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Author  |
Rivington, M.; Wallach, D. |
| Title |
Information to support input data quality and model improvement |
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Report |
| Year |
2015 |
Publication |
FACCE MACSUR Reports |
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6 |
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Pages |
D-C4.2.4 |
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Data quality is a key factor in determining the quality of model estimates and hence a models’ overall utility. Good models run with poor quality explanatory variables and parameters will produce meaningless estimates. Many models are now well developed and have been shown to perform well where and when good quality data is available. Hence a major limitation now to further use of models in new locations and applications is likely to be the availability of good quality data. Improvements in the quality of data may be seen as the starting point of further model improvement, in that better data itself will lead to more accurate model estimates (i.e. through better calibration), and it will facilitate reduction of model residual error by enabling refinements to model equations. This report sets out why data quality is important as well as the basis for additional investment in improving data quality. No Label |
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MA @ admin @ |
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2103 |
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| Author |
Rivington, M.; Wallach, D. |
| Title |
Communication strategy, including design of tools for more effective communication of uncertainty |
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Report |
| Year |
2015 |
Publication |
FACCE MACSUR Reports |
Abbreviated Journal |
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6 |
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Pages |
D-C4.1.4 |
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Communication is the key link between the generation of information by MACSUR about the uncertainty of climate change impacts on future food security and how information is used by decision makers. It is therefore important to make available the common tools for reporting uncertainty, with a discussion of the advantages or difficulties of each. That is the purpose of this report. No Label |
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no |
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MA @ admin @ |
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2099 |
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Roggero, P.P. |
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Oristano, Sardinia, Italy: Winners and losers from climate change in agriculture: a case study in the Mediterranean basin |
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Conference Article |
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2015 |
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6 |
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Sp6-7 |
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CropM |
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Focus questions • How to support effective adaptive responses to CC and stimulate proactive attitudes of farmers, policymakers & researchers? • How to co-construct the nature of the issues about CC adaptation? The «Oristanese» case study • Very diversified agricultural district in a Mediterranean context o Irrigated and rainfed farming systems o Variety of cropping systems, intensity levels, farm size • Multiple stakeholders o Cooperative agro-food system o Producers’ organizations (rice, horticulture) o Variety of extensive pastoral systems Emerging outcome • The dairy cattle coop is developing a new win-win pathway linking hi-input dairy cattle farming with low input beef cattle grazing systems • The local government is investing in the EIP for supporting the local beef production chain to reduce meat imports and enhance pasture biodiversity and ecosystem services (eg wildfire prevention) Emerging challenges Adaptive responses as co-evolution pathways • design social learning spaces for researchers, stakeholders and policy makers • combining integrated assessment modeling and social learning facilitation |
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Brussels |
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Climate-change impacts on farming systems in the next decades — why worry when you have CAP? A FACCE MACSUR workshop for policymakers, 2015-05-06 to 2015-05-06, Brussels |
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no |
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MA @ admin @ |
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2750 |
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Roggero, P.P.; Matthews, R. |
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Strategies for engagement on adaptation and mitigation with national and EU policy makers and with the agro--food chain sector (Update) |
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Report |
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2015 |
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FACCE MACSUR Reports |
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6 |
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D-C6.3 |
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This report is grounded on the hypotheses, methodologies and approaches for stakeholder mapping designed during the early stages of MACSUR and described in the previous report1. It describes the kind of activities conducted by the WPC6-3-4 MACSUR team and the emerging design of activities for the second phase of MACSUR (2015-2017). The designed process of strategic stakeholder mapping was implemented by some of the teams involved in the task and through hub initiatives. Key actions were the (i) development of suitable intermediary objects to engage with stakeholders, through the regional pilot case studies, (ii) the design and implementation of key events (we report here the case of the Agroscenari event at the case study scale, the national event between the MACSUR Italian partnership with Italian policy makers held in Rome in July 2014, the international stakeholder events at the MACSUR mid term meeting in Sassari (April 2014), and the one held in Bruxelles on 6 May 2015) and (iii) the process of stakeholder and stakeholding mapping at the case study scale. Results indicate that when dealing with high level stakeholders (e.g. institutional or large agro-food enterprises), occasional stakeholder events will only serve as opportunity for showcasing and possibly for a data collection useful for researchers, with almost no impact on the ongoing social learning process sought by the designed activities. At the case study scale, instead, the long term and ongoing activities can generate new spaces for mutual learning and knowledge hybridization, through a variety of mediating objects emerging from the continuous interactions. The lesson learned is that the engagement of high level stakeholders can be effective insofar they are somehow involved in the interactions with stakeholders at the case study scale, as this can provide a key experience leading to a change in understanding about the nature of the issues that can ultimately result into a change in practice. These results will be the basis for the design of new strategies for engaging EU policy makers and large agro-food energy representatives in the second phase of MACSUR. No Label |
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MA @ admin @ |
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2107 |
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Rolinski, S.; Weindl, I.; Heinke, J.; Bodirsky, B.L.; Biewald, A.; Lotze-Campen, H. |
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Pasture harvest, carbon sequestration and feeding potentials under different grazing intensities |
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Journal Article |
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2015 |
Publication |
Advances in Animal Biosciences |
Abbreviated Journal |
Advances in Animal Biosciences |
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6 |
Issue |
01 |
Pages |
43-45 |
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global dynamic vegetation model; LPJmL; grasslands; livestock production |
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English |
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CropM, LiveM, ft_macsur |
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no |
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MA @ admin @ |
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4541 |
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