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Resource effects on denitrification are mediated by community composition in tidal freshwater wetlands soils
Author(s) -
Morrissey Ember M.,
Franklin Rima B.
Publication year - 2015
Publication title -
environmental microbiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.954
H-Index - 188
eISSN - 1462-2920
pISSN - 1462-2912
DOI - 10.1111/1462-2920.12575
Subject(s) - denitrification , biology , wetland , soil water , microbial population biology , nitrate , ecology , terminal restriction fragment length polymorphism , organic matter , environmental chemistry , nitrogen , chemistry , polymerase chain reaction , biochemistry , genetics , organic chemistry , bacteria , gene , restriction fragment length polymorphism
Summary Accurate prediction of denitrification rates remains difficult, potentially owing to complex uncharacterized interactions between resource conditions and denitrifier communities. To better understand how the availability of organic matter ( OM ) and nitrate ( NO 3 – ), two of the resources most fundamental to denitrifiers, affect these populations and their activity, we performed an in situ resource manipulation in tidal freshwater wetland soils. Soils were augmented with OM to double ambient concentrations, using either compost or plant litter, and fertilized with KNO 3 at two levels (low: ∼ 5 mg l –1 NO 3 – – N and high: ∼ 50 mg l –1 NO 3 – – N ) in a full factorial design. Community composition of nirS ‐denitrifers (assessed using terminal restriction fragment length polymorphism) was interactively regulated by both NO 3 – concentration and OM type, and the associated shifts in community composition were relatively consistent across sampling dates (6, 9 and 12 months of incubation). Denitrification potential (p DNF ) rates were also strongly affected by NO 3 – fertilization and increased by ∼ 10–100‐fold. Path analysis revealed that the influence of resource availability on p DNF rates was largely mediated through changes in nirS ‐denitrifier community composition. These results suggest that a greater understanding of denitrifier community ecology may enable more accurate prediction of denitrification rates.