Agriculture (Nov 2021)

Predicting Possible Distribution of Tea (<i>Camellia sinensis</i> L.) under Climate Change Scenarios Using MaxEnt Model in China

  • Yuncheng Zhao,
  • Mingyue Zhao,
  • Lei Zhang,
  • Chunyi Wang,
  • Yinlong Xu

DOI
https://doi.org/10.3390/agriculture11111122
Journal volume & issue
Vol. 11, no. 11
p. 1122

Abstract

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Climate change has dramatic impacts on the growth and the geographical distribution of tea (Camellia sinensis L.). Assessing the potential distribution of tea will help decision makers to formulate appropriate adaptation measures to use the altered climatic resources and avoid the damage from climate hazards. The objective in this study is to model the current and future distribution of tea species based on the four SSPs scenarios using the MaxEnt model in China. For the modeling procedure, tea growth records in 410 sites and 9 climate variables were used in this paper. The area under the receiver operating characteristic (ROC) curve (AUC) was used to evaluate the performance of the model. The AUC value was over 0.9 in this study, showing the excellent simulation result of the model. In relation to the current distribution, areas of 82.01 × 104 km2 (8.51% of total land area in China), 115.97 × 104 km2 (12.03% of total land area in China), and 67.14 × 104 km2 (6.97% of total land area in China) were recognized as Marginal, Medium, and Optimal climate suitable habitats for tea over China. Compared to the current distribution, most of the Optimal suitability areas in southeast China would be lost in four scenarios. The area of Marginal and Medium suitable habitats would expand in SSP370 and SSP585, especially in 2041–2061 and 2081–2100. The suitable area of tea would expand northwards and westwards, suggesting that additional new suitable habitats could be created for tea production with the future climate change, especially in Shandong, Henan, Guizhou, and Yunnan Provinces. This research would provide vital scientific understanding for policy making on tea production, tea garden site chosen and adopyion of adaptation methods in the future.

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