Table 1. Traditional and modified ROC AUC values for ENMs built on GARP and Maxent algorithms.

MODEL TRAINING	MODEL TESTING	PARAMETER	GARP	Maxent
On-Diagonal	Off-Diagonal	Minimum	1.0914	1.2605
		Maximum	1.6151	1.7410
		Mean	1.4528	1.4403
		Standard deviation	0.0884	0.0876
		# replicates≤1	0	0
		P	<0.001	<0.001
		Traditional ROC AUC	0.8376	0.886
Off-Diagonal	On-Diagonal	Minimum	1.0171	1.2317
		Maximum	1.6569	1.8229
		Mean	1.3137	1.3439
		Standard deviation	0.2075	0.1637
		# replicates≤1	0	0
		P	<0.001	<0.001
		Traditional ROC AUC	0.8377	0.8770
1980s	2000s	Minimum	1.0014	1.1259
		Maximum	1.504	1.5011
		Mean	1.1025	1.1541
		Standard deviation	0.0992	0.0609
		# replicates≤1	0	0
		P	<0.001	<0.001
		Traditional ROC AUC	0.7306	0.7483
1980s projected onto 2000s conditions	2000s	Minimum	1.4170	1.4348
		Maximum	1.5431	1.7221
		Mean	1.4377	1.4449
		Standard deviation	0.2	0.326
		# replicates≤1	0	0
		P	<0.001	<0.001
		Traditional ROC AUC	0.7964	0.8622

Traditional and modified ROC AUC values for GARP and Maxent models trained and tested with independent spatial subsets of WHO occurrence data subsets (first two sections). Performance of models trained with data from WHO (1980s) and applied directly to recent occurrence data, or projected onto environmental conditions of the 2000s is shown in the succeeding sections. Modified ROC AUC values are reported as minimum, maximum, mean, and standard deviation of 1000 random replicates; also provided is the number of bootstrap replicates falling at or below 1.