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Record W4406108456 · doi:10.1038/s42003-024-07433-6

Invasive macroalgae shape chemical and microbial waterscapes on coral reefs

2025· article· en· W4406108456 on OpenAlexfundno aff
Chloé Pozas‐Schacre, Hugo Bischoff, Delphine Raviglione, Slimane Chaïb, Camille Clérissi, Isabelle Bonnard, Maggy M. Nugues

Bibliographic record

VenueCommunications Biology · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicCoral and Marine Ecosystems Studies
Canadian institutionsnot available
FundersAgence Nationale de la RechercheGénome Québec
KeywordsBenthic zoneCoral reefReefCoralEcologyDominance (genetics)BiologyResilience of coral reefsOrganic matterEpiphyteOceanographyGeology

Abstract

fetched live from OpenAlex

Over the past decades, human impacts have changed the structure of tropical benthic reef communities towards coral depletion and macroalgal proliferation. However, how these changes have modified chemical and microbial waterscapes is poorly known. Here, we assessed how the experimental removal of macroalgal assemblages influences the chemical and microbial composition of two reef boundary layers, the benthic and the momentum. Chemical and microbial waterscapes were spatially structured, both horizontally and vertically, according to macroalgal dominance and boundary layers. Microbes associated with reef degradation were enriched in the boundary layers surrounding macroalgal-dominated substrata. Dominant macroalgae were surrounded by a distinct chemical pool of diverse lipid classes (e.g., diterpenoids and glycerolipids) and labile organic matter (e.g., organooxygen compounds), which diffused from algal tissues to boundary layers according to their polarity. Finally, our results highlighted strong co-variations between specific algal-derived metabolites and planktonic microbes, giving insight into their roles in coral reef functioning and resilience.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.600
Threshold uncertainty score0.256

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 science0.0000.002
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 head0.017
GPT teacher head0.259
Teacher spread0.243 · 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

Citations7
Published2025
Admission routes1
Has abstractyes

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