Records |
Author |
van Lingen, H.J.; Plugge, C.M.; Fadel, J.G.; Kebreab, E.; Bannink, A.; Dijkstra, J. |
Title |
Correction: Thermodynamic Driving Force of Hydrogen on Rumen Microbial Metabolism: A Theoretical Investigation |
Type |
Miscellaneous |
Year |
2016 |
Publication |
PLoS One |
Abbreviated Journal |
PLoS One |
Volume |
11(12) |
Issue |
12 |
Pages |
e0168052 |
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Abstract |
[This corrects the article DOI: 10.1371/journal.pone.0161362.]. |
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1932-6203 |
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LiveM, ftnotmacsur |
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no |
Call Number |
MA @ admin @ |
Serial |
5020 |
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Author |
Kebreab, E.; Tedeschi, L.; Dijkstra, J.; Ellis, J.L.; Bannink, A.; France, J. |
Title |
Modeling Greenhouse Gas Emissions from Enteric Fermentation |
Type |
Book Chapter |
Year |
2016 |
Publication |
Advances in Agricultural Systems |
Abbreviated Journal |
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Volume |
6 |
Issue |
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Pages |
173-196 |
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Abstract |
Livestock directly contribute to greenhouse gas (GHG) emissions mainly through methane (CH4) and nitrous oxide (N2O) emissions. For cost and practicality reasons, quantification of GHG has been through development of various types of mathematical models. This chapter addresses the utility and limitations of mathematical models used to estimate enteric CH4 emissions from livestock production. Models used in GHG quantification can be broadly classified into either empirical or mechanistic models. Empirical models might be easier to use because they require fewer input variables compared with mechanistic models. However, their applicability in assessing mitigation options such as dietary manipulation may be limited. The major driving variables identified for both types of models include feed intake, lipid and nonstructural carbohydrate content of the feed, and animal variables. Knowledge gaps identified in empirical modeling were that some of the assumptions might not be valid because of geographical location, health status of animals, genetic differences, or production type. In mechanistic modeling, errors related to estimating feed intake, stoichiometry of volatile fatty acid (VFA) production, and acidity of rumen contents are limitations that need further investigation. Model prediction uncertainty was also investigated, and, depending on the intensity and source of the prediction uncertainty, the mathematical model may inaccurately predict the observed values with more or less variability. In conclusion, although there are quantification tools available, global collaboration is required to come to a consensus on quantification protocols. This can be achieved through developing various types of models specific to region, animal, and production type using large global datasets developed through international collaboration. |
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Kebreab, E. |
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Synthesis and Modeling of Greenhouse Gas Emissions and Carbon Storage in Agricultural and Forest Systems to Guide Mitigation and Adaptation |
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Series Volume |
Advances in Agricultural Systems (6) |
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Notes |
LiveM, ftnotmacsur |
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no |
Call Number |
MA @ admin @ |
Serial |
5032 |
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Author |
Scollan, N.; Bannink, A.; Kipling, R.; Saetnan, E.; Van Middelkoop, J. |
Title |
Livestock and feed production, especially dairy and beef |
Type |
Conference Article |
Year |
2015 |
Publication |
FACCE MACSUR Reports |
Abbreviated Journal |
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Volume |
6 |
Issue |
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Pages |
Sp6-3 |
Keywords |
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Abstract |
Improving health and welfare is an important adaptation and mitigation strategyDeveloping process based modelling, responsive to adaptationLinks to climate and land use change modelling are essential Livestock systems likely to be hit hardest by climate changeNeed to develop animal health models that respond to adaptation by farmersBringing together direct and indirect impacts of climate change vitalAdaptation and mitigation need to be considered and modelled togetherLinking models across scales is important to support policy decisionsLearning between sectors carries potential for novel solutions and methodological advancesEffective communication of outcomes to stakeholders (how?) No Label |
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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 |
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MA @ admin @ |
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2084 |
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