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Record W4377205929 · doi:10.3389/fevo.2023.1083315

Acidification and hypoxia drive physiological trade-offs in oysters and partial loss of nutrient cycling capacity in oyster holobiont

2023· article· en· W4377205929 on OpenAlexaff
Deevesh A. Hemraj, Laura J. Falkenberg, Khan Cheung, Lauren Man, Alessia Carini, Bayden D. Russell

Bibliographic record

VenueFrontiers in Ecology and Evolution · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOcean Acidification Effects and Responses
Canadian institutionsUniversity of Victoria
FundersChinese University of Hong KongUniversity of Hong Kong
KeywordsCyclingOysterHolobiontHypoxia (environmental)EcologyNutrientEnvironmental scienceNutrient cycleBiologyOcean acidificationPolychaeteOceanographyChemistryOxygenClimate changeSymbiosisBacteriaGeology

Abstract

fetched live from OpenAlex

Introduction Reef building oysters provide vast ecological benefits and ecosystem services. A large part of their role in driving ecological processes is mediated by the microbial communities that are associated with the oysters; together forming the oyster holobiont. While changing environmental conditions are known to alter the physiological performance of oysters, it is unclear how multiple stressors may alter the ability of the oyster holobiont to maintain its functional role. Methods Here, we exposed oysters to acidification and hypoxia to examine their physiological responses (molecular defense and immune response), changes in community structure of their associated microbial community, and changes in water nutrient concentrations to evaluate how acidification and hypoxia will alter the oyster holobiont’s ecological role. Results We found clear physiological stress in oysters exposed to acidification, hypoxia, and their combination but low mortality. However, there were different physiological trade-offs in oysters exposed to acidification or hypoxia, and the combination of stressors incited greater physiological costs (i.e., >600% increase in protein damage and drastic decrease in haemocyte counts). The microbial communities differed depending on the environment, with microbial community structure partly readjusted based on the environmental conditions. Microbes also seemed to have lost some capacity in nutrient cycling under hypoxia and multi-stressor conditions (~50% less nitrification) but not acidification. Discussion We show that the microbiota associated to the oyster can be enriched differently under climate change depending on the type of environmental change that the oyster holobiont is exposed to. In addition, it may be the primary impacts to oyster physiology which then drives changes to the associated microbial community. Therefore, we suggest the oyster holobiont may lose some of its nutrient cycling properties under hypoxia and multi-stressor conditions although the oysters can regulate their physiological processes to maintain homeostasis on the short-term.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.280

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 science0.0000.000
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 head0.019
GPT teacher head0.213
Teacher spread0.194 · 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

Citations10
Published2023
Admission routes1
Has abstractyes

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