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Record W2897026524 · doi:10.5194/bg-16-1729-2019

Patterns and drivers of dimethylsulfide concentration in the northeast subarctic Pacific across multiple spatial and temporal scales

2019· article· en· W2897026524 on OpenAlexafffund
Alysia E. Herr, Ronald P. Kiene, John W. H. Dacey, Philippe D. Tortell

Bibliographic record

VenueBiogeosciences · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsUniversity of British Columbia
FundersDivision of Ocean SciencesNatural Sciences and Engineering Research Council of CanadaNational Science Foundation
KeywordsOceanographyPolar frontHydrographyContinental shelfSubarctic climateContext (archaeology)Environmental scienceMesoscale meteorologyTransectSalinityDiatomGeology

Abstract

fetched live from OpenAlex

Abstract. The northeast subarctic Pacific (NESAP) is a globally important source of the climate-active gas dimethylsulfide (DMS), yet the processes driving DMS variability across this region are poorly understood. Here we examine the spatial distribution of DMS at various spatial scales in contrasting oceanographic regimes of the NESAP. We present new high-spatial-resolution measurements of DMS across hydrographic frontal zones along the British Columbia continental shelf, together with key environmental variables and biological rate measurements. We combine these new data with existing observations to produce a revised summertime DMS climatology for the NESAP, yielding a broader context for our sub-mesoscale process studies. Our results demonstrate sharp DMS concentration gradients across hydrographic frontal zones and suggest the presence of two distinct DMS cycling regimes in the NESAP, corresponding to microphytoplankton-dominated waters along the continental shelf and nanoplankton-dominated waters in the cross-shelf transitional zone. DMS concentrations across the continental shelf transition (range < 1–10 nM, mean 3.9 nM) exhibited positive correlations to salinity (r=0.80), sea surface height anomaly (SSHA; r=0.51), and the relative abundance of prymnesiophyte and dinoflagellates (r=0.89). In contrast, DMS concentrations in nearshore coastal transects (range < 1–24 nM, mean 6.1 nM) showed a negative correlation with salinity (r=-0.69; r=-0.78) and SSHA (r=-0.81; r=-0.75) and a positive correlation to relative diatom abundance (r=0.88; r=0.86). These results highlight the importance of bloom-driven DMS production in continental shelf waters of this region and the role of prymnesiophytes and dinoflagellates in DMS cycling further offshore. In all areas, the rate of DMS consumption appeared to be an important control on observed concentration gradients, with higher DMS consumption rate constants associated with lower DMS concentrations. We compiled a data set of all available summertime DMS observations for the NESAP (including previously unpublished results) to examine the performance of several existing algorithms for predicting regional DMS concentrations. None of these existing algorithms was able to accurately reproduce observed DMS distributions across the NESAP, although performance was improved by the use of regionally tuned coefficients. Based on our compiled observations, we derived an average summertime distribution map for DMS concentrations and sea–air fluxes across the NESAP, estimating a mean regional flux of 0.30 Tg of DMS-derived sulfur to the atmosphere during the summer season.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.211
Teacher spread0.201 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations23
Published2019
Admission routes2
Has abstractyes

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