Wang Jiazhi, Cheng Jiming, Zhang Chao, Feng Yingqun, Jin Lang, Wei Shuhua, Yang Hui, Cao Ziyu, Peng Jiuhui, Luo Yonghong
China Meteorological Administration Xiong'an Atmospheric Boundary Layer Key Laboratory, Xiong'an New Area 071800, China.
Key Laboratory of Meteorology and Ecological Environment of Hebei Province, Shijiazhuang 050021, China.
Biology (Basel). 2024 Nov 25;13(12):973. doi: 10.3390/biology13120973.
Mountain apricot () is an important fruit tree variety, and has a wide range of planting and application value in China and even the world. However, the current research on the suitable distribution area of is still inconclusive. In this study, we retrieved distribution data for in China from the Global Biodiversity Information Facility (GBIF), and identified six key environmental factors influencing its distribution through cluster analysis. Using these six selected climate factors and distribution points in China, we applied the maximum entropy model (MaxEnt) to evaluate 1160 candidate models for parameter optimization. The final results predict the potential distribution of under the current climate as well as two future climate scenarios (SSPs126 and SSPs585). This study shows that the model optimized with six key climate factors (AUC = 0.897, TSS = 0.658) outperforms the full model using nineteen climate factors (AUC = 0.894, TSS = 0.592). Under the high-emission scenario (SSPs585), the highly suitable habitat for is expected to gradually shrink towards the southeast and northwest, while expanding in the northeast and southwest. After the 2050s, highly suitable habitats are projected to completely disappear in Shandong, while new suitable areas may emerge in Tibet. Additionally, the total area of suitable habitat is projected to increase in the future, with a more significant expansion under the high-emission scenario (SSPs585) compared to the low-emission scenario (SSPs126) (7.33% vs. 0.16%). Seasonal changes in precipitation are identified as the most influential factor in driving the distribution of .
山杏（）是一种重要的果树品种，在中国乃至世界都具有广泛的种植和应用价值。然而，目前关于山杏适宜分布区的研究仍无定论。在本研究中，我们从全球生物多样性信息设施（GBIF）中检索了山杏在中国的分布数据，并通过聚类分析确定了影响其分布的六个关键环境因素。利用这六个选定的气候因素和山杏在中国的分布点，我们应用最大熵模型（MaxEnt）对1160个候选模型进行参数优化评估。最终结果预测了山杏在当前气候以及两种未来气候情景（SSPs126和SSPs585）下的潜在分布。本研究表明，用六个关键气候因素优化的模型（AUC = 0.897，TSS = 0.658）优于使用19个气候因素的完整模型（AUC = 0.894，TSS = 0.592）。在高排放情景（SSPs585）下，山杏的高度适宜栖息地预计将逐渐向东南和西北收缩，而在东北和西南地区扩张。2050年代之后，山东的高度适宜栖息地预计将完全消失，而西藏可能会出现新的适宜区域。此外，预计未来适宜栖息地的总面积将增加，高排放情景（SSPs585）下的扩张幅度比低排放情景（SSPs126）更大（7.33%对0.16%）。降水的季节性变化被确定为驱动山杏分布的最具影响力因素。
