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生态学杂志 ›› 2025, Vol. 44 ›› Issue (11): 3841-3851.doi: 10.13292/j.1000-4890.202511.009

• 技术与方法 • 上一篇    下一篇

基于PSR模型的东北三省耕地利用生态效率评价

王笑笑1,赵华甫1,2*,钱家乘1,冯喆1,2,李潇3,刘洪秀1,李嘉劲1   

  1. 1中国地质大学(北京)土地科学技术学院, 北京 100083; 2自然资源部土地整治重点实验室, 北京 100035; 3郑州轻工业大学政法学院, 郑州 450001)

  • 出版日期:2025-11-10 发布日期:2025-11-14

Evaluation of cultivated land use eco-efficiency in the three provinces in Northeast China based on Pressure-State-Response model.

WANG Xiaoxiao1, ZHAO Huafu1,2*, QIAN Jiacheng1, FENG Zhe1,2, LI Xiao3, LIU Hongxiu1, LI Jiajin1   

  1. (1School of Land Science & Technology, China University of Geosciences, Beijing 100083, China;  2Key Laboratory of Land Consolidation & Rehabilitation, Ministry of Natural Resources, Beijing 100035, China; 3School of Political Science and Law, Zhengzhou University of Light Industry, Zhengzhou 450001, China).

  • Online:2025-11-10 Published:2025-11-14

摘要: 东北地区作为我国重要的粮食主产区,探究其耕地利用生态效率时空演变特征与提升路径,对于实现区域耕地生态保护和粮食供需平衡、耕地可持续利用具有重要的理论和现实意义。基于PSR(PressureStateResponse)模型构建耕地利用生态效率分析框架,利用超效率松弛变量测度模型(Super-SBM)估算2000—2020年东北三省耕地利用生态效率时空变化;并运用随机森林模型与分段线性回归模型分析耕地利用生态效率的主要影响因素;最后,提出未来耕地利用生态效率改进的方向和政策建议。结果表明:东北三省耕地利用生态效率从2000年的0.462提高到2020年的0.636,总体呈上升趋势,但仍以低效率为主;耕地利用生态效率空间分异明显,呈现“东高西地,北高南低”的特征;人口密度、城镇化水平、灌溉指数、气温和降水量是影响耕地利用生态效率的主要压力因素,且存在阈值效应。建议政府要针对效率水平高低制定差异化发展战略,调控与适应主要压力因子,助推耕地利用生态效率提高。


关键词: 耕地利用生态效率, 压力-状态-响应模型, Super-SBM模型, 影响因素, 东北三省

Abstract: Exploring the spatiotemporal variation and improvement pathways of cultivated land use eco-efficiency (CLUE) in Northeast China, a key grain-producing area in China, is of great theoretical and practical significance for achieving regional cultivated land ecological protection, balancing food supply and demand, and promoting sustainable cultivated land use. In this study, we developed an analytical framework for CLUE based on the Pressure-State-Response (PSR) model and applied the Super-Efficiency Slack-Based Measure (Super-SBM) model to estimate the spatiotemporal variations in CLUE across the three provinces in Northeast China from 2000 to 2020. Key factors influencing CLUE were identified using the Random Forest model and piecewise linear regression analysis. Future directions and policy recommendations were proposed to enhance CLUE. We found that CLUE in the three provinces increased from 0.462 in 2000 to 0.636 in 2020, indicating an overall upward trend but with low efficiency. There were significant spatial differentiations of CLUE, presenting the characteristics of “high in the east and low in the west, high in the north and low in the south”. Population density, urbanization level, irrigation index, temperature, and precipitation were identified as the primary pressure factors influencing CLUE, with noticeable threshold effects. It is recommended that policymakers develop differentiated development strategies according to the levels of efficiency, and regulate and adapt to the key pressure factors to enhance CLUE.


Key words: cultivated land use eco-efficiency, Pressure-State-Response model, Super-SBM model, influencing factor, the three provinces in Northeast China