MétaCan
Menu
Back to cohort
Record W4388109653 · doi:10.3390/jmse11112063

Spatial Variability in the Primary Production Rates and Biomasses (Chl a) of Sea Ice Algae in the Canadian Arctic–Greenland Region: A Review

2023· review· en· W4388109653 on OpenAlexaboutno aff
Laura Martín García, Brian K. Sorrell, Dorte Haubjerg Søgaard, Lars Chresten Lund–Hansen

Bibliographic record

VenueJournal of Marine Science and Engineering · 2023
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicFood Industry and Aquatic Biology
Canadian institutionsnot available
FundersEuropean Commission
KeywordsOceanographyAlgaeSea iceArcticEnvironmental scienceGroenlandiaThe arcticArctic ice packPrimary (astronomy)ClimatologyPhysical geographyGeographyGeologyEcologyIce sheetBiology

Abstract

fetched live from OpenAlex

The aims of this review are to elucidate the spatial variation in the primary production rates and biomasses (Chl a) of sea ice algae in the Canadian Arctic–Greenland region, characterized by its comparable physical settings. A database was compiled from 30 studies of the production rates and biomasses (Chl a) of sea ice algae, the snow and ice thicknesses, ice types, nutrients (Si(OH)4, PO4, (NO3 + NO2)), and NH4 concentrations in the ice and below the ice from the region. Production rates were significantly higher (463 mg C m−2 d−1) in Resolute Bay and Northern Baffin Bay (317 mg C m−2 d−1), both in the Canadian Arctic, compared to a rate of 0.2 mg C m−2 d−1 in northeast Greenland. The biomasses reached 340 mg Chl a m−2 in Resolute Bay in comparison to 0.02 mg Chl a m−2 in southwest Greenland. Primary production at other Canadian and Greenland sites was comparable, but sea ice Chl a was higher (15.0 ± 13.4 mg Chl a m−2) at Canadian sites compared to Greenland ones (0.8 ± 0.5 mg Chl a m−2). Resolute and Northern Baffin Bay production rates were significantly higher when compared to other Arctic Ocean sites outside the studied region. The review concludes that the high production rates and biomasses in Resolute and Northern Baffin Bay are related to the inflow and mixing of nutrient-rich waters of Pacific origin. A conceptual model with drivers and inhibitors of the primary production of sea ice algae is proposed, and the database is compiled into a dataset of published data for further studies.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.992
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.063
GPT teacher head0.271
Teacher spread0.208 · 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 designOther design
Domainnot available
GenreReview

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

Citations5
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Marine Science and EngineeringSame topicFood Industry and Aquatic BiologyFrench-language works237,207