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Record W4322503762 · doi:10.1111/faf.12730

Revisiting a central prediction of the Gill Oxygen Limitation Theory: Gill area index and growth performance

2023· article· en· W4322503762 on OpenAlexafffund
Jennifer S. Bigman, Nicholas C. Wegner, Nicholas K. Dulvy

Bibliographic record

VenueFish and Fisheries · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsSimon Fraser University
FundersNational Science Foundation of Sri LankaNatural Sciences and Engineering Research Council of Canada
KeywordsGillAllometryIndex (typography)Linear relationshipFish <Actinopterygii>BiologyEcologyFisheryStatisticsMathematics

Abstract

fetched live from OpenAlex

Abstract The Gill Oxygen Limitation Theory (GOLT) posits that a mismatch in oxygen supply and demand stemming from geometric constraints on gill surface area limits metabolic rate and energy available for biological processes. This theory has been suggested to explain numerous phenomena observed with warming yet is based upon a relationship among maximum size, growth, and gill surface area established over 40 years ago. However, the metric used in this relationship to characterize gill surface area, gill area index, fails to capture the known variability in the scaling of gill surface area and is biased by the sizes at which gills were measured. Here, we revisit a central prediction of the GOLT, asking four key questions that examine limitations in the original relationship. We find that gill area index does indeed explain variation in growth performance across 132 species of fish and this relationship is strikingly similar to the original relationship across 42 species. Yet, we argue that gill area index is not an adequate measure of gill surface area because (1) gill surface area has a non‐linear relationship with size and, thus, changes ontogenetically as an individual grows over time and (2) because it is based on mean estimates of both gill surface area and body mass. Indeed, we show that the value of gill area index for a given species is variable depending on how it is calculated. We therefore suggest a pathway forward for assessing whether gill surface area is an important factor in explaining variation in growth performance.

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 score0.017
Threshold uncertainty score0.214

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 integrity0.0000.000
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 head0.012
GPT teacher head0.172
Teacher spread0.160 · 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

Citations11
Published2023
Admission routes2
Has abstractyes

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