TABLE 4.

Ten top performing multivariate models in each study area, ranked by performance of AUC and AUC_diff values

Model number	Linear/point features	Topographic	Climatic	Landcover Landscape level	Landcover Class level	AUC test	AUCdiff
QLSNP
QLSNP_1	DENS_set_28800	SLP_2400	TEMP_300	AI_28800	GYR_AM_Gr_4800	0,892	−0,027
QLSNP_2	DENS_set_28800	SLP_2400	TEMP_300	AI_28800	PLAND_Gr_14400	0,89	−0,018
QLSNP_3	DENS_riv_4800	SLP_2400	TEMP_300	AI_28800	GYR_AM_Gr_4800	0,887	−0,022
QLSNP_4	DENS_riv_4800	SLP_2400	TEMP_300	AI_28800	PLAND_Gr_14400	0,886	−0,011
QLSNP_5	DENS_set_28800	SLP_2400	TEMP_300	PD_28800	GYR_AM_Gr_4800	0,881	−0,033
QLSNP_6	DENS_rd_19200	SLP_2400	TEMP_300	AI_28800	PLAND_Gr_14400	0,879	0,001
QLSNP_7	DENS_rd_19200	SLP_2400	TEMP_300	AI_28800	GYR_AM_Gr_4800	0,878	−0,005
QLSNP_8	DENS_set_28800	DISS_600	TEMP_300	AI_28800	GYR_AM_Gr_4800	0,877	−0,020
QLSNP_9	DENS_set_28800	DISS_600	TEMP_300	AI_28800	PLAND_Gr_14400	0,875	−0,016
QLSNP_10	DENS_set_28800	SLP_2400	TEMP_300	AI_28800	AREA_AM_Shr_19200	0,875	−0,015
QMLNR
QMLNR_1	Dens_riv_19200	CTI_14400	TEMP_300	CWED_28800	PLAND_Gr_14400	0,975	0,002
QMLNR_2	Dens_riv_19200	CTI_14400	TEMP_300	CWED_28800	GYR_AM_ Gr_19200	0,973	−0,001
QMLNR_3	Dens_riv_19200	SLP_28800	TEMP_300	CWED_28800	PLAND_Br_28800	0,972	−0,004
QMLNR_4	Dens_riv_19200	CTI_14400	TEMP_300	CWED_28800	GYR_AM_Br_28800	0,972	0,000
QMLNR_5	Dens_riv_19200	CTI_14400	TEMP_300	CWED_28800	GYR_AM_NLF_14400	0,972	0,001
QMLNR_6	Dens_riv_19200	CTI_14400	TEMP_300	PD_19200	PLAND_Gr_14400	0,972	0,002
QMLNR_7	Dens_set_9600	CTI_14400	TEMP_300	CWED_28800	PLAND_Gr_14400	0,972	0,003
QMLNR_8	Dens_riv_19200	SLP_28800	TEMP_300	CWED_28800	GYR_AM_Br_28800	0,971	−0,008
QMLNR_9	Dens_set_9600	CTI_14400	TEMP_300	CWED_28800	GYR_AM_ Gr_19200	0,971	−0,001
QMLNR_10	Dens_set_9600	CTI_14400	TEMP_300	CWED_28800	GYR_AM_Br_28800	0,971	0,000

Abbreviations: QLSNP, Qilianshan National Park; QMLNR, Qomolangma National Nature Reserve.