水稻是主要的粮食作物之一,水稻适宜种植面积的研究对提高水稻产量和优化生产布局具有重要作用。本研究采用最大熵(MaxEnt)模型,结合气候,对1981-2020年我国水稻适宜种植面积的分布进行了模拟和预测,土壤,和人类活动,分析了我国水稻适宜种植面积的时空变化,确定了影响水稻种植适宜性的主要因素。结果表明,影响我国水稻适宜种植面积分布的主要因素是国内生产总值(GDP),人口密度(Pop),和年日照时间(太阳),人类活动起主导作用。水稻适宜种植面积主要分布在湖北,湖南,江西,安徽,广东,四川东南部和贵州西部。1981~1990年、1991~2000年、2001~2010年和2011~2020年水稻适宜种植面积分别为346.00×104km2、345.66×104km2、347.01×104km2和355.57×104km2。随着时间的流逝,水稻不适宜种植面积逐渐减少,中等适宜面积增加,高适宜区和低适宜区的面积变化较大。此外,由于近年来大量农村劳动力向城市转移,人口爆炸造成的人地关系紧张,导致Pop对水稻适宜区的影响越来越大,GDP对水稻生产干预的影响相对减弱。研究结果可为水稻种植管理和粮食安全生产提供科学依据,在全球气候变化的背景下,减少气候变化对农业生产的影响。
Rice is one of the major food crops, and the study of suitable planting areas for rice plays an important role in improving rice yield and optimizing the production layout. This study used Maximum Entropy (MaxEnt) model to simulate and predict the distribution of suitable rice planting areas in China from 1981 to 2020 by combining the climate, soil, and human activities, analyzed the spatial and temporal changes of suitable rice planting areas in China, and determined the main factors affecting rice planting suitability. The results indicated that the main factors influencing the distribution of suitable planting areas for rice in China were gross domestic product (GDP), population density (Pop), and annual sunshine duration (Sun), with human activities playing a dominant role. The high suitable planting areas of rice were mainly distributed in Hubei, Hunan, Jiangxi, Anhui, Guangdong, southeastern Sichuan and western Guizhou. The total suitable planting areas for rice were 346.00 × 104 km2, 345.66 × 104 km2, 347.01 × 104 km2, and 355.57 × 104 km2 from 1981 to 1990, 1991 to 2000, 2001 to 2010 and 2011 to 2020, respectively. With the passage of time, the area of unsuitable areas for rice gradually decreased, and the area of medium suitable areas increased, with large changes in the area of high- and low-suitable areas. Moreover, due to the transfer of a large number of rural laborers to the cities in recent years, the tension between people and land caused by the population explosion has led to the increasing impact of Pop on rice suitable areas and the relatively weakening of the impact of GDP on rice production interventions. The results can be used to provide scientific evidence for the management of rice cultivation and food production safety, with a view to reducing the impacts of climate change on agricultural production in the context of global climate change.