High-elevation western Anatolian topography delayed faunal migration during the Early Miocene
Bibliographic record
Abstract
Anatolia has been a major thoroughfare for faunal migration, and its paleogeography impacted faunal dispersal among Africa, Europe, and Asia. Delays in faunal migration from Africa into and through Anatolia and differences in faunal populations between Europe and Anatolia are evident in the Early Miocene record despite the prior closure of seaways separating the continents. We suggest that high elevations in western Anatolia posed migration barriers, leading to the observed delays. To test this hypothesis, we calculated paleoelevations based on hydrogen isotopic ratios of 12 volcanic glass samples and oxygen isotopic ratios of 25 new and 117 published carbonate samples. We constrained new sample ages to 19−16 Ma based on detrital and volcanic zircon U-Pb geochronology. Volcanic glass samples yielded δDpaleowater values ranging from −113.7‰ to −67.5‰, and alluvial paleosol carbonates yielded δ18Opaleowater values ranging from −13.7‰ to −7.5‰. The δ18Opaleowater value (−4.7‰) from an Oligocene marginal marine paleosol sample is consistent with the δ18O values (−5.6‰ to −4.3‰) of precipitation from Global Network of Isotopes in Precipitation (GNIP) stations on the SW Anatolian coast and provides a low-elevation baseline for paleoelevation calculations. Application of a thermodynamic Rayleigh distillation lapse rate to the mean values of the most negative quartile of δ18Opaleowater (−9.6‰) and δDpaleowater values (−75.5‰) yielded 19−16 Ma paleoelevations for western Anatolia of 3.6 ± 0.5 km and 3.9 ± 0.5 km (1σ), respectively. We conclude that the Early Miocene topography in western Anatolia was ∼2 km higher than the current topography, consistent with the hypothesis that high Early Miocene paleoelevations in western Anatolia hampered faunal dispersal.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".