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Author |
Rötter, R.P. |
Title |
Cross-cutting uncertainties in MACSUR impact projections |
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Conference Article |
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2014 |
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Projections into the future, such as climate change impact projections on crop production for a given region, or, on global food prices and trade are inherently uncertain. Uncertainty does not fall within a single discipline but is dealt with by a wide variety of disciplines, themes and problem domains. Model uncertainty pertaining to the impact modelling chain from climate via crop and livestock to economic and trade modelling is only part of the overall uncertainty*. There is also scenario uncertainty and many other known and unknown “unknowns”1 to be considered in efforts such as MACSUR and its themes (CropM, LiveM, TradeM) to advance model-based integrated assessment of climate change risk assessment for agriculture and food security. Propagation of uncertainties along the climate change impact modelling chain has been portrayed as “uncertainty cascade” 2. We will present different basic approaches for evaluating uncertainty in models. So far, studies addressing quantification and reporting of uncertainties in impact projections still largely focus on two major sources, i.e. the shares originating from climate modelling and from crop modelling. However, a more comprehensive treatment of uncertainty and how it is reported is urgently needed. |
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FACCE MACSUR Mid-term Scientific Conference |
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3(S) Sassari, Italy |
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Conference ![sorted by Conference field, ascending order (up)](img/sort_asc.gif) |
FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
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MA @ admin @ |
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5069 |
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Havlik, P.; Leclere, D.; Valin, H.; Herrero, M.; Schmid, E.; Obersteiner, M. |
Title |
Effects of climate change on feed availability and the implications for the livestock sector |
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Conference Article |
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2014 |
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Global mean surface temperature is projected to rise by 0.4-2.6°C until 2050, and the contrast in precipitations between wet and dry regions and wet and dry seasons will also increase according to the IPCC 5th Assessment Report (2013). The climate change will impact livestock in many ways going from heat stress through livestock diseases to feed quality and availability (Thornton et al., 2009). Recently, projected climate change impacts on crop and grassland productivity became available with high spatial resolution at global scale through the AgMIP and ISI-MIP projects. The objective of this paper is to investigate how climate change impacts on crops and grassland will influence livestock production globally and its distribution across regions. This analysis is carried out using the global partial equilibrium agricultural and forestry sector model GLOBIOM (Havlík et al., 2013). The model represents agricultural production at a spatial resolution going down to 5 x 5 minutes of arc. Crop and grassland productivities are estimated by means of biophysical process based models (EPIC and CENTURY) at this resolution for current and future climate. Livestock representation follows a simplified version of the Seré and Steinfeld (1996) production system classification. This approach recognizes differences in feed base and productivities between grazing and mixed crop-livestock production systems across different agro-ecological zones (arid, humid, temperate/highlands). Our study highlights that the differential impacts of climate change on crop and grassland productivity will influence the relative competitiveness of different livestock production systems. Maintaining livestock production in some regions will depend on their capacity to adapt. Institutional and physical infrastructure will be needed to facilitate these transformations. |
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FACCE MACSUR Mid-term Scientific Conference |
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3(S) Sassari, Italy |
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Conference ![sorted by Conference field, ascending order (up)](img/sort_asc.gif) |
FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
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MA @ admin @ |
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5076 |
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Hoffmann, H.; Zhao, G.; Van Bussel, L.; Enders, A.; Specka, X.; Sosa, C.; Yeluripati, J.; Tao, F.; Constantin, J.; Teixeira, E.; Grosz, B.; Doro, L.; Nendel, C.; Kiese, R.; Raynal, H.; Eckersten, H.; Haas, E.; Kuhnert, M.; Lewan, E.; Bach, M.; Kersebaum, K.-C.; Roggero, P.P.; Rötter, R.; Wallach, D.; Krauss, G.; Siebert, S.; Gaiser, T.; Wang, E.; Zhao, Z.; Ewert, F. |
Title |
Effects of climate input data aggregation on modelling regional crop yields |
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Conference Article |
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2014 |
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Crop models can be sensitive to climate input data aggregation and this response may differ among models. This should be considered when applying field-scale models for assessment of climate change impacts on larger spatial scales or when coupling models across scales. In order to evaluate these effects systematically, an ensemble of ten crop models was run with climate input data on different spatial aggregations ranging from 1, 10, 25, 50 and 100 km horizontal resolution for the state of North Rhine-Westphalia, Germany. Models were minimally calibrated to typical sowing and harvest dates, and crop yields observed in the region, subsequently simulating potential, water-limited and nitrogen-limited production of winter wheat and silage maize for 1982-2011. Outputs were analysed for 19 variables (yield, evapotranspiration, soil organic carbon, etc.). In this study the sensitivity of the individual models and the model ensemble in response to input data aggregation is assessed for crop yield. Results show that the mean yield of the region calculated from climate time series of 1 km horizontal resolution changes only little when using climate input data of higher aggregation levels for most models. However, yield frequency distributions change with aggregation, resembling observed data better with increasing resolution. With few exceptions, these results apply to the two crops and three production situations (potential, water-, nitrogen-limited) and across models including the model ensemble, regardless of differences among models in simulated yield levels and spatial yield patterns. Results of this study improve the confidence of using crop models at varying scales. |
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FACCE MACSUR Mid-term Scientific Conference |
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3(S) Sassari, Italy |
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Conference ![sorted by Conference field, ascending order (up)](img/sort_asc.gif) |
FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
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Approved |
no |
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MA @ admin @ |
Serial |
5077 |
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Author |
Lehtonen, H.S.; Liu, X.; Purola, T.; Rötter, R.; Palosuo, T. |
Title |
Farm level dynamic economic modelling of crop rotation with adaptation practices |
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Conference Article |
Year |
2014 |
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Agriculture is facing increasing challenges under volatile commodity markets, on-going climate change with more frequent extreme weather events and tightened environmental constraints. Crop rotation is considered essential and may even gain more importance for sustainable farming in the context of climate change challenges while monocropping is expected to become increasingly problematic. This is, among others, because of increasing plant protection challenges due to warmer climate which is expected to result in severe droughts, heavy rainfall and waterlogging in northern latitudes more frequently. Such changes require improved soil structure and water retention, also aided by crop rotations, to avoid yield losses. Our objective is to build and apply a dynamic optimization model of farm level crop rotation on many field parcels over 30-40 years. The model takes into account various adaptation management methods such as fungicide treatment, soil improvements such as liming, and nitrogen fertilization, simultaneously with dynamic crop rotation choices. However, these management options come along with costs. Using the model, outcomes of crop growth simulation modeling can be included into economic analysis. Simulated new cultivars, suited for a longer growing season, can be defined as alternatives to current cultivars, both having specific nutrient and other input requirements such as water, labor or pesticides. The model is used in evaluating the value of future cultivars and other management practices in climate and socio-economic scenarios. The first results show that expected market prices have major impacts on the management choices, the resulting yield levels, production and income over time. |
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FACCE MACSUR Mid-term Scientific Conference |
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3(S) Sassari, Italy |
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Conference ![sorted by Conference field, ascending order (up)](img/sort_asc.gif) |
FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
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MA @ admin @ |
Serial |
5081 |
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Author |
Köchy, M.; Banse, M.; Tiffin, R.; Ewert, F.; Rötter, R.; Van den Pol-van Dasselaar, A.; Brouwer, F.; Sinabell, F.; Jorgenson, J.; Sætnan, E.; Kipling, R. |
Title |
General outline of plans for an extension phase of MACSUR |
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Conference Article |
Year |
2014 |
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FACCE MACSUR has indicated a possible extension of funding by two years until May 2017 (phase 2).For phase 2, hub and theme coordinators suggest the following main activities, that will be discussed during the remainder of the meeting and in the coming months.Evolution, upscaling, and transfer of knowledge gained in regional case studies.Assessment of additional scenarios of socio-economic and climate trends.Further development of an interdisciplinary scientific community.Extending scaling methods for crop models to the European and global scale.Intensification of feed quality and animal health modelling with climate change.Economic models from farm to global level capable of reflecting climate change. |
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Series Editor |
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Abbreviated Series Title |
FACCE MACSUR Mid-term Scientific Conference |
Series Volume |
3(S) Sassari, Italy |
Series Issue |
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Edition |
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ISSN |
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ISBN |
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Medium |
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Area |
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Expedition |
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Conference ![sorted by Conference field, ascending order (up)](img/sort_asc.gif) |
FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
Notes |
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Approved |
no |
Call Number |
MA @ admin @ |
Serial |
5084 |
Permanent link to this record |