Acoustic and camera surveys inform models of current and future vertebrate distributions in a changing desert ecosystem

Abstract

Aim: Maintaining biodiversity in the face of land use and climate change is a paramount challenge, particularly when distributions of many species remain incompletely known. Emerging technologies help address this data deficiency by facilitating the collection of spatially explicit data for multiple species from multiple taxa. In this study, we combine acoustic and visual sensor surveys to inform conservation and land use planning in an area experiencing rapid climate and land use change.Location: Mojave Desert, California, United States. Methods: We deployed camera traps and acoustic detectors at 210 sites betweenMarch and July 2016. We identified photographic detections of mammals and acoustic recordings of songbirds to the species level and used multispecies occupancy models to estimate and evaluate species' occupancy probabilities. We then extrapolated model results to the region and forecasted how projected climate and land use changes might affect species' occupancy probabilities in 50 years. Lastly, we identified areas with high conservation value (i.e., high relative species richness) now and in 50 years, and related the distributions of these areas to land use designations. Results:We detected 15 mammal and 68 songbird species. At the community level, occupancy decreased with increasing temperatures and distances to woodlands. We forecasted that occupancy probabilities and areas with high conservation value would decline in 50 years due to projected increases in maximum temperatures and identified that up to 43%, 24% and 27% of land designated for renewable energy development, recreation and military activities, respectively, encompassed these high value areas. Main conclusions:Cooler areas close to woodlands and water are of high conservation value to mammals and songbirds in the Mojave. These areas will become increasingly limited with changing climate, however, making their protection from human disturbance imperative. We encourage continued use of visual and acoustic sensors across large spatial, temporal and taxonomic scales as tools to inform land use and wildlife conservation. K E Y W O R D Sacoustic recorder, camera trap, climate change, land use planning, Mojave Desert, multispecies occupancy model, species richness

Do acoustically detectable species reflect overall diversity? A case study from Australia’s arid zone

“…This is important because it allowed us to compare estimates of species richness and composition in varying climatic conditions, giving us a more robust understanding of the merits of each methodology. Additionally, as far as we are aware, this is the first published work to sample avian communities in the Australian arid zone using passive acoustic sensors and one of few in arid zones internationally (see Rich et al 2019). Our study sites are open habitats in which birds are often seen relatively easily.…”

Assessing occupancy and activity of two invasive carnivores in two Caribbean islands: implications for insular ecosystems

“…These approaches, such as occupancy‐detection models, represent effective tools for wildlife managers and land planners in order to develop proactive measures instead of reactive decisions (e.g. Ancillotto et al ., 2018; Rich et al ., 2019). The recent development of modern wildlife monitoring technologies, such as visual and acoustic sensors (i.e.…”

Insectivorous bat occupancy is mediated by drought and agricultural land use in a highly modified ecoregion

“…Our finer grid allowed us to integrate our data collection with other sensor‐based survey methods (e.g. acoustic recorders for birds, camera traps for terrestrial mammals), maximize coverage and provide stronger inference about stressor impacts on ecoregion biodiversity (Rich et al., 2019). We recommend that researchers weigh their specific data collection needs during the study design phase (Reichert et al., 2021), but acknowledge that broad‐scale deployments (e.g.…”

“…Specifically, we relied on covariate associations from regression to draw inferences and used those associations to predict occupancy across the study area (see Section 2.5). From positive landowner responses, we selected 1–2 survey locations within each hexagon and spaced sites at least 1,000 m apart (Rich et al., 2019). We chose this distance to maximize spatial replicates across the study area and target other study taxa (birds, mammals, herpetofauna; see Rich et al., 2019).…”

“…From positive landowner responses, we selected 1–2 survey locations within each hexagon and spaced sites at least 1,000 m apart (Rich et al., 2019). We chose this distance to maximize spatial replicates across the study area and target other study taxa (birds, mammals, herpetofauna; see Rich et al., 2019). All survey locations were treated as sites in analyses.…”