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Predicting the future redistribution of Chinese white pine Pinus armandii Franch. Under climate change scenarios in China using species distribution models
Global Ecology and Conservation ( IF 4 ) Pub Date : 2020-12-30 , DOI: 10.1016/j.gecco.2020.e01420
Hang Ning , Lei Ling , Xiangcheng Sun , Xiaotong Kang , Hui Chen

Pinus armandii, or Chinese white pine, is one of the pine species native to China and plays an important role in ecological conservation and regional socioeconomic development. However, few studies have focused on the distribution of its habitat and important environmental factors related to suitability. Therefore, we used a MaxEnt model to represent the current species distribution of P. armandii in China and predicted its future redistribution. The results show that precipitation and temperature are the two major limiting factors that constrain the current distribution of P. armandii. The average temperatures of 24 °C and −14 °C in July and January, respectively, are considered the limits that define the tree-line of P. armandii. Currently, P. armandii is mainly distributed in the Tsinling Mountains, Daba Mountains and terrains in the Yunnan-Kweichow Plateau. Under climate change scenarios, the distribution range of P. armandii is projected to decrease. The response of P. armandii to RCP 8.5 scenario is the most drastic, followed by the RCP 4.5 scenario. The most alarming change is that the suitable habitat in the Wushan Mountains, which connects the Daba Mountains and Yunnan-Kweichow Plateau, is expected to gradually disappear, leading to interruption of the current ecological corridor. The suitable habitat in the Hengduan Mountains is projected to gradually be lost. In the northern part of China, there is no suitable niche for P. armandii. However, the excellent habitat range for P. armandii in both the Tsinling Mountains and Daba Mountains is predicted to enlarge. Our study results can provide timely information for the monitoring of the health of tree populations and the impact of climate change, shedding light on the effectiveness of management responses.

更新日期:2020-12-30
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