Formation mechanism and sustainable productivity impacts of non‐grain croplands: Evidence from Sichuan Province, China

Abstract

Non‐grain cropland is a typical phenomenon with some common characteristics globally. As the most populous country, China's non‐grain cropland threatens global food supply stability and affects food production sustainability under the current complex situation of international food security. This paper used Sichuan Province, China, to explore the formation mechanism of non‐grain cropland and its potential impact on sustainable productivity, given the regional environment complexity and socioeconomic representativeness. High‐precision land survey data were used to detect multiscale non‐grain influencing factors and discuss non‐grain impacts on soil state to fill the knowledge gap on microlevel development of non‐grain issues. Results show that rotation type is the region's most abundant and widely distributed cropland type, accounting for about 59.38% of the total cropland area; the second is abandonment type. Urbanization indicators are the common factors affecting the non‐grain spatial distribution on the global scale; environmental variables' impact on non‐grain shows significant differences in geographical locations on the local scale. Overall, cash type and intercrop type aim at improving production conditions. Rotation type and fallow type mostly occur in areas with low production capacity and are prominently driven by policies. Abandonment type is subject to terrain constraints, production conditions, and social economy. Additionally, non‐grain trends have not caused significant damage to soil sustainable productivity except for the positive promotion of field biodiversity. Non‐grain cropland can be divided into three clusters according to the corresponding average soil fertility state, rotation, intercrop, cash, abandonment, and fallow. Policymakers must implement specific policies for different cropland types and formulate more refined farming management plans.

A non‐grain production on cropland spatiotemporal change detection method based on Landsat time‐series data

“…According to the “2023 World Food Security and Nutrition Report,” between 691 and 783 million people worldwide experienced hunger in 2022, with over 90 million people being affected by long‐term hunger (FAO et al, 2023). Conflicts, extreme weather events, diseases, and economic shocks are exacerbating the main driving factors of food insecurity, and stable food production is crucial for global food security and sustainable development (Liang et al, 2023). There are two types of production methods on arable land: grain production and non‐grain production (NGP) (Su et al, 2020; Wang & Dai, 2022).…”

“…These methods have gaps in temporal coverage, and cannot fully capture the spatial characteristics of NGP. The method that directly extracts NGP information from China's 2020 Land Survey Database has been shown to effectively display the spatial distribution of NGP in the study area up to the time of China's 2020 Land Survey (Guan et al, 2021; Liang et al, 2023; Yang & Zhang, 2021). However, it should be noted that the confidentiality of the data limits its application in research.…”

Spatio-Temporal Evolution and Multi-Scenario Simulation of Non-Grain Production on Cultivated Land in Jiangsu Province, China

“…Alternatively, remote sensing and GIS technologies have been employed by other researchers to identify NGP phenomena [16][17][18].Studies about the trends in land use change to NGP [19,20] and the drivers [21,22] and driving mechanisms [21,22] of NGP provide valuable insights into understanding its causes and mitigating its effects. These studies found that factors such as natural resources [23,24], socio-economics [21], transportation location [23], and policy considerations [21,25,26] may contribute to NGP. Considering previous research and the current agricultural production landscape in this study area, we defined NGP as the cultivation of crops other than rice, wheat, and maize on cultivated land.…”

Analysis of Characteristics and Driving Mechanisms of Non-Grain Production of Cropland in Mountainous Areas at the Plot Scale—A Case Study of Lechang City

“…Scholars commonly measure the level of NGPCL within research units based on indicators such as the proportion of cropland area planted with cash crops or the proportion of cropland area planted with cash crops amid transferred cropland [22,29]. Moreover, scholars often use administrative regions as research units and employ geographical analysis models, such as spatial autocorrelation and standard deviation ellipses, to explore the spatial patterns of NGPCL [30][31][32]. Research indicates that hilly and mountainous areas are prominent regions for NGPCL, and cropland in economically developed areas is more likely to be used for non-grain production [33,34].…”