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Maiorano, A., Martre, P., Asseng, S., Ewert, F., Müller, C., Rötter, R. P., et al. (2016). Crop model improvement reduces the uncertainty of the response to temperature of multi-model ensembles. Field Crops Research, 202, 5–20.
Abstract: To improve climate change impact estimates and to quantify their uncertainty, multi-model ensembles (MMEs) have been suggested. Model improvements can improve the accuracy of simulations and reduce the uncertainty of climate change impact assessments. Furthermore, they can reduce the number of models needed in a MME. Herein, 15 wheat growth models of a larger MME were improved through re-parameterization and/or incorporating or modifying heat stress effects on phenology, leaf growth and senescence, biomass growth, and grain number and size using detailed field experimental data from the USDA Hot Serial Cereal experiment (calibration data set). Simulation results from before and after model improvement were then evaluated with independent field experiments from a CIMMYT world-wide field trial network (evaluation data set). Model improvements decreased the variation (10th to 90th model ensemble percentile range) of grain yields simulated by the MME on average by 39% in the calibration data set and by 26% in the independent evaluation data set for crops grown in mean seasonal temperatures >24 °C. MME mean squared error in simulating grain yield decreased by 37%. A reduction in MME uncertainty range by 27% increased MME prediction skills by 47%. Results suggest that the mean level of variation observed in field experiments and used as a benchmark can be reached with half the number of models in the MME. Improving crop models is therefore important to increase the certainty of model-based impact assessments and allow more practical, i.e. smaller MMEs to be used effectively.
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Pohanková, E., Hlavinka, P., Kersebaum, K. C., Dubrovský, M., Fischer, M., Balek, J., et al. (2015). Pilot study: Field crop rotations modeling under present and future conditions in the Czech Republic using HERMES model (Vol. 5).
Abstract: The aim of this study is to compare the water and organic material balance, yields and other aspects estimated within crop rotations by the Hermes crop model for present and future climatic conditions in the Czech Republic. Moreover, this is a pilot study for the complex and continuous crop rotations modeling (using both single crop models and ensembles) in connection with transient climate change scenarios. For this purpose, three locations representing important agricultural regions of the Czech Republic (with different climatic conditions) were selected. The crop rotation (including spring barley, silage maize, winter wheat, winter rape, and winter wheat in the listed order) was simulated from 1981-2080. The period 1981-2010 was covered by measured meteorological data, and the period 2011-2080 was represented by a transient synthetic weather series from the weather generator M&Rfi. The generated data was based on five circulation models representing an ensemble of 18 CMIP3 global circulation models to preserve to a large degree the uncertainty of the original ensemble. Two types of crop management were compared, and the influences of soil quality, increasing atmospheric CO2 and magnitude of adaptation measure (in the form of sowing date changes) were also considered. According to the results, if a “dry” scenario (such as GFCM21) would occur, then all the C3 crops produced in drier regions would be devastated in a significant number of seasons; for example, by the 2070s, up to 19.5%, 21.5% and 47.0% of seasons with winter rape, spring barley and winter wheat, respectively, would have a yield level below 50% of the present yield. Negative impacts are likely even on premium-quality soils regardless of the use of a flexible sowing date and accounting for increasing CO2 concentrations. Moreover, in some cases, the use of catch crops can have negative impacts, exacerbating the soil water deficit for the subsequent crops. This study (submitted to Climate Research journal) will be used as a pilot for subsequent activities. In this area, following calculations (the same set of stations and updated climate scenarios) using growth models ensemble (currently includes 12 modeling approaches) started to estimate uncertainty aspects. Consequently, the analysis within wider range of conditions (across continents) and farming methods will be conducted. No Label
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Zander, P. (2015). Scenarios of regional agricultural land use under climate change for 4 case study regions in Northern Germany (Vol. 5).
Abstract: Agricultural land use in Northern Germany is characterized by a gradient of decreasing precipitation from west to east. Climate change is expected to increase temperature and decrease summer precipitation. In the context of a nationally funded project we aim to analyze climate change adaptation strategies for agricultural land use. The research is focused in 4 study regions from Eastern to Western Germany. The presented modelling approach analyses agricultural land use under climate change and for three policy scenarios (business as usual, biodiversity and climate protection). The biodiversity and climate protection scenarios each reserve area for specific scenario objectives: 10% for specific biodiversity measures and 20% for N-fixing legumes in case of the climate protection scenario. All scenarios are executed for three time steps representing year 2010, 2020 and 2030 with a constant yield increase, extrapolated from past observations. Building on IACS data for a farm typology and expert assessments of current and future land use options, we applied a linear programming farm model. Prices are exogenous and derived from CAPRI model runs for 2020 and 2030. First preliminary results show strong impacts of price assumptions and yield assessments. This results in 2020 in lower gross margins for a number of crops and finally to higher set aside areas in eastern Germany. For 2030 input–output price relations are more favourable for farmers and thus lead to lower set aside areas. No Label
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Sieber, S. (2015). The Tanzanian case study in MACSUR II (Vol. 5).
Abstract: The objective of the Tanzanian case study region is to provide MACSUR II a platform to concentrate climate research to a focal region in Morogoro and Dodoma in Tanzania. Hence, synergies among a number of other research projects will be used, which all focus on food security related to climate change.Within the case study region the projects aim at improving the food situation for the most-vulnerable rural poor population in Tanzania. They are designed to identify successful food securing upgrading strategies and innovations along local and regional food value chains, test and adjust them to site-specific, sustainable settings and tailor these concepts to be disseminated for national outreach. After the project lifetime, the results can be implemented at different levels of policy, extension and research.The basic concept applies the following steps in an iterative and partly recurrent procedure: (1) A stakeholder involvement process will be set up from the beginning as an integral part of most analytical steps; (2) case study sites within the focal regions Morogoro and Dodoma will be selected, set up and typologies of food value chains developed; (3) success stories of secure food production and/or good practice along the food value chains will be screened and inventoried; (4) an integrated in-depth analyses of food value chain components, their costs, benefits and impacts will be carried out; (5) a few of the most promising good practices with regard to positive impacts and implementation will be participatively discussed and identified for subsequent in-depth testing; (6) an in-depth participative field testing and/or analysis of selected, most promising technologies will be conducted for all food value chain components and requirements for implementation identified; (7) transferability and implementation capability will be assessed for different scenarios and for future condition simulations (model analysis); (8) a meta-model analysis including risk analysis and final proofing will identify hot spots of most sensitive, fragile regions and the potentials for alleviating food insecurity. Hence, the research concept`s main focuses on local and regional food security related to climate change, but the research design implies a national outreach for Tanzania as a whole.The research activities will be embedded into local and regional strategies to assess potential impacts and trade-offs and to be able to up-scale lessons learnt in a generic manner to regions with specific bio-physical, socio-cultural and economic conditions.Spatial Design: Conducting a literature research on relevant characteristic a considering the spatial design:two focal regions in Tanzania (Morogoro, Dodoma),each region with two case study sites (CSS) consisting of at least one local marketplace and surrounding 2-3 villages,the two CSS among the target regions are selected to differ in factors such as market and capital access for investments, remoteness, population density, land availability, soil types, infrastructure, facilities, and others,create sufficiently diverse environmental and socio-economic conditions for investigating food securing technologies along FVC and allowing for testing the transfer of results to other Tanzanian regions.Main selection criteria for regions: two climates types:semi-arid Dodoma (350-500mm),semi-humid Morogoro region (600-800mm)clear distinction between the regions.other criteria within the regions:rather similar climate (must) +-80mm,weak and good market access (must) (=market and capital access for investments),rainfed crop–livestock systems oriented, not too strongly paddy rice oriented (< 20% rice) (must),village size: approx. 800-1500 households (must)Stunting cases, logistics and infrastructure, different wards, land availability, facilities, capital, soil types, and population density etc. No Label
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Sándor, R. (2015). Sensitivity and uncertainty analysis of grassland models in Europe and Israel (Vol. 5).
Abstract: Grassland models are valuable tools to test hypotheses on grassland ecosystem functioning. In the frame of FACCE MACSUR LiveM, a model intercomparison was conducted using a dataset from an observational and experimental network of nine multi-year grassland sites spread across Europe (France, Italy, Germany, Switzerland, The Netherlands, and United Kingdom) and Israel, and a suite of nine models to understand grassland functioning in the region. Grassland-specific approaches were compared to approaches mainly conceived to simulate crops and plant functional types. Model evaluation against actual measurements was performed before and after model calibration. The calibrated models were used to analyze their sensitivity to independent variations of temperature, precipitation and [CO2]. The results show to which extent calibration can accommodate model discrepancies. The sensitivity of simulated gross primary production to [CO2] and temperature is an important outcome, considering the fundamental effect of rising temperature and [CO2] on the C cycling of terrestrial ecosystems in the Euro-Mediterranean region. Overall, alternative models exhibit a different sensitivity to climate change factors, with different performances over different conditions. Explained by the basic processes of each model and also induced by different calibration methods, this difference is indicative that more models can be complementary and deliver greater insights than if they were applied individually. No Label
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