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The Agricultural Model Intercomparison and Improvement Project (AgMIP) is a major international effort linking the climate, crop, and economic modeling communities with cutting-edge information technology to produce improved crop and economic models and the next generation of climate impact projections for the agricultural sector. The goals of AgMIP are to improve substantially the characterization of world food security due to climate change and to enhance adaptation capacity in both developing and developed countries. Analyses of the agricultural impacts of climate variability and change require a transdisciplinary effort to consistently link state-of-the-art climate scenarios to crop and economic models. Crop model outputs are aggregated as inputs to regional and global economic models to determine regional vulnerabilities, changes in comparative advantage, price effects, and potential adaptation strategies in the agricultural sector. Climate, Crop Modeling, Economics, and Information Technology Team Protocols are presented to guide coordinated climate, crop modeling, economics, and information technology research activities around the world, along with AgMIP Cross-Cutting Themes that address uncertainty, aggregation and scaling, and the development of Representative Agricultural Pathways (RAPs) to enable testing of climate change adaptations in the context of other regional and global trends. The organization of research activities by geographic region and specific crops is described, along with project milestones. Pilot results demonstrate AgMIP's role in assessing climate impacts with explicit representation of uncertainties in climate scenarios and simulations using crop and economic models. An intercomparison of wheat model simulations near Obregón, Mexico reveals inter-model differences in yield sensitivity to [CO2] with model uncertainty holding approximately steady as concentrations rise, while uncertainty related to choice of crop model increases with rising temperatures. Wheat model simulations with mid-century climate scenarios project a slight decline in absolute yields that is more sensitive to selection of crop model than to global climate model, emissions scenario, or climate scenario downscaling method. A comparison of regional and national-scale economic simulations finds a large sensitivity of projected yield changes to the simulations’ resolved scales. Finally, a global economic model intercomparison example demonstrates that improvements in the understanding of agriculture futures arise from integration of the range of uncertainty in crop, climate, and economic modeling results in multi-model assessments.

Biomass production in grasslands, a key component of food provision for domestic herbivores, is known to depend on climate, resource availability, and on the functional characteristics of communities. However, the combined effects of these different factors remain largely unknown. The aim of the present study was to unravel the causes of variations in the standing biomass of plant communities using a long‐term experiment conducted in a Mediterranean rangeland of Southern France. Two management regimes, sheep grazing and grazing associated with mineral fertilization, were applied to different areas of the study site over the past 25 years. Abiotic (temperature, available water, nutrients) and biotic (components of the functional structure communities) factors were considered to explain interannual and spatial variations in standing biomass in these rangelands.Standing biomass was highly predictable, with the best model explaining ∼80% of variations in the amount of biomass produced, but the variation explained by abiotic and biotic factors was dependent on the season and on the management regime. Abiotic factors were found to have comparable effects in both management regimes: The amount of biomass produced in the spring was limited by cold temperatures, while it was limited by water availability and high temperatures in the summer. In the fertilized community, the progressive change in the functional structure of the communities had significant effects on the amount of biomass produced: the dominance of few productive species which were functionally close led to higher peak standing biomass in spring.

Abstract The introduction of nitrogen fixing species (NFS) in fast-growing tree plantations is an alternative option to reduce fertilizer inputs. However, the success of mixed-species plantations depends on the balance between positive interactions among species (resulting from facilitation and/or complementarity) and the negative effects of interspecific competition. Using a carbon budget approach and coupling measurements of standing biomass, aboveground litterfall and soil CO2 efflux, we assessed the influence of replacing half of eucalypt trees by Acacia mangium on total belowground carbon flux (TBCF), net primary production (NPP) and its partitioning between above- and belowground growth at two tropical sites in Brazil (Itatinga) and in Congo (Kissoko) exhibiting contrasting climates, edaphic conditions and wood productions. Annual soil CO2 efflux (FS) was significantly lower in the acacia monocultures than in eucalypt monocultures and mixed-species stands at both sites. Annual FS was significantly lower at Itatinga compared to Kissoko for all stands while TBCF was significantly lower in the eucalypt stands only. In the eucalypt monocultures we found a significantly lower aboveground NPP (ANPP) and wood production (wood NPP) at Kissoko compared to Itatinga that was almost fully balanced by a significantly higher belowground NPP (BNPP), leading to similar NPP. Similarly, acacia monocultures exhibited significantly higher ANPP and wood NPP at Itatinga than at Kissoko. The mixed-species stands exhibited a significantly lower wood NPP and ANPP than the eucalypt monocultures at the Brazilian site while NPP of the mixture was not significantly different than the average NPP of the two monocultures. At the Congolese site, NPP of the mixture was significantly higher than the average NPP of the two monocultures. NPP was similar in the mixed-species stand and the eucalypt monoculture with a significantly lower partitioning of NPP to belowground production, leading to a one third higher wood biomass at harvest in the mixed-species stand. A positive effect of growing eucalypts with the nitrogen fixing acacia trees on stand wood production occurred at Kissoko but not at Itatinga. Mixed-species plantations with NFS can be advocated at sites where the productive gains resulting from nitrogen fixation are not compromised by other resource limitations.

Abstract The white‐clawed crayfish (Austropotamobius pallipes) is globally endangered due to the impacts of habitat modification and fragmentation, water pollution, climate change, and invasive species, particularly the signal crayfish (Pacifastacus leniusculus). These pressures have caused the decline of A. pallipes populations in Europe, demonstrating the importance of predicting the species' potential distribution under current and future conditions. Focusing on the watercourses of mainland France, we aimed to identify suitable areas for A. pallipes to guide the conservation of current populations and future introduction actions or protection measures. We applied ecological niche modelling to model the potential distribution of both A. pallipes and P. leniusculus and identified locations suitable for A. pallipes only. We also assessed the potential distribution of the species under two representative concentration pathway (RCP) scenarios: RCP 2.6 and RCP 8.5, respectively describing low‐warming and high‐warming conditions. We found that A. pallipes and P. leniusculus exploit equivalent niches in France. Despite this, under current conditions, about 5% of the study area simultaneously records a high suitability for A. pallipes and a low suitability for P. leniusculus and is therefore of significant conservation interest. This percentage remains relatively stable under RCP 2.6 for 2050 and 2100, but decreases to 2% under RCP 8.5 for 2100. Ecological niche modelling can supply crucial guidance for conservation actions aimed at protecting endangered species at a national scale by identifying sites most suitable for protection and sites where climate change and invasive species constitute a threat.

AbstractProcess‐based models are useful for assessing the impact of changing management practices and climate on yields and greenhouse gas (GHG) emissions from agricultural systems such as grasslands. They can be used to construct national GHG inventories using a Tier 3 approach. However, accurate simulations of nitrous oxide (N2O) fluxes remain challenging. Models are limited by our understanding of soil‐plant‐microbe interactions and the impact of uncertainty in measured input parameters on simulated outputs. To improve model performance, thorough evaluations against in situ measurements are needed. Experimental data of N2O emissions under two management practices (control with typical fertilization versus increased clover and no fertilization) were acquired in a Swiss field experiment. We conducted a multimodel evaluation with three commonly used biogeochemical models (DayCent in two variants, PaSim, APSIM in two variants) comparing four years of data. DayCent was the most accurate model for simulating N2O fluxes on annual timescales, while APSIM was most accurate for daily N2O fluxes. The multimodel ensemble average reduced the error in estimated annual fluxes by 41% compared to an estimate using the Intergovernmental Panel on Climate Change (IPCC)‐derived method for the Swiss agricultural GHG inventory (IPCC‐Swiss), but individual models were not systematically more accurate than IPCC‐Swiss. The model ensemble overestimated the N2O mitigation effect of the clover‐based treatment (measured: 39–45%; ensemble: 52–57%) but was more accurate than IPCC‐Swiss (IPCC‐Swiss: 72–81%). These results suggest that multimodel ensembles are valuable for estimating the impact of climate and management on N2O emissions.