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Record W4392585925 · doi:10.5194/egusphere-egu24-4078

Late Holocene calcium carbonate accumulation in a cold-water coral mound in the northern Bay of Biscay.

2024· preprint· en· W4392585925 on OpenAlexaff
Evan Edinger, Jean‐François Bourillet, Lénàïck Menot

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicCoral and Marine Ecosystems Studies
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsCoralBayHoloceneOceanographyGeologyCarbonateCalcium carbonateChemistry

Abstract

fetched live from OpenAlex

Cold-water coral reefs and communities can be locally important calcium carbonate factories in continental shelf and slope environments. Cold-water coral mounds dominated by Desmophyllum pertusum (=Lophelia pertusa) occur within Bay of Biscay submarine canyons. Here we present a late Holocene record of coral carbonate accumulation through a colonial scleractinian coral mound in the 750-850 m depth range in Guilvinec Canyon, northern Bay of Biscay. Guilvinec Canyon, like most submarine canyons of the Bay of Biscay, is a dominantly siliciclastic sandy environment, with occasional coral gardens. Maximum live coral cover in the area surveyed in Guilvinec Canyon was about 9%, measured close to the site of the sediment core analyzed.A 2011 sediment core through the mound recovered 1.18 m of sediment, consisting of mostly siliciclastic silty sand and coral gravel, strongly dominated by Lophelia pertusa fragments. In addition to standard geophysical, grain size, and mineralogical analyses, the core was analyzed by CT-scan. The number of coral calices visible per cm3 was counted, and the core was subsampled for coral calice abundance and mass in 5 mm increments, calculating the number of calices and mass of coral carbonate skeletons per cm3 subsample. An age model from previous 14C and U/Th ages of coral fragments in the core yielded a long-term average coral carbonate accretion rate of 78 g CaCO3 m-2 y-1 over the past ~2150 y, divided into two phases: 40.8 g CaCO3 m-2 y-1 (from core-bottom to -59 cm, approximately 685 ybp), and 156.2 g CaCO3 m-2 y-1 in the upper half of the core. Coarse coral-dominated gravel in the core-catcher contained coral fragments approximately 7 ka in age, indicating a long hiatus before the renewal of coral growth at this site. Aragonite % in the fine sediment was not correlated with coral abundance in the core. A second core recovered nearby was composed of siliciclastic silty sand, but contained almost no coral fragments. The large variation between the two cores indicates high levels of local heterogeneity in sediment accumulation patterns, apparently much greater than the variation in live coral cover at the surface.Coral carbonate accumulation rates in Guilvinec Canyon were 1-2 orders of magnitude lower than coral carbonate accumulation estimates from Lophelia pertusa reefs on the Norwegian Margin. Nonetheless, coral carbonate accumulation rates in the core were an order of magnitude higher than Recent coral carbonate production rates based on ROV-video estimates of coral biomass and published growth rates. This difference may be attributable to time-averaging, local heterogeneity, changes in sedimentation or current regime, or to late-20th century decline in coral abundance resulting from a variety of anthropogenic pressures. Recent threats to Bay of Biscay cold-water coral reefs include increased sediment mobilization from bottom trawling near the heads of submarine canyons, rising seawater temperatures, and declining aragonite saturation. New field and lab experiments on coral growth rates and skeletal degradation may help to disentangle anthropogenic pressures and project the fate of Bay of Biscay cold-water coral reefs in the face of climate change and ocean acidification.

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 score0.340
Threshold uncertainty score0.675

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
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 head0.037
GPT teacher head0.275
Teacher spread0.238 · 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
Published2024
Admission routes1
Has abstractyes

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