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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Journal of Soils and...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Journal of Soils and Sediments
Article . 2018 . Peer-reviewed
License: Springer TDM
Data sources: Crossref
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Spartina alterniflora invasion affects methane emissions in the Yangtze River estuary

Authors: Naishun Bu; Siqi Wu; Xiao Yang; Yuyang Sun; Zhonglin Chen; Xiping Ma; Youtao Song; +2 Authors

Spartina alterniflora invasion affects methane emissions in the Yangtze River estuary

Abstract

Wetlands are the largest natural sources of atmospheric methane (CH4) and are often susceptible to plant invasion and hydrological fluctuations. However, the effect of plant invasion on wetland CH4 emissions is still controversial, and little is known about the variation of invasion-induced CH4 emissions under heterogeneous conditions. A pairwise experimental design between Spartina alterniflora (invasive plant) and Phragmites australis (native plant) stands in high elevation sites (H-sites) and S. alterniflora and Scirpus mariqueter (native plant) stands in low elevation sites (L-sites) of the Yangtze River estuary was used to investigate how plant invasions affect CH4 emissions and whether CH4 emission changes significantly differ between the H- and L-sites with heterogeneous conditions. A static closed chamber method was used to conduct gas sampling measurements at both H- and L-sites. In addition, plant biomass and soil properties were investigated in both invasive and native plant stands. CH4 emissions from the S. alterniflora stands were all significantly higher than those from the native plant stands at both H- and L-sites. Furthermore, the difference in CH4 emissions between S. alterniflora and P. australis stands in the H-sites was significantly lower than that between S. alterniflora and S. mariqueter stands in the L-sites. Plant biomass, soil organic carbon, and microbial biomass in S. alterniflora stands were all significantly higher than those in the native plant stands in both H-sites and L-sites. The soil properties also changed. Our results indicate that the S. alterniflora invasion significantly enhanced CH4 emissions from wetlands in the Yangtze River estuary. The invasion-related CH4 emissions were highly spatially variable; this variability may have been driven by the soil’s anaerobic environments, induced by hydrological dynamics. These results can have important implications for improving our ability to predict invasion-induced changes in CH4 emissions from wetlands in the context of global climate change.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
14
Top 10%
Average
Average
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