| Records |
| Author |
Mandryk, M.; Reidsma, P.; Kanellopoulos, A.; Groot, J.C.J.; van Ittersum, M.K. |
| Title |
The role of farmers’ objectives in current farm practices and adaptation preferences: a case study in Flevoland, the Netherlands |
Type |
Journal Article |
| Year |
2014 |
Publication |
Regional Environmental Change |
Abbreviated Journal |
Reg Environ Change |
| Volume |
14 |
Issue |
4 |
Pages |
1463-1478 |
| Keywords |
multi-criteria decision-making; multi-objective optimization; agriculture; arable farm; vegetable farms; climate-change; south uruguay; land-use; design; agriculture; model; management; options; systems |
| Abstract |
The diversity in farmers’ objectives and responses to external drivers is usually not considered in integrated assessment studies that investigate impacts and adaptation to climate and socio-economic change. Here, we present an approach to assess how farmers’ stated objectives relate to their currently implemented practices and to preferred adaptation options, and we discuss what this implies for assessments of future changes. We based our approach on a combination of multi-criteria decision-making methods. We consistently assessed the importance of farmers’ objectives and adaptation preferences from what farmers say (based on interviews), from what farmers actually do (by analysing current farm performance) and from what farmers want (through a selected alternative farm plan). Our study was performed for six arable farms in Flevoland, a province in the Netherlands. Based on interviews with farmers, we reduced the long list of possible objectives to the most important ones. The objectives we assessed included maximization of economic result and soil organic matter, and minimization of gross margin variance, working hours and nitrogen balance. In our sample, farmers’ stated preferences in objectives were often not fully reflected in realized farming practices. Adaptation preferences of farmers largely resembled their current performance, but generally involved a trend towards stated preferences. Our results suggest that in Flevoland, although farmers do have more objectives, in practical decision-making they focus on economic result maximization, while for strategic decision-making they account for objectives influencing long-term performance and indicators associated with sustainability, in this case soil organic matter. |
| Address |
2016-10-31 |
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| Language |
English |
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Edition |
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| ISSN |
1436-3798 1436-378x |
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Article |
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| Notes |
CropM |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4794 |
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| Author |
Rötter, R.P.; Tao, F.; Höhn, J.G.; Palosuo, T. |
| Title |
Use of crop simulation modelling to aid ideotype design of future cereal cultivars |
Type |
Journal Article |
| Year |
2015 |
Publication |
Journal of Experimental Botany |
Abbreviated Journal |
J. Experim. Bot. |
| Volume |
66 |
Issue |
12 |
Pages |
3463-3476 |
| Keywords |
Breeding/*methods; Climate Change; *Computer Simulation; Ecotype; Edible Grain/*growth & development; *Models, Theoretical; cereals; climate extremes; crop growth simulation; ensemble modelling; future cultivars; genetic modelling; ideotype breeding; model improvement; model-aided design |
| Abstract |
A major challenge of the 21st century is to achieve food supply security under a changing climate and roughly a doubling in food demand by 2050 compared to present, the majority of which needs to be met by the cereals wheat, rice, maize, and barley. Future harvests are expected to be especially threatened through increased frequency and severity of extreme events, such as heat waves and drought, that pose particular challenges to plant breeders and crop scientists. Process-based crop models developed for simulating interactions between genotype, environment, and management are widely applied to assess impacts of environmental change on crop yield potentials, phenology, water use, etc. During the last decades, crop simulation has become important for supporting plant breeding, in particular in designing ideotypes, i.e. ‘model plants’, for different crops and cultivation environments. In this review we (i) examine the main limitations of crop simulation modelling for supporting ideotype breeding, (ii) describe developments in cultivar traits in response to climate variations, and (iii) present examples of how crop simulation has supported evaluation and design of cereal cultivars for future conditions. An early success story for rice demonstrates the potential of crop simulation modelling for ideotype breeding. Combining conventional crop simulation with new breeding methods and genetic modelling holds promise to accelerate delivery of future cereal cultivars for different environments. Robustness of model-aided ideotype design can further be enhanced through continued improvements of simulation models to better capture effects of extremes and the use of multi-model ensembles. |
| Address |
2016-10-31 |
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English |
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| ISSN |
0022-0957 1460-2431 |
ISBN |
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Medium |
Review |
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| Notes |
CropM, ft_macsur |
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no |
| Call Number |
MA @ admin @ |
Serial |
4804 |
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| Author |
Sieber, S.; Amjath-Babu, T.S.; McIntosh, B.S.; Tscherning, K.; Müller, K.; Helming, K.; Pohle, D.; Fricke, K.; Verweij, P.; Pacini, C.; Jansson, T.; Gomez y Paloma, S. |
| Title |
Evaluating the characteristics of a non-standardised Model Requirements Analysis (MRA) for the development of policy impact assessment tools |
Type |
Journal Article |
| Year |
2013 |
Publication |
Environmental Modelling & Software |
Abbreviated Journal |
Env. Model. Softw. |
| Volume |
49 |
Issue |
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Pages |
53-63 |
| Keywords |
impact assessment tools; iat; siat; sustainability; model requirements analysis; user requirement analysis; support; systems; design; methodology; management; decision; science |
| Abstract |
The aim of this paper is to provide a critical analysis of the strengths and weaknesses of a non-standardised Model Requirements Analysis (MRA) used for the purpose of developing the Sustainability Impact Assessment Tool (SIAT). By ‘non-standardised’ we mean not strictly following a published MRA method. The underlying question we are interested in addressing is how non-standardised methods, often employed in research driven projects, compare to defined methods with more standardised structure, with regards their ability to capture model requirements effectively, and with regards their overall usability. Through describing and critically assessing the specific features of the non-standardised MRA employed, the ambition of this paper is to provide insights useful for impact assessment tool (IAT) development. Specifically, the paper will (i) characterise kinds of user requirements relevant to the functionality and design of IATs; (ii) highlight the strengths and weaknesses of non-standardised MRA for user requirements capture, analysis and reflection in the context of IAT; (iii) critically reflect on the process and outcomes of having used a non-standardised MRA in comparison with other more standardised approaches. To accomplish these aims, we first review methods available for IAT development before describing the SIAT development process, including the MRA employed. Major strengths and weaknesses of the MRA method are then discussed in terms of user identification and characterisation, organisational characterisation and embedding, and ability to capture design options for ensuring usability and usefulness. A detailed assessment on the structural differences of MRA with two advanced approaches (Integrated DSS design and goal directed design) and their role in performance of the MRA tool is used to critique the approach employed. The results show that MRA is able to bring thematic integration, establish system performance and technical thresholds as well as detailing quality and transparency guidelines. Nevertheless the discussion points out to a number of deficiencies in application – (i) a need to more effectively characterise potential users, and; (ii) a need to better foster communication among the distinguished roles in the development process. If addressed these deficiencies, SIAT non-standardised MRA could have brought out better outcomes in terms of tool usability and usefulness, and improved embedding of the tool into conditions of targeted end-users. (C) 2013 Elsevier Ltd. All rights reserved. |
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English |
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Edition |
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| ISSN |
1364-8152 |
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Article |
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| Notes |
TradeM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4506 |
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| Author |
Stratonovitch, P.; Semenov, M.A. |
| Title |
Heat tolerance around flowering in wheat identified as a key trait for increased yield potential in Europe under climate change |
Type |
Journal Article |
| Year |
2015 |
Publication |
Journal of Experimental Botany |
Abbreviated Journal |
J. Experim. Bot. |
| Volume |
66 |
Issue |
12 |
Pages |
3599-3609 |
| Keywords |
Adaptation, Physiological; *Climate Change; Computer Simulation; Europe; Flowers/*physiology; *Hot Temperature; *Quantitative Trait, Heritable; Time Factors; Triticum/*growth & development/*physiology; Downscaling; LARS-WG weather generator; Sirius wheat model.; heat stress; ideotype design; impact assessment |
| Abstract |
To deliver food security for the 9 billon population in 2050, a 70% increase in world food supply will be required. Projected climatic and environmental changes emphasize the need for breeding strategies that delivers both a substantial increase in yield potential and resilience to extreme weather events such as heat waves, late frost, and drought. Heat stress around sensitive stages of wheat development has been identified as a possible threat to wheat production in Europe. However, no estimates have been made to assess yield losses due to increased frequency and magnitude of heat stress under climate change. Using existing experimental data, the Sirius wheat model was refined by incorporating the effects of extreme temperature during flowering and grain filling on accelerated leaf senescence, grain number, and grain weight. This allowed us, for the first time, to quantify yield losses resulting from heat stress under climate change. The model was used to optimize wheat ideotypes for CMIP5-based climate scenarios for 2050 at six sites in Europe with diverse climates. The yield potential for heat-tolerant ideotypes can be substantially increased in the future (e.g. by 80% at Seville, 100% at Debrecen) compared with the current cultivars by selecting an optimal combination of wheat traits, e.g. optimal phenology and extended duration of grain filling. However, at two sites, Seville and Debrecen, the grain yields of heat-sensitive ideotypes were substantially lower (by 54% and 16%) and more variable compared with heat-tolerant ideotypes, because the extended grain filling required for the increased yield potential was in conflict with episodes of high temperature during flowering and grain filling. Despite much earlier flowering at these sites, the risk of heat stress affecting yields of heat-sensitive ideotypes remained high. Therefore, heat tolerance in wheat is likely to become a key trait for increased yield potential and yield stability in southern Europe in the future. |
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English |
Summary Language |
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0022-0957 1460-2431 |
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| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4578 |
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| Author |
Watson, J.; Challinor, A.J.; Fricker, T.E.; Ferro, C.A.T. |
| Title |
Comparing the effects of calibration and climate errors on a statistical crop model and a process-based crop model |
Type |
Journal Article |
| Year |
2015 |
Publication |
Climatic Change |
Abbreviated Journal |
Clim. Change |
| Volume |
132 |
Issue |
1 |
Pages |
93-109 |
| Keywords |
maize; yield; ensemble; impacts; design; heat |
| Abstract |
Understanding the relationship between climate and crop productivity is a key component of projections of future food production, and hence assessments of food security. Climate models and crop yield datasets have errors, but the effects of these errors on regional scale crop models is not well categorized and understood. In this study we compare the effect of synthetic errors in temperature and precipitation observations on the hindcast skill of a process-based crop model and a statistical crop model. We find that errors in temperature data have a significantly stronger influence on both models than errors in precipitation. We also identify key differences in the responses of these models to different types of input data error. Statistical and process-based model responses differ depending on whether synthetic errors are overestimates or underestimates. We also investigate the impact of crop yield calibration data on model skill for both models, using datasets of yield at three different spatial scales. Whilst important for both models, the statistical model is more strongly influenced by crop yield scale than the process-based crop model. However, our results question the value of high resolution yield data for improving the skill of crop models; we find a focus on accuracy to be more likely to be valuable. For both crop models, and for all three spatial scales of yield calibration data, we found that model skill is greatest where growing area is above 10-15 %. Thus information on area harvested would appear to be a priority for data collection efforts. These results are important for three reasons. First, understanding how different crop models rely on different characteristics of temperature, precipitation and crop yield data allows us to match the model type to the available data. Second, we can prioritize where improvements in climate and crop yield data should be directed. Third, as better climate and crop yield data becomes available, we can predict how crop model skill should improve. |
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English |
Summary Language |
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Abbreviated Series Title |
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Series Issue |
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Edition |
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0165-0009 1573-1480 |
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Article |
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| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4546 |
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