文献类型：期刊文献

英文题名：The Future Potential Distribution and Sustainable Management of Ancient Pu’er Tea Trees (Camellia sinensis var. assamica (J. W. Mast.) Kitam.)

作者：Zhang, Shuqiao[1,2] Cheng, Xinmeng[1] Wang, Zizhi[1] Cui, Kai[1] Liao, Shengxi[1]

第一作者：Zhang, Shuqiao

机构：[1] Institute of Highland Forest Science, Chinese Academy of Forestry, Kunming, 650216, China; [2] Fenner School of Environment & Society, College of Science, Australian National University, Canberra, 2601, Australia

年份：2022

卷号：13

期号：7

外文期刊名：Forests

收录：EI(收录号：20222712307158);Scopus(收录号：2-s2.0-85133126763)

语种：英文

外文关键词：Climate change - Climate models - Environmental management - Forestry - Value engineering

摘要：Ancient Pu’er tea trees (Camellia sinensis var. assamica (J. W. Mast.) Kitam.) are an important ecological resource with high economic value. Knowledge of the environmental variables shaping the original distribution and the effects of climate change on the future potential distribution of these trees, as well as the identification of sustainable management approaches, is essential for ensuring their future health and production. Here, we used 28 current environmental variables and the future climate data to model the suitable areas for ancient Pu’er tea trees. We also compared the health of these ancient trees in areas under different local management strategies. The results suggested the general distribution is likely to remain stable, but there are environmentally suitable areas outside its current habitats. To achieve more sustainable management, the main areas in which the management of poorly-managed trees can be improved include learning from managers of well-managed trees and following the common technical management regulations stipulated by the local government. The suitable value ranges for environmental factors, potentially suitable areas under climate change, and assessment of management approaches will aid the future cultivation and transplantation of ancient Pu’er tea trees. The methodology includes management-level analysis and provides practical insights that could be applied to regions outside the most suitable areas identified. ? 2022 by the authors. Licensee MDPI, Basel, Switzerland.