Exploring the impact of rural labor transfer on the production and ecological sustainability of crop planting structure in China

Environ Sci Pollut Res Int. 2023 Feb;30(9):22668-22685. doi: 10.1007/s11356-022-23613-5. Epub 2022 Oct 27.

Abstract

With the improvement of industrialization, numerous rural laborers migrate to urban areas in search of off-farm jobs. Farmers change agricultural production decisions to adapt to the change of labor force, which will inevitably affect the crop planting structure. However, few studies have explored the sustainability of crop planting structure. Based on the calculation of the multiple cropping index (MCI), grain crops planting rate (GCR), economic crops planting rate (ECR), and ecological sustainability index (ESI) of crop planting structure, this study analyzes the impact of labor transfer rate (LTR) and labor cost (LC) on the sustainability of crop planting structure using a geographically and temporally weighted regression (GTWR) model. The results show that the scale of rural labor transfer and labor cost in China remains on the rise, but the growth rate has slowed down. The total carbon absorption of crops in China shows a U-shape trend, and the rice and maize have the largest carbon absorption. The impact of LTR on MCI is mainly positive, especially in the North China Plain in the early stage and some provinces in the Southwest China in the later stage. The impact of LTR on ECR and ESI is negative in most provinces. And the negative influence of LC on MCI is increasing, showing the spatial distribution characteristics of large influence in the southeast and small influence in the northwest. The impact of LC on ESI shows a negative effect in most provinces in the early stage, and the negative effect is more concentrated in some provinces in the southwest in the later stage.

Keywords: Crop planting structure; GTWR model; Labor cost; Labor transfer; Sustainability.

MeSH terms

  • Agriculture*
  • Carbon
  • China
  • Crop Production / methods
  • Crops, Agricultural
  • Farms
  • Humans
  • Rural Population*

Substances

  • Carbon