Farmland abandonment in Pakistan: patterns, influencing factors and cascading effects on food production
文献类型：期刊论文
| 作者 | Liu, Yunxi1,2; Zhang, Fuyao1; Wang, Xue1; Tan, Minghong1,2; Li, Xiubin1,2 |
| 刊名 | JOURNAL OF CLEANER PRODUCTION
 |
| 出版日期 | 2025-12-10 |
| 卷号 | 535页码:147127 |
| 关键词 | Pakistan Farmland abandonment Driving mechanisms Climate change SDGs |
| ISSN号 | 0959-6526 |
| DOI | 10.1016/j.jclepro.2025.147127 |
| 产权排序 | 1 |
| 文献子类 | Article |
| 英文摘要 | Farmland abandonment has emerged as a critical challenge to food security in Global South countries (GSCs). However, the spatiotemporal dynamics, driving mechanisms, and future trajectories of farmland abandonment in these regions remain insufficiently understood. Taking Pakistan as a case study, this research reconstructs a national farmland abandonment dataset from 2002 to 2020 using high-resolution land use data, thereby revealing its spatiotemporal evolution patterns. Based on this, we integrate multi-source datasets and employ a Gradient Boosting Regression Tree (GBRT) model coupled with SHapley Additive exPlanations (SHAP) analysis to quantitatively assess key drivers, predict future trends, and estimate potential grain production losses associated with farmland abandonment. The results indicate that: (1) Between 2002 and 2020, the total abandoned farmland area in Pakistan reached 28,414.37 km2 (11.17 %), with the largest extent observed in SIND (10,214.69 km2) and the highest abandonment rate in BALU (44.08 %). A significant negative correlation is observed between farmland resource endowment and abandonment intensity. (2) Farmland abandonment in Pakistan is driven by climate change, farmland endowment, cropping conditions, and socioeconomic factors, exhibiting pronounced spatial heterogeneity. Specifically, ethnic minority regions (KASH, GILG) are significantly affected by climate change; political and cultural centers (ISLA) face challenges related to labor shortages; and major agricultural production areas (KHYB, BALU, PUNJ, SIND) are constrained by low levels of farmland consolidation. (3) Under different SSP-RCP scenarios, SIND and PUNJ are projected to experience heightened risks of farmland abandonment. By 2050, the national abandonment rate is expected to reach 16.46 %-19.91 %, potentially resulting in grain production losses ranging from 12.04 to 14.56 million tonnes. (4) To address these challenges, we recommend coordinated actions focused on improving institutional frameworks, implementing differentiated governance strategies, and strengthening international cooperation. These measures are vital not only for promoting farmland conservation and achieving sustainable agricultural development in Pakistan and other Global South countries (GSCs), but also for supporting the implementation of the United Nations Sustainable Development Goals (SDGs). |
| URL标识 | 查看原文 |
| WOS关键词 | LAND ABANDONMENT ; CLIMATE-CHANGE ; AGRICULTURE |
| WOS研究方向 | Science & Technology - Other Topics ; Engineering ; Environmental Sciences & Ecology |
| 语种 | 英语 |
| WOS记录号 | WOS:001623260100001 |
| 出版者 | ELSEVIER SCI LTD |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/217716]  |
| 专题 | 陆地表层格局与模拟院重点实验室_外文论文 |
| 通讯作者 | Wang, Xue |
| 作者单位 | 1.Chinese Acad Sci, Key Lab Land Surface Pattern & Simulat, Inst Geog Sci & Nat Resources Res, 11A Datun Rd, Beijing 100101, Peoples R China; 2.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China |
| 推荐引用方式 GB/T 7714 | Liu, Yunxi,Zhang, Fuyao,Wang, Xue,et al. Farmland abandonment in Pakistan: patterns, influencing factors and cascading effects on food production[J]. JOURNAL OF CLEANER PRODUCTION,2025,535:147127. |
| APA | Liu, Yunxi,Zhang, Fuyao,Wang, Xue,Tan, Minghong,&Li, Xiubin.(2025).Farmland abandonment in Pakistan: patterns, influencing factors and cascading effects on food production.JOURNAL OF CLEANER PRODUCTION,535,147127. |
| MLA | Liu, Yunxi,et al."Farmland abandonment in Pakistan: patterns, influencing factors and cascading effects on food production".JOURNAL OF CLEANER PRODUCTION 535(2025):147127. |
入库方式： OAI收割
来源：地理科学与资源研究所
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