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Record W4414274972 · doi:10.1016/j.eve.2025.100079

Biomarkers in terrestrial organic matter from the Lower Devonian to Oligocene: Evidence from selected regions of the laurasian supercontinent

2025· article· en· W4414274972 on OpenAlexaboutno aff
Temitope O. Akinsanpe, Adebola O. Akinsanpe, Thomas S. Daniya, Solomon A. Adekola, Fadiya L. Suyi, Bamidele Adeniyi Adebambo, Charles I. Konwea

Bibliographic record

VenueEvolving Earth · 2025
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsnot available
Fundersnot available
KeywordsDevonianCarboniferousFlora (microbiology)Terrestrial plantLate Devonian extinctionPaleobotanySupercontinentGymnospermPaleozoicBiodiversity

Abstract

fetched live from OpenAlex

Biomarkers are chemical fossils which are valuable in organic matter provenance determination, and higher plant specific biomarkers could be utilised to deduce the precursor higher plants sources and their evolution through geological time. Twenty (20) selected rock samples from different areas within the Laurasian Supercontinent, including plant fossils of Lower Devonian to Oligocene Period from Canada, Germany, Northern Ireland, and the United Kingdom were examined for their record of aliphatic and aromatic biomarkers specific to higher plants. This aims to determine land plant-derived molecular compounds and its variations within the studied ages, as well as attribute biomarkers to different plant contributors. Aliphatic land plant biomarkers, including tetracyclic diterpenoids (beyerane, kaurane, phyllocladane) as well as high terrestrial/aquatic ratio (TAR >1) and conventional odd-numbered long-chain n-alkanes, which are derived from land plants were detected. Other aromatic land plant biomarkers, including naphthalenes and cadalene, were also distinguished in the samples. The presence of land plant biomarkers (beyerane, kaurane, phyllocladane, cadalene) and their slight increase in the examined Laurasian Devonian to Triassic samples signify the abundance and diversity of higher plants. Vascular plants, including psilophyton , pertica , leclercqia , drepanophycus , and sawdonia dominated the Lower Devonian flora (in the Rhynie Chert, for example), contributing to the evolution of the terrestrial ecosystem, with the diversity of seed plants, appearance of conifers and tall trees in the Carboniferous. Gymnosperms that appeared during the Upper Carboniferous period became the dominant flora in the Triassic and Jurassic periods, signalled by the abundance and increase in the concentration of higher plant biomarkers. The slight decrease of biomarkers post-Middle Jurassic may reflect organic matter degradation and erosion or mass extinction of plants and possible reorganisation in the plant fossil record marked by the Triassic-Jurassic boundary. Since land-plant derived biomarkers are not expected routinely in marine environments, the detected plant biomarkers in Jurassic marine sediments (Oxfordian and Kimmeridge shales) from England are interpreted to have been caused by run-off of terrigenous carbon from land to the marine environment. The study has enhanced our understanding of the organic matter provenance, terrestrialisation process, and spatiotemporal evolution of higher plants across different geological settings of the studied areas within the Laurasian Supercontinent. • We examined the ali- and aro-biomarkers in the TOM of the Laurasian Devonian to Oligocene ages. • TTD, naphthalenes and cadalene observed in the sediments are consistent with land plants. • Fluctuation of observed biomarkers through time revealed differential contributions of land plants to the ecosystem. • The sharp decrease of biomarkers post Middle Jurassic reflected possible mass extinction of plants at that time. • The study aided the understanding of terrestrialisation and higher plant evolution through geological time.

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 score0.238
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.009
GPT teacher head0.214
Teacher spread0.206 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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