Spatiotemporal Variability and Drivers of Cropland Non-Agricultural Conversion Across Mountainous County Types: Evidence from the Qian-Gui Karst Region, China

Qingping Lu, Siji Zhu, Zhaofu Xiao, Guifang Zhu, Jie Li, Jiahao Cui, Wen He and Jun Sun ()
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Qingping Lu: Faculty of Geography, Yunnan Normal University, Kunming 650500, China
Siji Zhu: Faculty of Geography, Yunnan Normal University, Kunming 650500, China
Zhaofu Xiao: School of Business and Tourism Management, Yunnan University, Kunming 650500, China
Guifang Zhu: School of History, Yunnan Normal University, Kunming 650500, China
Jie Li: Faculty of Geography, Yunnan Normal University, Kunming 650500, China
Jiahao Cui: Faculty of Geography, Yunnan Normal University, Kunming 650500, China
Wen He: Faculty of Geography, Yunnan Normal University, Kunming 650500, China
Jun Sun: Faculty of Geography, Yunnan Normal University, Kunming 650500, China

Agriculture, 2025, vol. 15, issue 7, 1-26

Abstract: The accelerating conversion of agricultural land to non-agricultural uses poses critical threats to food security and sustainable land management, particularly in ecologically fragile karst mountainous regions. This study investigated the spatiotemporal patterns and driving mechanisms of cropland non-agricultural conversion (CNAC) in the Qian-Gui karst region (Guangxi and Guizhou, China) from 2000 to 2020, employing land use datasets and socioeconomic indicators through geographically weighted regression (GWR) modeling. The results showed that (1) from 2000 to 2020, the CNAC rate in the Qian-Guizhou karst mountainous region reached 2.03%. The area of CNAC increased by 14.60 × 10 4 hm 2 , increasing 1.74 times in 2010–2020 compared to 2000–2010, showing a trend of rapid growth. Specifically, the growth rate of the CNAC area was the highest in apparent mountainous (110.36%) and quasi-mountainous counties (100.5%), followed by semi-mountainous counties (95.28%), while entirely mountainous (40.89%) and pure hilly counties (37.68%) experienced the lowest growth, revealing distinct regional disparities. (2) Spatially, CNAC exhibited a pattern of “high in the north and south, low in the central region”, and the overall level of CNAC displayed significant regional imbalances, with extreme grades distributed in provincial capitals, high and medium grades concentrated in prefecture-level city districts, and light and low grades mainly located in counties and districts (accounting for more than 55.56% of the total number of research units in the two time periods). (3) There was significant spatial heterogeneity in the driving effect of factors influencing CNAC. Agricultural output and population density showed the strongest positive correlations; effectively irrigated areas exhibited a growing influence over time (except for pure hilly counties); rocky desertification areas exerted a strengthened influence on CNAC in pure hilly counties, while their impact was relatively lower in other regions compared to other indicators. Therefore, when formulating policies to protect farmland, it is essential to take into account the specific conditions of different types of counties in mountainous areas and adopt management measures tailored to these regional characteristics.

Keywords: cropland; non-agriculturalization; GWR model; influencing factors; different type county; karst mountainous area (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2025
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