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Author  |
Mittenzwei, K.; Persson, T.; Höglind, M.; Kværnø, S. |
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Title |
Combined effects of climate change and policy uncertainty on the agricultural sector in Norway |
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Journal Article |
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Year |
2017 |
Publication |
Agricultural Systems |
Abbreviated Journal |
Agric. Syst. |
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Volume |
153 |
Issue |
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Pages |
118-126 |
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Keywords |
Climate change; Norway; Agriculture; Policy uncertainty; Modelling; LINGRA; CSM-CERES-Wheat; DSSAT |
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Abstract |
Highlights • A framework to study climate and policy uncertainty in agriculture is presented. • Combining both sources of uncertainty has ambiguous effects on agriculture. • Uncertainty needs to be highlighted in modelling tools for policy analysis. Abstract Farmers are exposed to climate change and uncertainty about how that change will develop. As farm incomes, in Norway and elsewhere, greatly depend on government subsidies, the risk of a policy change constitutes an additional uncertainty source. Hence, climate and policy uncertainty could substantially impact agricultural production and farm income. However, these sources of uncertainty have, so far, rarely been combined in food production analyses. The aim of this study was to determine the effects of a combination of policy and climate uncertainty on agricultural production, land use, and social welfare in Norway. Output yield distributions of spring wheat and timothy, a major forage grass, from simulations with the weather-driven crop models, CSM-CERES-Wheat and, LINGRA, were processed in the a stochastic version Jordmod, a price-endogenous spatial economic sector model of the Norwegian agriculture. To account for potential effects of climate uncertainty within a given future greenhouse gas emission scenario on farm profitability, effects on conditions that represented the projected climate for 2050 under the emission scenario A1B from the 4th assessment report of the Intergovernmental Panel on Climate Change and four Global Climate Models (GCM) was investigated. The uncertainty about the level of payment rates at the time farmers make their management decisions was handled by varying the distribution of payment rates applied in the Jordmod model. These changes were based on the change in the overall level of agricultural support in the past. Three uncertainty scenarios were developed and tested: one with climate change uncertainty, another with payment rate uncertainty, and a third where both types of uncertainty were combined. The three scenarios were compared with results from a deterministic scenario where crop yields and payment rates were constant. Climate change resulted in on average 9% lower cereal production, unchanged grass production and more volatile crop yield as well as 4% higher farm incomes on average compared to the deterministic scenario. The scenario with a combination of climate change and policy uncertainty increased the mean farm income more than a scenario with only one source of uncertainty. On the other hand, land use and farm labour were negatively affected under these conditions compared to the deterministic case. Highlighting the potential influence of climate change and policy uncertainty on the performance of the farm sector our results underline the potential error in neglecting either of these two uncertainties in studies of agricultural production, land use and welfare. |
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0308521x |
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CropM, TradeM |
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MA @ admin @ |
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4986 |
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Author |
Montesino-San Martín, M.; Olesen, J.E.; Porter, J.R. |
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Title |
Can crop-climate models be accurate and precise? A case study for wheat production in Denmark |
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Journal Article |
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Year |
2015 |
Publication |
Agricultural and Forest Meteorology |
Abbreviated Journal |
Agricultural and Forest Meteorology |
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Volume |
202 |
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51-60 |
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Uncertainty; Model intercomparison; Bayesian approach; Climate change; Wheat; Denmark; uncertainty analysis; simulation-models; bayesian-approach; change; impact; yields; variability; projections; scale; calibration; framework |
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Crop models, used to make projections of climate change impacts, differ greatly in structural detail. Complexity of model structure has generic effects on uncertainty and error propagation in climate change impact assessments. We applied Bayesian calibration to three distinctly different empirical and mechanistic wheat models to assess how differences in the extent of process understanding in models affects uncertainties in projected impact. Predictive power of the models was tested via both accuracy (bias) and precision (or tightness of grouping) of yield projections for extrapolated weather conditions. Yields predicted by the mechanistic model were generally more accurate than the empirical models for extrapolated conditions. This trend does not hold for all extrapolations; mechanistic and empirical models responded differently due to their sensitivities to distinct weather features. However, higher accuracy comes at the cost of precision of the mechanistic model to embrace all observations within given boundaries. The approaches showed complementarity in sensitivity to weather variables and in accuracy for different extrapolation domains. Their differences in model precision and accuracy make them suitable for generic model ensembles for near-term agricultural impact assessments of climate change. |
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0168-1923 |
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CropM, ftnotmacsur |
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MA @ admin @ |
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4572 |
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Montesino-San Martín, M.; Olesen, J.E.; Porter, J.R. |
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Title |
A genotype, environment and management (GxExM) analysis of adaptation in winter wheat to climate change in Denmark |
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Journal Article |
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Year |
2014 |
Publication |
Agricultural and Forest Meteorology |
Abbreviated Journal |
Agricultural and Forest Meteorology |
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187 |
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1-13 |
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Winter wheat; Climate change; Adaptation; Uncertainty; Europe; food security; model hadgem1; physical-properties; regional climate; change impacts; field-scale; land-use; yield; nitrogen; variability |
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Wheat yields in Europe have shown stagnating trends during the last two decades, partly attributed to climate change. Such developments challenge the needs for increased production, in particular at higher latitudes, to meet increasing global demands and expected productivity reductions at lower latitudes. Climate change projections from three General Circulation Models or GCMs (UKMO-HadGEM1, INM-GM3.0 and CSIRO-Mk3.1) for the A1FI SIZES emission scenario for 2000 to 2100 were downscaled at a northern latitude location (Foulum, Denmark) using LARS-WG5.3. The scenarios accounted for changes in temperature, precipitation and atmospheric CO2 concentration. In addition, three temperature-variability scenarios were included assuming different levels of decreased temperature variability in winter and increased in summer. Crop yield was simulated for the different climate change scenarios by a calibrated version of AFRCWHEAT2 to model several combinations of genotypes (varying in crop growth, development and tolerance to water and nitrogen scarcity) and management (sowing dates and nitrogen fertilization rate). The simulations showed a slight improvement of grain yields (0.3-1.2 Mg ha(-1)) in the medium-term (2030-2050), but not enough to cope with expected increases in demand for food and feed. Optimum management added up to 1.8 Mg ha(-1). Genetic modifications regarding winter wheat crop development exhibit the greatest sensitivity to climate and larger potential for improvement (+3.8 Mg ha(-1)). The results consistently points towards need for cultivars with a longer reproductive phases (2.9-7.5% per 1 degrees C) and lower photoperiod sensitivities. Due to the positive synergies between several genotypic characteristics, multiple-target breeding programmes would be necessary, possibly assisted by model-based assessments of optimal phenotypic characteristics. |
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0168-1923 |
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CropM, ftnotmacsur |
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MA @ admin @ |
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4630 |
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Moraru, P.I.; Rusu, T.; Guș, P.; Bogdan, I.; Pop, A.I. |
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Title |
The role of minimum tillage in protecting environmental resources of the Transylvanian Plain, Romania |
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Journal Article |
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2015 |
Publication |
Romanian Agricultural Research |
Abbreviated Journal |
Romanian Agricultural Research |
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32 |
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127-135 |
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minimum tillage; soil conservation; crop production; winter-wheat; systems; maize; conservation; temperature; yield; l. |
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Abstract |
Conservative tillage systems tested in the hilly area of the Transylvanian Plain (Romania), confirms the possibility of improving the biological, physical, chemical and technologizcal properties of the soil. Conservative components include minimum tillage systems and surface incorporation of crop residues. The minimum tillage soil systems with paraplow, chisel or rotary harrow are polyvalent alternatives for basic preparation, germination bed preparation and sowing, for fields and crops with moderate loose requirements being optimized technologies for: soil natural fertility activation and rationalization, reduction of erosion, increasing the accumulation capacity for water and realization of sowing in the optimal period. The minimum tillage systems ensure an adequate aerial-hydrical regime for the biological activity intensity and for the nutrients solubility equilibrium. The vegetal material remaining at the soil surface or superficially incorporated has its contribution to intensifying the biological activity, being an important resource of organic matter. Humus content increases by 0.41%. The minimum tillage systems rebuild the soil structure (hydrostable macroagregate content increases up to 2.2% to 5.2%), improving the global drainage of soil which allows a rapid infiltration of water in soil. Water reserve, accumulated in the 0-50 cm depth is with 1-32 m(3) ha(-1) higher in the minimum tillage variants. The result is a more productive soil, better protected against wind and water erosion and needing less fuel for preparing the germination bed. |
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2016-10-31 |
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1222-4227 |
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CropM, ftnotmacsur |
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MA @ admin @ |
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4795 |
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Author |
Müller, C.; Robertson, R.D. |
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Title |
Projecting future crop productivity for global economic modeling |
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Journal Article |
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2014 |
Publication |
Agricultural Economics |
Abbreviated Journal |
Agric. Econ. |
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45 |
Issue |
1 |
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37-50 |
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climate change; crop modeling; agricultural productivity; land use; greenhouse-gas emissions; soil organic-carbon; sub-saharan africa; climate-change; elevated co2; land-use; system model; wheat yields; maize yields; agriculture |
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Assessments of climate change impacts on agricultural markets and land-use patterns rely on quantification of climate change impacts on the spatial patterns of land productivity. We supply a set of climate impact scenarios on agricultural land productivity derived from two climate models and two biophysical crop growth models to account for some of the uncertainty inherent in climate and impact models. Aggregation in space and time leads to information losses that can determine climate change impacts on agricultural markets and land-use patterns because often aggregation is across steep gradients from low to high impacts or from increases to decreases. The four climate change impact scenarios supplied here were designed to represent the most significant impacts (high emission scenario only, assumed ineffectiveness of carbon dioxide fertilization on agricultural yields, no adjustments in management) but are consistent with the assumption that changes in agricultural practices are covered in the economic models. Globally, production of individual crops decrease by 10-38% under these climate change scenarios, with large uncertainties in spatial patterns that are determined by both the uncertainty in climate projections and the choice of impact model. This uncertainty in climate impact on crop productivity needs to be considered by economic assessments of climate change. |
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0169-5150 |
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CropM, TradeM, ft_macsur |
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MA @ admin @ |
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4533 |
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