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Record W1743529295 · doi:10.1890/es14-00399.1

Thermal stress increases fluctuating asymmetry in marine mussels: environmental variation and developmental instability

2015· article· en· W1743529295 on OpenAlexaff
Michael T. Nishizaki, Sivana Barron, Elizabeth Carew

Bibliographic record

VenueEcosphere · 2015
Typearticle
Languageen
FieldMathematics
TopicMorphological variations and asymmetry
Canadian institutionsUniversity of Guelph
FundersBowdoin College
KeywordsFluctuating asymmetryIntertidal zoneMusselBiologyEcologyHabitatEnvironmental stressInstabilityZoologyEnvironmental science

Abstract

fetched live from OpenAlex

Faced with rising environmental temperatures, there is growing evidence that species are exhibiting shifts in ecological distribution, physiological performance, and behavioral strategy. Less is understood, however, about links between environmental conditions and the precision with which organisms are able to fulfill their developmentally programmed phenotype. Here, we report that developmental instability, assessed by the fluctuating asymmetry (FA) of right versus left valves in intertidal mussel shells, increases under elevated thermal stress. In a growth experiment, mussels that were exposed to elevated aerial temperatures (21.5° ± 0.1°C) for three hours each day displayed higher levels of FA compared to mussels exposed to cooler aerial temperatures (12.6° ± 0.1°C). Reciprocal field transplant experiments revealed that FA increased under higher aerial temperatures (e.g., on a south facing surface [19.6° ± 0.2°C]) compared to individuals living in cooler habitats (e.g., on a north facing surface [15.2° ± 0.2°C] or lower in the intertidal zone [14.1° ± 0.6°C]). Together, these results imply that the precision of developmental processes can be perturbed by environmental conditions and raise developmental instability as a potential impact of future environmental variability alongside shifts in physiology, behavior and biogeographic distribution.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.068
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

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 communication0.0000.000
Open science0.0000.000
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 head0.031
GPT teacher head0.249
Teacher spread0.217 · 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 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

Citations21
Published2015
Admission routes1
Has abstractyes

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