Author(s)

Bin Guo^1,2, San Wang^1,2, Chao Chen^1,3*, Mingtian Wang^1,3,4, Tingting Li⁵

¹Chengdu/Heavy Rain and Drought-Flood Disasters in Plateau and Basin Key Laboratory of Sichuan Province, Institute of Plateau Meteorology, China Meteorological Administration, Chengdu, China.
²Aba Prefecture Meteorological Administration, Maerkang, China.
³Provincial Key Laboratory of Water-Saving Agriculture in Hill Areas of Southern China, Chengdu, China.
⁴Sichuan Meteorlogical Observatory, Chengdu, China.
⁵State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Science, Beijing, China.

In order to determine the threshold and potential distribution of climatic conditions for perennial cultivated grasses in the Northwest plateau of Sichuan, China, the niche model is used to simulate the main climatic factors affecting the distribution of perennial cultivated grasses, and to predict the current and future climate change prospects. The results show that: 1) Wet index, accumulated temperature, isothermal, and annual average temperature range are the four major climatic factors affecting the distribution of perennial cultivated grasses in the Northwest Sichuan Plateau. 2) Model training and prediction data can be achieved well under the appropriate range of major climatic factors. 3) Under the background of climate warming, from now to 2080, the potential distribution of perennial cultivated grasses in the Northwest plateau of Sichuan, China will increase. The study aims to provide scientific decision-making basis for maintaining grassland ecosystem stability and promoting desertification management and even industrial restructuring of agriculture and animal husbandry.

Clmatei Change, MaxEnt Model, Dominant Factor, Perennial Cultivated Grasses, Northwest Sichuan Plateau

Guo, B. , Wang, S. , Chen, C. , Wang, M. and Li, T. (2019) Prediction of the Distribution of Perennial Cultivated Grasses in the Northwest Sichuan Plateau, China under Climate Change. Journal of Geoscience and Environment Protection, 7, 95-111. doi: 10.4236/gep.2019.710008.