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description Publicationkeyboard_double_arrow_right Article , Journal , Other literature type 2018 Netherlands, France, Australia, FrancePublisher:Elsevier BV Pierre J. Gerber; Pierre J. Gerber; Timothy P. Robinson; Alessandra Falcucci; Benjamin B. Henderson; Henning Steinfeld; C. Opio; G. Tempio; Michael MacLeod; Harinder P. S. Makkar; Theun Vellinga; Anne Mottet;The livestock sector is one of the fastest growing subsectors of the agricultural economy and, while it makes a major contribution to global food supply and economic development, it also consumes significant amounts of natural resources and alters the environment. In order to improve our understanding of the global environmental impact of livestock supply chains, the Food and Agriculture Organization of the United Nations has developed the Global Livestock Environmental Assessment Model (GLEAM). The purpose of this paper is to provide a review of GLEAM. Specifically, it explains the model architecture, methods and functionality, that is the types of analysis that the model can perform. The model focuses primarily on the quantification of greenhouse gases emissions arising from the production of the 11 main livestock commodities. The model inputs and outputs are managed and produced as raster data sets, with spatial resolution of 0.05 decimal degrees. The Global Livestock Environmental Assessment Model v1.0 consists of five distinct modules: (a) the Herd Module; (b) the Manure Module; (c) the Feed Module; (d) the System Module; (e) the Allocation Module. In terms of the modelling approach, GLEAM has several advantages. For example spatial information on livestock distributions and crops yields enables rations to be derived that reflect the local availability of feed resources in developing countries. The Global Livestock Environmental Assessment Model also contains a herd model that enables livestock statistics to be disaggregated and variation in livestock performance and management to be captured. Priorities for future development of GLEAM include: improving data quality and the methods used to perform emissions calculations; extending the scope of the model to include selected additional environmental impacts and to enable predictive modelling; and improving the utility of GLEAM output.
CGIAR CGSpace (Consu... arrow_drop_down CGIAR CGSpace (Consultative Group on International Agricultural Research)Article . 2018License: CC BY NC NDFull-Text: https://hdl.handle.net/10568/90511Data sources: Bielefeld Academic Search Engine (BASE)The University of Queensland: UQ eSpaceArticle . 2018Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1017/s1751731117001847&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 57 citations 57 popularity Top 1% influence Top 10% impulse Top 10% Powered by BIP!
more_vert CGIAR CGSpace (Consu... arrow_drop_down CGIAR CGSpace (Consultative Group on International Agricultural Research)Article . 2018License: CC BY NC NDFull-Text: https://hdl.handle.net/10568/90511Data sources: Bielefeld Academic Search Engine (BASE)The University of Queensland: UQ eSpaceArticle . 2018Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1017/s1751731117001847&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal , Other literature type 2021 Italy, Netherlands, Sweden, United KingdomPublisher:Elsevier BV Kipling, R.P.; Bannink, A.; Bartley, D.J.; Blanco-Penedo, I.; Faverdin, P.; Graux, A.I.; Hutchings, N.J.; Kyriazakis, I.; Macleod, M.; Østergaard, S.; Robinson, T.P.; Vitali, A.; Ahmadi, B.V.; Özkan, Seyda;Improved animal health can reduce greenhouse gas (GHG) emissions intensity in livestock systems while increasing productivity. Integrated modelling of disease impacts on farm-scale emissions is important in identifying effective health strategies to reduce emissions. However, it requires that modellers understand the pathways linking animal health to emissions and how these might be incorporated into models. A key barrier to meeting this need has been the lack of a framework to facilitate effective exchange of knowledge and data between animal health experts and emissions modellers. Here, these two communities engaged in workshops, online exchanges and a survey to i) identify a comprehensive list of disease-related model parameters and ii) test its application to evaluating models. Fifty-six parameters were identified and proved effective in assessing the potential of farm-scale models to characterise livestock disease impacts on GHG emissions. Easy wins for the emissions models surveyed include characterising disease impacts related to feeding.
SLU publication data... arrow_drop_down Wageningen Staff PublicationsArticle . 2021License: CC BYData sources: Wageningen Staff PublicationsQueen's University Belfast Research PortalArticle . 2021Data sources: Bielefeld Academic Search Engine (BASE)Università degli studi della Tuscia: Unitus DSpaceArticle . 2021Data sources: Bielefeld Academic Search Engine (BASE)Università degli studi della Tuscia: Unitus DSpaceArticle . 2021Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.animal.2020.100023&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 9 citations 9 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
more_vert SLU publication data... arrow_drop_down Wageningen Staff PublicationsArticle . 2021License: CC BYData sources: Wageningen Staff PublicationsQueen's University Belfast Research PortalArticle . 2021Data sources: Bielefeld Academic Search Engine (BASE)Università degli studi della Tuscia: Unitus DSpaceArticle . 2021Data sources: Bielefeld Academic Search Engine (BASE)Università degli studi della Tuscia: Unitus DSpaceArticle . 2021Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.animal.2020.100023&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type , Journal 2017 United KingdomPublisher:Elsevier BV Authors: Ross, S. A.; Topp, C. F E; Ennos, R. A.; Chagunda, M. G G;pmid: 28183378
pmc: PMC5523730
This study aimed to assess the merit and suitability of individual functional units (FU) in expressing greenhouse gas emissions intensity in different dairy production systems. An FU provides a clearly defined and measurable reference to which input and output data are normalised. This enables the results from life-cycle assessment (LCA) of different systems to be treated as functionally equivalent. Although the methodological framework of LCA has been standardised, selection of an appropriate FU remains ultimately at the discretion of the individual study. The aim of the present analysis was to examine the effect of different FU on the emissions intensities of different dairy production systems. Analysis was based on 7 years of data (2004 to 2010) from four Holstein-Friesian dairy systems at Scotland's Rural College's long-term genetic and management systems project, the Langhill herd. Implementation of LCA accounted for the environmental impacts of the whole-farm systems and their production of milk from 'cradle to farm gate'. Emissions intensity was determined as kilograms of carbon dioxide equivalents referenced to six FU: UK livestock units, energy-corrected milk yield, total combined milk solids yield, on-farm land used for production, total combined on- and off-farm land used for production, and the proposed new FU-energy-corrected milk yield per hectare of total land used. Energy-corrected milk was the FU most effective for reflecting differences between the systems. Functional unit that incorporated a land-related aspect did not find difference between systems which were managed under the same forage regime, despite their comprising different genetic lines. Employing on-farm land as the FU favoured grazing systems. The proposed dual FU combining both productivity and land use did not differentiate between emissions intensity of systems as effectively as the productivity-based units. However, this dual unit displayed potential to quantify in a simple way the positive or negative outcome of trade-offs between land and production efficiencies, in which improvement in emissions intensity using one FU may be accompanied by deterioration using another FU. The perceived environmental efficiencies of different dairy production systems in terms of their emissions intensities were susceptible to change based upon the FU employed, and hence the FU used in any study needs to be taken into account in the interpretation of results.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1017/s1751731117000052&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 23 citations 23 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1017/s1751731117000052&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu
description Publicationkeyboard_double_arrow_right Article , Journal , Other literature type 2018 Netherlands, France, Australia, FrancePublisher:Elsevier BV Pierre J. Gerber; Pierre J. Gerber; Timothy P. Robinson; Alessandra Falcucci; Benjamin B. Henderson; Henning Steinfeld; C. Opio; G. Tempio; Michael MacLeod; Harinder P. S. Makkar; Theun Vellinga; Anne Mottet;The livestock sector is one of the fastest growing subsectors of the agricultural economy and, while it makes a major contribution to global food supply and economic development, it also consumes significant amounts of natural resources and alters the environment. In order to improve our understanding of the global environmental impact of livestock supply chains, the Food and Agriculture Organization of the United Nations has developed the Global Livestock Environmental Assessment Model (GLEAM). The purpose of this paper is to provide a review of GLEAM. Specifically, it explains the model architecture, methods and functionality, that is the types of analysis that the model can perform. The model focuses primarily on the quantification of greenhouse gases emissions arising from the production of the 11 main livestock commodities. The model inputs and outputs are managed and produced as raster data sets, with spatial resolution of 0.05 decimal degrees. The Global Livestock Environmental Assessment Model v1.0 consists of five distinct modules: (a) the Herd Module; (b) the Manure Module; (c) the Feed Module; (d) the System Module; (e) the Allocation Module. In terms of the modelling approach, GLEAM has several advantages. For example spatial information on livestock distributions and crops yields enables rations to be derived that reflect the local availability of feed resources in developing countries. The Global Livestock Environmental Assessment Model also contains a herd model that enables livestock statistics to be disaggregated and variation in livestock performance and management to be captured. Priorities for future development of GLEAM include: improving data quality and the methods used to perform emissions calculations; extending the scope of the model to include selected additional environmental impacts and to enable predictive modelling; and improving the utility of GLEAM output.
CGIAR CGSpace (Consu... arrow_drop_down CGIAR CGSpace (Consultative Group on International Agricultural Research)Article . 2018License: CC BY NC NDFull-Text: https://hdl.handle.net/10568/90511Data sources: Bielefeld Academic Search Engine (BASE)The University of Queensland: UQ eSpaceArticle . 2018Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1017/s1751731117001847&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 57 citations 57 popularity Top 1% influence Top 10% impulse Top 10% Powered by BIP!
more_vert CGIAR CGSpace (Consu... arrow_drop_down CGIAR CGSpace (Consultative Group on International Agricultural Research)Article . 2018License: CC BY NC NDFull-Text: https://hdl.handle.net/10568/90511Data sources: Bielefeld Academic Search Engine (BASE)The University of Queensland: UQ eSpaceArticle . 2018Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1017/s1751731117001847&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal , Other literature type 2021 Italy, Netherlands, Sweden, United KingdomPublisher:Elsevier BV Kipling, R.P.; Bannink, A.; Bartley, D.J.; Blanco-Penedo, I.; Faverdin, P.; Graux, A.I.; Hutchings, N.J.; Kyriazakis, I.; Macleod, M.; Østergaard, S.; Robinson, T.P.; Vitali, A.; Ahmadi, B.V.; Özkan, Seyda;Improved animal health can reduce greenhouse gas (GHG) emissions intensity in livestock systems while increasing productivity. Integrated modelling of disease impacts on farm-scale emissions is important in identifying effective health strategies to reduce emissions. However, it requires that modellers understand the pathways linking animal health to emissions and how these might be incorporated into models. A key barrier to meeting this need has been the lack of a framework to facilitate effective exchange of knowledge and data between animal health experts and emissions modellers. Here, these two communities engaged in workshops, online exchanges and a survey to i) identify a comprehensive list of disease-related model parameters and ii) test its application to evaluating models. Fifty-six parameters were identified and proved effective in assessing the potential of farm-scale models to characterise livestock disease impacts on GHG emissions. Easy wins for the emissions models surveyed include characterising disease impacts related to feeding.
SLU publication data... arrow_drop_down Wageningen Staff PublicationsArticle . 2021License: CC BYData sources: Wageningen Staff PublicationsQueen's University Belfast Research PortalArticle . 2021Data sources: Bielefeld Academic Search Engine (BASE)Università degli studi della Tuscia: Unitus DSpaceArticle . 2021Data sources: Bielefeld Academic Search Engine (BASE)Università degli studi della Tuscia: Unitus DSpaceArticle . 2021Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.animal.2020.100023&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 9 citations 9 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
more_vert SLU publication data... arrow_drop_down Wageningen Staff PublicationsArticle . 2021License: CC BYData sources: Wageningen Staff PublicationsQueen's University Belfast Research PortalArticle . 2021Data sources: Bielefeld Academic Search Engine (BASE)Università degli studi della Tuscia: Unitus DSpaceArticle . 2021Data sources: Bielefeld Academic Search Engine (BASE)Università degli studi della Tuscia: Unitus DSpaceArticle . 2021Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.animal.2020.100023&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type , Journal 2017 United KingdomPublisher:Elsevier BV Authors: Ross, S. A.; Topp, C. F E; Ennos, R. A.; Chagunda, M. G G;pmid: 28183378
pmc: PMC5523730
This study aimed to assess the merit and suitability of individual functional units (FU) in expressing greenhouse gas emissions intensity in different dairy production systems. An FU provides a clearly defined and measurable reference to which input and output data are normalised. This enables the results from life-cycle assessment (LCA) of different systems to be treated as functionally equivalent. Although the methodological framework of LCA has been standardised, selection of an appropriate FU remains ultimately at the discretion of the individual study. The aim of the present analysis was to examine the effect of different FU on the emissions intensities of different dairy production systems. Analysis was based on 7 years of data (2004 to 2010) from four Holstein-Friesian dairy systems at Scotland's Rural College's long-term genetic and management systems project, the Langhill herd. Implementation of LCA accounted for the environmental impacts of the whole-farm systems and their production of milk from 'cradle to farm gate'. Emissions intensity was determined as kilograms of carbon dioxide equivalents referenced to six FU: UK livestock units, energy-corrected milk yield, total combined milk solids yield, on-farm land used for production, total combined on- and off-farm land used for production, and the proposed new FU-energy-corrected milk yield per hectare of total land used. Energy-corrected milk was the FU most effective for reflecting differences between the systems. Functional unit that incorporated a land-related aspect did not find difference between systems which were managed under the same forage regime, despite their comprising different genetic lines. Employing on-farm land as the FU favoured grazing systems. The proposed dual FU combining both productivity and land use did not differentiate between emissions intensity of systems as effectively as the productivity-based units. However, this dual unit displayed potential to quantify in a simple way the positive or negative outcome of trade-offs between land and production efficiencies, in which improvement in emissions intensity using one FU may be accompanied by deterioration using another FU. The perceived environmental efficiencies of different dairy production systems in terms of their emissions intensities were susceptible to change based upon the FU employed, and hence the FU used in any study needs to be taken into account in the interpretation of results.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1017/s1751731117000052&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 23 citations 23 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1017/s1751731117000052&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu