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

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

Research output: Contribution to journalArticle

149 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number214
JournalFrontiers in Microbiology
Volume7
Issue numberFEB
DOIs
Publication statusPublished - 2016 Feb 24

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Ecosystem
Biomass
Biota
Respiratory Rate
Ecology
Nitrogen
Carbon
Research
Genes
Datasets

All Science Journal Classification (ASJC) codes

  • Microbiology
  • Microbiology (medical)

Cite this

Graham, E. B., Knelman, J. E., Schindlbacher, A., Siciliano, S., Breulmann, M., Yannarell, A., ... Nemergut, D. R. (2016). Microbes as engines of ecosystem function: When does community structure enhance predictions of ecosystem processes? Frontiers in Microbiology, 7(FEB), [214]. https://doi.org/10.3389/fmicb.2016.00214
Graham, Emily B. ; Knelman, Joseph E. ; Schindlbacher, Andreas ; Siciliano, Steven ; Breulmann, Marc ; Yannarell, Anthony ; Beman, J. M. ; Abell, Guy ; Philippot, Laurent ; Prosser, James ; 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?. In: Frontiers in Microbiology. 2016 ; Vol. 7, No. FEB.
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abstract = "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.",
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Graham, EB, Knelman, JE, Schindlbacher, A, Siciliano, S, Breulmann, M, Yannarell, A, Beman, JM, Abell, G, Philippot, L, Prosser, J, Foulquier, A, Yuste, JC, Glanville, HC, Jones, DL, Angel, R, Salminen, J, Newton, RJ, Bürgmann, H, Ingram, LJ, Hamer, U, Siljanen, HMP, Peltoniemi, K, Potthast, K, Bañeras, L, Hartmann, M, Banerjee, S, Yu, RQ, Nogaro, G, Richter, A, Koranda, M, Castle, SC, Goberna, M, Song, B, Chatterjee, A, Nunes, OC, Lopes, AR, Cao, Y, Kaisermann, A, Hallin, S, Strickland, MS, Garcia-Pausas, J, Barba, J, Kang, H, Isobe, K, Papaspyrou, S, Pastorelli, R, Lagomarsino, A, Lindström, ES, Basiliko, N & Nemergut, DR 2016, 'Microbes as engines of ecosystem function: When does community structure enhance predictions of ecosystem processes?', Frontiers in Microbiology, vol. 7, no. FEB, 214. https://doi.org/10.3389/fmicb.2016.00214

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; 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.

In: Frontiers in Microbiology, Vol. 7, No. FEB, 214, 24.02.2016.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Microbes as engines of ecosystem function

T2 - When does community structure enhance predictions of ecosystem processes?

AU - Graham, Emily B.

AU - Knelman, Joseph E.

AU - Schindlbacher, Andreas

AU - Siciliano, Steven

AU - Breulmann, Marc

AU - Yannarell, Anthony

AU - Beman, J. M.

AU - Abell, Guy

AU - Philippot, Laurent

AU - Prosser, James

AU - Foulquier, Arnaud

AU - Yuste, Jorge C.

AU - Glanville, Helen C.

AU - Jones, Davey L.

AU - Angel, Roey

AU - Salminen, Janne

AU - Newton, Ryan J.

AU - Bürgmann, Helmut

AU - Ingram, Lachlan J.

AU - Hamer, Ute

AU - Siljanen, Henri M.P.

AU - Peltoniemi, Krista

AU - Potthast, Karin

AU - Bañeras, Lluís

AU - Hartmann, Martin

AU - Banerjee, Samiran

AU - Yu, Ri Qing

AU - Nogaro, Geraldine

AU - Richter, Andreas

AU - Koranda, Marianne

AU - Castle, Sarah C.

AU - Goberna, Marta

AU - Song, Bongkeun

AU - Chatterjee, Amitava

AU - Nunes, Olga C.

AU - Lopes, Ana R.

AU - Cao, Yiping

AU - Kaisermann, Aurore

AU - Hallin, Sara

AU - Strickland, Michael S.

AU - Garcia-Pausas, Jordi

AU - Barba, Josep

AU - Kang, Hojeong

AU - Isobe, Kazuo

AU - Papaspyrou, Sokratis

AU - Pastorelli, Roberta

AU - Lagomarsino, Alessandra

AU - Lindström, Eva S.

AU - Basiliko, Nathan

AU - Nemergut, Diana R.

PY - 2016/2/24

Y1 - 2016/2/24

N2 - 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.

AB - 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.

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