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Record W2099095738 · doi:10.1098/rspb.2007.1283

Scents and scents-ability: pollution disrupts chemical social recognition and shoaling in fish

2007· article· en· W2099095738 on OpenAlexafffund
Ashley J. W. Ward, Alison J. Duff, Jennifer S Horsfall, Suzanne Currie

Bibliographic record

VenueProceedings of the Royal Society B Biological Sciences · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsMount Allison University
FundersNatural Sciences and Engineering Research Council of CanadaFisheries Society of the British Isles
KeywordsShoaling and schoolingFish <Actinopterygii>PollutionCommunicationFisheryPsychologyEcologyBiology

Abstract

fetched live from OpenAlex

Chemical cues are of enormous importance in mediating the behaviour of animals, enabling them to navigate throughout their habitats, to detect the presence of predators or prey and for social recognition-identifying and discriminating between conspecifics. In many species of freshwater fish, social recognition is known to be based primarily on chemical cues. Such recognition mechanisms are vulnerable to disruption by the presence of anthropogenic contaminants in the aquatic environment. Here we show that acute exposure to low, environmentally relevant dosages of the ubiquitous contaminant, 4-nonylphenol, can seriously affect social recognition and ultimately social organization in fishes. A 1 hour 0.5 microgl-1 dose was sufficient to alter the response of members of a shoaling fish species (juvenile banded killifish, Fundulus diaphanus) to conspecific chemical cues. Dosages of 1-2 microgl-1 caused killifish to orient away from dosed conspecifics, in both a flow channel and an arena. Given the overall importance of shoaling as an adaptive strategy against predators and for locating food, it is likely that its disruption by anthropogenic contaminants would have serious implications for fishes' fitness.

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)0.002
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 score0.175
Threshold uncertainty score0.752

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
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 head0.032
GPT teacher head0.257
Teacher spread0.226 · 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

Citations92
Published2007
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the Royal Society B Biological SciencesSame topicToxic Organic Pollutants ImpactFrench-language works237,207