| Home | << 1 2 3 4 5 6 7 8 9 10 >> [11–16] |
|
| Records | |||||
|---|---|---|---|---|---|
| Author | Nelson, G.C.; van der Mensbrugghe, D.; Ahammad, H.; Blanc, E.; Calvin, K.; Hasegawa, T.; Havlik, P.; Heyhoe, E.; Kyle, P.; Lotze-Campen, H.; von Lampe, M.; Mason, d’C., Daniel; van Meijl, H.; Müller, C.; Reilly, J.; Robertson, R.; Sands, R.D.; Schmitz, C.; Tabeau, A.; Takahashi, K.; Valin, H.; Willenbockel, D. | ||||
| Title | Agriculture and climate change in global scenarios: why don’t the models agree | Type | Journal Article | ||
| Year | 2014 | Publication | Agricultural Economics | Abbreviated Journal  |
Agric. Econ. |
| Volume | 45 | Issue | 1 | Pages | 85-85 |
| Keywords | climate change impacts; economic models of agriculture; scenarios; system model; demand; cmip5 | ||||
| Abstract | Agriculture is unique among economic sectors in the nature of impacts from climate change. The production activity that transforms inputs into agricultural outputs involves direct use of weather inputs (temperature, solar radiation available to the plant, and precipitation). Previous studies of the impacts of climate change on agriculture have reported substantial differences in outcomes such as prices, production, and trade arising from differences in model inputs and model specification. This article presents climate change results and underlying determinants from a model comparison exercise with 10 of the leading global economic models that include significant representation of agriculture. By harmonizing key drivers that include climate change effects, differences in model outcomes were reduced. The particular choice of climate change drivers for this comparison activity results in large and negative productivity effects. All models respond with higher prices. Producer behavior differs by model with some emphasizing area response and others yield response. Demand response is least important. The differences reflect both differences in model specification and perspectives on the future. The results from this study highlight the need to more fully compare the deep model parameters, to generate a call for a combination of econometric and validation studies to narrow the degree of uncertainty and variability in these parameters and to move to Monte Carlo type simulations to better map the contours of economic uncertainty. | ||||
| Address | 2016-10-31 | ||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Editor | |||
| Language | English | Summary Language | Original Title | ||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0169-5150 | ISBN | Medium | Article | |
| Area | Expedition | Conference | |||
| Notes | CropM, TradeM, ft_macsur | Approved | no | ||
| Call Number | MA @ admin @ | Serial | 4796 | ||
| Permanent link to this record | |||||
| Author | Nelson, G.C.; van der Mensbrugghe, D.; Ahammad, H.; Blanc, E.; Calvin, K.; Hasegawa, T.; Havlik, P.; Heyhoe, E.; Kyle, P.; Lotze-Campen, H.; von Lampe, M.; Mason, d’C., Daniel; van Meijl, H.; Müller, C.; Reilly, J.; Robertson, R.; Sands, R.D.; Schmitz, C.; Tabeau, A.; Takahashi, K.; Valin, H.; Willenbockel, D. | ||||
| Title | Agriculture and climate change in global scenarios: why don’t the models agree | Type | Journal Article | ||
| Year | 2014 | Publication | Agricultural Economics | Abbreviated Journal |
Agric. Econ. |
| Volume | 45 | Issue | 1 | Pages | 85-101 |
| Keywords | climate change impacts; economic models of agriculture; scenarios; system model; demand; CMIP5 | ||||
| Abstract | Agriculture is unique among economic sectors in the nature of impacts from climate change. The production activity that transforms inputs into agricultural outputs involves direct use of weather inputs (temperature, solar radiation available to the plant, and precipitation). Previous studies of the impacts of climate change on agriculture have reported substantial differences in outcomes such as prices, production, and trade arising from differences in model inputs and model specification. This article presents climate change results and underlying determinants from a model comparison exercise with 10 of the leading global economic models that include significant representation of agriculture. By harmonizing key drivers that include climate change effects, differences in model outcomes were reduced. The particular choice of climate change drivers for this comparison activity results in large and negative productivity effects. All models respond with higher prices. Producer behavior differs by model with some emphasizing area response and others yield response. Demand response is least important. The differences reflect both differences in model specification and perspectives on the future. The results from this study highlight the need to more fully compare the deep model parameters, to generate a call for a combination of econometric and validation studies to narrow the degree of uncertainty and variability in these parameters and to move to Monte Carlo type simulations to better map the contours of economic uncertainty. | ||||
| Address | |||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Editor | |||
| Language | English | Summary Language | Original Title | ||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0169-5150 | ISBN | Medium | Article | |
| Area | Expedition | Conference | |||
| Notes | CropM, TradeM, ft_macsur | Approved | no | ||
| Call Number | MA @ admin @ | Serial | 4536 | ||
| Permanent link to this record | |||||
| Author | Holman, I.P.; Brown, C.; Janes, V.; Sandars, D. | ||||
| Title | Can we be certain about future land use change in Europe? A multi-scenario, integrated-assessment analysis | Type | Journal Article | ||
| Year | 2017 | Publication | Agricultural Systems | Abbreviated Journal |
Agric. Syst. |
| Volume | 151 | Issue | Pages | 126-135 | |
| Keywords | Climate change, Socio-economic change, Impacts, Integrated assessment, Uncertainty; Climate-Change Impacts; Water-Based Sectors; North-West England; Socioeconomic Change; Change Vulnerability; East-Anglia; Adaptation; Policy; Uncertainties; Agriculture | ||||
| Abstract | The global land system is facing unprecedented pressures from growing human populations and climatic change. Understanding the effects these pressures may have is necessary to designing land management strategies that ensure food security, ecosystem service provision and successful climate mitigation and adaptation. However, the number of complex, interacting effects involved makes any complete understanding very difficult to achieve. Nevertheless, the recent development of integrated modelling frameworks allows for the exploration of the co-development of human and natural systems under scenarios of global change, potentially illuminating the main drivers and processes in future land system change. Here, we use one such integrated modelling framework (the CLIMSAVE Integrated Assessment Platform) to investigate the range of projected outcomes in the European land system across climatic and socio-economic scenarios for the 2050s. We find substantial consistency in locations and types of change even under the most divergent conditions, with results suggesting that climate change alone will lead to a contraction in the agricultural and forest area within Europe, particularly in southern Europe. This is partly offset by the introduction of socioeconomic changes that change both the demand for agricultural production, through changing food demand and net imports, and the efficiency of agricultural production. Simulated extensification and abandonment in the Mediterranean region is driven by future decreases in the relative profitability of the agricultural sector in southern Europe, owing to decreased productivity as a consequence of increased heat and drought stress and reduced irrigation water availability. The very low likelihood (<33% probability) that current land use proportions in many parts of Europe will remain unchanged suggests that future policy should seek to promote and support the multifunctional role of agriculture and forests in different European regions, rather than focusing on increased productivity as a route to agricultural and forestry viability. | ||||
| Address | 2017-02-23 | ||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | |||
| Notes | LiveM, TradeM, ft_MACSUR | Approved | no | ||
| Call Number | MA @ admin @ | Serial | 4937 | ||
| Permanent link to this record | |||||
| 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. |
||||
| Address | |||||
| 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 | ||
| Permanent link to this record | |||||
| Author | Ruiz-Ramos, M.; Ferrise, R.; Rodriguez, A.; Lorite, I.J.; Bindi, M.; Carter, T.R.; Fronzek, S.; Palosuo, T.; Pirttioja, N.; Baranowski, P.; Buis, S.; Cammarano, D.; Chen, Y.; Dumont, B.; Ewert, F.; Gaiser, T.; Hlavinka, P.; Hoffmann, H.; Hoehn, J.G.; Jurecka, F.; Kersebaum, K.C.; Krzyszczak, J.; Lana, M.; Mechiche-Alami, A.; Minet, J.; Montesino, M.; Nendel, C.; Porter, J.R.; Ruget, F.; Semenov, M.A.; Steinmetz, Z.; Stratonovitch, P.; Supit, I.; Tao, F.; Trnka, M.; de Wit, A.; Roetter, R.P. | ||||
| Title | Adaptation response surfaces for managing wheat under perturbed climate and CO2 in a Mediterranean environment | Type | Journal Article | ||
| Year | 2018 | Publication | Agricultural Systems | Abbreviated Journal |
Agric. Syst. |
| Volume | 159 | Issue | Pages | 260-274 | |
| Keywords | Wheat adaptation; Sensitivity analysis; Crop model ensemble; Rainfed, Mediterranean cropping system; AOCK concept; Iberian Peninsula; Simulation-Model; Change Impacts; Crop; Uncertainty; Ensemble; Europe; Yield; Productivity; Irrigation | ||||
| Abstract | Adaptation of crops to climate change has to be addressed locally due to the variability of soil, climate and the specific socio-economic settings influencing farm management decisions. Adaptation of rainfed cropping systems in the Mediterranean is especially challenging due to the projected decline in precipitation in the coming decades, which will increase the risk of droughts. Methods that can help explore uncertainties in climate projections and crop modelling, such as impact response surfaces (IRSs) and ensemble modelling, can then be valuable for identifying effective adaptations. Here, an ensemble of 17 crop models was used to simulate a total of 54 adaptation options for rainfed winter wheat (Triticum aestivum) at Lleida (NE Spain). To support the ensemble building, an ex post quality check of model simulations based on several criteria was performed. Those criteria were based on the “According to Our Current Knowledge” (AOCK) concept, which has been formalized here. Adaptations were based on changes in cultivars and management regarding phenology, vernalization, sowing date and irrigation. The effects of adaptation options under changed precipitation (P), temperature (T.),[CO2] and soil type were analysed by constructing response surfaces, which we termed, in accordance with their specific purpose, adaptation response surfaces (ARSs). These were created to assess the effect of adaptations through a range of plausible P, T and [CO2] perturbations. The results indicated that impacts of altered climate were predominantly negative. No single adaptation was capable of overcoming the detrimental effect of the complex interactions imposed by the P, T and [CO2] perturbations except for supplementary irrigation (sI), which reduced the potential impacts under most of the perturbations. Yet, a combination of adaptations for dealing with climate change demonstrated that effective adaptation is possible at Lleida. Combinations based on a cultivar without vernalization requirements showed good and wide adaptation potential. Few combined adaptation options performed well under rainfed conditions. However, a single sI was sufficient to develop a high adaptation potential, including options mainly based on spring wheat, current cycle duration and early sowing date. Depending on local environment (e.g. soil type), many of these adaptations can maintain current yield levels under moderate changes in T and P, and some also under strong changes. We conclude that ARSs can offer a useful tool for supporting planning of field level adaptation under conditions of high uncertainty. (C) 2017 Elsevier Ltd. All rights reserved. | ||||
| Address | 2018-01-25 | ||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Editor | |||
| Language | English | Summary Language | Original Title | ||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0308-521x | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | CropM, ft_macsur | Approved | no | ||
| Call Number | MA @ admin @ | Serial | 5184 | ||
| Permanent link to this record | |||||