Degree of Abandoned Cropland and Socioeconomic Impact Factors in China: Multi-Level Analysis Model Based on the Farmer and District/County Levels

Abstract

At present, abandoned cropland has become a common phenomenon spreading to countries around the world. China has seen widespread abandoned cropland in recent years. However, there are extremely few empirical studies of cropland abandonment and influencing factors nationwide. In this study, survey data from 8071 farmer households in 14 Chinese provinces were used to analyze the degree of cropland abandonment in China and its spatial distribution. A multi-level model was constructed to quantitatively explore the socioeconomic factors affecting the degree of cropland abandonment, at both the farmer and district/county levels. The results show that: (1) the proportion of farmers and the spatial distribution of abandoned cropland are consistent. (2) Chongqing City, Guangdong Province, and Shanxi Province are high-value areas of abandoned cropland, while Shandong, Liaoning, Henan and Jiangsu provinces are low-value areas. (3) Among the differences in cropland abandonment, 68.5% and 31.5% can be explained at the farmer and district/county level, respectively. (4) At the farmer level, all labor and cropland transfer indicators, including land labor quantity per unit area, male agricultural labor ratio, farmers mainly of middle-aged labor, cropland transfer area and cropland subcontract amount, have significant negative effects on the degree of abandoned cropland. There is a significant negative correlation between the value of agricultural operating fixed assets in the agricultural input indicators and the degree of abandoned cropland, but participation in professional, cooperative, economic, agricultural organizations has no significant impact on the degree of abandoned cropland. The per capita disposable income, which represents the quality of life indicator, has a significant positive impact on the degree of abandoned cropland. (5) At the district/county level, the proportion of the total co-working labor force and the transfer rate of cropland are negatively related to the degree of cropland abandonment, and the proportion of the co-working labor force outside the district/county is positively related to the degree of cropland abandonment. In addition, we briefly analyzed the mechanism and process of cropland abandonment from the perspective of farmers’ decision-making. Finally, the policy suggestions to alleviate the abandonment of cropland were put forward from the district/county and farmer level, respectively.

Mapping Cropland Abandonment in the Cloudy Hilly Regions Surrounding the Southwest Basin of China

“…In contrast, this study incorporates dynamic distance-based social data into the analysis, explaining the differences in cropland abandonment across different stages using evolving social data. An important future direction for this research involves continuously optimizing and refining the established indicator system of driving factors while exploring the underlying mechanisms from a multi-stakeholder perspective [65,66]. This approach will facilitate more meticulous and precise analysis at the micro-level, further validating the findings of this study and providing firmer theoretical support and practical guidance for the development of related fields.…”

Do agricultural productive services alleviate farmland abandonment? Evidence from China rural household panel survey data

“…Existing research used the proportion of abandoned farmland in the total farmland to measure land abandonment (Deng et al, 2020;Jiang and Song, 2022). Land abandonment, including the land abandonment behaviour and land abandonment area, is the dependent variable concerned in this study.…”

“…Farmers' personal characteristics include age, gender, education level, marital status, health status, and the experience of migrant workers. Existing studies have shown the probability of abandoned land increases when farmers' age increases (Jiang and Song, 2022).…”

Assessing and mapping cropland abandonment risk in China

“…In the past few decades, CA has spread throughout China (Zhang et al, 2019). This issue has also attracted considerable academic and public attention, and some research has been conducted on identifying the CA state in China (Jiang & Song, 2021; Li et al, 2022), as well as revealing its determinants and consequences (Subedi et al, 2022b; Yan et al, 2016; Zhang et al, 2014), but few studies have explored and mapped CAR in China.…”