Frontiers in Microbiology (Feb 2016)
Microbes as engines of ecosystem function: when does community structure enhance predictions of ecosystem processes?
- Emily B. Graham,
- Emily B. Graham,
- Joseph E. Knelman,
- Joseph E. Knelman,
- Andreas eSchindlbacher,
- Steven eSiciliano,
- Marc eBreulmann,
- Anthony eYannarell,
- J. Michael eBeman,
- Guy eAbell,
- Laurent ePhilippot,
- James eProsser,
- Arnaud eFoulquier,
- Jorge Curiel eYuste,
- Helen C. eGlanville,
- Davey eJones,
- Roey eAngel,
- Janne eSalminen,
- Ryan J Newton,
- Helmut eBürgmann,
- Lachlan J. Ingram,
- Ute eHamer,
- Henri MP Siljanen,
- Krista ePeltoniemi,
- Karin ePotthast,
- Lluís eBañeras,
- Martin eHartmann,
- Samiran eBanerjee,
- Ri-Qing eYu,
- Geraldine eNogaro,
- Andreas eRichter,
- Marianne eKoranda,
- Sarah eCastle,
- Marta eGoberna,
- Bongkeun eSong,
- Amitava eChatterjee,
- Olga Cristina Nunes,
- Ana Rita Lopes,
- Yiping eCao,
- Aurore eKaisermann,
- Sara eHallin,
- Michael S Strickland,
- Jordi eGarcia-Pausas,
- Josep eBarba,
- Hojeong eKang,
- Kazuo eIsobe,
- Sokratis ePapaspyrou,
- Roberta ePastorelli,
- Alessandra eLagomarsino,
- Eva eLindström,
- Nathan eBasiliko,
- Diana Reid Nemergut,
- Diana Reid Nemergut
Affiliations
- Emily B. Graham
- University of Colorado
- Emily B. Graham
- Pacific Northwest National Laboratory
- Joseph E. Knelman
- University of Colorado
- Joseph E. Knelman
- US Department of Energy
- Andreas eSchindlbacher
- BFW
- Steven eSiciliano
- Univ. of Saskatchewan
- Marc eBreulmann
- UBZ
- Anthony eYannarell
- Univ. of Illinois at Urbana-Champaign
- J. Michael eBeman
- Univ. of California - Merced
- Guy eAbell
- Flinders Univ.
- Laurent ePhilippot
- INRA
- James eProsser
- Univ. of Aberdeen
- Arnaud eFoulquier
- UR MALY
- Jorge Curiel eYuste
- CSIC
- Helen C. eGlanville
- Bangor Univ.
- Davey eJones
- Bangor Univ.
- Roey eAngel
- Univ. of Vienna
- Janne eSalminen
- Häme Univ. of Applied Sci.
- Ryan J Newton
- Univ. of Wisconsin-Milwaukee
- Helmut eBürgmann
- Eawag: Swiss Federal Inst. of Aquatic Sci. & Technology
- Lachlan J. Ingram
- The Univ. of Sydney
- Ute eHamer
- Univ. of Münster
- Henri MP Siljanen
- Univ. of Eastern Finland
- Krista ePeltoniemi
- Nat. Resources Inst. Finland (Luke)
- Karin ePotthast
- Technische Univ.
- Lluís eBañeras
- Univ. of Girona
- Martin eHartmann
- Agroscope
- Samiran eBanerjee
- CSIRO Agriculture Flagship
- Ri-Qing eYu
- Univ. of Texas at Tyler
- Geraldine eNogaro
- LNHE
- Andreas eRichter
- Univ. of Vienna
- Marianne eKoranda
- Univ. of Vienna
- Sarah eCastle
- Univ. of Montana
- Marta eGoberna
- CIDE-CSIC
- Bongkeun eSong
- Virginia Institute of Marine Science
- Amitava eChatterjee
- North Dakota State Univ.
- Olga Cristina Nunes
- Univ. of Porto
- Ana Rita Lopes
- Univ. of Porto
- Yiping eCao
- Southern California Coastal Water Res. Project Authority
- Aurore eKaisermann
- INRA Bordeaux
- Sara eHallin
- Swedish Univ. of Agricultural Sci.
- Michael S Strickland
- Virginia Polytechnic Inst. & State Univ.
- Jordi eGarcia-Pausas
- Centre Tecnològic Forestal de Catalunya
- Josep eBarba
- CREAF
- Hojeong eKang
- Yonsei Univ.
- Kazuo eIsobe
- The Univ. of Tokyo
- Sokratis ePapaspyrou
- Univ. of Cadiz
- Roberta ePastorelli
- Res. Centre for Agrobiology & Pedology
- Alessandra eLagomarsino
- Res. Centre for Agrobiology & Pedology
- Eva eLindström
- Uppsala Univ.
- Nathan eBasiliko
- Laurentian Univ.
- Diana Reid Nemergut
- University of Colorado
- Diana Reid Nemergut
- Duke University
- DOI
- https://doi.org/10.3389/fmicb.2016.00214
- Journal volume & issue
-
Vol. 7
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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