| Summary: | <p>Camera trapping studies often focus on estimating population density, which is critical for managing wild populations. Density estimators typically require unique markers such as stripe patterns to identify individuals but most animals do not have such markings. The spatial capture model (SC model; Chandler & Royle, 2013) estimates density without individual identification but lacks sufficient field testing. Here, both the SC model and calibrated capture rate indices were compared against ten sessions of live trapping data on kangaroo rats (Dipodomys spp). These camera and live trapping data were combined in a joint-likelihood model to further compare the two methods. From these comparisons, the factors governing the SC model?s success were scrutinized. Additionally, a method for estimating missed captures was developed and tested here. Regressions comparing live trapping density to the SC model density and capture rate were significant only for the capture rate comparison. Missed image rate had a significant relationship with ambient nighttime temperatures but only marginally improved the capture rate index calibration. Results showed the SC model was highly sensitive to deviations from its movement model, producing potentially misleading results. The model may be effective only when movement assumptions hold. Several factors such as camera coverage area, microhabitat, and burrow locations could be incorporated into the SC model density estimation process to improve precision and inference.
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