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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. |
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Title |
Improving the use of crop models for risk assessment and climate change adaptation |
Type |
Journal Article |
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Year |
2017 |
Publication |
Agricultural Systems |
Abbreviated Journal |
Agric. Syst. |
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Volume |
159 |
Issue |
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Pages  |
296-306 |
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Keywords |
Crop model; Risk assessment; Climate change impacts; Adaptation; Climate models; Uncertainty |
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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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phase 2+ |
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0308521x |
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CropM |
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CropM, ft_macsur |
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no |
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Call Number |
MA @ admin @ |
Serial |
5175 |
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Author |
Mitter, H.; Schoenhart, M.; Larcher, M.; Schmid, E. |
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Title |
The Stimuli-Actions-Effects-Responses (SAER)-framework for exploring perceived relationships between private and public climate change adaptation in agriculture |
Type |
Journal Article |
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Year |
2018 |
Publication |
Journal of Environmental Management |
Abbreviated Journal |
J. Environ. Manage. |
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Volume |
209 |
Issue |
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Pages |
286-300 |
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Keywords |
Climate change perception; Private adaptation, Public adaptation; Qualitative analysis; Adaptation stimulus; Adaptation effect; Transformational Adaptation; Adapting Agriculture; Farmers Perceptions; Change Scenarios; Decision-Making; Change Impacts; Land-Use; Vulnerability; Framework; Science |
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Abstract |
Empirical findings on actors’ roles and responsibilities in the climate change adaptation process are rare even though cooperation between private and public actors is perceived important to foster adaptation in agriculture. We therefore developed the framework SAER (Stimuli-Actions-Effects-Responses) to investigate perceived relationships between private and public climate change adaptation in agriculture at regional scale. In particular, we explore agricultural experts’ perceptions on (i) climatic and non climatic factors stimulating private adaptation, (ii) farm adaption actions, (iii) potential on-farm and off-farm effects from adaptation, and (iv) the relationships between private and public adaptation. The SAER-framework is built on a comprehensive literature review and empirical findings from semi structured interviews with agricultural experts from two case study regions in Austria. We find that private adaptation is perceived as incremental, systemic or transformational. It is typically stimulated by a mix of bio-physical and socio-economic on-farm and off-farm factors. Stimulating factors related to climate change are perceived of highest relevance for systemic and transformational adaptation whereas already implemented adaptation is mostly perceived to be incremental. Perceived effects of private adaptation are related to the environment, weather and climate, quality and quantity of agricultural products as well as human, social and economic resources. Our results also show that public adaptation can influence factors stimulating private adaptation as well as adaptation effects through the design and development of the legal, policy and organizational environment as well as the provision of educational, informational, financial, and technical infrastructure. Hence, facilitating existing and new collaborations between private and public actors may enable farmers to adapt effectively to climate change. (C) 2018 Elsevier Ltd. All rights reserved. |
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2018-03-02 |
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0301-4797 |
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TradeM, ft_macsur |
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Call Number |
MA @ admin @ |
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5192 |
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Author |
Lorite, I.J.; Gabaldon-Leal, C.; Ruiz-Ramos, M.; Belaj, A.; de la Rosa, R.; Leon, L.; Santos, C. |
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Title |
Evaluation of olive response and adaptation strategies to climate change under semi-arid conditions |
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Journal Article |
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Year |
2018 |
Publication |
Agricultural Water Management |
Abbreviated Journal |
Agric. Water Manage. |
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Volume |
204 |
Issue |
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Pages |
247-261 |
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Keywords |
Irrigation requirements; Yield; Irrigation water productivity; Olive; Climate change; Olea-Europaea L.; Different Irrigation Regimes; Water Deficits; Iberian; Peninsula; CO2 Concentration; Potential Growth; Atmospheric CO2; Southern Spain; Change Impacts; River-Basin |
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AdaptaOlive is a simplified physically-based model that has been developed to assess the behavior of olive under future climate conditions in Andalusia, southern Spain. The integration of different approaches based on experimental data from previous studies, combined with weather data from 11 climate models, is aimed at overcoming the high degree of uncertainty in the simulation of the response of agricultural systems under predicted climate conditions. The AdaptaOlive model was applied in a representative olive orchard in the Baeza area, one of the main producer zone in Spain, with the cultivar ‘Picual’. Simulations for the end of the 21st century showed olive oil yield increases of 7.1 and 28.9% under rainfed and full irrigated conditions, respectively, while irrigation requirements decreased between 0.5 and 6.2% for full irrigation and regulated deficit irrigation, respectively. These effects were caused by the positive impact of the increase in atmospheric CO2 that counterbalanced the negative impacts of the reduction in rainfall. The high degree of uncertainty associated with climate projections translated into a high range of yield and irrigation requirement projections, confirming the need for an ensemble of climate models in climate change impact assessment. The AdaptaOlive model also was applied for evaluating adaptation strategies related to cultivars, irrigation strategies and locations. The best performance was registered for cultivars with early flowering dates and regulated deficit irrigation. Thus, in the Baeza area full irrigation requirements were reduced by 12% and the yield in rainfed conditions increased by 7% compared with late flowering cultivars. Similarly, regulated deficit irrigation requirements and yield were reduced by 46% and 18%, respectively, compared with full irrigation. The results confirm the promise offered by these strategies as adaptation measures for managing an olive crop under semi-arid conditions in a changing climate. |
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2018-06-28 |
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0378-3774 |
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CropM, ft_macsur |
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MA @ admin @ |
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5204 |
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Author |
Lehtonen, H. |
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Title |
Evaluating adaptation and the production development of Finnish agriculture in climate and global change |
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Journal Article |
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Year |
2015 |
Publication |
Agricultural and Food Science |
Abbreviated Journal |
Agricultural and Food Science |
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24 |
Issue |
3 |
Pages |
219-234 |
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Keywords |
agricultural sector modelling; economic adjustment; global prices; climate change; finnish agriculture; crop production; land-use; challenge; ensembles; Finland; Europe; policy |
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Abstract |
Agricultural product prices and policies influence the development of crop yields under climate change through farm level management decisions. On this basis, five main scenarios were specified for agricultural commodity prices and crop yields. An economic agricultural sector model was used in order to assess the impacts of the scenarios on production, land use and farm income in Finland. The results suggest that falling crop yields, if realized due to low prices and restrictive policies, will result in decreasing crop and livestock production and increasing nutrient surplus. Slowly increasing crop yields could stabilise production and increase farm income. Significantly higher crop prices and yields are required, however, for any marked increase in production in Finland. Cereals production would increase relatively more than livestock production, if there were high prices for agricultural products. This is explained by abundant land resources, a high opportunity cost of labour and policies maintaining current dairy and beef production. |
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2016-07-22 |
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1459-6067 |
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TradeM, ft_macsur |
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MA @ admin @ |
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4750 |
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Fronzek, S.; Pirttioja, N.; Carter, T.R.; Bindi, M.; Hoffmann, H.; Palosuo, T.; Ruiz-Ramos, M.; Tao, F.; Trnka, M.; Acutis, M.; Asseng, S.; Baranowski, P.; Basso, B.; Bodin, P.; Buis, S.; Cammarano, D.; Deligios, P.; Destain, M.-F.; Dumont, B.; Ewert, F.; Ferrise, R.; Francois, L.; Gaiser, T.; Hlavinka, P.; Jacquemin, I.; Kersebaum, K.C.; Kollas, C.; Krzyszczaki, J.; Lorite, I.J.; Minet, J.; Ines Minguez, M.; Montesino, M.; Moriondo, M.; Mueller, C.; Nendel, C.; Ozturk, I.; Perego, A.; Rodriguez, A.; Ruane, A.C.; Ruget, F.; Sanna, M.; Semenov, M.A.; Slawinski, C.; Stratonovitch, P.; Supit, I.; Waha, K.; Wang, E.; Wu, L.; Zhao, Z.; Rotter, R.P. |
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Title |
Classifying multi-model wheat yield impact response surfaces showing sensitivity to temperature and precipitation change |
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Journal Article |
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Year |
2018 |
Publication |
Agricultural Systems |
Abbreviated Journal |
Agric. Syst. |
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Volume |
159 |
Issue |
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Pages |
209-224 |
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Keywords |
Classification; Climate change; Crop model; Ensemble; Sensitivity analysis; Wheat; Climate-Change; Crop Models; Probabilistic Assessment; Simulating; Impacts; British Catchments; Uncertainty; Europe; Productivity; Calibration; Adaptation |
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Abstract |
Crop growth simulation models can differ greatly in their treatment of key processes and hence in their response to environmental conditions. Here, we used an ensemble of 26 process-based wheat models applied at sites across a European transect to compare their sensitivity to changes in temperature (-2 to +9 degrees C) and precipitation (-50 to +50%). Model results were analysed by plotting them as impact response surfaces (IRSs), classifying the IRS patterns of individual model simulations, describing these classes and analysing factors that may explain the major differences in model responses. The model ensemble was used to simulate yields of winter and spring wheat at four sites in Finland, Germany and Spain. Results were plotted as IRSs that show changes in yields relative to the baseline with respect to temperature and precipitation. IRSs of 30-year means and selected extreme years were classified using two approaches describing their pattern. The expert diagnostic approach (EDA) combines two aspects of IRS patterns: location of the maximum yield (nine classes) and strength of the yield response with respect to climate (four classes), resulting in a total of 36 combined classes defined using criteria pre-specified by experts. The statistical diagnostic approach (SDA) groups IRSs by comparing their pattern and magnitude, without attempting to interpret these features. It applies a hierarchical clustering method, grouping response patterns using a distance metric that combines the spatial correlation and Euclidian distance between IRS pairs. The two approaches were used to investigate whether different patterns of yield response could be related to different properties of the crop models, specifically their genealogy, calibration and process description. Although no single model property across a large model ensemble was found to explain the integrated yield response to temperature and precipitation perturbations, the application of the EDA and SDA approaches revealed their capability to distinguish: (i) stronger yield responses to precipitation for winter wheat than spring wheat; (ii) differing strengths of response to climate changes for years with anomalous weather conditions compared to period-average conditions; (iii) the influence of site conditions on yield patterns; (iv) similarities in IRS patterns among models with related genealogy; (v) similarities in IRS patterns for models with simpler process descriptions of root growth and water uptake compared to those with more complex descriptions; and (vi) a closer correspondence of IRS patterns in models using partitioning schemes to represent yield formation than in those using a harvest index. Such results can inform future crop modelling studies that seek to exploit the diversity of multi-model ensembles, by distinguishing ensemble members that span a wide range of responses as well as those that display implausible behaviour or strong mutual similarities. |
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2018-01-25 |
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0308-521x |
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CropM, ft_macsur |
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Call Number |
MA @ admin @ |
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5186 |
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