TABLE 1.

Estimated Chinese pangolin (Manis pentadactyla) occupancy ( $\widehat{\mathrm{\Psi }}$ ) and detection probabilities ( $\widehat{p}$ ) from top‐ranked models in Nepal

ID	Models	N	Δ AICc	Wi	$\widehat{\mathrm{\Psi }}$ (1 ± SE)	$\widehat{p}$ (1 ± SE)	Model precision
	covariates
1.1	Ψ(Elevation)p( Forest+Slope+Ground+Red+Food+DR+DS+PA)	11	0.00	0.50	0.84 (0.09)	0.22 (0.05)	10.71
1.2	Ψ(Elevation)p(Farmland+Red+Food+DS+DL+DR+Canopy+PA)	11	0.17	0.46	0.92 (0.12)	0.16 (0.04)	11.08
1.3	Ψ(.)p(Farmland+Red+Food+DR+DS+PA)	8	7.28	0.01	0.76 (0.08)	0.31 (0.05)	10.52
1.4	Ψ(Elevation)p(DW+non‐PA)	5	7.75	0.01	0.70 (0.07)	0.35 (0.03)	10.00
1.5	Ψ(Elevation)p( Forest+Brown+Food+DL+DR+DS+non‐PA)	10	8.06	0.00	0.81 (0.09)	0.27 (0.06)	11.11
1.6	Ψ(.)p(.)	2	13.33	0.00	0.58 (0.05)	0.31 (0.026)	8.62
1.7	Model averaged				0.77 (0.08)	0.27 (0.05)	10.34

The covariates used in the study were habitat types (forest or farmland), soil type (red or brown), tree canopy, ground cover, distance to nearest human settlement (DS), distance to nearest road/foot trail (DR), distance to nearest livestock/sign (DL), food source, elevation, and slope after pooling the data from a protected (PA) and non‐protected (non‐PA) areas in Nepal. Ψ is the probability a site is occupied by Chinese pangolin, and p is the probability of detecting Chinese pangolin in the jth survey where Ψ (.)p(.) assumes that pangolin presence and detection probability are constant across sites, $\widehat{\mathrm{\Psi }}$ is the estimated over all occupancy probability, K is the number of parameters in the model, ΔAICc is the difference in AIC values between each model with the lowest AIC model, and W_i is the AIC model weight.