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Record W4401451615 · doi:10.1007/s11356-024-34618-7

Investigating intraspecific variability in the biological responses of sea urchins (Paracentrotus lividus) to seawater acidification

2024· article· en· W4401451615 on OpenAlexaff
Davide Asnicar, Federica Stranci, Silvia Monti, Denis Badocco, Tihana Marčeta, Marco Munari, María Gabriella Marin

Bibliographic record

VenueEnvironmental Science and Pollution Research · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOcean Acidification Effects and Responses
Canadian institutionsHuntsman Marine Science Centre
FundersUniversità degli Studi di Padova
KeywordsParacentrotus lividusSea urchinIntraspecific competitionOcean acidificationBiologySeawaterStrongylocentrotus droebachiensisEcotoxicologyGonadosomatic IndexEcologyZoologyEnvironmental chemistryPopulationChemistryFecundity

Abstract

fetched live from OpenAlex

Alterations in seawater chemistry posed by acidification may lead to immunological and antioxidant defence impairment in sea urchins, with differences among local populations. Here, we analyzed the effects of reduced pH on Paracentrotus lividus, with a multibiomarker approach, and the possible intraspecific variations in sea urchin responses. Two groups of animals with different ecological histories (i.e., the pattern of environmental characteristics and pressures experienced throughout the organism's lifetime) were maintained at ambient pH and pH reduced of 0.4 units for 8 months. Changes in gonadosomatic index (GSI), immunological, and oxidative stress biomarkers were assessed in coelomic fluid, gonads, and digestive tract. Animals maintained at reduced pH showed limited impact of seawater acidification compared to the ambient pH condition. However, sea urchins from the two sites were differently influenced by the seawater pH (as shown by multivariate analyses). GSI and immunological and antioxidant status were differentially modulated between the two sexes, with generally higher values in females, but differences between sexes in relation to the pH of exposure were limited. Overall, our findings highlight that the impact of environmental stressors may differ in sea urchins from different locations. This has implications for the maintenance of P. lividus wild populations under future global change scenarios.

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)0.013
metaresearch head score (Gemma)0.001
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 score0.615
Threshold uncertainty score0.669

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
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 head0.067
GPT teacher head0.322
Teacher spread0.256 · 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
Published2024
Admission routes1
Has abstractyes

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