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Record W3095562531 · doi:10.1098/rspb.2020.1947

Microplastic exposure interacts with habitat degradation to affect behaviour and survival of juvenile fish in the field

2020· article· en· W3095562531 on OpenAlexaff
Mark I. McCormick, Douglas P. Chivers, Maud C. O. Ferrari, Makeely I. Blandford, Gerrit B. Nanninga, Celia Richardson, Eric P. Fakan, George Vamvounis, Alexandra M. Gulizia, Bridie J. M. Allan

Bibliographic record

VenueProceedings of the Royal Society B Biological Sciences · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsUniversity of Saskatchewan
FundersAustralian Research CouncilEuropean Commission
KeywordsMicroplasticsReefHabitatCoralEcologyCoral reefCoral reef fishBiologyFisheryEnvironmental science

Abstract

fetched live from OpenAlex

Coral reefs are degrading globally due to increased environmental stressors including warming and elevated levels of pollutants. These stressors affect not only habitat-forming organisms, such as corals, but they may also directly affect the organisms that inhabit these ecosystems. Here, we explore how the dual threat of habitat degradation and microplastic exposure may affect the behaviour and survival of coral reef fish in the field. Fish were caught prior to settlement and pulse-fed polystyrene microplastics six times over 4 days, then placed in the field on live or dead-degraded coral patches. Exposure to microplastics or dead coral led fish to be bolder, more active and stray further from shelter compared to control fish. Effect sizes indicated that plastic exposure had a greater effect on behaviour than degraded habitat, and we found no evidence of synergistic effects. This pattern was also displayed in their survival in the field. Our results highlight that attaining low concentrations of microplastic in the environment will be a useful management strategy, since minimizing microplastic intake by fishes may work concurrently with reef restoration strategies to enhance the resilience of coral reef populations.

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 score0.143

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 head0.016
GPT teacher head0.224
Teacher spread0.208 · 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

Citations78
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the Royal Society B Biological SciencesSame topicMicroplastics and Plastic PollutionFrench-language works237,207