*3.1. Model Accuracy and Prediction of Potentially Suitable Areas*

Generally, both GARP and Maxent showed a good performance when considering all accuracy measures considered (AUC, Kappa, and TSS; Table 2); thus the resulting potential distributions of the species were considered to provide a reliable estimate of the forecasted effects of climate change. However, the values of the AUC, Kappa, and TSS of GARP were significantly higher than Maxent (Table 2), indicating that GARP had a higher performance than Maxent.

**Table 2.** Comparison of area under the ROC curve (AUC), kappa and true skill statistic (TSS) of Genetic Algorithm for Rule-set Prediction (GARP) and Maxent models.


The predicted potential geographic distribution of *E. japonica* from both GARP and Maxent models were projected onto China using the identical environmental variables (Figure 2). The output maps for China's potential distribution of *E. japonica* based on GARP analysis were consistent with Maxent's projected distribution. Both models predict that the climate in temperate and subtropical regions of southeastern China is suitable for the growth of *E. japonica*. However, differences were also detected in the current potential distributions predicted by Maxent and GARP; to be specific, GARP predicted that large areas of habitat in Anhui, Jiangsu and Yunnan provinces were suitable; however, the areas predicted by Maxent in those two province were small. Moreover, GARP predicted that the potential geographic distribution with high suitability was continuous and covers a large area, whereas that predicted by Maxent was scattered and small.

#### *3.2. Variable Importance and Climatic Preference*

Jackknife tests (Figure 3) analyzed in Maxent on the environmental variables indicated that (Bio 6, Bio 12, Bio 2, and Bio 1 were the most important environmental factors affecting the distribution of *E. japonica*. Analyzing those response curves (Figure 4) also indicated how the logistic prediction for *E. japonica* changes while maintaining the remaining predicting factors at their average values. Generally, the minimum temperature of the coldest month and the annual mean temperature showed a

positively non-linear response, but a negative nonlinear response for mean diurnal range. The optimum annual precipitation for the probability of *E. japonica* occurrence was approximately 1000–2000 mm.

**Figure 3.** Jackknife test used to evaluate the relative importance of environmental variables for *Euscaphis japonica* in China by Maxent.

**Figure 4.** Average response curves of the main predictor variables of the modeled distribution of *Euscaphis japonica* based on the Maxent algorithm.
