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Record W7034503035

What do marine particle characteristics and dynamics tell us about the efficiency of the Biological Carbon Pump?

2023· other· en· W7034503035 on OpenAlexaboutno aff

Bibliographic record

VenueeScholarship (California Digital Library) · 2023
Typeother
Languageen
FieldArts and Humanities
TopicCultural Heritage Materials Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsMarine snowBiological pumpExopolymerBiogeochemical cycleSubarctic climateParticle (ecology)RemineralisationTotal organic carbonCarbon fibersWater column
DOInot available

Abstract

fetched live from OpenAlex

Gravitational sinking of particles is a key pathway for the transport of particulate organic carbon (POC) into the deep ocean. The sinking of POC and its remineralization directly impact ocean carbon storage on climatologically relevant timescales. Particle size, density and composition influence particle sinking velocity and the remineralization length scale i.e., the depth where POC is converted to suspended organic carbon or inorganic carbon. However, the factors affecting this relationship and their spatiotemporal variability are not well understood. Here, we use data collected from Marine Snow Catchers to characterize profiles of both suspended and sinking particles. Particle size, biogeochemical composition, and microbial activity are used to understand the controls and fate of suspended and sinking POC in the upper ocean. My first chapter shows that during the late summer in the subarctic Pacific POC fluxes were low, marine snow-sized aggregates (d > 0.5 mm) were rare and small, suspended particles differed from small sinking particles by their higher TEP (transparent exopolymer particles) content. This work provides the first in situ data to support the hypothesis by Xavier et al. (2017) that the ratio between TEP-C and POC determines, at least partially, the efficiency of the biological carbon pump (i.e., POC flux 100 m below reference depth/flux at reference depth).My second chapter focuses on the decline of the spring diatom bloom in the NE Atlantic and shows that turbulent disaggregation and changes in the mixed layer depth due to four strong storms delayed the formation and sinking of POC-rich marine snow-sized aggregates (d > 0.1 mm) while small, slow-sinking silica-rich particles sank from the mixed layer, creating an inefficient POC export event. After the last storm passed, we observed the sinking of marine snow aggregates, which resulted in vertical flux of a mixed post-bloom plankton community out of the euphotic zone.\nMy third chapter focuses on a study conducted in the Labrador Sea, where microbial degradation of total organic carbon (TOC) differed between suspended and sinking particles and across different stages of a spring Phaeocystis bloom. Carbon removal rates for fast-sinking and slow-sinking particles were similar but were on average one order of magnitude larger than those found for the suspended fraction. However, at the station characterized by abundant free-floating Phaeocystis colonies, the suspended fraction sustained a TOC removal rate similar to the ones for sinking particles. This observation suggests that the presence of Phaeocystis colonies may have enhanced the rate of microbial degradation of TOC. \nOverall, this work highlights the importance of investigating characteristics and dynamics of suspended and sinking particles to understand which factors affect the efficiency of the biological carbon pump in different open ocean systems.\n

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)0.004
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 score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0030.004
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.020
GPT teacher head0.200
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

Citations0
Published2023
Admission routes1
Has abstractyes

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