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Record W4309126316 · doi:10.1201/9781003288602-13

Adaptations and Plastic Phenotypic Responses of Marine Animals to the Environmental Challenges of the High Intertidal Zone

2022· book-chapter· en· W4309126316 on OpenAlexafffund
Robine H. J. Leeuwis, A. K. Gamperl

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEarth and Planetary Sciences
TopicOcean Acidification Effects and Responses
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of CanadaCanada First Research Excellence FundOcean Frontier Institute
KeywordsIntertidal zoneIntertidal ecologyBiologyEcologyPhenotypic plasticityGeographyZoology

Abstract

fetched live from OpenAlex

The high intertidal zone is home to an incredible variety of marine animals, as it offers an escape from low intertidal/subtidal predation and competition, among other advantages. However, this area of the shore also comes with many tide-driven and emersion-associated environmental stressors, such as desiccation, high temperatures and freezing stress, hypoxia, salinity fluctuations, nitrogenous waste accumulation, ultraviolet (UV) radiation, wave and ice disturbance and hydrogen sulphide (H 2 S) toxicity. This review explores the diversity of evolutionary adaptations and plastic phenotypic responses that high intertidal animals use to cope with these challenges. Examples are provided of behavioural, morphological, physiological and biochemical adaptations/responses, along with some of the underlying molecular mechanisms that have been elucidated to date. Adaptations of many different worms, anemones, molluscs, crustaceans and fishes are highlighted. Many adaptations and mechanisms of plasticity are universal among animal phyla, and some are multifunctional (serve more than one function) or provide tolerance to multiple stressors (i.e. 'cross-tolerance'). High intertidal animals have received considerable attention by scientists, given their accessibility and that they can provide valuable insights into the transition from a marine to a terrestrial lifestyle. Nevertheless, further research is needed to understand the adaptations/responses of these animals more thoroughly, and the future holds great promise for accomplishing this with recent advances in epigenetics, transcriptomics, protein biochemistry and other molecular tools.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.912
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0120.000

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 head0.018
GPT teacher head0.193
Teacher spread0.175 · 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

Citations25
Published2022
Admission routes2
Has abstractyes

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