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Record W4292181077 · doi:10.1525/elementa.2021.00018

Particle cycling rates at Station P as estimated from the inversion of POC concentration data

2022· article· en· W4292181077 on OpenAlexaff
Vinícius J. Amaral, Phoebe J. Lam, Olivier Marchal, Montserrat Roca‐Martí, James Fox, Norman B. Nelson

Bibliographic record

VenueElementa Science of the Anthropocene · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsDalhousie University
FundersNuclear Safety and Security CommissionNational Aeronautics and Space AdministrationNational Science Foundation
KeywordsMesopelagic zonePhotic zoneWater columnDiel vertical migrationEnvironmental scienceSettlingOceanographyZooplanktonMarine snowBiological pumpFlux (metallurgy)Atmospheric sciencesPelagic zoneGeologyChemistryNutrientPhytoplankton

Abstract

fetched live from OpenAlex

Particle cycling rates in marine systems are difficult to measure directly, but of great interest in understanding how carbon and other elements are distributed throughout the ocean. Here, rates of particle production, aggregation, disaggregation, sinking, remineralization, and transport mediated by zooplankton diel vertical migration were estimated from size-fractionated measurements of particulate organic carbon (POC) concentration collected during the NASA EXport Processes in the Ocean from RemoTe Sensing (EXPORTS) cruise at Station P in summer 2018. POC data were combined with a particle cycling model using an inverse method. Our estimates of the total POC settling flux throughout the water column are consistent with those derived from thorium-234 disequilibrium and sediment traps. A budget for POC in two size fractions, small (1–51 µm) and large (> 51 µm), was produced for both the euphotic zone (0–100 m) and the upper mesopelagic zone (100–500 m). We estimated that POC export at the base of the euphotic zone was 2.2 ± 0.8 mmol m−2 d−1, and that both small and large particles contributed considerably to the total export flux along the water column. The model results indicated that throughout the upper 500 m, remineralization leads to a larger loss of small POC than does aggregation, whereas disaggregation results in a larger loss of large POC than does remineralization. Of the processes explicitly represented in the model, zooplankton diel vertical migration is a larger source of large POC to the upper mesopelagic zone than the convergence of large POC due to particle sinking. Positive model residuals reveal an even larger unidentified source of large POC in the upper mesopelagic zone. Overall, our posterior estimates of particle cycling rate constants do not deviate much from values reported in the literature, i.e., size-fractionated POC concentration data collected at Station P are largely consistent with prior estimates given their uncertainties. Our budget estimates should provide a useful framework for the interpretation of process-specific observations obtained by various research groups in EXPORTS. Applying our inverse method to other systems could provide insight into how different biogeochemical processes affect the cycling of POC in the upper water column.

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)0.001
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 score0.030
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.042
GPT teacher head0.290
Teacher spread0.249 · 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

Citations16
Published2022
Admission routes1
Has abstractyes

Explore more

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