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

Assessing the Impacts of Mulching-Induced Warming Effects on Machine-Picked Cotton Zones

“…With the warming climate, the heat resources in Xinjiang have improved, resulting in an increasing cultivated area for the most suitable cotton zone (variety: mid-maturity cotton) and the suitable cotton zone (variety: mid-early-maturity cotton), while the area for the unsuitable cotton zone (variety: extra-early-maturity cotton) has decreased. Similar conclusions were drawn by Li et al [23], who also noted a decreasing trend for the less suitable cotton zone (variety: early-maturity cotton) and the unsuitable cotton zone. The observed increase in the cultivated area for the suitable cotton zone and the decrease in the area for the less suitable cotton zone and unsuitable cotton zone in this study are consistent with the changes in cotton zoning reported by Mai et al [15].…”

“…Recent studies have shown that because it is influenced by changes in heat resources, the area of suitable cotton regions in Xinjiang has gradually increased, while the areas of less suitable and unsuitable cotton regions have decreased. At the same time, the areas of mid-mature and early-mid-mature cotton regions in Southern Xinjiang have been continuously expanding, while the areas of early-ripening and unsuitable cotton regions have decreased [23][24][25]. However, in actual production, due to the complexity of cotton varieties, there are cases of unreasonable selection regarding the maturity of varieties and the blind expansion of planting areas in some regions, which have a significant impact on the quality and yield of cotton [21,22,26].…”

“…Mulching not only increases the soil temperature and moisture retention but also com-pensates for the temperature conditions required for cotton growth [27][28][29][30]. Both global climate warming and the use of mulching techniques in cotton cultivation can affect the heat conditions required for cotton plants' growth, which may influence the planting regions for cotton; however, most of the current research focuses on the suitability zoning of Xinjiang cotton under the background of global warming [23,24,31].…”

Potential Distribution of 11 Species of the Genus <em>Zephyranthes </em>Herb. (Amaryllidaceae) in Mexico

“…Potential distribution modeling is a tool that has been used in ecology and biogeography for several years, in different taxonomic groups (Abdelaal et al, 2019;Jiménez et al, 2023;Li et al, 2023;Martínez-Méndez et al, 2016;Murillo-Pérez et al, 2022;Yun et al, 2022). This tool has been of great importance in the development of scientific strategies in the conservation of species or habitats (Austin, 2002;Beaumont et al, 2005;Espejo-Serna & López-Ferrari, 2018;López-Sandoval et al, 2015;Martínez-Méndez et al, 2016;Palma-Ordaz & Delgadillo Rodríguez, 2014;Rodríguez & López-Toledo, 2016;Soberón, 2010;Solís-Montero et al, 2022;Suárez-Mota et al, 2022;Villaseñor, 2018;Ye et al, 2021).…”

The Supply of Macro- and Microelements to Cotton Plants at Different Distances from a Fertilizer Production Factory

“…There are numerous studies on cotton cultivation in terms of its environmental impact (the use of pesticides, water consumption, and soil degradation), agronomic approaches, the phenological and physiological aspects of cotton growth and development, cotton cultivation during climate change, sustainable cotton production and organic cotton, the effects of air pollution on cotton fabric, cotton breeding and genetics, cotton yield and quality, the utilization of cotton, the cotton market, etc. [26,29,[33][34][35][36][37]. However, no published studies were found on the effects of technogenic air pollution on the biochemical composition of cotton grown in the immediate vicinity of a nitrogen-phosphate fertilizer factory.…”