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Record W4296516538 · doi:10.3389/fmars.2022.933823

Apparent shifts in the microplankton community in response to zinc and iron enrichments in the Northeastern Subarctic Pacific

2022· article· en· W4296516538 on OpenAlexaff
David W. Crawford, Duncan A. Purdie, Maeve C. Lohan, Peter J. Statham, Tawnya D. Peterson, Hilary Kennedy, Michael S. Lipsen, Jennifer Putland, Frank A. Whitney

Bibliographic record

VenueFrontiers in Marine Science · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsFisheries and Oceans CanadaUniversity of British Columbia
FundersDivision of Ocean SciencesNatural Environment Research CouncilUniversity of Southampton
KeywordsSubarctic climatePhytoplanktonChlorophyll aEnvironmental chemistryNitrateOceanographyChemistryBiomass (ecology)NutrientEnvironmental scienceGeology

Abstract

fetched live from OpenAlex

The offshore Gulf of Alaska—in the northeastern subarctic Pacific—is a high-nitrate, low-chlorophyll (HNLC) oceanic region where concentrations of dissolved iron (DFe) and zinc (DZn) are of the order ~0.1 nmol kg−1 in surface waters. At the average winter mixed layer depth of ~120 m, DFe and DZn are of the orders ~0.1–0.2 nmol kg−1 and ~1–2 nmol kg−1, respectively. Vertical supply of Fe to surface waters is therefore limited, with phytoplankton blooms driven by episodic atmospheric and lateral inputs of Fe. In contrast, DZn is presumably replenished through seasonal vertical mixing, though maintained at low levels in surface waters, even in winter, implying that removal processes are in operation. Previous supplementation experiments have demonstrated that phytoplankton biomass (chl-a), growth, and drawdown of nitrate (NO3-) are stimulated strongly by Fe but only minimally, if at all, by Zn alone. Using on-deck bioassay incubations of surface waters, we confirm that the addition of Fe stimulates significant increases in chl-a and large diatoms, and drawdown of NO3- and silicic acid [Si(OH)4]. Associated drawdown of DZn and dissolved cadmium (DCd) indicated Zn stress in the control and +Fe treatment. Supplementation with Zn alone had no significant impact on NO3- and commonly monitored pigments such as chl-a and fucoxanthin. However, in the +Zn treatment, DFe and coccolithophore abundance were significantly lower, and the concentration of particulate organic carbon (POC) and that of the pigments alloxanthin and chlorophyll c1+2 were significantly higher than those in control incubations. Our experiment corroborates previously observed relationships between DZn and alloxanthin and chlorophyll c across the subarctic north Pacific and Bering Sea and could help to explain the low or undetectable concentrations of alloxanthin frequently observed in this region. Alloxanthin is a pigment specific to the cryptophytes, either within free-living cells or within functional plastids retained by mixotrophic protists. Both cryptophytes and mixotrophic ciliates, such as Laboea sp. and Strombidium spp., make a variable but significant contribution to phytoplankton biomass in this area. In the absence of Fe supply to surface waters, Zn could play a hitherto unsuspected role in shaping plankton communities in the HNLC Gulf of Alaska.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.209
Teacher spread0.199 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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