EN
The earth is now facing the land degradation due to human disturbance, natural habitats were converted to rural and agricultural areas in order to fulfill the increasing demand of human population. The deforestation of Picea crassifolia (Qinghai spruce) forest at Qilian Mts is an example of such disturbance. P. crassifolia is an ecologically and hydrologically important plant species in the northwestern arid area of China. However, the forests have been intensively and extensively deforested. In order to restore the human-disturbed ecosystems, the spatial distribution of P. crassifolia needs to be delineated. This study employed Genetic Algorithm for Rule-set Prediction model (GARP) and Maximum entropy model (Maxent) and four environmental variables (mean temperature of the warmest quarter, precipitation of the wettest quarter, annual solar radiation, topographic wetness index) to predict the potential distribution of P. crassifolia in Qilian Mts. Genetic Algorithm for Rule-set Prediction model (GARP) produces a model of species niches in geographic space based on heterogeneous rule-sets. Maximum entropy model (Maxent) focuses on fitting a probability distribution for occurrence based on the idea that the best explanation to unknown phenomena will maximize the entropy of the probability distribution, subject to the appropriate constraints. The environmental variables were spatially interpolated throughout the entire study area. We used sensitivity-specificity sum maximum approach to select the threshold value. The projected niche space for the mean temperature of the warmest quarter is between 8.5 and 18.1°C; the space for the precipitation of the wettest quarter is between 149 and 245 mm; the space for annual solar radiation is 118–1100×103 wh m–2 and the space for topographic wetness index is between –0.4 and 5.1. The results show that both GARP and Maxent’s models produce acceptable predictions, but the overall comparison shows that GARP prediction is better than Maxent’s; the comparison between the observed distribution and the predicted distribution suggests that 61% (2869 km2) of P. crassifolia forests have been deforested.