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Record W4308458156 · doi:10.1016/j.jhydrol.2022.128677

Dissolved inorganic carbon export from rivers of Great Britain: Spatial distribution and potential catchment-scale controls

2022· article· en· W4308458156 on OpenAlexafffund
A.M. Tye, Jennifer Williamson, Helen P. Jarvie, Nancy B. Dise, Dan Lapworth, Don Monteith, Richard Sanders, Daniel J. Mayor, Michael Bowes, Annette Burden, Nathan Callaghan, Gareth Farr, Stacey L. Felgate, Stuart W. Gibb, Peter Gilbert, Geoff Hargreaves, Patrick Keenan, Vassilis Kitidis, Monika D. Jürgens, Adrian P. Martin, Ian Mounteney, Philip D. Nightingale, M. Glória Pereira, Justyna Olszewska, Amy Pickard, Andrew P. Rees, Bryan M. Spears, Mark Stinchcombe, Debbie White, Peter J. Williams, Fred Worrall, Chris Evans

Bibliographic record

VenueJournal of Hydrology · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsUniversity of Waterloo
FundersBiogeoscience Institute, University of CalgaryBritish Geological SurveyNatural Environment Research CouncilSight Research UKUK Research and Innovation
KeywordsDrainage basinDissolved organic carbonTotal inorganic carbonHydrology (agriculture)Environmental scienceCarbon cycleAtmosphere (unit)CarbonatePrecipitationFlux (metallurgy)Carbon dioxideGeologyOceanographyEcosystemChemistryGeographyEcology

Abstract

fetched live from OpenAlex

Dissolved inorganic carbon (DIC) fluxes from the land to ocean have been quantified for many rivers globally. However, CO2 fluxes to the atmosphere from inland waters are quantitatively significant components of the global carbon cycle that are currently poorly constrained. Understanding, the relative contributions of natural and human-impacted processes on the DIC cycle within catchments may provide a basis for developing improved management strategies to mitigate free CO2 concentrations in rivers and subsequent evasion to the atmosphere. Here, a large, internally consistent dataset collected from 41 catchments across Great Britain (GB), accounting for ∼36% of land area (∼83,997 km2) and representative of national land cover, was used to investigate catchment controls on riverine dissolved inorganic carbon (DIC), bicarbonate (HCO3−) and free CO2 concentrations, fluxes to the coastal sea and annual yields per unit area of catchment. Estimated DIC flux to sea for the survey catchments was 647 kt DIC yr−1 which represented 69% of the total dissolved carbon flux from these catchments. Generally, those catchments with large proportions of carbonate and sedimentary sandstone were found to deliver greater DIC and HCO3− to the ocean. The calculated mean free CO2 yield for survey catchments (i.e. potential CO2 emission to the atmosphere) was 0.56 t C km−2 yr−1. Regression models demonstrated that whilst river DIC (R2 = 0.77) and HCO3− (R2 = 0.77) concentrations are largely explained by the geology of the landmass, along with a negative correlation to annual precipitation, free CO2 concentrations were strongly linked to catchment macronutrient status. Overall, DIC dominates dissolved C inputs to coastal waters, meaning that estuarine carbon dynamics are sensitive to underlying geology and therefore are likely to be reasonably constant. In contrast, potential losses of carbon to the atmosphere via dissolved CO2, which likely constitute a significant fraction of net terrestrial ecosystem production and hence the national carbon budget, may be amenable to greater direct management via altering patterns of land use.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.093
Threshold uncertainty score0.184

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.001
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 head0.004
GPT teacher head0.172
Teacher spread0.168 · 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

Citations18
Published2022
Admission routes2
Has abstractyes

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