Frontiers in Microbiology (May 2016)

Predicting the responses of soil nitrite-oxidizers to multi-factorial global change: a trait-based approach

  • Xavier eLE ROUX,
  • Nick eBouskill,
  • Audrey eNiboyet,
  • Laure eBarthes,
  • Paul eDijkstra,
  • Chris eField,
  • Bruce A Hungate,
  • Catherine eLerondelle,
  • Thomas ePommier,
  • Jinyun eTang,
  • Akihiko eTerada,
  • Maria eTourna,
  • Franck ePoly

DOI
https://doi.org/10.3389/fmicb.2016.00628
Journal volume & issue
Vol. 7

Abstract

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Soil microbial diversity is huge and a few grams of soil contain more bacterial taxa than there are bird species on Earth. This high diversity often makes predicting the responses of soil bacteria to environmental change intractable and restricts our capacity to predict the responses of soil functions to global change. Here, using a long-term field experiment in a California grassland, we studied the main and interactive effects of three global change factors (increased atmospheric CO2 concentration, precipitation and nitrogen addition, and all their factorial combinations, based on global change scenarios for central California) on the potential activity, abundance and dominant taxa of soil nitrite-oxidizing bacteria (NOB). Using a trait-based model, we then tested whether categorizing NOB into a few functional groups unified by physiological traits enables understanding and predicting how soil NOB respond to global environmental change. Contrasted responses to global change treatments were observed between three main NOB functional types. In particular, putatively mixotrophic Nitrobacter, rare under most treatments, became dominant under the ‘High CO2+Nitrogen+Precipitation’ treatment. The mechanistic trait-based model, which simulated ecological niches of NOB types consistent with previous ecophysiological reports, helped predicting the observed effects of global change on NOB and elucidating the underlying biotic and abiotic controls. Our results are a starting point for representing the overwhelming diversity of soil bacteria by a few functional types that can be incorporated into models of terrestrial ecosystems and biogeochemical processes.

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