FACCE MACSUR Reports (Modelling European Agriculture with Climate Change for Food Security)
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Evaluation of CERES Wheat and Rice Model for changing Climatic Conditions in Haryana, India
No full textThe simulation models with its soil-weather-plant atmosphere interacting system are important tools for assessing the crops in changing climate conditions. The CERES-Wheat & Rice vs. 4.6 DSSAT was calibrated and evaluated for one of major producers of wheat and rice state- Haryana, India. The simulation runs were made under irrigated conditions and three fertilizer applications dose of N-P-K to estimate crop yield and other growth parameters along with phenological development of the crop. The genetic coefficients derived by iteratively manipulating the relevant coefficients that characterize the phenological process of wheat and rice crop to best fit match between the simulated and observed anthesis, physiological maturity and final grain yield.The model validated by plotting the simulated and remote sensing derived Leaf Area Index (LAI). LAI product from remote sensing provides the edge of spatial, timely and accurate assessment of crop. For validating the yield and yield components, the error percentage between the observed and simulated data was calculated. The analysis shows that the model can be used to simulate crop yield and yield components for selected wheat and rice cultivar under different management practices. During the validation, the error percentage was less than 10%, indicating the utility of the calibrated model for climate risk assessment in the selected region
Can we be certain about future landuse change in Europe? A multi-scenario, integrated-assessment analysis
Full text linkThe global land system is facing unprecedented pressures from growing human populations and climatic change. However, the number of complex, interacting effects involved makes any complete understanding very difficult to achieve. Integrated modelling frameworks allows for the exploration of the co-development of human and natural systems under scenarios of global change. Here, we describe the use of one such integrated modelling framework (the CLIMSAVE Integrated Assessment Platform) to investigate the range of projected outcomes in the European land system across climatic and socio-economic scenarios for the 2050s. We demonstrate substantial consistency in locations and types of change even under the most divergent conditions, with results suggesting that climate change alone will lead to a contraction in the agricultural and forest area within Europe, particularly in southern Europe. This is partly offset by the introduction of socioeconomic changes that change both the demand for agricultural production, through changing food demand and net imports, and the efficiency of agricultural production. Sensitivity analysis of the land use change thresholds of between 0.1 and 25% within each grid cell demonstrates the robustness of the results. The very low likelihood (< 33% probability) that current land use proportions in many parts of Europe will remain unchanged suggests that future policy should seek to promote and support the multi-functional role of agriculture and forests in different European regions, rather than focusing on increased productivity as a route to agricultural and forestry viability
Impacts of Climate Change Adaptation Options in Agriculture on Soil Functions: Examples from European Case Studies
No full textSoil functions are fundamental for food security and for provision of ecosystem services for sustainable development. Climate change affects soil functions directly through changes in temperature, rainfall and moisture regimes, and indirectly via adapted management practices. While comprehensive evidence exists for the direct effects such as increased soil erosion risks, accelerated nutrient turnover and gas fluxes, less is known about how agricultural adaptation pathways may affect soil functions. The objective of this study was to analyze the evidence from European case studies about the possible impacts of climate change adaptations on soil threats and soil functions, and link soil functions to the Sustainable Development Goals (SDGs). We analyzed 20 regional case studies across Europe using Driver-Pressure-State-Impact-Response (DPSIR) framework. Our major findings were (1) adaptation pathways reflected local conditions, (2) reduced soil erosion threats and decelerated organic matter decline were anticipated in more than half of the cases, but soil compaction risks may increase in some areas, (3) the majority of adaptation pathways were expected to improve three soil functions, namely food and biomass production, carbon sequestration, and storing, filtering, transforming and recycling capacities, with little evidence about possible implications for soil biodiversity, (4) the linkage between soil functions and SDGs suggest improvements regarding SDG 2 (food security and sustainable agriculture) and SDG 13 (climate action), whereas SDG 15 (terrestrial ecosystems) requires attention. In conclusion: while direct climate change effects are expected to increase soil degradation, agricultural adaptation may counteract this process in many regions in Europe
Is a green tax on red meat a feasible strategy to achieve Norwegian GHG-emission targets for agriculture
Full text linkNorway has decided to follow the EU in setting ambitious targets for reducing greenhouse gas (GHG) emissions from agriculture. The aim is to reduce GHG-emissions by 40 per cent by 2030. The paper discusses three policy measures to achieve this target in Norway: Reduced direct payments to red meat (beef, sheep, and lamb), a consumption fee for red meat, and informational measures that align red meat consumption with official public health recommendations.The per capita consumption of red meat has shown a negative development in recent years. A continuation of that trend will positively contribute in the challenge to reach the emission target. However, there is currently a significant import of red meat that is expected to be reduced before domestic production eventually will fall.Model results based on the sector model Jordmod indicate that all policy options have significant effects on Norwegian agriculture. The current level of the EU carbon tax is used as a proxy for the reduced direct payments and the consumption fee. The implicit amount of 410 (820) nkr per ton CO2-equivalent translates into a reduction of between 5 (7) per cent and is far from achieving the 40 per cent target. The result is partly based on some stickiness in the model that prevents an immediate fall in production due to lower profitability. A moderate change in the diet from red meat to white meat follows from the implementation of the policies. The consumption fee and the reduced payments have, in principle, the same effect on agriculture. This result relies on the assumption that import protection is no longer prohibitive at a commodity basis, and only partially prohibitive at the processed food level
Challenges and research gaps in the area of integrated climate change risk assessment for European agriculture and food security
Full text linkPriorities in addressing research gaps and challenges should follow the order of importance, which in itself would be a matter of defining goals and metrics of importance, e.g. the extent, impact and likelihood of occurrence. For improving assessments of climate change impacts on agriculture for achieving food security and other sustainable development goals across the European continent, the most important research gaps and challenges appear to be the agreement on goals with a wide range of stakeholders from policy, science, producers and society, better reflection of political and societal preferences in the modelling process, and the reflection of economic decisions in farm management within models. These and other challenges could be approached in phase 3 of MACSUR
User co-design of state-of-the-art climate simulations: towards a better-informed agricultural sector
No full textSimulation of perennial ryegrass quality traits using PaSim in a breeding context
No full textForage quality is important for an efficient uptake and digestion by ruminants. Factors that may limit the animal's ability to reach production goals (high nutritional value of milk and meat) may include the forage's energy and protein content. Moreover, a balanced energy/protein feed can contribute to reduce greenhouse gas emissions from forage protein during digestion. Together with dry matter yield, several quality traits are used as selection criteria in breeding programs of perennial ryegrass (Lolium perenne L.). Though the different components of forage quality have a genetic basis, quality traits are strongly influenced by environmental conditions and their expression varies over the growing season. Consequently, the selection progress is often slow for quality traits because the appreciation of a candidate variety differs largely across years and locations.Modelling approaches can assist here. We refer to the vegetation module of the grassland model PaSim, which simulates different quality traits in response to growing conditions. We investigated whether PaSim can explain the variation in quality traits of candidate varieties of perennial ryegrass throughout the year, and whether model parameter values can be set to characterize each candidate variety.For that, we used a wide set of observations from 65 candidate varieties of the ILVO perennial ryegrass breeding program started in 2012. Observed data from five cutting events in 2013 include: dry matter yield, crude protein content, water soluble carbohydrate content, neutral detergent fiber content (NDF, i.e. cell wall content) and digestible neutral detergent fiber content (NDFD, i.e. cell wall digestibility). Dry matter yield data were also measured in 2014. Model parameter values were estimated for each candidate variety, based on observations and using the parameter optimization function of Package-FME–R Project.This allowed us assigning a set of parameter values to each candidate variety, which can now be evaluated in virtual experiments for a better appreciation of the candidate varieties
Effect of climate changes on plant disease under simulated conditions: challenges and limits
Full text linkIncreases in CO2 and temperatures are expected to induce complex effects on plant pathogens. Different approaches were used to study the effect of climate on plant diseases, including laboratory and/or field studies, as well as modeling-based assessments and simulations under phytotrons. During the last 10 years, the impact of climate changes such as increased CO2 and temperature on pathogens affecting grapevine, basil, rocket, beet, lettuce, zucchini, radish, bean and geranium was assessed under phytotrons. Plants were grown under different simulated climatic conditions, at standard (400-450 ppm), average (600 ppm) and high (800 ppm) CO2 concentration and at standard (ranging from 18 to 22/24°C) and elevated temperature (4°C higher than standard). Variable effects were observed when individual parameters were taken into consideration. An increase of downy mildew on grapes, of powdery mildew on zucchini, of Alternaria leaf spot on rocket salad, of black spot on basil and of Phoma leaf spot on garden beet was observed when both CO2 level and temperature increased. Powdery mildew of grape was not influenced by increasing carbon dioxide and temperature. Downy mildew of basil and rusts affecting bean and geranium increased at higher CO2 levels, but only at lower temperatures, while the combination of high CO2 and high temperature lead to a reduction of the diseases. Regarding the effects of climate changes on Fusarium wilt of lettuce and rocket, the soil fungal and bacterial development was not affected by the different CO2 and temperature levels, while an increasing disease incidence was observed at high CO2 and high temperature, probably through plant-mediated effects. The role of phytotrons in the study of climate changes is discussed
Representative Agricultural Pathways (RAPs) for Austria: conceptual thoughts on its demand and stakeholder-driven development.
No full textModelling communities in climate change research developed so-called Shared Socioeconomic Pathways (SSPs), which can be attributed to particular Representative Concentration Pathways (RCPs). SSPs are available at global to continental scales and describe major socio-economic developments. Such resolution is insufficient in particular for global to local mitigation, adaptation, and impact studies in agriculture. Hence, Representative Agricultural Pathways (RAPs) shall overcome this gap by developing narratives of plausible potential futures for the agricultural sector at regional to national scale. They should be consistent with SSPs and RCPs. These RAPs narratives are operationalized by variables and parameters usable in bio-physical and economic modeling of farms, landscapes and the agricultural and food sector.In our presentation, we argue that there is demand of RAPs in local to regional land use studies up to the national scale. RAPs contribute to increase the consistency of climate change studies across scales and enhance harmonization of inputs and comparability of results. They are a service to the research community to save resources in scenario development. In the second part of the talk, we present a methodology for a stakeholder-driven design of RAPs. We refer to methodologies for RAPs-development in international studies and identify necessary deviations to take into account idiosyncratic features of Austria, which is our country of interest. Stakeholder engagement during the definition of RAPs may improve the acceptance of modelling results among practitioners and foster its implementation in policy processes. Besides, the process itself can stimulate a debate on the future of agriculture under climate change and its inherent uncertainties
Assessment of soil and climate change data aggregation impact on crop yield simulation: from local to regional study in NRW, Germany
No full textThe soil and historic climate data aggregated at different scale has been applied in crop models to quantify aggregation impact on yield simulation and other model output variables in past studies. Here we have evaluated the aggregation effect of soil and future climate data sets (12 GCM - RCP scenarios) on yield simulation for the period of 2040-2070 and 2070-2100. The climate change data sets for North Rhine-Westphalia (NRW), Germany were spatially aggregated from 25 km grid cells to 50 km and 100 km. In contrast, the soil data for NRW was aggregated from 1km by selecting dominant soil type within the respective coarser grid cells (25 km, 50 km and 100 km). We have applied SIMPLACE, a crop modelling platform to simulate crop yield for winter wheat under water limited condition for all climate change scenarios. We found the application of aggregated soil and climate change data at 50 km and 100 km resolutions have simulated yield (winter wheat) differences from -6 to 4 ton ha-1 compared to yield simulated due to input data at higher resolution (25 km). Therefore, the application of coarser data (50 and 100 km) has higher impact on simulated yield difference at local level. In contrast, at the regional level for entire NRW, with input data (soil and climate) aggregated at 50 and 100 km the mean absolute simulated yield differences (bias) compared to 25 km (highest resolution data) were less than 2 ton ha-1. In addition, we found the annual variability of simulated yield was not significantly influenced by input data aggregated at coarser resolution. However, the impact assessment of aggregated data on yield simulation for other crops and regions by ensemble crop models could provide different range of aggregation effects than this stud