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Using In‐Situ Optical Sensors to Understand the Biogeochemistry of Dissolved Organic Matter Across a Stream Network
Author(s) -
Wymore Adam S.,
Potter Jody,
RodríguezCardona Bianca,
McDowell William H.
Publication year - 2018
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1002/2017wr022168
Subject(s) - dissolved organic carbon , biogeochemistry , organic matter , environmental chemistry , environmental science , remineralisation , aquatic ecosystem , chemistry , inorganic chemistry , organic chemistry , fluoride
The advent of high‐frequency in situ optical sensors provides new opportunities to study the biogeochemistry of dissolved organic matter (DOM) in aquatic ecosystems. We used fDOM (fluorescent dissolved organic matter) to examine the spatial and temporal variability in dissolved organic carbon (DOC) and dissolved organic nitrogen (DON) across a heterogeneous stream network that varies inNO 3 −concentration. Across the ten study streams fDOM explained twice the variability in the concentration of DOC ( r 2 = 0.82) compared to DON ( r 2 = 0.39), which suggests that the N‐rich fraction of DOM is either more variable in its sources or more bioreactive than the more stable C‐rich fraction. Among sites, DON molar fluorescence was approximately 3x more variable than DOC molar fluorescence and was correlated with changes in inorganic N, indicating that DON is both more variable in composition as well as highly responsive to changes in inorganic N. Laboratory results also indicate that the fDOM sensors we used perform as well as the excitation‐emission wavelength pair generally referred to as the “tryptophan‐like” peak when measured under laboratory conditions. However, since neither the field sensor not the laboratory measurements explained a large percentage of variation in DON concentrations, challenges still remain for monitoring the ambient pool of dissolved organic nitrogen. Sensor networks provide new insights into the potential reactivity of DOM and the variability in DOC and DON biogeochemistry across sites. These insights are needed to build spatially explicit models describing organic matter dynamics and water quality.