Modelling Chinese grassland systems to improve herder livelihoods and grassland sustainability

Abstract

Recent degradation of Chinese grasslands has contributed to declining herder productivity and profitability, increased incidence of dust storms and regionally reduced air quality. Overgrazing due to a doubling of stocking rates since the mid-1980s has been identified as a key contributing factor. Several pathways and strategies exist to improve grassland management; however, there remains uncertainty around the long-term sustainability of alternative systems. Nineteen years of grasslands research in China has produced a suite of models designed to improve understanding of grassland systems and investigate options for change. The StageTHREE Sustainable Grasslands Model was used to evaluate the ability of selected strategies to meet economic, production and environmental objectives. Sets of strategies that focussed on flock size, lambing and selling times, supplementary feeding rules and grazing management were simulated for a typical herder located in the desert steppe of Siziwang Banner, in the Inner Mongolia Autonomous Region of China. The results from the risk efficiency analysis indicated that no single strategy set clearly dominates across all objectives. Although the current practice of herders was found to be risk-efficient, it did not achieve the highest rate of grassland recovery, minimise soil erosion or minimise the greenhouse gas (GHG) emission intensity for sheepmeat production. Targeting further improvements in these attributes could be at the detriment of herder livelihoods. The analysis indicated that if herders adopted biomass-based grazing management and improved supplementary feeding they would be able to improve grassland resilience and maintain positive long-term economic performance under reduced flock sizes. Individual decision-making units, however, would still need to trade off the importance of different attributes to identify the strategy set, or system, that best meets their objectives and attitude to risk.