A mechanistic model of methane emission from animal slurry with a focus on microbial groups
Liquid manure (slurry) from livestock releases methane (CH.sub.4) that contributes significantly to global warming. Existing models for slurry CH.sub.4 production-used for mitigation and inventories-include effects of organic matter loading, temperature, and retention time but cannot predict importa...
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| Veröffentlicht in: | PloS one 2021-06, Vol.16 (6), p.e0252881 |
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| creator | Dalby, Frederik R Hafner, Sasha D Petersen, Søren O Vanderzaag, Andrew Habtewold, Jemaneh Dunfield, Kari Chantigny, Martin H Sommer, Sven G |
| description | Liquid manure (slurry) from livestock releases methane (CH.sub.4) that contributes significantly to global warming. Existing models for slurry CH.sub.4 production-used for mitigation and inventories-include effects of organic matter loading, temperature, and retention time but cannot predict important effects of management, or adequately capture essential temperature-driven dynamics. Here we present a new model that includes multiple methanogenic groups whose relative abundance shifts in response to changes in temperature or other environmental conditions. By default, the temperature responses of five groups correspond to those of four methanogenic species and one uncultured methanogen, although any number of groups could be defined. We argue that this simple mechanistic approach is able to describe both short- and long-term responses to temperature where other existing approaches fall short. The model is available in the open-source R package ABM ( |
| doi_str_mv | 10.1371/journal.pone.0252881 |
| format | Article |
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Existing models for slurry CH.sub.4 production-used for mitigation and inventories-include effects of organic matter loading, temperature, and retention time but cannot predict important effects of management, or adequately capture essential temperature-driven dynamics. Here we present a new model that includes multiple methanogenic groups whose relative abundance shifts in response to changes in temperature or other environmental conditions. By default, the temperature responses of five groups correspond to those of four methanogenic species and one uncultured methanogen, although any number of groups could be defined. We argue that this simple mechanistic approach is able to describe both short- and long-term responses to temperature where other existing approaches fall short. The model is available in the open-source R package ABM (</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0252881</identifier><identifier>PMID: 34111183</identifier><language>eng</language><publisher>San Francisco: Public Library of Science</publisher><subject>Acetic acid ; Animal manures ; Animal waste ; Biodegradation ; Biology and Life Sciences ; Biotechnology ; Chemical engineering ; Community development ; Emissions ; Emissions (Pollution) ; Empirical equations ; Environmental aspects ; Farms ; Hydrogen ; Hydrogen sulfide ; Inoculum ; Livestock ; Manures ; Mathematical analysis ; Methane ; Methane emissions ; Methanogenic bacteria ; Microorganisms ; Organic matter ; Physical Sciences ; Properties ; R&D ; Research & development ; Research and Analysis Methods ; Slurries ; Substrates ; Sulfate reduction ; Sulfate-reducing bacteria ; Temperature variations</subject><ispartof>PloS one, 2021-06, Vol.16 (6), p.e0252881</ispartof><rights>COPYRIGHT 2021 Public Library of Science</rights><rights>2021 Dalby et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2021 Dalby et al 2021 Dalby et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c669t-1611a0479240a50b192887e7f9f5b1562fd3c2505ae933e70a27363dffd60d453</citedby><cites>FETCH-LOGICAL-c669t-1611a0479240a50b192887e7f9f5b1562fd3c2505ae933e70a27363dffd60d453</cites><orcidid>0000-0003-0955-0327 ; 0000-0002-2673-0162 ; 0000-0003-2437-064X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8191904/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8191904/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,2102,2928,23866,27924,27925,53791,53793</link.rule.ids></links><search><contributor>Li, Huan</contributor><creatorcontrib>Dalby, Frederik R</creatorcontrib><creatorcontrib>Hafner, Sasha D</creatorcontrib><creatorcontrib>Petersen, Søren O</creatorcontrib><creatorcontrib>Vanderzaag, Andrew</creatorcontrib><creatorcontrib>Habtewold, Jemaneh</creatorcontrib><creatorcontrib>Dunfield, Kari</creatorcontrib><creatorcontrib>Chantigny, Martin H</creatorcontrib><creatorcontrib>Sommer, Sven G</creatorcontrib><title>A mechanistic model of methane emission from animal slurry with a focus on microbial groups</title><title>PloS one</title><description>Liquid manure (slurry) from livestock releases methane (CH.sub.4) that contributes significantly to global warming. Existing models for slurry CH.sub.4 production-used for mitigation and inventories-include effects of organic matter loading, temperature, and retention time but cannot predict important effects of management, or adequately capture essential temperature-driven dynamics. Here we present a new model that includes multiple methanogenic groups whose relative abundance shifts in response to changes in temperature or other environmental conditions. By default, the temperature responses of five groups correspond to those of four methanogenic species and one uncultured methanogen, although any number of groups could be defined. We argue that this simple mechanistic approach is able to describe both short- and long-term responses to temperature where other existing approaches fall short. The model is available in the open-source R package ABM (</description><subject>Acetic acid</subject><subject>Animal manures</subject><subject>Animal waste</subject><subject>Biodegradation</subject><subject>Biology and Life Sciences</subject><subject>Biotechnology</subject><subject>Chemical engineering</subject><subject>Community development</subject><subject>Emissions</subject><subject>Emissions (Pollution)</subject><subject>Empirical equations</subject><subject>Environmental aspects</subject><subject>Farms</subject><subject>Hydrogen</subject><subject>Hydrogen sulfide</subject><subject>Inoculum</subject><subject>Livestock</subject><subject>Manures</subject><subject>Mathematical analysis</subject><subject>Methane</subject><subject>Methane emissions</subject><subject>Methanogenic bacteria</subject><subject>Microorganisms</subject><subject>Organic matter</subject><subject>Physical Sciences</subject><subject>Properties</subject><subject>R&D</subject><subject>Research & 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mechanistic model of methane emission from animal slurry with a focus on microbial groups</title><author>Dalby, Frederik R ; Hafner, Sasha D ; Petersen, Søren O ; Vanderzaag, Andrew ; Habtewold, Jemaneh ; Dunfield, Kari ; Chantigny, Martin H ; Sommer, Sven G</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c669t-1611a0479240a50b192887e7f9f5b1562fd3c2505ae933e70a27363dffd60d453</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Acetic acid</topic><topic>Animal manures</topic><topic>Animal waste</topic><topic>Biodegradation</topic><topic>Biology and Life Sciences</topic><topic>Biotechnology</topic><topic>Chemical engineering</topic><topic>Community development</topic><topic>Emissions</topic><topic>Emissions (Pollution)</topic><topic>Empirical equations</topic><topic>Environmental aspects</topic><topic>Farms</topic><topic>Hydrogen</topic><topic>Hydrogen 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Existing models for slurry CH.sub.4 production-used for mitigation and inventories-include effects of organic matter loading, temperature, and retention time but cannot predict important effects of management, or adequately capture essential temperature-driven dynamics. Here we present a new model that includes multiple methanogenic groups whose relative abundance shifts in response to changes in temperature or other environmental conditions. By default, the temperature responses of five groups correspond to those of four methanogenic species and one uncultured methanogen, although any number of groups could be defined. We argue that this simple mechanistic approach is able to describe both short- and long-term responses to temperature where other existing approaches fall short. The model is available in the open-source R package ABM (</abstract><cop>San Francisco</cop><pub>Public Library of Science</pub><pmid>34111183</pmid><doi>10.1371/journal.pone.0252881</doi><tpages>e0252881</tpages><orcidid>https://orcid.org/0000-0003-0955-0327</orcidid><orcidid>https://orcid.org/0000-0002-2673-0162</orcidid><orcidid>https://orcid.org/0000-0003-2437-064X</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Acetic acid Animal manures Animal waste Biodegradation Biology and Life Sciences Biotechnology Chemical engineering Community development Emissions Emissions (Pollution) Empirical equations Environmental aspects Farms Hydrogen Hydrogen sulfide Inoculum Livestock Manures Mathematical analysis Methane Methane emissions Methanogenic bacteria Microorganisms Organic matter Physical Sciences Properties R&D Research & development Research and Analysis Methods Slurries Substrates Sulfate reduction Sulfate-reducing bacteria Temperature variations |
| title | A mechanistic model of methane emission from animal slurry with a focus on microbial groups |
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