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Hutchings, N.; Kipling, R. |
Title |
Inventory of farm-scale models within LiveM |
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Report |
Year |
2014 |
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FACCE MACSUR Reports |
Abbreviated Journal |
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3 |
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D-L3.1 |
Keywords |
LiveM; |
Abstract |
The aim of WP3 is to improve the assessment of the impact of climate change on livestock and grassland systems at the farm-scale. The first step in this process is to understand the current state of the art in farm-scale modelling, and the resources available within the MACSUR knowledge hub. Here, an inventory of the farm-scale models available within LiveM is presented, along with a summary of the types of model represented. Thirteen farm-scale models were identified, three of which focus on environmental aspects of farm systems (GHG emissions etc.) and ten of which focus on management strategies (productivity, economics etc.). |
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MA @ admin @ |
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2064 |
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Hutchings, N.; Sanders, D.; Özkan, S.; De, H., Michel |
Title |
Farm model comparison |
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Conference Article |
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2014 |
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LiveM |
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International Livestock Modelling and Research Colloquium, Bilbao, Spain, 2014-10-14 to 2014-10-16 |
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MA @ admin @ |
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2497 |
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Hutchings, N.; Weindl, I.; Topp, C.F.E.; Snow, V.O.; Rotz, A.; Raynal, H.; Özkan Gülzari, Ş.; Martin, R.; Holzworth, D.P.; Graux, A.-I.; Faverdin, P.; Del Prado, A.; Eckard, R.; Bannink, A. |
Title |
Does collaborative farm-scale modelling address current challenges and future opportunities |
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Report |
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2017 |
Publication |
FACCE MACSUR Reports |
Abbreviated Journal |
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Volume |
10 |
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Pages |
L1.4-D2 |
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Resources required increasing, resources available decreasing Farm-scale modellers will need to make strategic decisions Single-owner models May continue with additional resources Risk of ‘succession’ problem Community modelling is an alternative Need to continue building a community of farm modellers |
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LiveM |
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MA @ admin @ |
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4978 |
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Author ![sorted by Author field, ascending order (up)](img/sort_asc.gif) |
Hutchings, N.J.; Özkan Gülzari, Ş.; de Haan, M.; Sandars, D. |
Title |
How do farm models compare when estimating greenhouse gas emissions from dairy cattle production |
Type |
Journal Article |
Year |
2018 |
Publication |
Animal |
Abbreviated Journal |
Animal |
Volume |
12 |
Issue |
10 |
Pages |
2171-2180 |
Keywords |
dairy cattle; farm-scale; model; greenhouse gas; Future Climate Scenarios; Systems-Analysis; Milk-Production; Crop; Production; Mitigation; Intensity; Impacts |
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The European Union Effort Sharing Regulation (ESR) will require a 30% reduction in greenhouse gas (GHG) emissions by 2030 compared with 2005 from the sectors not included in the European Emissions Trading Scheme, including agriculture. This will require the estimation of current and future emissions from agriculture, including dairy cattle production systems. Using a farm-scale model as part of a Tier 3 method for farm to national scales provides a more holistic and informative approach than IPCC (2006) Tier 2 but requires independent quality control. Comparing the results of using models to simulate a range of scenarios that explore an appropriate range of biophysical and management situations can support this process by providing a framework for placing model results in context. To assess the variation between models and the process of understanding differences, estimates of GHG emissions from four farm-scale models (DailyWise, FarmAC, HolosNor and SFARMMOD) were calculated for eight dairy farming scenarios within a factorial design consisting of two climates (cool/dry and warm/wet) x two soil types (sandy and clayey) x two feeding systems (grass only and grass/maize). The milk yield per cow, follower cow ratio, manure management system, nitrogen (N) fertilisation and land area were standardised for all scenarios in order to associate the differences in the results with the model structure and function. Potential yield and application of available N in fertiliser and manure were specified separately for grass and maize. Significant differences between models were found in GHG emissions at the farm-scale and for most contributory sources, although there was no difference in the ranking of source magnitudes. The farm-scale GHG emissions, averaged over the four models, was 10.6 t carbon dioxide equivalents (CO(2)e)/ha per year, with a range of 1.9 t CO(2)e/ha per year. Even though key production characteristics were specified in the scenarios, there were still significant differences between models in the annual milk production per ha and the amounts of N fertiliser and concentrate feed imported. This was because the models differed in their description of biophysical responses and feedback mechanisms, and in the extent to which management functions were internalised. We conclude that comparing the results of different farm-scale models when applied to a range of scenarios would build confidence in their use in achieving ESR targets, justifying further investment in the development of a wider range of scenarios and software tools. |
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2019-01-07 |
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English |
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1751-7311 |
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TradeM, ft_macsur |
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MA @ admin @ |
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5212 |
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Iocola, I. |
Title |
Past experience supports future choices for cropping systems management: the Italian long-term agro-ecosystem experiments (LTAEs) through the IC-FAR network |
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Book Whole |
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2017 |
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Ph.D. thesis |
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University of Sassari |
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Sassari |
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PhD |
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CropM |
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MA @ admin @ |
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5166 |
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