Differential
Effects of Nitrogenous Fertilizers on Methane-Consuming Microbes
in Rice Field and Forest Soils†‡
Santosh R. Mohanty,1§
Paul L. E. Bodelier,2* Virgilio Floris,2
and Ralf Conrad1
Netherlands Institute of Ecology (NIOO-KNAW), Centre for
Limnology, Department of Microbial
Wetland Ecology, Rijksstraatweg 6, 3631 AC Nieuwersluis,
The Netherlands.
Abstract
The impact of environmental perturbation
(e.g., nitrogenous fertilizers) on the dynamics of methane
fluxes from soils and wetland systems is poorly understood.
Results of fertilizer studies are often contradictory, even
within similar ecosystems. In the present study the hypothesis
of whether these contradictory results may be explained by
the composition of the methane-consuming microbial community
and hence whether methanotrophic diversity affects methane
fluxes was investigated. To this end, rice field and forest
soils were incubated in microcosms and supplemented with different
nitrogenous fertilizers and methane concentrations. By labeling
the methane with 13C, diversity and function could
be coupled by analyses of phospholipid-derived fatty acids
(PLFA) extracted from the soils at different time points during
incubation. In both rice field and forest soils, the activity
as well as the growth rate of methane-consuming bacteria was
affected differentially. For type I methanotrophs, fertilizer
application stimulated the consumption of methane and the
subsequent growth, while type II methanotrophs were generally
inhibited. Terminal restriction fragment length polymorphism
analyses of the pmoA gene supported the PLFA results.
Multivariate analyses of stable-isotope-probing PLFA profiles
indicated that in forest and rice field soils, Methylocystis
(type II) species were affected by fertilization. The type
I methanotrophs active in forest soils (Methylomicrobium/Methylosarcina
related) differed from the active species in rice field soils
(Methylobacter/Methylomonas related). Our
results provide a case example showing that microbial community
structure indeed matters, especially when assessing and predicting
the impact of environmental change on biodiversity loss and
ecosystem functioning.
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