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Author | Schönhart, M.; Schauppenlehner, T.; Kuttner, M.; Kirchner, M.; Schmid, E. | ||||
Title | Climate change impacts on farm production, landscape appearance, and the environment: Policy scenario results from an integrated field-farm-landscape model in Austria | Type | Journal Article | ||
Year | 2016 | Publication | Agricultural Systems | Abbreviated Journal | Agricultural Systems |
Volume | 145 | Issue | Pages | 39-50 | |
Keywords | Integrated land use modeling; Climate change impacts; Mitigation; Adaptation; Field-farm-landscape; Environment; agricultural landscapes; land-use; netherlands; adaptation; indicators; management; responses | ||||
Abstract | Climate change is among the major drivers of agricultural land use change and demands autonomous farm adaptation as well as public mitigation and adaptation policies. In this article, we present an integrated land use model (ILM) mainly combining a bio-physical model and a bio-economic farm model at field, farm and landscape levels. The ILM is applied to a cropland dominated landscape in Austria to analyze impacts of climate change and mitigation and adaptation policy scenarios on farm production as well as on the abiotic environment and biotic environment. Changes in aggregated total farm gross margins from three climate change scenarios for 2040 range between + 1% and + 5% without policy intervention” and compared to a reference situation under the current climate. Changes in aggregated gross margins are even higher if adaptation policies are in place. However, increasing productivity from climate change leads to deteriorating environmental conditions such as declining plant species richness and landscape appearance. It has to be balanced by mitigation and adaptation policies taking into account effects from the considerable spatial heterogeneity such as revealed by the ILM. (C) 2016 Elsevier Ltd. All rights reserved. | ||||
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Language | English | Summary Language | Original Title | ||
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ISSN | 0308-521x | ISBN | Medium | Article | |
Area | Expedition | Conference | |||
Notes | CropM, TradeM, ft_macsur | Approved | no | ||
Call Number | MA @ admin @ | Serial | 4767 | ||
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Author | Siebert, S.; Webber, H.; Zhao, G.; Ewert, F.; Siebert, S.; Webber, H.; Zhao, G.; Ewert, F. | ||||
Title | Heat stress is overestimated in climate impact studies for irrigated agriculture | Type | Journal Article | ||
Year | 2017 | Publication | Environmental Research Letters | Abbreviated Journal | Environ. Res. Lett. |
Volume | 12 | Issue | 5 | Pages | 054023 |
Keywords | heat stress; climate change impact assessment; irrigation; canopy temperature; CANOPY TEMPERATURE; WINTER-WHEAT; WATER-STRESS; CROP YIELDS; GROWTH; MAIZE; DROUGHT; UNCERTAINTY; ENVIRONMENT; PHENOLOGY | ||||
Abstract | Climate change will increase the number and severity of heat waves, and is expected to negatively affect crop yields. Here we show for wheat and maize across Europe that heat stress is considerably reduced by irrigation due to surface cooling for both current and projected future climate. We demonstrate that crop heat stress impact assessments should be based on canopy temperature because simulations with air temperatures measured at standard weather stations cannot reproduce differences in crop heat stress between irrigated and rainfed conditions. Crop heat stress was overestimated on irrigated land when air temperature was used with errors becoming larger with projected climate change. Corresponding errors in mean crop yield calculated across Europe for baseline climate 1984-2013 of 0.2 Mg yr(-1) (2%) and 0.6 Mg yr(-1) (5%) for irrigated winter wheat and irrigated grain maize, respectively, would increase to up to 1.5 Mg yr (1) (16%) for irrigated winter wheat and 4.1 Mg yr (1) (39%) for irrigated grain maize, depending on the climate change projection/GCM combination considered. We conclude that climate change impact assessments for crop heat stress need to account explicitly for the impact of irrigation. | ||||
Address | 2017-06-22 | ||||
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Publisher | Place of Publication | Editor | |||
Language | English | Summary Language | Original Title | ||
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Series Volume | Series Issue | Edition | |||
ISSN | 1748-9326 | ISBN | Medium | ||
Area | Expedition | Conference | |||
Notes | CropM, ft_macsur | Approved | no | ||
Call Number | MA @ admin @ | Serial | 5035 | ||
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Author | Webber, H.; White, J.W.; Kimball, B.A.; Ewert, F.; Asseng, S.; Rezaei, E.E.; Pinter, P.J., Jr.; Hatfield, J.L.; Reynolds, M.P.; Ababaei, B.; Bindi, M.; Doltra, J.; Ferrise, R.; Kage, H.; Kassie, B.T.; Kersebaum, K.-C.; Luig, A.; Olesen, J.E.; Semenov, M.A.; Stratonovitch, P.; Ratjen, A.M.; LaMorte, R.L.; Leavitt, S.W.; Hunsaker, D.J.; Wall, G.W.; Martre, P. | ||||
Title | Physical robustness of canopy temperature models for crop heat stress simulation across environments and production conditions | Type | Journal Article | ||
Year | 2018 | Publication | Field Crops Research | Abbreviated Journal | Field Crops Research |
Volume | 216 | Issue | Pages | 75-88 | |
Keywords | Heat stress; Crop model improvement; Heat and drought interactions; Climate change impact assessments; Canopy temperature; Wheat; Air CO2 Enrichment; Elevated Carbon-Dioxide; Water-Use Efficiency; Climate-Change; Wheat Evapotranspiration; Stomatal Conductance; Multimodel Ensembles; Farming Systems; Drought-Stress; Spring Wheat | ||||
Abstract | Despite widespread application in studying climate change impacts, most crop models ignore complex interactions among air temperature, crop and soil water status, CO2 concentration and atmospheric conditions that influence crop canopy temperature. The current study extended previous studies by evaluating Tc simulations from nine crop models at six locations across environmental and production conditions. Each crop model implemented one of an empirical (EMP), an energy balance assuming neutral stability (EBN) or an energy balance correcting for atmospheric stability conditions (EBSC) approach to simulate Tc. Model performance in predicting Tc was evaluated for two experiments in continental North America with various water, nitrogen and CO2 treatments. An empirical model fit to one dataset had the best performance, followed by the EBSC models. Stability conditions explained much of the differences between modeling approaches. More accurate simulation of heat stress will likely require use of energy balance approaches that consider atmospheric stability conditions. | ||||
Address | 2018-02-19 | ||||
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Language | English | Summary Language | Original Title | ||
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ISSN | 0378-4290 | ISBN | Medium | Article | |
Area | Expedition | Conference | |||
Notes | CropM, ft_macsur | Approved | no | ||
Call Number | MA @ admin @ | Serial | 5189 | ||
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Author | Semenov, M.A.; Stratonovitch, P. | ||||
Title | Designing high-yielding wheat ideotypes for a changing climate | Type | Journal Article | ||
Year | 2013 | Publication | Food and Energy Security | Abbreviated Journal | Food Energy Secur. |
Volume | 2 | Issue | 3 | Pages | 185-196 |
Keywords | Climate change impacts; crop modeling; LARS-WG; Sirius; wheat | ||||
Abstract | Global warming is characterized by shifts in weather patterns and increases in climatic variability and extreme events. New wheat cultivars will be required for a rapidly changing environment, putting severe pressure on breeders who must select for climate conditions which can only be predicted with a great degree of uncertainty. To assist breeders to identify key wheat traits for improvements under climate change, wheat ideotypes can be designed and tested in silico using a wheat simulation model for a wide range of future climate scenarios predicted by global climate models. A wheat ideotype is represented by a set of cultivar parameters in a model, which could be optimized for best wheat performance under projected climate change. As an example, high-yielding wheat ideotypes were designed at two contrasting European sites for the 2050 (A1B) climate scenario. Simulations showed that wheat yield potential can be substantially increased for new ideotypes compared with current wheat varieties under climate change. The main factors contributing to yield increase were improvement in light conversion efficiency, extended duration of grain filling resulting in a higher harvest index, and optimal phenology. | ||||
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Language | English | Summary Language | Original Title | ||
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ISSN | 2048-3694 | ISBN | Medium | Article | |
Area | Expedition | Conference | |||
Notes | CropM, ft_macsur | Approved | no | ||
Call Number | MA @ admin @ | Serial | 4505 | ||
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Author | Challinor, A.J.; Müller, C.; Asseng, S.; Deva, C.; Nicklin, K.J.; Wallach, D.; Vanuytrecht, E.; Whitfield, S.; Ramirez-Villegas, J.; Koehler, A.-K. | ||||
Title | Improving the use of crop models for risk assessment and climate change adaptation | Type | Journal Article | ||
Year | 2017 | Publication | Agricultural Systems | Abbreviated Journal | Agric. Syst. |
Volume | 159 | Issue | Pages | 296-306 | |
Keywords | Crop model; Risk assessment; Climate change impacts; Adaptation; Climate models; Uncertainty | ||||
Abstract | Highlights • 14 criteria for use of crop models in assessments of impacts, adaptation and risk • Working with stakeholders to identify timing of risks is key to risk assessments. • Multiple methods needed to critically assess the use of climate model output • Increasing transparency and inter-comparability needed in risk assessments Abstract Crop models are used for an increasingly broad range of applications, with a commensurate proliferation of methods. Careful framing of research questions and development of targeted and appropriate methods are therefore increasingly important. In conjunction with the other authors in this special issue, we have developed a set of criteria for use of crop models in assessments of impacts, adaptation and risk. Our analysis drew on the other papers in this special issue, and on our experience in the UK Climate Change Risk Assessment 2017 and the MACSUR, AgMIP and ISIMIP projects. The criteria were used to assess how improvements could be made to the framing of climate change risks, and to outline the good practice and new developments that are needed to improve risk assessment. Key areas of good practice include: i. the development, running and documentation of crop models, with attention given to issues of spatial scale and complexity; ii. the methods used to form crop-climate ensembles, which can be based on model skill and/or spread; iii. the methods used to assess adaptation, which need broadening to account for technological development and to reflect the full range options available. The analysis highlights the limitations of focussing only on projections of future impacts and adaptation options using pre-determined time slices. Whilst this long-standing approach may remain an essential component of risk assessments, we identify three further key components: 1. Working with stakeholders to identify the timing of risks. What are the key vulnerabilities of food systems and what does crop-climate modelling tell us about when those systems are at risk? 2. Use of multiple methods that critically assess the use of climate model output and avoid any presumption that analyses should begin and end with gridded output. 3. Increasing transparency and inter-comparability in risk assessments. Whilst studies frequently produce ranges that quantify uncertainty, the assumptions underlying these ranges are not always clear. We suggest that the contingency of results upon assumptions is made explicit via a common uncertainty reporting format; and/or that studies are assessed against a set of criteria, such as those presented in this paper. |
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Corporate Author | Thesis | ||||
Publisher | Place of Publication | Editor | |||
Language | Summary Language | phase 2+ | Original Title | ||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 0308521x | ISBN | Medium | ||
Area | CropM | Expedition | Conference | ||
Notes | CropM, ft_macsur | Approved | no | ||
Call Number | MA @ admin @ | Serial | 5175 | ||
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