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Record W4383619934 · doi:10.1101/2023.07.07.548145

The Prokaryotic and Eukaryotic Microbiome of Pacific Oyster Spat is Shaped by Ocean Warming but not Acidification

2023· preprint· en· W4383619934 on OpenAlexafffund
Kevin Xu Zhong, Amy M. Chan, Brenna Collicutt, Maxim Daspe, Jan F. Finke, Megan Foss, Timothy J. Green, Christopher D. G. Harley, Amelia V. Hesketh, Kristina M. Miller, Sarah P. Otto, Kate Rolheiser, Rob Saunders, Ben Sutherland, Curtis A. Suttle

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2023
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicOcean Acidification Effects and Responses
Canadian institutionsFisheries and Oceans CanadaVancouver Island UniversityShell (Canada)Tula FoundationUniversity of British Columbia
FundersBritish Columbia Knowledge Development FundFisheries and Oceans CanadaHakai InstituteTula FoundationGordon and Betty Moore Foundation
KeywordsOcean acidificationMicrobiomeCrassostreaPacific oysterBiologyOysterEffects of global warming on oceansShellfishFisheryGlobal warmingEcologyClimate changeAquatic animalFish <Actinopterygii>Bioinformatics

Abstract

fetched live from OpenAlex

Abstract Pacific oysters ( Magallana gigas, also known as Crassostrea gigas ), the most widely farmed oysters, are under threat from climate change and emerging pathogens. In part, their resilience may be affected by their microbiome, which, in turn, may be influenced by ocean warming and acidification. Consequently, for three weeks, we exposed early-development Pacific oyster spat to different temperatures (18 and 24 °C) and p CO 2 levels (800, 1600 and 2800 µ atm) in a fully crossed design. Under all conditions, the microbiome developed over time, with potentially pathogenic ciliates ( Uronema marinum ) greatly reduced in all treatments, suggesting that the spat’s microbiome undergoes adaptive shifts as the oysters age. The microbiome composition also differed significantly with temperature, but not acidification, indicating that M. gigas spat microbiomes can be altered by ocean warming but resilient to ocean acidification in our experiments. These findings highlight the spat microbiome’s flexibility to environmental changes as well as its “protective” capability against potentially pathogenic microbes.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.627
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.203
Teacher spread0.187 · 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.

Study designBench or experimental
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

Citations2
Published2023
Admission routes2
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)Same topicOcean Acidification Effects and ResponsesFrench-language works237,207