Microbes as engines of ecosystem function: when does community structure enhance predictions of ecosystem processes?

Graham, Emily B.; Knelman, Joseph E.; Schindlbacher, Andreas; Siciliano, Steven; Breulmann, Marc; Yannarell, Anthony; Beman, J.M.; Abell, Guy; Philippot, Laurent; Prosser, James I.; Foulquier, Arnaud; Yuste, Jorge C.; Glanville, Helen C.; Jones, Davey L.; Angel, Roey; Salminen, Janne; Newton, Ryan J.; Bürgmann, Helmut; Ingram, Lachlan J.; Hamer, Ute; Siljanen, Henri M.P.; Peltoniemi, Krista; Potthast, Karin; Bañeras, Lluís; Hartmann, Martin; Banerjee, Samiran; Yu, Ri-Qing; Nogaro, Geraldine; Richter, Andreas; Koranda, Marianne; Castle, Sarah C.; Goberna, Marta; Song, Bongkeun; Chatterjee, Amitava; Nunes, Olga C.; Lopes, Ana R.; Cao, Yiping; Kaisermann, Aurore; Hallin, Sara; Strickland, Michael S.; Garcia-Pausas, Jordi; Barba, Josep; Kang, Hojeong; Isobe, Kazuo; Papaspyrou, Sokratis; Pastorelli, Roberta; Lagomarsino, Alessandra; Lindström, Eva S.; Basiliko, Nathan; Nemergut, Diana R.

Microbes as engines of ecosystem function: when does community structure enhance predictions of ecosystem processes?

Microorganisms are vital in mediating the earth’s biogeochemical cycles; yet, despite our rapidly increasing ability to explore complex environmental microbial communities, the relationship between microbial community structure and ecosystem processes remains poorly understood. Here, we address a fu...

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Autores:	Graham, Emily B., Knelman, Joseph E., Schindlbacher, Andreas, Siciliano, Steven, Breulmann, Marc, Yannarell, Anthony, Beman, J.M., Abell, Guy, Philippot, Laurent, Prosser, James I., Foulquier, Arnaud, Yuste, Jorge C., Glanville, Helen C., Jones, Davey L., Angel, Roey, Salminen, Janne, Newton, Ryan J., Bürgmann, Helmut, Ingram, Lachlan J., Hamer, Ute, Siljanen, Henri M.P., Peltoniemi, Krista, Potthast, Karin, Bañeras, Lluís, Hartmann, Martin, Banerjee, Samiran, Yu, Ri-Qing, Nogaro, Geraldine, Richter, Andreas, Koranda, Marianne, Castle, Sarah C., Goberna, Marta, Song, Bongkeun, Chatterjee, Amitava, Nunes, Olga C., Lopes, Ana R., Cao, Yiping, Kaisermann, Aurore, Hallin, Sara, Strickland, Michael S., Garcia-Pausas, Jordi, Barba, Josep, Kang, Hojeong, Isobe, Kazuo, Papaspyrou, Sokratis, Pastorelli, Roberta, Lagomarsino, Alessandra, Lindström, Eva S., Basiliko, Nathan, Nemergut, Diana R.
Tipo de recurso:	artículo
Estado:	Versión publicada
Fecha de publicación:	2016
País:	España
Institución:	Universitat de Lleida (UdL)
Repositorio:	Repositori Obert UdL
OAI Identifier:	oai:repositori.udl.cat:10459.1/69109
Acceso en línea:	https://doi.org/10.3389/fmicb.2016.00214 http://hdl.handle.net/10459.1/69109
Access Level:	acceso abierto
Palabra clave:	Microbial diversity Functional gene Statistical modeling Microbial ecology Ecosystem processes Respiration Nitrification Denitrification

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spelling	Microbes as engines of ecosystem function: when does community structure enhance predictions of ecosystem processes?Graham, Emily B.Knelman, Joseph E.Schindlbacher, AndreasSiciliano, StevenBreulmann, MarcYannarell, AnthonyBeman, J.M.Abell, GuyPhilippot, LaurentProsser, James I.Foulquier, ArnaudYuste, Jorge C.Glanville, Helen C.Jones, Davey L.Angel, RoeySalminen, JanneNewton, Ryan J.Bürgmann, HelmutIngram, Lachlan J.Hamer, UteSiljanen, Henri M.P.Peltoniemi, KristaPotthast, KarinBañeras, LluísHartmann, MartinBanerjee, SamiranYu, Ri-QingNogaro, GeraldineRichter, AndreasKoranda, MarianneCastle, Sarah C.Goberna, MartaSong, BongkeunChatterjee, AmitavaNunes, Olga C.Lopes, Ana R.Cao, YipingKaisermann, AuroreHallin, SaraStrickland, Michael S.Garcia-Pausas, JordiBarba, JosepKang, HojeongIsobe, KazuoPapaspyrou, SokratisPastorelli, RobertaLagomarsino, AlessandraLindström, Eva S.Basiliko, NathanNemergut, Diana R.Microbial diversityFunctional geneStatistical modelingMicrobial ecologyEcosystem processesRespirationNitrificationDenitrificationMicroorganisms are vital in mediating the earth’s biogeochemical cycles; yet, despite our rapidly increasing ability to explore complex environmental microbial communities, the relationship between microbial community structure and ecosystem processes remains poorly understood. Here, we address a fundamental and unanswered question in microbial ecology: ‘When do we need to understand microbial community structure to accurately predict function?’ We present a statistical analysis investigating the value of environmental data and microbial community structure independently and in combination for explaining rates of carbon and nitrogen cycling processes within 82 global datasets. Environmental variables were the strongest predictors of process rates but left 44% of variation unexplained on average, suggesting the potential for microbial data to increase model accuracy. Although only 29% of our datasets were significantly improved by adding information on microbial community structure, we observed improvement in models of processes mediated by narrow phylogenetic guilds via functional gene data, and conversely, improvement in models of facultative microbial processes via community diversity metrics. Our results also suggest that microbial diversity can strengthen predictions of respiration rates beyond microbial biomass parameters, as 53% of models were improved by incorporating both sets of predictors compared to 35% by microbial biomass alone. Our analysis represents the first comprehensive analysis of research examining links between microbial community structure and ecosystem function. Taken together, our results indicate that a greater understanding of microbial communities informed by ecological principles may enhance our ability to predict ecosystem process rates relative to assessments based on environmental variables and microbial physiology.This work was supported by NSF grant DEB-1221215 to DN, as well as grants supporting the generation of our datasets as acknowledged in their original publications and in Supplementary Table S1.Frontiers Media2016info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttps://doi.org/10.3389/fmicb.2016.00214http://hdl.handle.net/10459.1/69109reponame:Repositori Obert UdL instname:Universitat de Lleida (UdL)InglésReproducció del document publicat a: https://doi.org/10.3389/fmicb.2016.00214Frontiers in Microbiology, 2016, vol. 7, article 214cc-by (c) Graham et al., 2016info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/oai:repositori.udl.cat:10459.1/691092026-06-24T12:42:17Z
dc.title.none.fl_str_mv	Microbes as engines of ecosystem function: when does community structure enhance predictions of ecosystem processes?
title	Microbes as engines of ecosystem function: when does community structure enhance predictions of ecosystem processes?
spellingShingle	Microbes as engines of ecosystem function: when does community structure enhance predictions of ecosystem processes? Graham, Emily B. Microbial diversity Functional gene Statistical modeling Microbial ecology Ecosystem processes Respiration Nitrification Denitrification
title_short	Microbes as engines of ecosystem function: when does community structure enhance predictions of ecosystem processes?
title_full	Microbes as engines of ecosystem function: when does community structure enhance predictions of ecosystem processes?
title_fullStr	Microbes as engines of ecosystem function: when does community structure enhance predictions of ecosystem processes?
title_full_unstemmed	Microbes as engines of ecosystem function: when does community structure enhance predictions of ecosystem processes?
title_sort	Microbes as engines of ecosystem function: when does community structure enhance predictions of ecosystem processes?
dc.creator.none.fl_str_mv	Graham, Emily B. Knelman, Joseph E. Schindlbacher, Andreas Siciliano, Steven Breulmann, Marc Yannarell, Anthony Beman, J.M. Abell, Guy Philippot, Laurent Prosser, James I. Foulquier, Arnaud Yuste, Jorge C. Glanville, Helen C. Jones, Davey L. Angel, Roey Salminen, Janne Newton, Ryan J. Bürgmann, Helmut Ingram, Lachlan J. Hamer, Ute Siljanen, Henri M.P. Peltoniemi, Krista Potthast, Karin Bañeras, Lluís Hartmann, Martin Banerjee, Samiran Yu, Ri-Qing Nogaro, Geraldine Richter, Andreas Koranda, Marianne Castle, Sarah C. Goberna, Marta Song, Bongkeun Chatterjee, Amitava Nunes, Olga C. Lopes, Ana R. Cao, Yiping Kaisermann, Aurore Hallin, Sara Strickland, Michael S. Garcia-Pausas, Jordi Barba, Josep Kang, Hojeong Isobe, Kazuo Papaspyrou, Sokratis Pastorelli, Roberta Lagomarsino, Alessandra Lindström, Eva S. Basiliko, Nathan Nemergut, Diana R.
author	Graham, Emily B.
author_facet	Graham, Emily B. Knelman, Joseph E. Schindlbacher, Andreas Siciliano, Steven Breulmann, Marc Yannarell, Anthony Beman, J.M. Abell, Guy Philippot, Laurent Prosser, James I. Foulquier, Arnaud Yuste, Jorge C. Glanville, Helen C. Jones, Davey L. Angel, Roey Salminen, Janne Newton, Ryan J. Bürgmann, Helmut Ingram, Lachlan J. Hamer, Ute Siljanen, Henri M.P. Peltoniemi, Krista Potthast, Karin Bañeras, Lluís Hartmann, Martin Banerjee, Samiran Yu, Ri-Qing Nogaro, Geraldine Richter, Andreas Koranda, Marianne Castle, Sarah C. Goberna, Marta Song, Bongkeun Chatterjee, Amitava Nunes, Olga C. Lopes, Ana R. Cao, Yiping Kaisermann, Aurore Hallin, Sara Strickland, Michael S. Garcia-Pausas, Jordi Barba, Josep Kang, Hojeong Isobe, Kazuo Papaspyrou, Sokratis Pastorelli, Roberta Lagomarsino, Alessandra Lindström, Eva S. Basiliko, Nathan Nemergut, Diana R.
author_role	author
author2	Knelman, Joseph E. Schindlbacher, Andreas Siciliano, Steven Breulmann, Marc Yannarell, Anthony Beman, J.M. Abell, Guy Philippot, Laurent Prosser, James I. Foulquier, Arnaud Yuste, Jorge C. Glanville, Helen C. Jones, Davey L. Angel, Roey Salminen, Janne Newton, Ryan J. Bürgmann, Helmut Ingram, Lachlan J. Hamer, Ute Siljanen, Henri M.P. Peltoniemi, Krista Potthast, Karin Bañeras, Lluís Hartmann, Martin Banerjee, Samiran Yu, Ri-Qing Nogaro, Geraldine Richter, Andreas Koranda, Marianne Castle, Sarah C. Goberna, Marta Song, Bongkeun Chatterjee, Amitava Nunes, Olga C. Lopes, Ana R. Cao, Yiping Kaisermann, Aurore Hallin, Sara Strickland, Michael S. Garcia-Pausas, Jordi Barba, Josep Kang, Hojeong Isobe, Kazuo Papaspyrou, Sokratis Pastorelli, Roberta Lagomarsino, Alessandra Lindström, Eva S. Basiliko, Nathan Nemergut, Diana R.
author2_role	author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author
dc.subject.none.fl_str_mv	Microbial diversity Functional gene Statistical modeling Microbial ecology Ecosystem processes Respiration Nitrification Denitrification
topic	Microbial diversity Functional gene Statistical modeling Microbial ecology Ecosystem processes Respiration Nitrification Denitrification
description	Microorganisms are vital in mediating the earth’s biogeochemical cycles; yet, despite our rapidly increasing ability to explore complex environmental microbial communities, the relationship between microbial community structure and ecosystem processes remains poorly understood. Here, we address a fundamental and unanswered question in microbial ecology: ‘When do we need to understand microbial community structure to accurately predict function?’ We present a statistical analysis investigating the value of environmental data and microbial community structure independently and in combination for explaining rates of carbon and nitrogen cycling processes within 82 global datasets. Environmental variables were the strongest predictors of process rates but left 44% of variation unexplained on average, suggesting the potential for microbial data to increase model accuracy. Although only 29% of our datasets were significantly improved by adding information on microbial community structure, we observed improvement in models of processes mediated by narrow phylogenetic guilds via functional gene data, and conversely, improvement in models of facultative microbial processes via community diversity metrics. Our results also suggest that microbial diversity can strengthen predictions of respiration rates beyond microbial biomass parameters, as 53% of models were improved by incorporating both sets of predictors compared to 35% by microbial biomass alone. Our analysis represents the first comprehensive analysis of research examining links between microbial community structure and ecosystem function. Taken together, our results indicate that a greater understanding of microbial communities informed by ecological principles may enhance our ability to predict ecosystem process rates relative to assessments based on environmental variables and microbial physiology.
publishDate	2016
dc.date.none.fl_str_mv	2016
dc.type.none.fl_str_mv	info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion
format	article
status_str	publishedVersion
dc.identifier.none.fl_str_mv	https://doi.org/10.3389/fmicb.2016.00214 http://hdl.handle.net/10459.1/69109
url	https://doi.org/10.3389/fmicb.2016.00214 http://hdl.handle.net/10459.1/69109
dc.language.none.fl_str_mv	Inglés
language_invalid_str_mv	Inglés
dc.relation.none.fl_str_mv	Reproducció del document publicat a: https://doi.org/10.3389/fmicb.2016.00214 Frontiers in Microbiology, 2016, vol. 7, article 214
dc.rights.none.fl_str_mv	cc-by (c) Graham et al., 2016 info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/4.0/
rights_invalid_str_mv	cc-by (c) Graham et al., 2016 http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv	openAccess
dc.publisher.none.fl_str_mv	Frontiers Media
publisher.none.fl_str_mv	Frontiers Media
dc.source.none.fl_str_mv	reponame:Repositori Obert UdL instname:Universitat de Lleida (UdL)
instname_str	Universitat de Lleida (UdL)
reponame_str	Repositori Obert UdL
collection	Repositori Obert UdL
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repository.mail.fl_str_mv
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Microbes as engines of ecosystem function: when does community structure enhance predictions of ecosystem processes?

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