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Record W4220868479 · doi:10.5194/bg-19-1657-2022

Tidal mixing of estuarine and coastal waters in the western English Channel is a control on spatial and temporal variability in seawater CO <sub>2</sub>

2022· article· en· W4220868479 on OpenAlexaff
Richard Sims, Michael Bedington, Ute Schuster, Andrew Watson, Vassilis Kitidis, Ricardo Torres, Helen S. Findlay, James Fishwick, Ian Brown, Thomas G. Bell

Bibliographic record

VenueBiogeosciences · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsUniversity of Calgary
FundersInterregFP7 Research infrastructuresHorizon 2020Horizon 2020 Framework ProgrammeNatural Environment Research CouncilSight Research UK
KeywordsOceanographyEstuaryTransectSpatial variabilitySeawaterBayEnvironmental scienceSalinitySurface waterFlux (metallurgy)Spatial ecologyChannel (broadcasting)TRACERGeologyHydrology (agriculture)Ecology

Abstract

fetched live from OpenAlex

Surface ocean carbon dioxide (CO 2 ) measurements are used to compute the oceanic air–sea CO 2 flux. The CO 2 flux component from rivers and estuaries is uncertain due to the high spatial and seasonal heterogeneity of CO 2 in coastal waters. Existing high-quality CO 2 instrumentation predominantly utilises showerhead and percolating style equilibrators optimised for open-ocean observations. The intervals between measurements made with such instrumentation make it difficult to resolve the fine-scale spatial variability of surface water CO 2 at timescales relevant to the high frequency variability in estuarine and coastal environments. Here we present a novel dataset with unprecedented frequency and spatial resolution transects made at the Western Channel Observatory in the south-west of the UK from June to September 2016, using a fast-response seawater CO 2 system. Novel observations were made along the estuarine–coastal continuum at different stages of the tide and reveal distinct spatial patterns in the surface water CO 2 fugacity ( f CO 2 ) at different stages of the tidal cycle. Changes in salinity and f CO 2 were closely correlated at all stages of the tidal cycle and suggest that the mixing of oceanic and riverine endmembers partially determines the variations in f CO 2 . The correlation between salinity and f CO 2 was different in Cawsand Bay, which could be due to enhanced gas exchange or to enhanced biological activity in the region. The observations demonstrate the complex dynamics determining spatial and temporal patterns of salinity and f CO 2 in the region. Spatial variations in observed surface salinity were used to validate the output of a regional high-resolution hydrodynamic model. The model enables a novel estimate of the air–sea CO 2 flux in the estuarine–coastal zone. Air–sea CO 2 flux variability in the estuarine–coastal boundary region is influenced by the state of the tide because of strong CO 2 outgassing from the river plume. The observations and model output demonstrate that undersampling the complex tidal and mixing processes characteristic of estuarine and coastal environment biases quantification of air–sea CO 2 fluxes in coastal waters. The results provide a mechanism to support critical national and regional policy implementation by reducing uncertainty in carbon budgets.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.121
Threshold uncertainty score0.240

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.188
Teacher spread0.179 · 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 source (direct Gemma or distilled Codex), 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

Citations12
Published2022
Admission routes1
Has abstractyes

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