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Suitability regionalization of Chinese medicinal yam under the impact of climate change simulated by CMIP5 multi-model ensemble projections
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Paper Abstract

Chinese yam (Dioscorea opposita Thunb.) is consumed and regarded as medicinal food in traditional Chinese herbal medicine, Chinese medicinal yam especially is one of the most important Chinese herbal medicines and its medicinal needs have been increasing in recent decades1. Furthermore, Chinese medicinal yam is susceptible to climate conditions during the growth period. Therefore, a better understanding of the suitability regionalization of Chinese medicinal yam under the impact of climate change is of both scientific and practical importance to spacial development and reasonable layout of Chinese yam in China. In this study, based on the Coupled Model Inter-comparison Project, Phase 5 (CMIP5) climate model projections with 5 Global Circulation Models (GCMs) developed by the Inter-Sectoral Impact Model Inter-comparison Project (ISIMIP) driven by 4 Representative Concentration Pathways (RCPs), we assessed the changes of potential planting area of Chinese medicinal yam between the baseline climatology of 1981-2010 and the future climatology of the 2050s (2041-2070) under the RCP 4.5 scenario by the Geographic Information System (GIS) technology. Results indicate that regions with high ecological similarity to the Geo-authentic producing areas of Chinese medicinal yam include northeastern Henan, southeastern Hebei and western Shandong, mainly distribute in the lower reaches of the Yellow River basin and other major floodplains. In the future, the climate suitability of Chinese medicinal yam in these areas will be weakened, but that will still be the main suitable planting regions.

Paper Details

Date Published: 18 September 2018
PDF: 6 pages
Proc. SPIE 10767, Remote Sensing and Modeling of Ecosystems for Sustainability XV, 1076718 (18 September 2018); doi: 10.1117/12.2320710
Show Author Affiliations
Biao Hu, Shanghai Institute of Technology (China)
Zhan Tian, Shanghai Institute of Technology (China)
Shanghai Climate Ctr. (China)
Dongli Fan, Shanghai Institute of Technology (China)
Hanqing Xu, East China Normal Univ. (China)
Yinghao Ji, Univ. Ca' Foscari di Venezia (Italy)
Xiangyi Wang, Shanghai Institute of Technology (China)
Runhe Shi, East China Normal Univ. (China)
Maosi Chen, Colorado State Univ. (United States)


Published in SPIE Proceedings Vol. 10767:
Remote Sensing and Modeling of Ecosystems for Sustainability XV
Wei Gao; Ni-Bin Chang; Jinnian Wang, Editor(s)

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