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Record W1871013410 · doi:10.1111/jpy.12348

Seasonal differences in the effects of oscillatory and uni‐directional flow on the growth and nitrate‐uptake rates of juvenile <i>Laminaria digitata</i> (Phaeophyceae)

2015· article· en· W1871013410 on OpenAlexaff
Louise Kregting, Christopher D. Hepburn, Graham Savidge

Bibliographic record

VenueJournal of Phycology · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsQueen's University
FundersEngineering and Physical Sciences Research Council
KeywordsNitrateBiologyLaminaria digitataKelpGrowth rateNutrientNitrogenJuvenileEcologyBotanyChemistry

Abstract

fetched live from OpenAlex

The influence of oscillatory versus unidirectional flow on the growth and nitrate-uptake rates of juvenile kelp, Laminaria digitata, was determined seasonally in experimental treatments that simulated as closely as possible natural environmental conditions. In winter, regardless of flow condition (oscillatory and unidirectional) or water velocity, no influence of water motion was observed on the growth rate of L. digitata. In summer, when ambient nitrate concentrations were low, increased water motion enhanced macroalgal growth, which is assumed to be related to an increase in the rate of supply of nutrients to the blade surface. Nitrate-uptake rates were significantly influenced by water motion and season. Lowest nitrate-uptake rates were observed for velocities <5 cm · s(-1) and nitrate-uptake rates increased by 20%-50% under oscillatory motion compared to unidirectional flow at the same average speed. These data further suggested that the diffusion boundary layer played a significant role in influencing nitrate-uptake rates. However, while increased nitrate-uptake in oscillatory flow was clear, this was not reflected in growth rates and further work is required to understand the disconnection of nitrate-uptake and growth by L. digitata in oscillatory flow. The data obtained support those from related field-based studies, which suggest that in summer, when insufficient nitrogen is available in the water to saturate metabolic demand, the growth rate of kelps will be influenced by water motion restricting mass transfer of nitrogen.

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)0.001
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 score0.023
Threshold uncertainty score0.171

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.016
GPT teacher head0.204
Teacher spread0.187 · 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

Citations16
Published2015
Admission routes1
Has abstractyes

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