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Record W4416259785 · doi:10.1111/ele.70263

Marine Heatwaves Transform Coral Symbioses With Enduring Effects

2025· article· en· W4416259785 on OpenAlexafffund
Alexander Van Nynatten, Ross Cunning, Kristina L. Tietjen, Julia K. Baum

Bibliographic record

VenueEcology Letters · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicCoral and Marine Ecosystems Studies
Canadian institutionsUniversity of Victoria
FundersNational Geographic SocietyCentre for Asia-Pacific InitiativesPew Charitable TrustsBritish Columbia Knowledge Development FundNatural Sciences and Engineering Research Council of CanadaRufford FoundationDavid and Lucile Packard Foundation
KeywordsCoralObligateCoral reefCoral bleachingSymbiodiniumSymbiosisClimate change

Abstract

fetched live from OpenAlex

Climate change-amplified extreme weather events are reshaping ecological communities globally. On coral reefs, heatwaves typically disrupt the obligate coral-algal symbiosis, with symbiont identity a prime determinant of coral resilience to these thermal extremes. Yet, whether heatwaves have long-term effects on coral symbioses remains unclear due to a lack of longitudinal symbiont data. Here, we report on a decadal coral symbiont survey (2013-2023), spanning the most prolonged tropical marine heatwave on record (2015-2016) and its aftermath. Concomitant with mass coral mortality, we document wholesale transformation of the symbiont assemblages in two coral species, the legacy of which was persistent for 7 years post heatwave. We also found evidence suggestive of a symbiont's local extinction, of local human disturbance impeding symbiont recovery, and of new coral recruits hosting symbiont assemblages distinct from survivors. Our study demonstrates heatwaves can have long-lasting impacts on symbioses raising concern for coral resilience to future heatwaves.

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)0.001
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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.002
GPT teacher head0.173
Teacher spread0.171 · 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

Citations3
Published2025
Admission routes2
Has abstractyes

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