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Trait-based representation of biological nitrification: model development, testing, and predicted community composition.

Bouskill NJ, Tang J, Riley WJ, Brodie EL - Front Microbiol (2012)

Bottom Line: The model predicted that transient N(2)O production rates are maximized by a decoupling of the AOB and NOB communities, resulting in an accumulation and detoxification of nitrite to N(2)O by AOB.When the reactions uncouple, the AOB become unstable and biomass declines rapidly, resulting in decreased NH(3) oxidation and N(2)O production.We evaluated this model against site level chemical datasets from the interior of Alaska and accurately simulated NH(3) oxidation rates and the relative ratio of AOA:AOB biomass.

View Article: PubMed Central - PubMed

Affiliation: Ecology Department, Earth Sciences Division, Lawrence Berkeley National Laboratory Berkeley, CA, USA.

ABSTRACT
Trait-based microbial models show clear promise as tools to represent the diversity and activity of microorganisms across ecosystem gradients. These models parameterize specific traits that determine the relative fitness of an "organism" in a given environment, and represent the complexity of biological systems across temporal and spatial scales. In this study we introduce a microbial community trait-based modeling framework (MicroTrait) focused on nitrification (MicroTrait-N) that represents the ammonia-oxidizing bacteria (AOB) and ammonia-oxidizing archaea (AOA) and nitrite-oxidizing bacteria (NOB) using traits related to enzyme kinetics and physiological properties. We used this model to predict nitrifier diversity, ammonia (NH(3)) oxidation rates, and nitrous oxide (N(2)O) production across pH, temperature, and substrate gradients. Predicted nitrifier diversity was predominantly determined by temperature and substrate availability, the latter was strongly influenced by pH. The model predicted that transient N(2)O production rates are maximized by a decoupling of the AOB and NOB communities, resulting in an accumulation and detoxification of nitrite to N(2)O by AOB. However, cumulative N(2)O production (over 6 month simulations) is maximized in a system where the relationship between AOB and NOB is maintained. When the reactions uncouple, the AOB become unstable and biomass declines rapidly, resulting in decreased NH(3) oxidation and N(2)O production. We evaluated this model against site level chemical datasets from the interior of Alaska and accurately simulated NH(3) oxidation rates and the relative ratio of AOA:AOB biomass. The predicted community structure and activity indicate (a) parameterization of a small number of traits may be sufficient to broadly characterize nitrifying community structure and (b) changing decadal trends in climate and edaphic conditions could impact nitrification rates in ways that are not captured by extant biogeochemical models.

No MeSH data available.


Related in: MedlinePlus

N2O production under a coupled AOB-NOB nitrification reaction and also as the AOB-NOB reaction becomes uncoupled and the detoxification reaction is activated. (A) Maximal rate of N2O production (B) Cumulative N2O production over the 6-month simulation. Error bars are the result of three simulations per temperature.
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Figure 4: N2O production under a coupled AOB-NOB nitrification reaction and also as the AOB-NOB reaction becomes uncoupled and the detoxification reaction is activated. (A) Maximal rate of N2O production (B) Cumulative N2O production over the 6-month simulation. Error bars are the result of three simulations per temperature.

Mentions: We simulated N2O production through two pathways described above (Figure A1 in Appendix). After running the simulations to steady state biomass, the NOB were removed allowing rapid accumulation of NO2 and invoking a detoxification response in the AOO. NO2 was rapidly converted to N2O, via NO, using cellular biomass as an energy source. This conversion resulted in a transient N2O production rate significantly higher than in the scenarios with a steady state community and when the NOB were present (ANOVA, p < 0.05; Figure 4A). Despite a higher N2O production rate in the absence of NOB, cumulative production of N2O over 6 months was significantly (ANOVA, p < 0.05) lower than when NOB were present (Figure 4B) due to the creation of an unstable half reaction (lacking NO2 oxidation) resulting in a rapid crash in AOO community biomass (data not shown).


Trait-based representation of biological nitrification: model development, testing, and predicted community composition.

Bouskill NJ, Tang J, Riley WJ, Brodie EL - Front Microbiol (2012)

N2O production under a coupled AOB-NOB nitrification reaction and also as the AOB-NOB reaction becomes uncoupled and the detoxification reaction is activated. (A) Maximal rate of N2O production (B) Cumulative N2O production over the 6-month simulation. Error bars are the result of three simulations per temperature.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3475126&req=5

Figure 4: N2O production under a coupled AOB-NOB nitrification reaction and also as the AOB-NOB reaction becomes uncoupled and the detoxification reaction is activated. (A) Maximal rate of N2O production (B) Cumulative N2O production over the 6-month simulation. Error bars are the result of three simulations per temperature.
Mentions: We simulated N2O production through two pathways described above (Figure A1 in Appendix). After running the simulations to steady state biomass, the NOB were removed allowing rapid accumulation of NO2 and invoking a detoxification response in the AOO. NO2 was rapidly converted to N2O, via NO, using cellular biomass as an energy source. This conversion resulted in a transient N2O production rate significantly higher than in the scenarios with a steady state community and when the NOB were present (ANOVA, p < 0.05; Figure 4A). Despite a higher N2O production rate in the absence of NOB, cumulative production of N2O over 6 months was significantly (ANOVA, p < 0.05) lower than when NOB were present (Figure 4B) due to the creation of an unstable half reaction (lacking NO2 oxidation) resulting in a rapid crash in AOO community biomass (data not shown).

Bottom Line: The model predicted that transient N(2)O production rates are maximized by a decoupling of the AOB and NOB communities, resulting in an accumulation and detoxification of nitrite to N(2)O by AOB.When the reactions uncouple, the AOB become unstable and biomass declines rapidly, resulting in decreased NH(3) oxidation and N(2)O production.We evaluated this model against site level chemical datasets from the interior of Alaska and accurately simulated NH(3) oxidation rates and the relative ratio of AOA:AOB biomass.

View Article: PubMed Central - PubMed

Affiliation: Ecology Department, Earth Sciences Division, Lawrence Berkeley National Laboratory Berkeley, CA, USA.

ABSTRACT
Trait-based microbial models show clear promise as tools to represent the diversity and activity of microorganisms across ecosystem gradients. These models parameterize specific traits that determine the relative fitness of an "organism" in a given environment, and represent the complexity of biological systems across temporal and spatial scales. In this study we introduce a microbial community trait-based modeling framework (MicroTrait) focused on nitrification (MicroTrait-N) that represents the ammonia-oxidizing bacteria (AOB) and ammonia-oxidizing archaea (AOA) and nitrite-oxidizing bacteria (NOB) using traits related to enzyme kinetics and physiological properties. We used this model to predict nitrifier diversity, ammonia (NH(3)) oxidation rates, and nitrous oxide (N(2)O) production across pH, temperature, and substrate gradients. Predicted nitrifier diversity was predominantly determined by temperature and substrate availability, the latter was strongly influenced by pH. The model predicted that transient N(2)O production rates are maximized by a decoupling of the AOB and NOB communities, resulting in an accumulation and detoxification of nitrite to N(2)O by AOB. However, cumulative N(2)O production (over 6 month simulations) is maximized in a system where the relationship between AOB and NOB is maintained. When the reactions uncouple, the AOB become unstable and biomass declines rapidly, resulting in decreased NH(3) oxidation and N(2)O production. We evaluated this model against site level chemical datasets from the interior of Alaska and accurately simulated NH(3) oxidation rates and the relative ratio of AOA:AOB biomass. The predicted community structure and activity indicate (a) parameterization of a small number of traits may be sufficient to broadly characterize nitrifying community structure and (b) changing decadal trends in climate and edaphic conditions could impact nitrification rates in ways that are not captured by extant biogeochemical models.

No MeSH data available.


Related in: MedlinePlus