Declining suitability for conversion of drylands to paddy fields in Northeast China: Impact of future climate and socio-economic changes

Abstract

Conversion of dryland to paddy fields (CDPF) is an effective way to transition from rain-fed to irrigated agriculture, helping to mitigate the effects of climate change on agriculture and increase yields to meet growing food demand. However, the suitability of CDPF is spatio-temporally dynamic but has often been neglected in previous studies. To fill this knowledge gap, this research developed a novel method for quantifying the suitability of CDPF, based on the MaxEnt model for application in Northeast China. We explored the spatiotemporal characteristics of the suitability of CDPF under the baseline scenario (2010–2020), and future projections (2030–2090) coupled with climate change and socioeconomic development scenarios (SSP126, SSP245, and SSP585), and revealed the driving factors behind it. Based on this, we identified potential priority areas for future CDPF implementation. The results show that the suitability of CDPF projects implemented in the past ten years is relatively high. Compared with the baseline scenario, the suitability of CDPF under the future scenarios will decline overall, with the lightest decrease in the RCP585 and the most severe decrease in the RCP245. The key drivers affecting the suitability of CDPF are elevation, slope, population count, total nitrogen, soil organic carbon content, and precipitation seasonality. The potential priority areas for the future CDPF range from 6,284.61 km2 to 37,006.02 km2. These findings demonstrate the challenges of CDPF in adapting to climate change and food security, and provide insights for food-producing regions around the world facing climate crises.

Keywords

• Cropland conversion
• Food security
• Suitability
• Climate change
• Machine learning model
• Northeast China