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Abstract. We present protocols and input data for Phase 1 of the Global Gridded Crop Model Intercomparison, a project of the Agricultural Model Intercomparison and Improvement Project (AgMIP). The project includes global simulations of yields, phenologies, and many land-surface fluxes using 12-15 modeling groups for many crops, climate forcing data sets, and scenarios over the historical period from 1948 to 2012. The primary outcomes of the project include (1) a detailed comparison of the major differences and similarities among global models commonly used for large-scale climate impact assessment, (2) an evaluation of model and ensemble hindcasting skill, (3) quantification of key uncertainties from climate input data, model choice, and other sources, and (4) a multi-model analysis of the agricultural impacts of largescale climate extremes from the historical record.

The United States is one of the largest soybean exporters in the world. Production is concentrated in the upper Midwest(1). Much of this region is not irrigated, rendering soybean production systems in the area highly sensitive to in-season variations in weather. Although the influence of in-season weather trends on the yields of crops such as soybean, wheat and maize has been explored in several countries(2-6), the potentially confounding influence of genetic improvements on yields has been overlooked. Here we assess the effect of in-season weather trends on soybean yields in the United States between 1994 and 2013, using field trial data, meteorological data and information on crop management practices, including the adoption of new cultivars. We show that in-season temperature trends had a greater impact on soybean yields than in-season precipitation trends over the measurement period. Averaging across the United States, we show that soybean yields fell by around 2.4% for every 1 °C rise in growing season temperature. However, the response varied significantly among individual states, ranging from -22% to +9%, and also with the month of the year in which the warming occurred. We estimate that year-to-year changes in precipitation and temperature combined suppressed the US average yield gain by around 30% over the measurement period, leading to a loss of US$11 billion. Our data highlight the importance of developing location-specific adaptation strategies for climate change based on early-, mid- and late-growing season climate trends.

A B S T R A C TCrops and livestock play a synergistic role in global food production and farmer livelihoods. Increasingly, however, crops and livestock are produced in isolation, particularly in farms operating at the commercial scale. It has been suggested that re-integrating crop and livestock systems at the field and farm level could help reduce the pollution associated with modern agricultural production and increase yields. Despite this potential, there has been no systematic review to assess remaining knowledge gaps in both the social and ecological dimensions of integrated crop and livestock systems (ICLS), particularly within commercial agricultural systems. Based on a multi-disciplinary workshop of international experts and additional literature review, we assess the current knowledge and remaining uncertainties about large-scale, commercial ICLS and identify the source of remaining knowledge gaps to establish priorities for future research. We find that much is understood about nutrient flows, soil quality, crop performance, and animal weight gain in commercial ICLS, but there is little knowledge about its spatial extent, animal behavior or welfare in ICLS, or the tradeoffs between biodiversity, pest and disease control, greenhouse gas (GHG) mitigation, and drought and heat tolerance in ICLS. There is some evidence regarding the economic outcomes in commercial ICLS and supply chain and policy barriers to adoption, but little understanding of broader social outcomes or cultural factors influencing adoption. Many of these knowledge gaps arise from a basic lack of data at both the field and system scales, which undermines both statistical analysis and modeling efforts. Future priorities for the international community of researchers investigating the tradeoffs and scalability of ICLS include: methods standardization to better facilitate international collaborations and comparisons, continued social organization for better data utilization and collaboration, meta-analyses to answer key questions from existing data, the establishment of long term experiments and surveys in key regions, a portal for citizen science, and more engagement with ICLS farmers.

A hopeful vision of the future is a world in which both people and nature thrive, but there is little evidence to support the feasibility of such a vision. We used a global, spatially explicit, systems modeling approach to explore the possibility of meeting the demands of increased populations and economic growth in 2050 while simultaneously advancing multiple conservation goals. Our results demonstrate that if, instead of “business as usual” practices, the world changes how and where food and energy are produced, this could help to meet projected increases in food (54%) and energy (56%) demand while achieving habitat protection (>50% of natural habitat remains unconverted in most biomes globally; 17% area of each ecoregion protected in each country), reducing atmospheric greenhouse‐gas emissions consistent with the Paris Climate Agreement (≤1.6°C warming by 2100), ending overfishing, and reducing water stress and particulate air pollution. Achieving this hopeful vision for people and nature is attainable with existing technology and consumption patterns. However, success will require major shifts in production methods and an ability to overcome substantial economic, social, and political challenges.