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Record W2505200869 · doi:10.5194/bg-14-1235-2017

Spring phytoplankton communities of the Labrador Sea (2005–2014): pigment signatures, photophysiology and elemental ratios

2017· article· en· W2505200869 on OpenAlexaffabout
Glaucia M. Fragoso, Alex J. Poulton, Igor Yashayaev, Erica Head, Duncan A. Purdie

Bibliographic record

VenueBiogeosciences · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsBedford Institute of OceanographyFisheries and Oceans Canada
FundersAustralian Antarctic DivisionCiência sem FronteirasNatural Environment Research CouncilConselho Nacional de Desenvolvimento Científico e TecnológicoSight Research UK
KeywordsPhytoplanktonOceanographyBiogeochemical cycleSpring bloomDiatomChlorophyll aHydrographyEnvironmental scienceBloomArcticDeep chlorophyll maximumEcologyBiologyGeologyPhotic zoneBotanyNutrient

Abstract

fetched live from OpenAlex

Abstract. The Labrador Sea is an ideal region to study the biogeographical, physiological, and biogeochemical implications of phytoplankton community composition due to sharp transitions between distinct water masses across its shelves and central basin. We have investigated the multi-year (2005–2014) distributions of late spring and early summer (May to June) phytoplankton communities in the various hydrographic settings of the Labrador Sea. Our analysis is based on pigment markers (using CHEMTAX analysis), and photophysiological and biogeochemical characteristics associated with each phytoplankton community. Diatoms were the most abundant group, blooming first in shallow mixed layers of haline-stratified Arctic shelf waters. Along with diatoms, chlorophytes co-dominated at the western end of the section (particularly in the polar waters of the Labrador Current (LC)), whilst Phaeocystis co-dominated in the east (modified polar waters of the West Greenland Current (WGC)). Pre-bloom conditions occurred in deeper mixed layers of the central Labrador Sea in May, where a mixed assemblage of flagellates (dinoflagellates, prasinophytes, prymnesiophytes, particularly coccolithophores, and chrysophytes/pelagophytes) occurred in low-chlorophyll areas, succeeding to blooms of diatoms and dinoflagellates in thermally stratified Atlantic waters in June. Light-saturated photosynthetic rates and saturation irradiance levels were highest at stations where diatoms were the dominant phytoplankton group ( > 70 % of total chlorophyll a), as opposed to stations where flagellates were more abundant (from 40 up to 70 % of total chlorophyll a). Phytoplankton communities from the WGC (Phaeocystis and diatoms) had lower light-limited photosynthetic rates, with little evidence of photoinhibition, indicating greater tolerance to a high light environment. By contrast, communities from the central Labrador Sea (dinoflagellates and diatoms), which bloomed later in the season (June), appeared to be more sensitive to high light levels. Ratios of accessory pigments (AP) to total chlorophyll a (TChl a) varied according to phytoplankton community composition, with polar phytoplankton (cold-water related) having lower AP : TChl a. Polar waters (LC and WGC) also had higher and more variable particulate organic carbon (POC) to particulate organic nitrogen (PON) ratios, suggesting the influence of detritus from freshwater input, derived from riverine, glacial, and/or sea ice meltwater. Long-term observational shifts in phytoplankton communities were not assessed in this study due to the short temporal frame (May to June) of the data. Nevertheless, these results add to our current understanding of phytoplankton group distribution, as well as an evaluation of the biogeochemical role (in terms of C : N ratios) of spring phytoplankton communities in the Labrador Sea, which will assist our understanding of potential long-term responses of phytoplankton communities in high-latitude oceans to a changing climate.

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 score0.009
Threshold uncertainty score0.841

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.013
GPT teacher head0.209
Teacher spread0.196 · 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

Citations38
Published2017
Admission routes2
Has abstractyes

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