Fig 1.
ROC curve and AUC value under the current period (10 runs).
The current period is from 1950 to 2000.
Fig 2.
ROC curves and AUC values in future periods.
The future periods is 2030s (2021–2040), 2050s (2041–2060), 2070s (2061–2080) and 2080s (2071–2090).
Fig 3.
Jackknife test for variable importance of Psa habitat suitability distribution.
Values shown are averages over 10 replicate runs.
Table 1.
Estimates of contribution and permutation importance of environmental variables in MaxEnt modeling of Psa.
Fig 4.
Distribution of core suitable areas of Psa under current climate condition in China.
The probability of Psa is shown in the color scale in the legend. Red indicates highly suitable area with >66 probability of occurrence, orange indicates moderately suitable area with 33–66 probability of occurrence, yellow indicates poorly suitable area with 5–33 probability of occurrence and white indicates unsuitable area.
Table 2.
Analysis of highly suitable main distributions of Psa.
Fig 5.
Distribution of core suitable areas of Psa under different climate change scenarios in China.
The probability of Psa is shown in the color scale in the legend. Red indicates highly suitable area with >66 probability of occurrence, orange indicates moderately suitable area with 33–66 probability of occurrence, yellow indicates poorly suitable area with 5–33 probability of occurrence and white indicates unsuitable area of occurrence.
Fig 6.
Center displacement of highly suitable areas during different periods.
Table 3.
Predicted suitable areas for Psa under current and future climatic conditions.
Table 4.
Shifts in distance and direction of the mean centers of highly suitable areas in different periods.
Fig 7.
Response curves of the variables contributing most to the prediction by the MaxEnt models for Psa.
(A) Mean Temperature of Coldest Quarter (bio11; °C). (B) Precipitation of May (prec5; mm), (C) Maximum temperature of April (tmax4; °C), (D) Minimum temperature of October (tmin10; °C).
Table 5.
The suitable range of dominant environmental variables affecting the potential distribution of Psa.