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Britz, W. |
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Title  |
Importance of considering crop management adaptation in CC impact studies: A Pan-European integrated assessment |
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2015 |
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FACCE MACSUR Reports |
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4 |
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SP4-4 |
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No abstract. No Label |
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TradeM International Workshop 2014 »Economics of integrated assessment approaches for agriculture and the food sector«, 25–27 November 2014, Hurdalsjø, Norway |
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no |
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MA @ admin @ |
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2194 |
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Author |
Liu, X. |
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Incentivising for climage change mitigation in the context of adaptation to climate and market changes at the farm level in North Savo region |
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2015 |
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FACCE MACSUR Reports |
Abbreviated Journal |
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4 |
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SP4-10 |
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Authors: Lehtonen, H., Liu, X. & Purola, T. No Label |
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TradeM International Workshop 2014 »Economics of integrated assessment approaches for agriculture and the food sector«, 25–27 November 2014, Hurdalsjø, Norway |
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no |
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MA @ admin @ |
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2200 |
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Heinschink et al. |
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Title |
Index-based costs of livestock production (INCAP.l) in Austria – the suckler cow and beef calf production activity |
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2016 |
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FACCE MACSUR Reports |
Abbreviated Journal |
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8 |
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SP8-1 |
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Conference presentation PDF |
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LiveM2016: International livestock modelling conference – Modelling grassland-livestock systems under climate change |
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no |
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MA @ admin @ |
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4846 |
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Rivington, M.; Wallach, D. |
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Title |
Information to support input data quality and model improvement |
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2015 |
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FACCE MACSUR Reports |
Abbreviated Journal |
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6 |
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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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no |
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MA @ admin @ |
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2103 |
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Author |
Menardo et al. |
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Title |
INNO Mil-CH4 GHG Emissions from Milk Production |
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2016 |
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FACCE MACSUR Reports |
Abbreviated Journal |
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8 |
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SP8-4 |
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Conference poster PDF |
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LiveM2016: International livestock modelling conference – Modelling grassland-livestock systems under climate change |
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no |
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Call Number |
MA @ admin @ |
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4845 |
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