Short-term Farm Level Adaptations of EU15 Agricultural Supply to Climate Change

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.Environmental Economics and Policy, Farm Management,

QUANTIFYING THE HETEROGENEITY OF ABATEMENT COSTS UNDER CLIMATIC AND ENVIRONMENTAL REGULATION CHANGES: AN INTEGRATED MODELLING APPROACH

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.Crop Production/Industries, Environmental Economics and Policy, International Relations/Trade, Land Economics/Use, Resource /Energy Economics and Policy,

Características de la superficie terrestre y clima en África occidental: sesgos e impactos de los modelos de la deforestación histórica inducida antropogénicamente

Land Use Land-Cover Change (LULCC), such as deforestation, affects the climate system and land-atmosphere interactions. Using simulations carried out within the LUCID (Land Use and Climate, IDentification of robust Impacts) project framework, we first quantify the role of historical land-cover change induced by human activities on surface climate in West Africa. Focusing on two contrasted African regions, we find that climate responses of land-use changes are small but they are still statistically significant. In Western Sahel, a statistically significant near-surface atmospheric cooling and a decrease in water recycling are simulated in summer in response to LULCC. Over the Guinean zone, models simulate a significant decrease in precipitation and water recycling in autumn in response to LULCC. This signal is comparable in magnitude with the effect induced by the increase in greenhouse gases. Simulated climate changes due to historical LULCC could however be underestimated because: (i) the prescribed LULCC can be underestimated in those regions; (ii) the climate models underestimate the coupling strength between West African surface climate and leaf area index (LAI) and (iii) the lack of interactive LAI in some models. Finally, our study reveals indirect atmospheric processes triggered by LULCC. Over the Western Sahel, models reveal that a significant decrease in solar reflection tend to cool down the surface and thus counteract the atmospheric feedback. Conversely, over the Guinea zone, models reveal that the indirect atmospheric processes and turbulent heat fluxes dominate the climatic responses over the direct effects of LULCC

Current challenges of implementing anthropogenic land-use and land-cover change in models contributing to climate change assessments

This is the author accepted manuscript. The final version is available from European Geosciences Union (EGU) via the DOI in this record.Land-use and land-cover change (LULCC) represents one of the key drivers of global environmental change. However, the processes and drivers of anthropogenic land-use activity are still overly simplistically implemented in terrestrial biosphere models (TBMs). The published results of these models are used in major assessments of processes and impacts of global environmental change, such as the reports of the Intergovernmental Panel on Climate Change (IPCC). Fully coupled models of climate, land use and biogeochemical cycles to explore land use-climate interactions across spatial scales are currently not available. Instead, information on land use is provided as exogenous data from the land-use change modules of integrated assessment models (IAMs) to TBMs. In this article, we discuss, based on literature review and illustrative analysis of empirical and modeled LULCC data, three major challenges of this current LULCC representation and their implications for land use-climate interaction studies: (I) provision of consistent, harmonized, land-use time series spanning from historical reconstructions to future projections while accounting for uncertainties associated with different land-use modeling approaches, (II) accounting for sub-grid processes and bidirectional changes (gross changes) across spatial scales, and (III) the allocation strategy of independent land-use data at the grid cell level in TBMs. We discuss the factors that hamper the development of improved land-use representation, which sufficiently accounts for uncertainties in the land-use modeling process. We propose that LULCC data-provider and user communities should engage in the joint development and evaluation of enhanced LULCC time series, which account for the diversity of LULCC modeling and increasingly include empirically based information about sub-grid processes and land-use transition trajectories, to improve the representation of land use in TBMs. Moreover, we suggest concentrating on the development of integrated modeling frameworks that may provide further understanding of possible land-climate-society feedbacks.The research in this paper has been supported by the European Research Council under the European Union’s Seventh Framework Programme project LUC4C (Grant No. 603542), ERC grant GLOLAND (No. 311819) and BiodivERsA project TALE (No. 832.14.006) funded by the Dutch National Science Foundation (NWO). This research contributes to the Global Land Project (www.globallandproject.org). This is paper number 26 of the Birmingham Institute of Forest Research

Global and regional effects of land-use change on climate in 21st century simulations with interactive carbon cycle

Biogeophysical (BGP) and biogeochemical (BGC) effects of land-use and land cover change (LULCC) are separated at the global and regional scales in new interactive CO2 simulations for the 21st century. Results from four earth system models (ESMs) are analyzed for the future RCP8.5 scenario from simulations with and without land-use and land cover change (LULCC), contributing to the Land-Use and Climate, IDentification of robust impacts (LUCID) project. Over the period 2006–2100, LULCC causes the atmospheric CO2 concentration to increase by 12, 22, and 66 ppm in CanESM2, MIROC-ESM, and MPI-ESM-LR, respectively. Statistically significant changes in global near-surface temperature are found in three models with a BGC-induced global mean annual warming between 0.07 and 0.23 K. BGP-induced responses are simulated by three models in areas of intense LULCC of varying sign and magnitude (between −0.47 and 0.10 K). Modifications of the land carbon pool by LULCC are disentangled in accordance with processes that can lead to increases and decreases in this carbon pool. Global land carbon losses due to LULCC are simulated by all models: 218, 57, 35 and 34 Gt C by MPI-ESM-LR, MIROC-ESM, IPSL-CM5A-LR and CanESM2, respectively. On the contrary, the CO2-fertilization effect caused by elevated atmospheric CO2 concentrations due to LULCC leads to a land carbon gain of 39 Gt C in MPI-ESM-LR and is almost negligible in the other models. A substantial part of the spread in models' responses to LULCC is attributed to the differences in implementation of LULCC (e.g., whether pastures or crops are simulated explicitly) and the simulation of specific processes. Simple idealized experiments with clear protocols for implementing LULCC in ESMs are needed to increase the understanding of model responses and the statistical significance of results, especially when analyzing the regional-scale impacts of LULCC