The evaluation of ensemble model performance and the calculation of environmental variable importance within the ensemble model

[xunuan2020]

Hello, SIR: This question is about how to evaluate ensemble model performance and calculate environmental variable importance. When conducting the following steps, I utilized the parameters below: mxnt.mdls.preds.lst<-calib_mdl_b(ENMeval.o.l = ENMeval.res.lst, a.calib.l = clim.stack.list, occ.l = occ.list, mSel = "EBPM") I obtained the following results in model performance and variable importance: (1) metric.var.PermImportance.csv sp sel.crit wc2_13 wc2_14 wc2_15 wc2_3 wc2_4 wc2_8 wrb_MostProba 1 R Mod.EBPM_1 3.3966 0 0 3.5917 17.5038 20.1878 18.6949 2 R Mod.EBPM_2 4.4336 1.446 2.0736 3.4377 16.4984 1.3751 45.5691 3 R Mod.EBPM_4 3.1912 9.8249 14.111 2.0451 5.4621 1.5338 36.9477 4 R Mod.EBPM_5 1.7422 2.8706 0 3.5272 11.5683 0.1122 59.874 5 R Mod.EBPM_3 2.4887 23.3218 1.7355 0 2.6066 0.0851 51.2607 (2) sel.mdls.smmr.Rho.csv Optimality criteria FC RM AICc delta AICc wAIC parameters Rank AIC avg OR10 avg ORLPT avg AUC 2 EBPM_1 LQ 0.5 NA NA NA 17 12 0.25 0.083333333 0.986241667 10 EBPM_2 LQH 1 NA NA NA 29 20 0.416666667 0.083333333 0.983875 11 EBPM_4 LQHP 1 NA NA NA 31 21 0.416666667 0.083333333 0.983333333 16 EBPM_5 LQH 1.5 NA NA NA 21 25 0.333333333 0.083333333 0.982458333 18 EBPM_3 LQHPT 1.5 NA NA NA 23 27 0.333333333 0.083333333 0.983758333 But I want to obtain the overall evaluation results of this ensemble model, not individual evaluation results. What should I do? Thanks!