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A high‐resolution survey of DMS, CO 2 , and O 2 /Ar distributions in productive coastal waters
Author(s) -
Nemcek Nina,
Ianson Debby,
Tortell Philippe D.
Publication year - 2008
Publication title -
global biogeochemical cycles
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.512
H-Index - 187
eISSN - 1944-9224
pISSN - 0886-6236
DOI - 10.1029/2006gb002879
Subject(s) - hydrography , sampling (signal processing) , environmental science , chlorophyll a , resolution (logic) , atmospheric sciences , spatial variability , image resolution , oceanography , chemistry , geology , physics , statistics , mathematics , artificial intelligence , computer science , biochemistry , detector , optics
We present continuous, high‐resolution measurements of surface dimethylsulfide (DMS), p CO 2 , and O 2 /Ar obtained in coastal waters off British Columbia, Canada, using membrane inlet mass spectrometry (MIMS). Sampled underway at a frequency of twice per minute (every ∼160 m at 10 knots cruising speed), our data reveal fine‐scale structure in gas variability and its covariance with a number of hydrographic parameters. All parameters exhibited large ranges ( p CO 2 , 200–747 ppm; DMS, <1–29 nM; chl a , <0.1–33 μ g L −1 ), highlighting the dynamic nature of the study area. A strong anticorrelation between p CO 2 and O 2 /Ar was observed across the survey region, with the distributions of these gases influenced by biology and its interplay with physical processes. In contrast, DMS levels, which varied dramatically over short distances, showed no significant correlations with any single variable for the full, high‐resolution data set. However, when measurements were binned to a much coarser spatial resolution, we found a linear relationship between surface DMS and the chlorophyll/mixed layer depth ratio. The slope of this relationship differed significantly from that previously derived from open ocean data. We used several statistical techniques to estimate the spatial variability of gases and hydrographic parameters and the inherent sampling errors associated with low‐frequency sampling approaches. These analyses emphasize the importance of high‐resolution sampling in coastal areas, particularly for DMS.