Quantifying the conservation status and abundance trends of wildlife communities with detection-nondetection data

Effective conservation requires understanding species' abundance patterns and demographic rates across space and time. Ideally, such knowledge should be available for whole communities because variation in species' dynamics can elucidate factors leading to biodiversity losses. However, collecting data to simultaneously estimate abundance and demographic rates of communities of species is often prohibitively time intensive and expensive. We developed a multispecies dynamic N-occupancy model to estimate unbiased, community-wide relative abundance and demographic rates. In this model, detection-nondetection data (e.g., repeated presence-absence surveys) are used to estimate species- and community-level parameters and the effects of environmental factors. To validate our model, we conducted a simulation study to determine how and when such an approach can be valuable and found that our multispecies model outperformed comparable single-species models in estimating abundance and demographic rates in many cases. Using data from a network of camera traps across tropical equatorial Africa, we then used our model to evaluate the statuses and trends of a forest-dwelling antelope community. We estimated relative abundance, rates of recruitment (i.e., reproduction and immigration), and apparent survival probabilities for each species' local population. The antelope community was fairly stable (although 17% of populations [species-park combinations] declined over the study period). Variation in apparent survival was linked more closely to differences among national parks than to individual species' life histories. The multispecies dynamic N-occupancy model requires only detection-nondetection data to evaluate the population dynamics of multiple sympatric species and can thus be a valuable tool for examining the reasons behind recent biodiversity loss.