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Record W4416466512 · doi:10.5194/cp-21-2361-2025

Living on the edge: Response of Late Cretaceous rudist bivalves (Hippuritida) to hot and highly seasonal climate in the low-latitude Saiwan site, Oman

2025· article· en· W4416466512 on OpenAlexaff
Niels J. de Winter, Najat al Fudhaili, Iris Arndt, Philippe Claeys, René H.B. Fraaije, Steven Goderis, John W.M. Jagt, Matthias López Correa, Axel Munnecke, Jarosław Stolarski, Martin Ziegler

Bibliographic record

VenueClimate of the past · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicPaleontology and Stratigraphy of Fossils
Canadian institutionsUniversity of British Columbia
FundersAard- en Levenswetenschappen, Nederlandse Organisatie voor Wetenschappelijk OnderzoekHorizon 2020 Framework ProgrammeFonds Wetenschappelijk Onderzoek
KeywordsIsotopes of oxygenCretaceousSeawaterLatitudeSeasonalityStable isotope ratioδ18Oδ13CNatural (archaeology)Pelagic zone

Abstract

fetched live from OpenAlex

Abstract. Earth's climate history serves as a natural laboratory for testing the effect of warm climates on the biosphere. The Cretaceous period featured a prolonged greenhouse climate characterized by higher-than-modern atmospheric CO2 concentrations and mostly ice-free poles. In such a climate, shallow seas in low latitudes probably became very hot, especially during the summers. At the same time, life seems to have thrived there in reef-like ecosystems built by rudists, an extinct group of bivalve molluscs. To test the seasonal temperature variability in this greenhouse period, and whether temperature extremes exceed the maximum tolerable temperatures of modern marine molluscs, we discuss a detailed sclerochronological (incrementally sampled) dataset of seasonal scale variability in shell chemistry from fossil rudist (Torreites sanchezi and Vaccinites vesiculosus) and oyster (Oscillopha figari) shells from the late Campanian (75-million-year-old) low latitude (3° S paleolatitude) Saiwan site in present-day Oman. We combine trace element data and microscopy to screen fossil shells for diagenesis, before sampling well-preserved sections of a Torreites sanchezi rudist specimen for clumped isotope analysis. Based on this specimen alone, we identify a strong seasonal variability in temperature of 19.2 ± 3.8 to 44.2 ± 4.0 °C in the seawater at the Saiwan site. The oxygen isotopic composition of the seawater (δ18Osw) varied from −4.62 ± 0.86 ‰ VSMOW in winter to +0.86 ± 1.6 ‰ VSMOW in summer. We use this information in combination with age modelling to infer temperature seasonality from incrementally sampled oxygen isotope profiles sourced from the literature, sampling multiple shells and species in the assemblage. We find that, on average, the Saiwan seawater experienced strong seasonal fluctuations in monthly temperature (18.7 ± 3.8 to 42.6 ± 4.0 °C seasonal range) and water isotopic composition (−4.33 ± 0.86 to 0.59 ± 1.03 ‰ VSMOW). The latter would strongly bias the interpretation of stable oxygen isotopes in shell carbonate without independent control on either temperature or seawater composition. Combining our seasonal temperature estimates with shell chronologies based on seasonal cyclicity in stable isotope records and daily variability in trace element data, we show that T. sanchezi rudists record temperatures during the hottest periods of the year as well as during the winters, which were characterized by cooler temperatures and enhanced influx of freshwater. Both O. figari and V. vesiculosus plausibly stopped growing during these seasonal extremes. This study aims to demonstrate how high-resolution geochemical records through fossil mollusc shells can shed light on the variability in past warm ecosystems and open the discussion about the limits of life in the shallow marine realm during greenhouse climates. Future work should apply the clumped isotope paleothermometer on incrementally sampled bio-archives to explore the upper-temperature limits experienced by calcifiers in different environments throughout geological history.

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 score0.030
Threshold uncertainty score0.216

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 head0.011
GPT teacher head0.234
Teacher spread0.223 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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