Unintended consequences of combating desertification in China

China's desertification-prone region (DPR), spanning over 1.2 million km², supports traditional pastoral and agricultural systems impacting over 47.9 million people. Desertification significantly threatens China's ecology and food security. Since the early 2000s, the Chinese government has invested over 780 billion RMB (~112 billion USD) in "grain-for-green" and grazing exclusion practices. However, the effectiveness and broader sustainability impacts of these massive investments remain unclear. This study aims to comprehensively assess the environmental and economic impacts of these practices over the past two decades. This is crucial for informing policy adaptations to enhance ecological restoration while ensuring the economic well-being and food security of the region's population. The study addresses the need for a balanced approach, integrating environmental protection with socioeconomic considerations, aligning with several UN Sustainable Development Goals (SDGs).

Existing literature highlights the positive effects of China's ecological programs on vegetation restoration and carbon sequestration. However, studies on the economic and social consequences of these programs, specifically the "grain-for-green" and grazing exclusion initiatives, have been limited. Some research emphasizes the need to balance ecological conservation with socioeconomic considerations, acknowledging potential trade-offs between environmental benefits and livelihood security. This paper builds upon previous work by providing a more comprehensive assessment that integrates both ecological and economic data to quantify the impact of these policies.

This study employs a multi-faceted methodology integrating remote sensing, statistical modeling, and socioeconomic data analysis. First, a high-resolution fractional vegetation cover (FVC) dataset was constructed using improved pixel bipartite models and multi-source remote sensing data (1982-2018). The study then used stepwise multiple linear regression (SMLR) models to quantify the contributions of climate change (precipitation, temperature, solar radiation, wind speed), CO2 fertilization, and the "grain-for-green" and grazing exclusion practices to vegetation restoration. The impact on grain and meat production was assessed using land use data and county-level socioeconomic data (population, disposable income, GDP, grain production, livestock production). A "without-practice" hypothesis was used to estimate the foregone grain and meat production resulting from land-use restrictions. Finally, future vegetation trends were projected using CMIP6 climate model outputs. The study area, the DPR, was defined using data from the Cold and Arid Regions Environmental and Engineering Research Institute (CAREERI) and the Institute of Glaciology, Frozen Soil and Desert. Land use data were sourced from the Multi-Period Land Use Land Cover Remote Sensing Monitoring Dataset for China (CNLUCC). Economic data were compiled from the China Database on Country-level Agricultural and Rural Indicators and the Resources and Environmental Science Data Center.

The study reveals a complex interplay of factors influencing vegetation changes in China's DPR. While climate change and CO2 fertilization were identified as strong drivers of vegetation recovery (1982-2018), the contribution of the "grain-for-green" and grazing exclusion practices was significantly less than expected. Specifically, only 63% of the restored land involved in the "grain-for-green" program showed positive contributions to FVC increases, with an average contribution of -1.06%. The average contribution of grazing exclusion to vegetation restoration was 13.40%. The combined effect of both practices on FVC increases was only 13.07%. Furthermore, these practices negatively impacted grain and meat production, resulting in substantial economic losses for farmers and herders. Compared to expected yields, mean costs in terms of foregone grain and meat production were 13.4% and 24.2%, respectively. The decrease in the direct income of farmers and herders (15%) significantly outweighed government subsidies (-6.10% of direct income). Projections based on CMIP6 models suggest a continued warming and wetting trend until 2050, which is expected to further enhance vegetation restoration, highlighting the potentially excessive implementation of current desertification-combating practices.

The findings challenge the prevailing narrative of unmitigated success for China's desertification-combating programs. The limited contribution of the "grain-for-green" and grazing exclusion practices, coupled with substantial socioeconomic costs, suggests a need for policy adjustments. The study's results underscore the importance of considering both environmental and economic factors in policy design. The current practices may be suboptimal in many areas of the DPR, particularly given the significant role of climate change and CO2 fertilization in vegetation recovery. Alternative approaches, such as farmland shelterbelts, water conservation, and rotational grazing, should be explored to maximize environmental benefits while minimizing economic hardship. The study also highlights the inadequacy of current subsidy mechanisms in compensating for income losses, emphasizing the need for improved financial support and more transparent fund management.

This research demonstrates that China's current desertification-combating strategies, while well-intentioned, have generated unintended negative consequences on the socioeconomic well-being of the region's inhabitants. The findings emphasize the need to move away from blanket land-use restrictions in favor of more targeted interventions that integrate environmental restoration with socioeconomic development. Future research should focus on developing and testing alternative sustainable land management practices that create positive synergies for both ecological and economic improvements. A thorough cost-benefit analysis of different approaches is crucial to optimize resource allocation and achieve a more balanced and sustainable approach to combating desertification.

The study relies on existing data sources, which may have limitations in terms of spatial and temporal resolution. The economic analysis is based on aggregated data, potentially obscuring variations at the household or individual level. Furthermore, the model projections for future vegetation trends depend on the accuracy of the CMIP6 climate models, which inherently involve uncertainties. Finally, the study primarily focuses on the economic consequences for farmers and herders, potentially overlooking the impacts on other stakeholder groups.