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

Abstract

In this study, 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.more » 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.« less

Authors:
 [1];  [2];  [3];  [4];  [5];  [6];  [7];  [8];  [9];  [10];  [11];  [12];  [13];  [13];  [14];  [15];  [16];  [17];  [18];  [19] more »;  [20];  [21];  [22];  [23];  [24];  [25];  [26];  [27];  [14];  [14];  [28];  [29];  [30];  [31];  [32];  [32];  [33];  [34];  [35];  [36];  [37];  [38];  [39];  [40];  [41];  [42];  [42];  [43];  [44];  [45] « less
  1. Univ. of Colorado, Boulder, CO (United States); Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  2. Univ. of Colorado, Boulder, CO (United States); U.S. Dept. of Energy, Joint Genome Institute, Walnut Creek, CA (United States)
  3. Federal Research and Training Centre for Forests, Vienna (Austria)
  4. Univ. of Saskatchewan, Saskatoon, SK (Canada)
  5. Helmholtz Centre for Environmental Research, Leipzig (Germany)
  6. Univ. of Illinois at Urbana-Champaign, Urbana, IL (United States)
  7. Univ. of California - Merced, Merced, CA (United States)
  8. Flinders Univ., Adelaide, SA (Australia)
  9. Institut National de la Recherche Agronomique - Agroecology, Dijon (France)
  10. Univ. of Aberdeen, Aberdeen (United Kingdom)
  11. Centre de Lyon-Villeurbanne, Villeurbanne (France)
  12. Museo Nacional de Ciencias Naturales, Madrid (Spain)
  13. Bangor Univ., Gwynedd (United Kingdom)
  14. Univ. of Vienna, Vienna (Austria)
  15. Hame Univ. of Applied Sciences, Hameenlinna (Finland)
  16. Univ. of Wisconsin-Milwaukee, Milwaukee, WI (United States)
  17. Swiss Federal Institute of Aquatic Science and Technology, Kastanienbaum (Switzerland)
  18. The Univ. of Sydney, Sydney (Australia)
  19. Univ. of Munster, Munster (Germany)
  20. Univ. of Eastern Finland, Kuopio (Finland)
  21. Natural Resources Institute, Vantaa (Finland)
  22. Technische Univ., Dresden (Germany)
  23. Univ. of Girona, Girona (Spain)
  24. Institute for Sustainability Sciences - Agroscope, Zurich (Switzerland)
  25. CSIRO Agriculture Flagship, Crace (Australia)
  26. Univ. of Texas at Tyler, Tyler, TX (United States)
  27. National Hydraulics and Environmental Lab., Chatou (France)
  28. Univ. of Montana, Missoula, MT (United States)
  29. Centro de Investigacion y Docencia Economicas - Consejo Superior de Investigaciones Cientificas, Valencia (Spain)
  30. Virginia Institute of Marine Science, Gloucester Point, VA (United States)
  31. North Dakota State Univ., Fargo, ND (United States)
  32. Faculdade de Engenharia da Univ. do Porto, Porto (Portugal)
  33. Southern California Coastal Water Research Project Authority, Costa Mesa, CA (United States)
  34. UMR, Interactions Sol Plante Atmosphere, Villenave d'Ornon (France)
  35. Swedish Univ. of Agricultural Sciences, Uppsala (Sweden)
  36. Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States)
  37. Centre Tecnologic Forestal de Catalunya, Solsona (Spain)
  38. Centre de Recerca Ecologica i Aplicacions Forestals, Barcelona (Spain)
  39. Yonsei Univ., Seoul (South Korea)
  40. The Univ. of Tokyo, Tokyo (Japan)
  41. Univ. of Cadiz, Puerto Real (Spain)
  42. Research Centre for Agrobiology and Pedology, Florence (Italy)
  43. Uppsala Univ., Uppsala (Sweden)
  44. Laurentian Univ., Sudbury, ON (Canada)
  45. Duke Univ., Durham, NC (United States)
Publication Date:
Research Org.:
Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1249360
Grant/Contract Number:  
DEB1221215; AC0576RL01830
Resource Type:
Accepted Manuscript
Journal Name:
Frontiers in Microbiology
Additional Journal Information:
Journal Volume: 7; Journal Issue: C; Journal ID: ISSN 1664-302X
Publisher:
Frontiers Research Foundation
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; 59 BASIC BIOLOGICAL SCIENCES; microbial diversity; functional gene; statistical modeling; microbial ecology; ecosystem processes; respiration; nitrification; denitrification

Citation Formats

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., Burgmann, Helmut, Ingram, Lachlan J., Hamer, Ute, Siljanen, Henri M. P., Peltoniemi, Krista, Potthast, Karin, Baneras, Lluis, 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, Lindstrom, Eva S., Basiliko, Nathan, and Nemergut, Diana R. Microbes as engines of ecosystem function: When does community structure enhance predictions of ecosystem processes?. United States: N. p., 2016. Web. doi: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., Burgmann, Helmut, Ingram, Lachlan J., Hamer, Ute, Siljanen, Henri M. P., Peltoniemi, Krista, Potthast, Karin, Baneras, Lluis, 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, Lindstrom, Eva S., Basiliko, Nathan, & Nemergut, Diana R. Microbes as engines of ecosystem function: When does community structure enhance predictions of ecosystem processes?. United States. 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., Burgmann, Helmut, Ingram, Lachlan J., Hamer, Ute, Siljanen, Henri M. P., Peltoniemi, Krista, Potthast, Karin, Baneras, Lluis, 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, Lindstrom, Eva S., Basiliko, Nathan, and Nemergut, Diana R. Wed . "Microbes as engines of ecosystem function: When does community structure enhance predictions of ecosystem processes?". United States. https://doi.org/10.3389/fmicb.2016.00214. https://www.osti.gov/servlets/purl/1249360.
@article{osti_1249360,
title = {Microbes as engines of ecosystem function: When does community structure enhance predictions of ecosystem processes?},
author = {Graham, Emily B. and Knelman, Joseph E. and Schindlbacher, Andreas and Siciliano, Steven and Breulmann, Marc and Yannarell, Anthony and Beman, J. M. and Abell, Guy and Philippot, Laurent and Prosser, James and Foulquier, Arnaud and Yuste, Jorge C. and Glanville, Helen C. and Jones, Davey L. and Angel, Roey and Salminen, Janne and Newton, Ryan J. and Burgmann, Helmut and Ingram, Lachlan J. and Hamer, Ute and Siljanen, Henri M. P. and Peltoniemi, Krista and Potthast, Karin and Baneras, Lluis and Hartmann, Martin and Banerjee, Samiran and Yu, Ri -Qing and Nogaro, Geraldine and Richter, Andreas and Koranda, Marianne and Castle, Sarah C. and Goberna, Marta and Song, Bongkeun and Chatterjee, Amitava and Nunes, Olga C. and Lopes, Ana R. and Cao, Yiping and Kaisermann, Aurore and Hallin, Sara and Strickland, Michael S. and Garcia-Pausas, Jordi and Barba, Josep and Kang, Hojeong and Isobe, Kazuo and Papaspyrou, Sokratis and Pastorelli, Roberta and Lagomarsino, Alessandra and Lindstrom, Eva S. and Basiliko, Nathan and Nemergut, Diana R.},
abstractNote = {In this study, 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.},
doi = {10.3389/fmicb.2016.00214},
journal = {Frontiers in Microbiology},
number = C,
volume = 7,
place = {United States},
year = {Wed Feb 24 00:00:00 EST 2016},
month = {Wed Feb 24 00:00:00 EST 2016}
}

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Cross-biome metagenomic analyses of soil microbial communities and their functional attributes
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Gene-centric approach to integrating environmental genomics and biogeochemical models
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Soil biodiversity and soil community composition determine ecosystem multifunctionality
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Functional identity and diversity of animals predict ecosystem functioning better than species-based indices
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Primers for overlooked nirK, qnorB, and nosZ genes of thermophilic Gram-positive denitrifiers
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Microbial community dynamics alleviate stoichiometric constraints during litter decay
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Decomposers in disguise: mycorrhizal fungi as regulators of soil C dynamics in ecosystems under global change
journal, December 2008


Beyond species: functional diversity and the maintenance of ecological processes and services: Functional diversity in ecology and conservation
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The unseen majority: soil microbes as drivers of plant diversity and productivity in terrestrial ecosystems
journal, March 2008


Assembly history dictates ecosystem functioning: evidence from wood decomposer communities: Carbon dynamics and fungal community assembly
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Effects of estuarine sediment hypoxia on nitrogen fluxes and ammonia oxidizer gene transcription: Nitrification and sediment hypoxia
journal, November 2010


Microbiomes in light of traits: A phylogenetic perspective
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Assembly History Interacts with Ecosystem size to Influence Species Diversity
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Microbial functional diversity enhances predictive models linking environmental parameters to ecosystem properties
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Changes in community assembly may shift the relationship between biodiversity and ecosystem function
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When, where and how does microbial community composition matter?
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Coastal hypoxia and sediment biogeochemistry
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Distinct temporal diversity profiles for nitrogen cycling genes in a hyporheic microbiome
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Captivity causes taxonomic and functional convergence of gut microbial communities in bats
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