Spatiotemporal variation in determinants of cropland abandonment across Yangtze River Economic Belt, China

Abstract

Cropland abandonment is a widespread land-change phenomenon globally, driven by complex social, economic, and political transformations, with significant implications for the environment and society. However, the inconsistent definitions of cropland abandonment and the bias in the selection of study areas hinder the comparison of identified determinants of cropland abandonment. In this study, we defined cropland abandonment from the perspective of vegetation succession. By employing land-cover change detection with Landsat time-series images from 1990 to 2021, we analyzed the spatiotemporal patterns of cropland abandonment across the cities of Yibin, Huangshi, and Chaohu within the Yangtze River Economic Belt. Furthermore, we utilized the Gradient-Boosting Decision Tree model to identify the primary spatial determinants and their relative importance in each city. Our findings showed significant variations in abandonment rates by 2021. Huangshi exhibited the highest rate of cropland abandonment, leading with 53.81±2.1 %, followed by Yibin with 45.36±2.18 %, and Chaohu with the lowest at 36.94±2.21 %. Interestingly, a consistent spatiotemporal trend, areas with higher abandonment rates tended to be abandoned earlier, emerged in abandonment determinants across cities. Areas with lower bulk density, higher soil clay content, and greater organic carbon contents exhibited higher abandonment rates. However, the most influential determinants varied: the distance from water bodies was the most important in Yibin and Huangshi, while the distance from the forest had a greater impact in Chaohu. This study offers a more nuanced perspective on defining cropland abandonment and can be applied to other regions after some adjustment. Our results provide valuable insights for cropland abandonment management by protecting high-value croplands and setting aside some areas for environmental amenities.