Work

Low-Carbon Cropland Use Performance in China: Network Evolution, Structural Positions, and Governance Implications

Year: 2026

Type: article

Abstract: Improving cropland carbon performance while maintaining food security is central to China’s agricultural transition and climate goals This study examines low-carbon cropland use performance (PCLU) and its model-implied interprovincial association network across 31 Chinese provinces from 2010 to 2023. A global super-efficiency slacks-based measure model estimated PCLU by incorporating agricultural output, carbon emissions, nonpoint-source pollution, and crop sequestration; annual directed networks were constructed with a modified gravity model and analyzed using social network analysis, a temporal exponential random graph model (TERGM), and complementary quadratic-assignment analyses. Mean PCLU increased from 0.524 to 0.861, while the interquartile range widened from 0.146 to 0.310; network density declined before partially recovering as hierarchy increased, indicating improvement without provincial convergence and reconnection within a more differentiated multi-hub structure. Persistence (β = 4.510) and reciprocity (β = 2.376) dominated network evolution, whereas shared partners produced neither additional triadic closure nor expanding open chains; similarities in urbanization and planting structure favored ties, while rural-income differences reflected socioeconomic complementarity. External validation showed moderate overall correspondence with green-technology patent collaboration (mean annual QAP r = 0.335) but limited overlap among the strongest dyads. Overall, China’s low-carbon cropland transition combined rising but increasingly uneven performance with a path-dependent and selective interprovincial structure, providing an empirical basis for differentiated coordination based on provincial performance and network position.

Source: Land

DOI: 10.3390/land15081491

Authors: Qi Xia, Yi Chen, Yi Chen, Yinrong Chen, Yinrong Chen

Institution: Huazhong Agricultural University

Language: English

Topic: Efficiency Analysis Using DEA

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

SDGs: Climate action, Zero hunger, Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $3,137