising questions about the predictability of carnivore community disassembly. Our results imply an urgent need for new initiatives to better protect and restore West Africa’s embattled carnivore populations, and they highlight a broader need for more empirical study of the response of entire carnivore communities to anthropogenic impact.

Species-area models have become the primary tool used to predict baseline extinction rates for species in isolated habitats, and have influenced conservation and land-use planning worldwide. In particular, these models have been used to predict extinction rates following the loss or fragmentation of natural habitats in the absence of direct human influence on species persistence. Thus, where direct human influences, such as hunting, put added pressure on species in remnant habitat patches, we should expect to observe extinction rates higher than those predicted by simple species-area models. Here, we show that extinction rates for 41 species of large mammals in six nature reserves in West Africa are 14-307 times higher than those predicted by models based on reserve size alone. Human population and reserve size accounted for 98% of the observed variation in extinction rates between reserves. Extinction occurred at higher rates than predicted by species-area models for carnivores, primates and ungulates, and at the highest rates overall near reserve borders. Our results indicate that, where the harvest of wildlife is common, conservation plans should focus on increasing the size of reserves and reducing the rate of hunting.

Protected areas (PAs) are a cornerstone of global efforts to shield wildlife from anthropogenic impacts, yet their effectiveness at protecting wide-ranging species prone to human conflict – notably mammalian carnivores – is increasingly in question. An understanding of carnivore responses to human-induced and natural changes in and around PAs is critical not only to the conservation of threatened carnivore populations, but also to the effective protection of ecosystems in which they play key functional roles. However, an important challenge to assessing carnivore communities is the often infrequent and imperfect nature of survey detections. We applied a novel hierarchical multi-species occupancy model that accounted for detectability and spatial autocorrelation to data from 224 camera trap stations (sampled between October 2006 and January 2009) in order to test hypotheses about extrinsic influences on carnivore community dynamics in a West African protected area (Mole National Park, Ghana). We developed spatially explicit indices of illegal hunting activity, law enforcement patrol effort, prey biomass, and habitat productivity across the park, and used a Bayesian model selection framework to identify predictors of site occurrence for individual species and the entire carnivore community. Contrary to our expectation, hunting pressure and edge proximity did not have consistent, negative effects on occurrence across the nine carnivore species detected. Occurrence patterns for most species were positively associated with small prey biomass, and several species had either positive or negative associations with riverine forest (but not with other habitat descriptors). Influences of sampling design on carnivore detectability were also identified and addressed within our modeling framework (e.g., road and observer effects), and the multi-species approach facilitated inference on even the rarest carnivore species in the park. Our study provides insight for the conservation of these regionally significant carnivore populations, and our approach is broadly applicable to the robust assessment of communities of rare and elusive species subject to environmental change.