| Records |
| Author |
Eyshi Rezaei, E.; Siebert, S.; Ewert, F. |
| Title |
Impact of data resolution on heat and drought stress simulated for winter wheat in Germany |
Type |
Journal Article |
| Year |
2015 |
Publication |
European Journal of Agronomy |
Abbreviated Journal |
European Journal of Agronomy |
| Volume |
65 |
Issue |
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Pages  |
69-82 |
| Keywords |
crop modeling; heat; drought; spatial resolution; wheat; high-temperature stress; climate-change; grain-yield; crop models; data aggregation; abiotic stress; short periods; variability; growth; duration |
| Abstract |
Heat and drought stress can reduce crop yields considerably which is increasingly assessed with crop models for larger areas. Applying these models originally developed for the field scale at large spatial extent typically implies the use of input data with coarse resolution. Little is known about the effect of data resolution on the simulated impact of extreme events like heat and drought on crops. Hence, in this study the effect of input and output data aggregation on simulated heat and drought stress and their impact on yield of winter wheat is systematically analyzed. The crop model SIMPLACE was applied for the period 1980-2011 across Germany at a resolution of 1 km x 1 km. Weather and soil input data and model output data were then aggregated to 10 km x 10 km, 25 km x 25 km, 50 km x 50 km and 100 km x 100 km resolution to analyze the aggregation effect on heat and drought stress and crop yield. We found that aggregation of model input and output data barely influenced the mean and median of heat and drought stress reduction factors and crop yields simulated across Germany. However, data aggregation resulted in less spatial variability of model results and a reduced severity of simulated stress events, particularly for regions with high heterogeneity in weather and soil conditions. Comparisons of simulations at coarse resolution with those at high resolution showed distinct patterns of positive and negative deviations which compensated each other so that aggregation effects for large regions were small for mean or median yields. Therefore, modelling at a resolution of 100 km x 100 km was sufficient to determine mean wheat yield as affected by heat and drought stress for Germany. Further research is required to clarify whether the results can be generalized across crop models differing in structure and detail. Attention should also be given to better understand the effect of data resolution on interactions between heat and drought impacts. (C) 2015 Elsevier B.V. All rights reserved. |
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English |
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1161-0301 |
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CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4751 |
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| Author |
Persson, T.; Kværnø, S.; Höglind, M. |
| Title |
Impact of soil type extrapolation on timothy grass yield under baseline and future climate conditions in southeastern Norway |
Type |
Journal Article |
| Year |
2015 |
Publication |
Climate Research |
Abbreviated Journal |
Clim. Res. |
| Volume |
65 |
Issue |
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Pages |
71-86 |
| Keywords |
climate change scenarios; crop modelling; forage grass; lingra; soil properties; spatial variability; phleum pretense; poaceae; simulation-model; nutritive-value; systems simulation; catimo model; crop models; growth; nitrogen; scale; productivity; regrowth |
| Abstract |
Interactions between soil properties and climate affect forage grass productivity. Dynamic models, simulating crop performance as a function of environmental conditions, are valid for a specific location with given soil and weather conditions. Extrapolations of local soil properties to larger regions can help assess the requirement for soil input in regional yield estimations. Using the LINGRA model, we simulated the regional yield level and variability of timothy, a forage grass, in Akershus and Ostfold counties, Norway. Soils were grouped according to physical similarities according to 4 sets of criteria. This resulted in 66, 15, 5 and 1 groups of soils. The properties of the soil with the largest area was extrapolated to the other soils within each group and input to the simulations. All analyses were conducted for 100 yr of generated weather representing the period 1961-1990, and climate projections for the period 2046-2065, the Intergovernmental Panel on Climate Change greenhouse gas emission scenario A1B, and 4 global climate models. The simulated regional seasonal timothy yields were 5-13% lower on average and had higher inter-annual variability for the least detailed soil extrapolation than for the other soil extrapolations, across climates. There were up to 20% spatial intra-regional differences in simulated yield between soil extrapolations. The results indicate that, for conditions similar to these studied here, a few representative profiles are sufficient for simulations of average regional seasonal timothy yield. More spatially detailed yield analyses would benefit from more detailed soil input. |
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0936-577x 1616-1572 |
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CropM, ft_macsur |
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no |
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MA @ admin @ |
Serial |
4674 |
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Biewald, A.; Lotze-Campen, H.; Otto, I.; Brinckmann, N.; Bodirsky, B.; Weindl, I.; Popp, A.; Schellnhuber, H.J. |
| Title |
The Impact of Climate Change on Costs of Food and People Exposed to Hunger at Subnational Scale |
Type |
Report |
| Year |
2015 |
Publication |
PIK Report |
Abbreviated Journal |
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| Volume |
128 |
Issue |
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Pages |
73 |
| Keywords |
ftnotmacsur |
| Abstract |
Climate change and socioeconomic developments will have a decisive impact on people exposed to hunger. This study analyses climate change impacts on agriculture and potential implications for the occurrence of hunger under different socioeconomic scenarios for 2030, focusing on the world regions most affected by poverty today: the Middle East and North Africa, South Asia, and Sub-Saharan Africa. We use a spatially explicit, agroeconomic land-use model to assess agricultural vulnerability to climate change. The aims of our study are to provide spatially explicit projections of climate change impacts on Costs of Food, and to combine them with spatially explicit hunger projections for the year 2030, both under a poverty, as well as a prosperity scenario. Our model results indicate that while average yields decrease with climate change in all focus regions, the impact on the Costs of Food is very diverse. Costs of Food increase most in the Middle East and North Africa, where available agricultural land is already fully utilized and options to import food are limited. The increase is least in Sub-Saharan Africa, since production there can be shifted to areas which are only marginally affected by climate change and imports from other regions increase. South Asia and Sub-Saharan Africa can partly adapt to climate change, in our model, by modifying trade and expanding agricultural land. In the Middle East and North Africa, almost the entire population is affected by increasing Costs of Food, but the share of people vulnerable to hunger is relatively low, due to relatively strong economic development in these projections. In Sub-Saharan Africa, the Vulnerability to Hunger will persist, but increases in Costs of Food are moderate. While in South Asia a high share of the population suffers from increases in Costs of Food and is exposed to hunger, only a negligible number of people will be exposed at extreme levels. Independent of the region, the impacts of climate change are less severe in a richer and more globalized world. Adverse climate impacts on the Costs of Food could be moderated by promoting technological progress in agriculture. Improving market access would be advantageous for farmers, providing the opportunity to profitably increase production in the Middle East and North Africa as well as in South Asia, but may lead to increasing Costs of Food for consumers. In the long-term perspective until 2080, the consequences of climate change will become even more severe: while in 2030 56% of the global population may face increasing Costs of Food in a poor and fragmented world, in 2080 the proportion will rise to 73%. |
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Potsdam |
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Potsdam-Institut für Klimafolgenforschung |
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TradeM |
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no |
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MA @ admin @ |
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5000 |
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| Author |
Mitter, H.; Heumesser, C.; Schmid, E. |
| Title |
Spatial modeling of robust crop production portfolios to assess agricultural vulnerability and adaptation to climate change |
Type |
Journal Article |
| Year |
2015 |
Publication |
Land Use Policy |
Abbreviated Journal |
Land Use Policy |
| Volume |
46 |
Issue |
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Pages |
75-90 |
| Keywords |
climate change impact; adaptation; agricultural vulnerability; portfolio optimization; agricultural policy; agri-environmental payment; adaptive capacity; change impacts; risk-aversion; land-use; ecosystem services; change scenarios; europe; policy; future; water |
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Agricultural vulnerability to climate change is likely to vary considerably between agro-environmental regions. Exemplified on Austrian cropland, we aim at (i) quantifying climate change impacts on agricultural vulnerability which is approximated by the indicators crop yields and gross margins, (ii) developing robust crop production portfolios for adaptation, and (iii) analyzing the effect of agricultural policies and risk aversion on the choice of crop production portfolios. We have employed a spatially explicit, integrated framework to assess agricultural vulnerability and adaptation. It combines a statistical climate change model for Austria and the period 2010-2040, a crop rotation model, the bio-physical process model EPIC (Environmental Policy Integrated Climate), and a portfolio optimization model. We find that under climate change, crop production portfolios include higher shares of intensive crop management practices, increasing average crop yields by 2-15% and expected gross margins by 3-18%, respectively. The results depend on the choice of adaptation measures and on the level of risk aversion and vary by region. In the semi-arid eastern parts of Austria, average dry matter crop yields are lower but gross margins are higher than in western Austria due to bio-physical and agronomic heterogeneities. An abolishment of decoupled farm payments and a threefold increase in agri-environmental premiums would reduce nitrogen inputs by 23-33%, but also crop yields and gross margins by 18-37%, on average. From a policy perspective, a twofold increase in agri-environmental premiums could effectively reduce the trade-offs between crop production and environmental impacts. (C) 2015 Elsevier Ltd. All rights reserved. |
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English |
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0264-8377 |
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TradeM, ft_macsur |
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no |
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MA @ admin @ |
Serial |
4675 |
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Lotze-Campen, H.; von Witzke, H.; Noleppa, S.; Schwarz, G. |
| Title |
Science for food, climate protection and welfare: An economic analysis of plant breeding research in Germany |
Type |
Journal Article |
| Year |
2015 |
Publication |
Agricultural Systems |
Abbreviated Journal |
Agric. Syst. |
| Volume |
136 |
Issue |
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Pages |
79-84 |
| Keywords |
Plant breeding; CO2 emissions; Cost–benefit analysis; Social rate of return; Agricultural research policy |
| Abstract |
Highlights • We analyze the economic effects of plant breeding research in Germany. • Effects of reduced CO2 emissions due to productivity increases are being quantified. • Expansion of global agricultural area has been reduced by 1–1.5 million ha. • CO2 emissions have been reduced by 160–235 million tons. • German plant breeding research has an economic value of 10.8–15.6 billion EUR. Abstract We analyze the economic effects of plant breeding research in Germany. In addition to market effects, for the first time also effects of reduced CO2 emissions due to productivity increases are being quantified. The analysis shows that investments in German plant breeding research in the period 1991–2010 have reduced the global expansion of agricultural area by 1–1.5 million hectares. This has led to reduced CO2 emissions of 160–235 million tons. The economic value generated by plant breeding research, through increased production and reduced greenhouse gas emissions, is estimated at 10.8–15.6 billion EUR in the same period. This can be translated into a social rate of return on research investment in the range of 40–80% per year. Projections for the period 2011–2030 generate a return rate in the range of 65–140% per year. Investments into plant breeding research in Germany are highly profitable from a societal point of view. At the same time, our results show significant under-investments in agricultural research in Germany. These results provide a good justification for policy-makers to reverse funding cuts for public agricultural research over the last decades and to improve institutional conditions for private research, e.g. through better protection of intellectual property rights. |
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0308521x |
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TradeM, ftnotmacsur |
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no |
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MA @ admin @ |
Serial |
4999 |
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