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Egalement publié en 2014 dans Pour la Science n°437; National audience

Assessing climate change impact on agriculture is a complex task involving a wide range of economical and physical processes, leading to significant uncertainties. At European scale, climate change impacts on agricultural supply have been appraised to be of relatively less important driver by the end of century compared to other global drivers. However these diagnoses are incomplete due to a limited representation of both spatial heterogeneity in important determinants of agricultural supply (soil, management practices and producer typology) and fine scale processes such as farm scale autonomous adaptation. We propose a complementary approach based on a modeling framework including a spatially explicit representation of productivity and producer behavior with regard to heterogeneity in soil, climate, and producer socio-economic context to appraise climate change impacts including autonomous farm-scale adaptations of EU15 agricultural supply to climate change. Our results suggest that without accounting for autonomous adaptation European agricultural supply may have interesting resilience properties at an aggregated scale despite significant heterogeneity at smaller resolution. Accounting for autonomous adaptations result in significant yield gains, and may lead to (i) a significant increase in the relative profitability of crops compared to other land-covers, thus possibly increasing its agricultural land-use share over other land covers, and (ii) an increase in total European production which may have impacts on agricultural goods markets, thus highlighting the need for integrating fine scale processes such as autonomous adaptation.

We present here preliminary results of an integrated modelling approach combining a crop model (STICS) and an economic model (AROPAj) of European agricultural supply. This modelling framework is designed to perform quantitative analysis, regarding climate change impacts on agriculture and more generally the interactions between soils, land use, agriculture and climate integrating physical and economical elements (data, process, models). It explicitly integrates an agricultural diversity dimension with regards to economic set of choices and soil climate spatial variability. First results are given in term of quantitative analysis combining optimal land allocation (economic optimality) and “dose-response” functions related to a large set of crops in Europe, at the farm group level, covering part of the European Union (EU15). They indicate that accounting for economical and spatial variability may impact both regional aggregated scales results.

International audience; We assessed the effects of rising atmospheric CO(2), changing climate, and farmers' practice on the carbon and water balance of European croplands during the past century (1901-2000). The coupled vegetation-crop model ORCHIDEE-STICS is applied over western Europe for C3 crops (winter wheat) and for maize, with prescribed historical agricultural practice changes. Not surprisingly, the enormous crop yield increase observed in all European regions, 300-400% between 1950 and 2000, is found to be dominantly explained by improved practice and varieties selection, rather than by rising CO(2) (explaining a similar to 11% uniform increase in yield) and changing climate (no further change in yield on average, but causing a decrease of similar to 19% in the southern Iberian Peninsula). Agricultural soil carbon stocks in Europe are modeled to have decreased between 1950 and 1970, and since then to have increased again. Thus, the current stocks only differ by 1 +/- 6 tC ha(-1) from their 1900 value. Compensating effects of increasing yields on the one hand (increasing stocks) and of higher harvest index values and ploughing on the other hand (decreasing stocks) occur. Each of these processes taken individually has the potential to strongly alter the croplands soil carbon balance in the model. Consequently, large uncertainties are associated to the estimated change in carbon stocks between 1901 and 2001, roughly +/- 6 tC ha(-1) a(-1). In our most realistic simulation, the current cropland carbon balance is a net sink of 0.16 +/- 0.15 tC ha(-1) a(-1). The annual water balance of cropland soils is influenced by increasing crop water use efficiency, one third of which is caused by rising CO(2). However, increasing water use efficiency occurred mainly in spring and winter, when water is not limiting for plant growth, whereas no strong savings of soil water are achieved in summer through elevated CO(2). Overall, trends in cultivation practices have caused a 3 times larger increase of water use efficiency than rising CO(2).

Human land-use activities have resulted in large changes to the Earth’s surface, with resulting implications for climate. In the future, land-use activities are likely to expand and intensify further to meet growing demands for food, fiber, and energy. The Land Use Model Intercomparison Project (LUMIP) aims to further advance understanding of the impacts of land-use and land-cover change (LULCC) on climate, specifically addressing the following questions. (1) What are the effects of LULCC on climate and biogeochemical cycling (past–future)? (2) What are the impacts of land management on surface fluxes of carbon, water, and energy, and are there regional land-management strategies with the promise to help mitigate climate change? In addressing these questions, LUMIP will also address a range of more detailed science questions to get at process-level attribution, uncertainty, data requirements, and other related issues in more depth and sophistication than possible in a multi-model context to date. There will be particular focus on the separation and quantification of the effects on climate from LULCC relative to all forcings, separation of biogeochemical from biogeophysical effects of land use, the unique impacts of land-cover change vs. land-management change, modulation of land-use impact on climate by land–atmosphere coupling strength, and the extent to which impacts of enhanced CO2 concentrations on plant photosynthesis are modulated by past and future land use. LUMIP involves three major sets of science activities: (1) development of an updated and expanded historical and future land-use data set, (2) an experimental protocol for specific LUMIP experiments for CMIP6, and (3) definition of metrics and diagnostic protocols that quantify model performance, and related sensitivities, with respect to LULCC. In this paper, we describe LUMIP activity (2), i.e., the LUMIP simulations that will formally be part of CMIP6. These experiments are explicitly designed to be complementary to simulations requested in the CMIP6 DECK and historical simulations and other CMIP6 MIPs including ScenarioMIP, C4MIP, LS3MIP, and DAMIP. LUMIP includes a twophase experimental design. Phase one features idealized coupled and land-only model simulations designed to advance process-level understanding of LULCC impacts on climate, as well as to quantify model sensitivity to potential landcover and land-use change. Phase two experiments focus on quantification of the historic impact of land use and the po- tential for future land management decisions to aid in mitigation of climate change. This paper documents these simulations in detail, explains their rationale, outlines plans for analysis, and describes a new subgrid land-use tile data request for selected variables (reporting model output data separately for primary and secondary land, crops, pasture, and urban land-use types). It is essential that modeling groups participating in LUMIP adhere to the experimental design as closely as possible and clearly report how the model experiments were executed.