Sustainable Land Production Methods: The Spatiotemporal Evolution, Determinants, and Future Implications of Grain Crop Production Agglomeration in China Under Resource Constraints

ABSTRACT Amid the backdrop of increasing global extreme weather events and tightening resource constraints on grain crop production. China, as the world's most populous country, faces persistent challenges to grain security. On one hand, grain crop production agglomeration (GCPA) can effectively address grain security challenges by optimizing the spatial layout of agricultural production. On the other hand, it can enhance the efficiency of resource utilization in grain production, thereby ensuring the stability and sustainability of the national grain supply. The study uses 1980 as the baseline and employs a range of analytical methods, including the spatial Gini coefficient, industrial concentration, global Moran's I, and LISA agglomeration map, to investigate the temporal–spatial variation trends and characteristics of GCPA in China from 2000 to 2020. Subsequently, a spatial Durbin model with time and space fixed effects is applied to identify the key factors influencing changes in the level of GCPA. The findings are further contextualized to explore opportunities for leveraging GCPA to promote sustainable land resource development. The results reveal that, from temporal variation trends in GCPA, the overall level of GCPA in China has exhibited a steady upward trend. From temporal variation characteristics in GCPA, the provinces contributing to GCPA have gradually concentrated in Heilongjiang, Henan, Shandong, and Anhui, demonstrating significant provincial convergence. From spatial variation trends in GCPA, while the global Moran's I of GCPA experienced brief declines in 2009 and 2018, it has generally shown a steadily increasing trend, reflecting strong spatial dependence. From spatial variation characteristics in GCPA, the spatial distribution of GCPA exhibits polarization, with provinces transitioning between high‐high (H‐H) and low‐low (L‐L) agglomeration clusters. This indicates that regions with lower grain production capacity are likely to experience further declines, regardless of their proximity to high‐production regions. The analysis identifies agricultural transportation infrastructure as the most critical factor promoting GCPA. Conversely, excessive use of chemical fertilizers and labor inputs in grain crop production are found to hinder GCPA. Based on these findings, the study recommends enhancing agricultural transportation infrastructure and improving the efficiency of traditional agricultural inputs to elevate GCPA levels, thereby fostering sustainable land resource development.

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Publication Details

Journal
Land Degradation and Development
Published
2025-11-30
DOI
https://doi.org/10.1002/ldr.70268
Primary Topic
Land Use and Ecosystem Services
Type
article
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article

Sustainable Land Production Methods: The Spatiotemporal Evolution, Determinants, and Future Implications of Grain Crop Production Agglomeration in China Under Resource Constraints

Irum Shahzadi, Zhaocai Cui, Mingxing Zheng, Feng Wu et al.
Land Degradation and Development
Land Use and Ecosystem Services
article

Sustainable Land Production Methods: The Spatiotemporal Evolution, Determinants, and Future Implications of Grain Crop Production Agglomeration in China Under Resource Constraints

Irum Shahzadi, Zhaocai Cui, Mingxing Zheng, Feng Wu, Cheng Li
article en

Abstract

ABSTRACT Amid the backdrop of increasing global extreme weather events and tightening resource constraints on grain crop production. China, as the world's most populous country, faces persistent challenges to grain security. On one hand, grain crop production agglomeration (GCPA) can effectively address grain security challenges by optimizing the spatial layout of agricultural production. On the other hand, it can enhance the efficiency of resource utilization in grain production, thereby ensuring the stability and sustainability of the national grain supply. The study uses 1980 as the baseline and employs a range of analytical methods, including the spatial Gini coefficient, industrial concentration, global Moran's I, and LISA agglomeration map, to investigate the temporal–spatial variation trends and characteristics of GCPA in China from 2000 to 2020. Subsequently, a spatial Durbin model with time and space fixed effects is applied to identify the key factors influencing changes in the level of GCPA. The findings are further contextualized to explore opportunities for leveraging GCPA to promote sustainable land resource development. The results reveal that, from temporal variation trends in GCPA, the overall level of GCPA in China has exhibited a steady upward trend. From temporal variation characteristics in GCPA, the provinces contributing to GCPA have gradually concentrated in Heilongjiang, Henan, Shandong, and Anhui, demonstrating significant provincial convergence. From spatial variation trends in GCPA, while the global Moran's I of GCPA experienced brief declines in 2009 and 2018, it has generally shown a steadily increasing trend, reflecting strong spatial dependence. From spatial variation characteristics in GCPA, the spatial distribution of GCPA exhibits polarization, with provinces transitioning between high‐high (H‐H) and low‐low (L‐L) agglomeration clusters. This indicates that regions with lower grain production capacity are likely to experience further declines, regardless of their proximity to high‐production regions. The analysis identifies agricultural transportation infrastructure as the most critical factor promoting GCPA. Conversely, excessive use of chemical fertilizers and labor inputs in grain crop production are found to hinder GCPA. Based on these findings, the study recommends enhancing agricultural transportation infrastructure and improving the efficiency of traditional agricultural inputs to elevate GCPA levels, thereby fostering sustainable land resource development.

Land Degradation and Development
Kunming University of Science and Technology (CN), European University of Lefke (TR), Hainan Normal University (CN), Yunnan University (CN), Dalian University of Technology (CN), Haikou City People's Hospital (CN), People's Government of Yunnan Province (CN), Yunnan University of Finance And Economics (CN), Széchenyi István University (HU)
Openalex Percentile: Top 65%
Land Use and Ecosystem Services
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