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Record W2052439360 · doi:10.4319/lo.2000.45.7.1485

Inorganic carbon acquisition in coastal Pacific phytoplankton communities

2000· article· en· W2052439360 on OpenAlexfundno aff
Philippe D. Tortell, Greg H. Rau, François M. M. Morel

Bibliographic record

VenueLimnology and Oceanography · 2000
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaNational Science Foundation
KeywordsPhytoplanktonDiatomCyanobacteriaAlgaePhotosynthesisTotal inorganic carbonBiologyCarbon fixationBotanyEnvironmental chemistryPrimary productivityCarbon cycleEcologyNutrientChemistryCarbon dioxideBacteriaEcosystem

Abstract

fetched live from OpenAlex

Despite significant advances in the understanding of carbon acquisition in eukaryotic algae and cyanobacteria, very little information is available on the mechanisms of C uptake in natural phytoplankton communities or the effects of CO2 variations on marine primary productivity. In this article, we present the results of a 3‐yr study of C acquisition in coastal Pacific phytoplankton populations and their responses to experimental CO2 manipulations. Diatom‐dominated phytoplankton assemblages collected without incubation showed photosynthetic characteristics indicative of a carbon concentrating mechanism. Cells possessed a high affinity for external inorganic C (apparent Km ~1 µM CO2) and accumulated internal inorganic C pools that were ~3–5.5‐fold higher than those in the external medium. Evidence of in situ carbonic anhydrase expression was found in some of the phytoplankton populations we examined, and inhibitor experiments showed that this enzyme was essential for C fixation by cells. The presence of carbon concentrating mechanisms enabled the phytoplankton to maintain rapid growth rates over a wide range of CO2 concentrations (3–32 µM). In five of six long‐term (~2–5‐d) CO2 manipulation experiments, no difference in growth rates could be detected across treatments. However, a significant decrease in growth rate (30%) was observed in one experiment at the lowest CO2 level tested (3 mM). Although phytoplankton growth rates were generally unaffected by the CO2 manipulations, significant CO2‐dependent changes occurred in the cellular biochemistry and physiology of two assemblages that were examined. Cells grown at low CO2 showed higher short‐term rates of C uptake (indicative of transport system up‐regulation), as well as enhanced expression of Rubisco and carbonic anhydrase. In one of these two incubation experiments, lower C:N and carbohydrate:protein ratios were observed at low CO2 . Phytoplankton from both incubations showed low C isotope discrimination relative to the 13C/12C of the available CO2. Photosynthetic fractionation factors (ϵp) ranged from ~3.5‰ to 7.5‰ and were independent of both cellular growth rates and aqueous CO2 concentrations. Our data indicate that nutrient‐replete, rapidly growing coastal phytoplankton can use carbon concentrating mechanisms and respond physiologically and biochemically to changing dissolved CO2 concentrations. Future field studies should examine the effects of CO2 on the growth of nutrient‐limited phytoplankton and assess the potential long‐term ecological shifts that may result from CO2 variations.

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 score0.010
Threshold uncertainty score0.020

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 studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.006
GPT teacher head0.172
Teacher spread0.166 · 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

Citations204
Published2000
Admission routes1
Has abstractyes

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