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Record W4407983151 · doi:10.5194/bg-22-1057-2025

Spatial distributions of iron and manganese in surface waters of the Arctic's Laptev and East Siberian seas

2025· article· en· W4407983151 on OpenAlexfundno aff
Naoya Kanna, Kazutaka Tateyama, Takuji Waseda, Anna Timofeeva, Maria Papadimitraki, Laura M. Whitmore, Hajime Obata, Daïki Nomura, Hiroshi Ogawa, Youhei Yamashita, Igor V. Polyakov

Bibliographic record

VenueBiogeosciences · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and environmental studies
Canadian institutionsnot available
FundersMinistry of Education, Culture, Sports, Science and TechnologyResearch Institute for Oceanochemistry FoundationAlberta Agricultural Research Institute
KeywordsManganeseArcticOceanographyThe arcticSpatial distributionEnvironmental scienceGeologyGeographyChemistryRemote sensing

Abstract

fetched live from OpenAlex

Abstract. The Arctic Laptev and East Siberian seas (LESS) have high biogeochemical activity. Nutrient inputs associated with river runoff and shelf sediment–water exchange processes are vital for supporting primary production in the LESS. Relative to macronutrients, data on dissolved iron (dFe) and manganese (dMn), which are essential micronutrients for primary producers, have historically been sparse for LESS. Some dFe and dMn are reportedly carried in the central Arctic by the Transpolar Drift, a major current that directly transports Eurasian shelf water, river water, and sea ice from the LESS continental margins. However, the supply of dFe and dMn to the surface waters of the LESS and the subsequent biogeochemical processes are not well constrained. In the summer of 2021, we investigated the following questions: what are the sources of dFe and dMn in the surface layer and which factors control their concentrations and distributions on the LESS continental margins? We demonstrated strong regional controls on dFe and dMn distributions based on distinct hydrographic regimes between the eastern side of the LESS (East Siberian Sea and Chukchi Abyssal Plain) and the western side (Makarov and Amundsen basins). Specifically, the East Siberian Sea and Chukchi Abyssal Plain were governed by Pacific-sourced water, and the Makarov and Amundsen basins were influenced by Atlantic-sourced water. Pacific-sourced water contained higher levels of dMn released from continental shelf sediments than Atlantic-sourced water. In contrast, elevated dFe signals were not observed, likely because sedimentary dFe was more rapidly removed from the water column through oxidation or scavenging than dMn was. The impact of river water discharge on the dFe distributions of Pacific- and Atlantic-sourced water was significant. A positive correlation between the fraction of meteoric water (river water and precipitation), dFe, and humic-like colored dissolved organic matter (CDOM) in these waters confirmed that dFe and CDOM are common freshwater sources. Terrigenous organic ligands likely stabilize Fe in the dissolved phase, which is not the case for Mn. Sea ice melting and formation were not significant sources during the observation period. We conclude that the major sources controlling the dFe and dMn distributions on the LESS continental margins are river discharge and shelf sediment input.

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)0.000
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 score0.032
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.007
GPT teacher head0.181
Teacher spread0.175 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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