Spatial network correlation and driving factors of agricultural resilience in the Yangtze River Basin, China.

Agricultural resilience and stability are critical to achieving high quality agricultural development. We developed an agricultural resilience assessment framework with three dimensions: disturbance resistance, stability and innovation capacity. Then, we measured the agricultural resilience of 11 province-level regions in the Yangtze River Basin from 2011 to 2021, and applied social network to examine the spatial network characteristics of agricultural resilience, employed quadratic assignment procedure model to analyze key driving factors. The results showed that, from 2011 to 2021, the agricultural resilience of different provinces in the Yangtze River basin had some differences, but the overall average value showed an upward trend, increasing from 0.28 in 2011 to 0.38 in 2021. The overall network connection of agricultural resilience among the provinces in the Yangtze River Basin was not close. Results of individual network and block model analysis showed that Hubei Province played a crucial role in the overall network, with the spillover relation number of 4 and a beneficiary relation number of 10. Agricultural human capital, market scale, and ecological governance level had a significant positive impact on regional agricultural resilience, with the model explaining 94.2% of the variance. To effectively enhance agricultural resilience in the Yangtze River basin, it is essential to promote coordinated and shared agricultural development, strengthen agricultural education, continuously deepen agricultural system reform and supply-side structural reform, and adhere to ecological governance.

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Publication Details

Journal
PubMed
Published
2025-05-01
DOI
https://doi.org/10.13287/j.1001-9332.202505.025
Primary Topic
Land Use and Ecosystem Services
Type
article
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article

Spatial network correlation and driving factors of agricultural resilience in the Yangtze River Basin, China.

Hui-Yan Qin, Hongge Zhu, Ming Kong
PubMed
Land Use and Ecosystem Services
article

Spatial network correlation and driving factors of agricultural resilience in the Yangtze River Basin, China.

Hui-Yan Qin, Hongge Zhu, Ming Kong
article en

Abstract

Agricultural resilience and stability are critical to achieving high quality agricultural development. We developed an agricultural resilience assessment framework with three dimensions: disturbance resistance, stability and innovation capacity. Then, we measured the agricultural resilience of 11 province-level regions in the Yangtze River Basin from 2011 to 2021, and applied social network to examine the spatial network characteristics of agricultural resilience, employed quadratic assignment procedure model to analyze key driving factors. The results showed that, from 2011 to 2021, the agricultural resilience of different provinces in the Yangtze River basin had some differences, but the overall average value showed an upward trend, increasing from 0.28 in 2011 to 0.38 in 2021. The overall network connection of agricultural resilience among the provinces in the Yangtze River Basin was not close. Results of individual network and block model analysis showed that Hubei Province played a crucial role in the overall network, with the spillover relation number of 4 and a beneficiary relation number of 10. Agricultural human capital, market scale, and ecological governance level had a significant positive impact on regional agricultural resilience, with the model explaining 94.2% of the variance. To effectively enhance agricultural resilience in the Yangtze River basin, it is essential to promote coordinated and shared agricultural development, strengthen agricultural education, continuously deepen agricultural system reform and supply-side structural reform, and adhere to ecological governance.

PubMedVol. 36(5)
Northeast Forestry University (CN)
Openalex Percentile: Top 88%
Land Use and Ecosystem Services
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Spatial network correlation and driving factors of agricultural resilience in the Yangtze River Basin, China. — Hui-Yan Qin, Hongge Zhu, et al. · PubMed (2025) | TGRS Research Map | TGRS