Abstract: Projections of climate change impacts on crop yields are inherently uncertain(1). Uncertainty is often quantified when projecting future greenhouse gas emissions and their influence on climate(2). However, multi-model uncertainty analysis of crop responses to climate change is rare because systematic and objective comparisons among process-based crop simulation models(1,3) are difficult(4). Here we present the largest standardized model intercomparison for climate change impacts so far. We found that individual crop models are able to simulate measured wheat grain yields accurately under a range of environments, particularly if the input information is sufficient. However, simulated climate change impacts vary across models owing to differences in model structures and parameter values. A greater proportion of the uncertainty in climate change impact projections was due to variations among crop models than to variations among downscaled general circulation models. Uncertainties in simulated impacts increased with CO2 concentrations and associated warming. These impact uncertainties can be reduced by improving temperature and CO2 relationships in models and better quantified through use of multi-model ensembles. Less uncertainty in describing how climate change may affect agricultural productivity will aid adaptation strategy development and policymaking.

Abstract: Government policy is a major human factor that causes changes in land use. Decisions on land management and land-use planning, as well as the analysis and quantification of policy consequences, may greatly benefit from the simulation of the dynamics of land-use systems. In the present study, we predicted land-use changes and their potential impacts on food security in the environmentally fragile Guyuan District, Ningxia Hui Autonomous Region (north-central China), under the influence of a program to convert sloping agricultural land to conservation uses. Baseline and conservation policy scenarios (2005 to 2020) were developed based on input from local stakeholders and expert knowledge. For the baseline and conservation policies, we formulated high-, moderate-, and low-growth scenarios, analyzed the driving mechanisms responsible for the land-use dynamics, and then applied a previously developed “dynamics of land systems” model to simulate changes in land uses based on the driving mechanisms. We found that spatially explicit policies can promote the conversion of land to more sustainable uses; however, decreasing the amount of agricultural and urban land and increasing grassland and forest cover will increase the risk of grain shortages, and the effect will be more severe under the conservation and high- growth scenarios than under the baseline and low-growth scenarios. The Guyuan case study suggests that, during the next decade, important trade-offs between environmental conservation and food security will inevitably occur. Future land-use decisions should carefully consider the balance between land resource conservation, agricultural production, and urban expansion.