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Record W4404800767 · doi:10.1016/j.gecco.2024.e03334

An emerging hazard to nesting sea turtles in the face of sea-level rise

2024· article· en· W4404800767 on OpenAlexaboutno aff
Natalie Wildermann, Héctor Barrios–Garrido, Khuld Jabby, Royale S. Hardenstine, Takahiro Shimada, Ivor D. Williams, Carlos M. Duarte

Bibliographic record

VenueGlobal Ecology and Conservation · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicTurtle Biology and Conservation
Canadian institutionsnot available
FundersKing Abdullah University of Science and Technology
KeywordsNesting (process)FisherySea turtleFace (sociological concept)HazardGeographyOceanographyEcologyGeologyBiologyTurtle (robot)Engineering

Abstract

fetched live from OpenAlex

Climate change poses a significant threat to sea turtles. In particular, beach erosion due to sea-level rise endangers sea turtle nests and can hinder the inland movement of nesting females. This study highlights an overlooked indirect hazard in the context of sea-level rise, namely the risk of nesting turtles to lethal falls from rocky cliffs exposed by beach erosion. We provide evidence of mortality of nine nesting green turtles ( Chelonia mydas ) found upside-down on the base of cliff ledges in Breem Island (locally known as جزيرة بريم), located along the northern Saudi Arabian Red Sea coast. One additional turtle was found flipped over but still alive. Our observations suggest that in areas where there is a continuum from the beach to the rocky cliffs (contrary to very steep cliffs bordering beaches), these structures pose a substantial hazard to nesting sea turtles when they attempt to return to the sea. Moreover, mean daily air temperatures of 31 ˚C (max. 44 ˚C) in the northern Red Sea likely exacerbate heat exhaustion of turtles that fall off the cliffs, providing a very narrow window for the animals to be rescued. This study underscores the need to integrate these indirect effects of sea-level rise into sea turtle vulnerability assessments, as well as the importance of implementing timely mitigation measures. Such steps are essential to meet the goals of the Kunming-Montreal Global Biodiversity Framework and support the survival of breeding sea turtles amidst climate change challenges.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.602

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)0.0000.000

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 head0.023
GPT teacher head0.276
Teacher spread0.253 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

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