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Record W4308723457 · doi:10.3389/fmars.2022.1021675

Comparison of macroalgae meadows in warm Atlantic versus cold Arctic regimes in the high-Arctic Svalbard

2022· article· en· W4308723457 on OpenAlexaff
Józef Wiktor, Agnieszka Tatarek, Aleksandra Kruss, Rakesh Kumar Singh, Janne E. Søreide

Bibliographic record

VenueFrontiers in Marine Science · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsUniversité du Québec à Rimouski
FundersNorges ForskningsrådBiodiversa+National Aeronautics and Space Administration
KeywordsThallusArcticOceanographyKelpAlgaeArctic ice packSea iceSaccharinaEnvironmental scienceEcologyLaminariaBiologyGeologyBotany

Abstract

fetched live from OpenAlex

A warmer Arctic with less sea ice will likely improve macroalgae growth conditions, but observational data to support this hypothesis are scarce. In this study, we combined hydroacoustic and video inspections to compare the depth of growth, density and thickness of macroalgae (>10 cm) meadows in two contrasting climate regimes in Svalbard 1) the warm, ice free, Atlantic influenced West Spitsbergen and 2) the cold, Arctic and seasonal ice covered East Spitsbergen. Both places had similar insolation and comparable turbidity levels. Macroalgae communities at both places were similar and were formed mainly by common north Atlantic kelp species: Saccharina latissima, Alaria esculenta, Laminaria digitata and L. hyperborea . However, the density of the bottom coverage and thalli condition were strikingly different between the two sites. Algae at the warmer site were intact and fully developed and occupied most of the available hard substrate. At the colder site, only patchy macroalgae canopies were found and most thallies were physically damaged and trimmed at a uniform height due to physical ice scouring. These differences in macroalgal density and thalli condition were only found at depths down to 5 m. Deeper, no distinct differences were observed between the warm and cold sites. Sea urchins were only observed at the warm site, but in few numbers with no visible negative top-down control on macroalgae growth.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.043
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.017
GPT teacher head0.240
Teacher spread0.223 · 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 teacher head, 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

Citations14
Published2022
Admission routes1
Has abstractyes

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