2015
DOI: 10.1111/php.12448
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Utilization of PARAFAC‐Modeled Excitation‐Emission Matrix (EEM) Fluorescence Spectroscopy to Identify Biogeochemical Processing of Dissolved Organic Matter in a Northern Peatland

Abstract: In this study, we contrast the fluorescent properties of dissolved organic matter (DOM) in fens and bogs in a Northern Minnesota peatland using excitation emission matrix fluorescence spectroscopy with parallel factor analysis (EEM-PARAFAC). EEM-PARAFAC identified four humic-like components and one protein-like component and the dynamics of each were evaluated based on their distribution with depth as well as across sites differing in hydrology and major biological species. The PARAFAC-EEM experiments were sup… Show more

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Cited by 35 publications
(18 citation statements)
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“…The most positive PC1 score was observed in deep pore water samples, followed by intermediate depth pore water samples that suggest evidence of microbial utilization of pore water DOM deeper in the peat column. The decrease in the ubiquitous high MW humic‐like component C4 with depth and the increase in C2 and C3 are in contrast to observations from a previous study in another northern peatland (Tfaily et al, ) where C3 was negatively correlated with C1, and C4 was relatively refractory. These data suggest that at the S1 bog, high molecular weight highly aromatic C4 appears to be more bioavailable for microbial communities than the C1 component and that DOM decomposition dynamics vary across different peatland sites.…”
Section: Discussioncontrasting
confidence: 99%
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“…The most positive PC1 score was observed in deep pore water samples, followed by intermediate depth pore water samples that suggest evidence of microbial utilization of pore water DOM deeper in the peat column. The decrease in the ubiquitous high MW humic‐like component C4 with depth and the increase in C2 and C3 are in contrast to observations from a previous study in another northern peatland (Tfaily et al, ) where C3 was negatively correlated with C1, and C4 was relatively refractory. These data suggest that at the S1 bog, high molecular weight highly aromatic C4 appears to be more bioavailable for microbial communities than the C1 component and that DOM decomposition dynamics vary across different peatland sites.…”
Section: Discussioncontrasting
confidence: 99%
“…Principal Component 1 (PC1) accounted for 74.4%, and Principal Component (PC2) accounted for another 21.3% of the variability. As illustrated in the loading plot of PCA (Figure a), the five PARAFAC components are distributed along PC1 such that the relative abundance of humic‐like terrestrial C4 and C1 (Tfaily et al, ) correlates most negatively with PC1, and the relative abundance of humic microbial‐like C3, C2, and protein‐like C5 (Tfaily et al, ) is positively correlated with PC1. The terrestrial and microbial/protein components have dissimilar distributions along PC1, suggesting that the DOM source controls PC1.…”
Section: Resultsmentioning
confidence: 99%
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“…These groups which mediate fermentation, syntrophy, and utilize fumarate as the sole electron acceptor by direct interspecies electron transfer (Sieber et al, 2012;Wang et al, 2016) are also prevalent at Stordalen Mire (Mondav and Woodcroft et al 2014, supplemental data). Furthermore, Tfaily et al (2015) identified a unique fluorescent chromophore in pore waters from the nearby Glacial Lake Agassiz peatlands in Minnesota that appeared to be a microbial by-product originating from humic matter, consistent with the microbial transformation of unsaturated compounds. Increasing alkylation of dissolved organic matter with increasing depth was also observed in the Glacial Lake Agassiz peatlands which is consistent with our hypothesis of increasing hydrogenation of organic matter .…”
Section: Discussionmentioning
confidence: 65%
“…Depending on the position in the van Krevelen diagram, all assigned formulae can roughly be grouped according to major classes of biopolymers found in natural organic matter like tannin, lignin, lipids, proteins, amino sugars, and hydrocarbons. We used the classification according to Sleighter and Hatcher 2007 The number of formulae in each class were then summed and normalized by the total number of assignable formulae for all functional groups to produce a relative abundance (as percent) for the six classes of biopolymers (Tfaily et al, 2015).…”
Section: Analysis Of Fluorescence and Ft-icr-ms Datamentioning
confidence: 99%