2000—2020年中国县域粮食单产的时空格局及其影响因素

SPATIAL-TEMPORAL PATTERNS AND INFLUENCING FACTORS OF GRAIN YIELD IN CHINESE COUNTIES FROM 2000 TO 2020

关键词:  粮食单产  时空格局  影响因素  中国县域  粮食安全

Key words:  grain yield  spatio-temporal pattern  influencing factors  Chinese counties  grain security

摘要:

目的 粮食产量受到耕地面积和粮食单产的影响。在当前耕地面积难以增加的背景下，揭示粮食单产变化的时空格局，探索单产变化的关键影响因素，对保障粮食安全具有重要的现实意义。方法 文章以中国2 060个县域为研究单元，基于2000—2020年粮食单产数据，借助Daniel趋势分析、标准差椭圆和重心迁移模型、空间自相关分析、地理探测器等方法，对中国县域粮食单产的时空格局和典型地区影响单产的因素进行了分析。结果 （1）粮食单产呈现出“胡焕庸线沿线向两侧递增”的特点，单产沿胡焕庸线向东南和西北递增。（2）粮食单产经历了“快速增长—缓慢增长”的过程，变化“北方增长快于南方”，内蒙古高原、黄土高原、华北平原北部和新疆的单产增长快。（3）粮食单产重心向西北移动，空间形态呈现“东—西”分布格局，方向性不明显，不同地域间单产差异小。在空间上形成了以东北平原、华北平原、洞庭湖平原、鄱阳湖平原、河西走廊和新疆西北部的高值区，以内蒙古高原中部和青藏高原为中心的低值区，但这种空间集聚性有所减弱。（4）降水和坡度对单产的影响大，化肥施用量和劳动力数量对单产的影响正在逐渐减弱。社会经济因素对单产减少的影响大，人为投入因素对单产增加的影响大。结论 根据不同区域粮食单产的影响因素，政府应制定区域化的粮食生产政策，因地制宜地提高粮食单产。

Abstract:

Grain yield is influenced by both the extent of cultivated land and grain yield per unit area. Under the premise that the cultivated land area is difficult to increase, it is crucial to study the temporal and spatial changes in grain yield and the influencing factors to ensure food security. Data on grain yield from 2000 to 2020 for 2 060 counties in China were selected. The Daniel trend analysis, standard deviation ellipse, gravity center model, spatial autocorrelation analysis, and geodetector were used to analyze the spatio-temporal patterns of grain yield and the influencing factors at the county level in China in this study. The results showed that: (1) China's grain yield was low along the Hu Huangyong Line, increasing gradually towards the southeast and northwest. (2) Overall, the grain yield increased, although the rate of increase slowed down from 2000 to 2020.The northern region of China experienced faster growth than the southern region, particularly in the Inner Mongolia Plateau, Loess Plateau, northern North China Plain, and Xinjiang. (3) The center of grain yield shifted northwest, creating an "east-west" spatial distribution pattern characterized by unclear directionality and minimal differences in yield among various regions. High-value areas were concentrated in the Northeast Plain, North China Plain, Dongting Lake Plain, Poyang Lake Plain, Hexi Corridor, and Northwest Xinjiang; while low-value areas were centered in the middle of Inner Mongolia Plateau and Xizang Plateau. However, this spatial agglomeration trend had slightly weakened. (4) Precipitation and slope were significant factors affecting grain yield, whereas the impacts of fertilizer application and labor quantity on grain yield had gradually diminished. Socio-economic factors tended to reduce grain yield, while artificial inputs contributed significantly to its increase. Based on the identified spatio-temporal patterns of grain yield and their influencing factors, the government should develop grain production policies according to local conditions to improve grain yield.