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Contrasting coral community structures between natural and artificial substrates at Koh Tao, Gulf of Thailand

2021· article· en· W3205185161 on OpenAlexaff
Coline Monchanin, Rahul Mehrotra, Elouise Haskin, Chad M. Scott, Pau Urgell Plaza, Alyssa Allchurch, Spencer Arnold, Kirsty Magson, Bert W. Hoeksema

Bibliographic record

VenueMarine Environmental Research · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicCoral and Marine Ecosystems Studies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsArtificial reefCoralCoral reefNatural (archaeology)ReefCommunity structureEcologySubstrate (aquarium)Recreational fishingOceanographySeafloor spreadingFisheryEnvironmental scienceRecreationGeographyBiologyGeologyArchaeology

Abstract

fetched live from OpenAlex

Concrete cubic frames and decommissioned steel naval vessels have been deployed in Thailand liberally to act as artificial substrates for coral restoration and marine recreation. We assessed recruitment at such substrate types at Koh Tao, Gulf of Thailand, and compared the community structure of scleractinian corals between artificial substrates and nearby natural reefs. Our results from a sample of 2677 recruits from nine sites highlighted significant differences in community structure between both reef types. Investigations of variables including time since deployment, distance from the natural reef, and seafloor depth revealed only the latter as a possible influencing factor. The diversity of recruits could not be explained by dynamics in coral spawning, and were found to represent groups with lower structural complexity. Our results suggest that coral community structure on artificial and natural reefs differs and supports distinct ecological and functional roles.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.047
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.054
GPT teacher head0.298
Teacher spread0.244 · 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 source (direct Gemma or distilled Codex), 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

Citations28
Published2021
Admission routes1
Has abstractno

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