N-mixture models with camera trap imagery produce accurate abundance estimates of ungulates

Abundance estimates inform ungulate management and recovery efforts. Yet effective and affordable estimation techniques remain absent for most ungulates lacking identifiable marks and inhabiting rugged or highly vegetated terrain. Methods using N-mixture models with camera trap imagery form an appealing solution but remain unvalidated. We assess this method using populations of desert bighorn sheep (DBS; Ovis canadensis) in New Mexico, USA, plus bison (Bison bison bison) and Texas longhorn cattle (Bos taurus taurus) in Oklahoma, USA, by calculating and comparing abundance estimates to censused values. We parsed data by 3 and 7-day intervals, using images filtered or unfiltered, and collected with motion detection or timed camera settings. We employed priors informed by subject matter experts (SME) and calculated using detection-nondetection methods. Abundance estimates from filtered images captured by motion detection in 3-day intervals included the censused value across all seasons for adult DBS, rams and ewes, indicating "best practices". This "best practices" method also captured censused values for population estimates of bison (detection-nondetection) and cattle with both priors. Our assessment validates the use of N-mixture with camera trap imagery, while presenting sampling approaches, data handling procedures and model calibration to estimate wildlife population sizes more appropriately and accurately.