Predicting Ecologically Suitable Areas of Cotton Cultivation Using the MaxEnt Model in Xinjiang, China

Author:

Li Lingling12,Wu Hongqi1,Gao Yimin2,Zhang Sance2

Affiliation:

1. College of Resources and Environment, Xinjiang Agricultural University, Urumqi 830052, China

2. College of Natural Resources and Environment, Northwest A&F University, Xianyang 712100, China

Abstract

Cultivating cotton and sustaining its productivity are challenging in temperate arid regions around the globe. Exploring suitable cotton cultivation areas to improve productivity in such climatic regions is essential. Thus, this study explores the ecologically suitable areas for cotton cultivation using the MaxEnt model, having 375 distribution points of long-staple cotton and various factors, including 19 climatic factors, 2 terrain factors, and 6 soil factors in Xinjiang. The area under the curve (AUC) of the predicted results was greater than 0.9, indicating that the model’s predictions had fairly high accuracy. However, the main environmental factors that affected the cotton’s growth were the lowest temperature in the coldest month, the hottest month, the precipitation in the driest season, and the monthly average temperature difference. Further, the temperature factors contributed 71%, while the contribution ratio of terrain and soil factors was only 22%. The research indicated that the current planting area was consistent with the predicted area in many areas of the study. Still, some areas, such as the Turpan region northwest of Bayingolin Mongol Autonomous Prefecture, are supposed to be suitable for planting cotton, but it is not planted. The current potential distribution area of long-staple cotton is mainly located in Aksu Prefecture and the northern part of the Kashgar Prefecture region. The climatic prediction shows that the growing area of long-staple cotton may expand to southern Altay, central Aksu, and Bortala Mongol Autonomous Prefecture. This study will be helpful for cotton cultivation suitability areas in Xinjiang and other regions with similar environments.

Funder

technical innovation guidance special fund of Shaanxi province

Publisher

MDPI AG

Subject

General Medicine

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