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INTERACTIVE EFFECTS OF IRRADIANCE AND TEMPERATURE ON THE PHOTOSYNTHETIC PHYSIOLOGY OF THE PENNATE DIATOM <i>PSEUDO‐NITZSCHIA GRANII</i> (BACILLARIOPHYCEAE) FROM THE NORTHEAST SUBARCTIC PACIFIC<sup>1</sup>

2006· article· en· W2059912249 on OpenAlexaff
Rana W. El‐Sabaawi, Paul J. Harrison

Bibliographic record

VenueJournal of Phycology · 2006
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSubarctic climateDiatomPhotosynthesisBiologyIrradiancePhytoplanktonChlorophyll aBotanyPhotoinhibitionAlgaeChlorophyllNitzschiaPhotosynthetic efficiencyEcologyPhotosystem IINutrient

Abstract

fetched live from OpenAlex

This study examined how light and temperature interact to influence growth rates, chl a , and photosynthetic efficiency of the oceanic pennate diatom Pseudo‐nitzschia granii Hasle, isolated from the northeast subarctic Pacific. Growth rates were modulated by both light and temperature, although for each irradiance tested, the growth rate was always the greatest at ∼14°C. Chl a per cell was affected primarily by temperature, except at the maximum chl a per cell (at 10°C) where the effects of light were noticeable. At both ends of the temperature gradient, cells displayed evidence of chlorosis even at low light intensities. Chl fluorescence data suggested that cells at 8°C were significantly more efficient in their photosynthetic processes than cells at 20°C, despite having comparable concentrations of chl. Cells at low temperature showed photosynthetic characteristics similar to high‐irradiance‐adapted cells. The decline of growth rates beyond the optimum growth temperature coincided with the cell's inability to accumulate chl in response to increasing temperature. The decline in photosynthetic ability at 20°C was likely due to a combination of high‐temperature stress on cellular membranes and a decline in chl. Our results highlight the important interactions between light and temperature and the need to incorporate these interactions into the development of phytoplankton models for the subarctic Pacific.

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 score0.115
Threshold uncertainty score0.490

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.003
GPT teacher head0.157
Teacher spread0.154 · 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

Citations33
Published2006
Admission routes1
Has abstractyes

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