Role of covariates in determining probability of leopard occupancy in the west Chure range, structured on Pt obtained from Appendix 2

Model	AIC	ΔAIC	w	Model likelihood	K
$\widehat{\mathrm{\Psi }}$(IO+T+PS) θ 0(·) θ 1(·) p(IO+N+L) θ 0 pi(·)	614.78	0	0.6939	1	26
$\widehat{\mathrm{\Psi }}$(IO+T+PS+N), θ 0(·) θ 1(·),p(IO+N+L) θ 0 pi(·)	616.58	1.8	0.2821	0.4066	27
$\widehat{\mathrm{\Psi }}$(IO+T), θ 0(·) θ 1(·) p(IO+N+L) θ 0 pi(·)	623.99	9.21	0.0069	0.01	25
$\widehat{\mathrm{\Psi }}$(IO+T+L) θ 0(·) θ 1(·) p(IO+N+L) θ 0 pi(·)	624.2	9.42	0.0062	0.009	26
$\widehat{\mathrm{\Psi }}$(IO+T+PD) θ 0(·) θ 1(·) p(IO+N+L) θ 0 pi(·)	624.8	10.02	0.0046	0.0067	26
$\widehat{\mathrm{\Psi }}$(IO+T+R) θ 0(·) θ 1(·) p(IO+N+L) θ 0 pi(·)	625.98	11.2	0.0026	0.0037	26
$\widehat{\mathrm{\Psi }}$(IO+W) θ 0(·) θ 1(·) p(IO+N+L) θ 0 pi(·)	627.07	12.29	0.0015	0.0021	25
$\widehat{\mathrm{\Psi }}$(IO+T+N) θ 0(·) θ 1(·) p(IO+N+L) θ 0 pi(·)	627.52	12.74	0.0012	0.0017	26
$\widehat{\mathrm{\Psi }}$(IO+PS), θ 0(·) θ 1(·),p(IO+N+L), θ 0 pi(·)	628.11	13.33	0.0009	0.0013	25
$\widehat{\mathrm{\Psi }}$(IO), θ 0(·) θ 1(·),p(IO+N+L), θ 0 pi(·)	640.82	26.04	0	0	24
$\widehat{\mathrm{\Psi }}$(IO+R), θ 0(·) θ 1(·),p(IO+N+L), θ 0 pi(·)	641.08	26.3	0	0	25
$\widehat{\mathrm{\Psi }}$(PS), θ 0(·) θ 1(·),p(IO+N+L), θ 0 pi(·)	641.23	26.45	0	0	24
$\widehat{\mathrm{\Psi }}$(IO+N), θ 0(·) θ 1(·),p(IO+N+L), θ 0 pi(·)	642.43	27.65	0	0	25
$\widehat{\mathrm{\Psi }}$(IO+PD), θ 0(·) θ 1(·),p(IO+N+L), θ 0 pi(·)	642.77	27.99	0	0	25
$\widehat{\mathrm{\Psi }}$(IO+L), θ 0(·) θ 1(·),p(IO+N+L), θ 0 pi(·)	647.88	33.1	0	0	25
$\widehat{\mathrm{\Psi }}$(W), θ 0(·) θ 1(·),p(IO+N+L), θ 0 pi(·)	648.16	33.38	0	0	24
$\widehat{\mathrm{\Psi }}$(L), θ 0(·) θ 1(·),p(IO+N+L), θ 0 pi(·)	648.2	33.42	0	0	24
$\widehat{\mathrm{\Psi }}$(T), θ 0(·) θ 1(·),p(IO+N+L), θ 0 pi(·)	648.76	33.98	0	0	24
$\widehat{\mathrm{\Psi }}$, θ 0(·) θ 1(·),p(IO+N+L), θ 0 pi(·)	650.37	35.59	0	0	23
$\widehat{\mathrm{\Psi }}$(N), θ 0(·) θ 1(·),p(IO+N+L), θ 0 pi(·)	650.67	35.89	0	0	24
$\widehat{\mathrm{\Psi }}$(R), θ 0(·) θ 1(·),p(IO+N+L), θ 0 pi(·)	650.79	36.01	0	0	24
$\widehat{\mathrm{\Psi }}$(PD), θ 0(·) θ 1(·),p(IO+N+L), θ 0 pi(·)	651.02	36.24	0	0	24

$\widehat{\mathrm{\Psi }}$: 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; θ ₀ = Pr (leopard presence in a replicate/grid occupied and which was absent in the previous replicate) and “θ ₁”= Pr (leopard presence in a replicate/grid occupied and was present in the previous replicate); k = number of model parameters; Covariates: IO: management regime (grids inside and outside of the protected areas); 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; T = tiger; In all models, Pt from the top model (Appendix 2) was modeled as p(IO+N+L); + = covariates modeled additively; (·) = parameters are held constant. Model‐specific β‐coefficient estimates for covariates IO, T, PS from the top model determining leopard occupancy in the west Chure = 2.62 (SE 0.75), 2.93 (SE 1.09), and 2.16 (SE 0.70), respectively.