MétaCan
Menu
Back to cohort
Record W3023482817 · doi:10.1139/er-2019-0076

Size does matter — the eco-evolutionary effects of changing body size in fish

2020· article· en· W3023482817 on OpenAlexfundvenueno aff
Pauliina A. Ahti, Anna Kuparinen, Silva Uusi‐Heikkilä

Bibliographic record

VenueEnvironmental Reviews · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaEmil Aaltosen SäätiöSuomen Kulttuurirahasto
KeywordsPredationEcologyBiologyEcosystemPopulation sizeFishingPopulationFecundity

Abstract

fetched live from OpenAlex

Body size acts as a proxy for many fitness-related traits. Body size is also subject to directional selection from various anthropogenic stressors such as increasing water temperature, decreasing dissolved oxygen, fisheries, as well as natural predators. Changes in individual body size correlate with changes in fecundity, behaviour, and survival and can propagate through populations and ecosystems by truncating age and size structures and changing predator–prey dynamics. In this review, we will explore the causes and consequences of changing body size in fish in the light of recent literature and relevant theories. We will investigate the central role of body size in ecology by first discussing the main selective agents that influence body size: fishing, increasing water temperature, decreasing dissolved oxygen, and predation. We will then explore the impacts of these changes at the individual, population, and ecosystem levels. Considering the relatively high heritability of body size, we will discuss how a change in body size can leave a genetic signature in the population and translate to a change in the evolutionary potential of the species.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score0.999

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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.002

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 head0.005
GPT teacher head0.194
Teacher spread0.189 · 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; both teacher heads agree on what is shown here.

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

Citations80
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueEnvironmental ReviewsSame topicFish Ecology and Management StudiesFrench-language works237,207