Role of covariates in determining probability of leopard occupancy in the east Chure range, structured on Pt obtained from Appendix 1

Model	AIC	ΔAIC	w	Model Likelihood	K
$\widehat{\mathrm{\Psi }}$(PS)(N),p(R)	243.64	0	0.3073	1	20
$\widehat{\mathrm{\Psi }}$(PS),p(R)	244.27	0.63	0.2242	0.7298	19
$\widehat{\mathrm{\Psi }}$(PS+N+L),p(R)	245.54	1.9	0.1188	0.3867	21
$\widehat{\mathrm{\Psi }}$(PS+PD),p(R)	245.86	2.22	0.1013	0.3296	20
$\widehat{\mathrm{\Psi }}$(PS+R),p(R)	245.96	2.32	0.0963	0.3135	20
$\widehat{\mathrm{\Psi }}$(PS+L),p(R)	246.13	2.49	0.0885	0.2879	20
$\widehat{\mathrm{\Psi }}$(·),p(R)	249.03	5.39	0.0208	0.0675	18
$\widehat{\mathrm{\Psi }}$(N),p(R)	249.36	5.72	0.0176	0.0573	19
$\widehat{\mathrm{\Psi }}$(PD),p(R)	250.64	7	0.0093	0.0302	19
$\widehat{\mathrm{\Psi }}$(L),p(R)	250.86	7.22	0.0083	0.0271	19
$\widehat{\mathrm{\Psi }}$(R),p(R)	251.02	7.38	0.0077	0.025	19

$\widehat{\mathrm{\Psi }}$: model‐averaged leopard occupancy; p = replicate‐level detectability; AIC = Akaike's information criterion, ΔAIC = difference in AIC value between the top model and the focal model; w = AIC weight; Model likelihood is −2 logarithm of the likelihood function evaluated at maximum; k = number of model parameters; Covariates: R = terrain ruggedness averaged across each grid; N = nondifferent vegetative index averaged across each grid; PD: averaged human population density in each grid; PS: prey species (rhesus, barking deer, chital); WB = wild boar; L = livestock presence; In all models, Pt from the top model (Appendix 1) was modeled as p(R); + = covariates modeled additively; (·) = parameters are held constant. β‐coefficient estimates for PS and N from the top model determining the leopard occupancy in the east Chure = 3.58(SE 1.89) and 0.68 (SE 0.48), respectively. The model‐averaged ${\widehat{\mathrm{\Psi }}}_{\mathrm{e}}$ was 0.46 (SE 0.043).