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Record W4416225830 · doi:10.1038/s41467-025-64963-1

Controls on the southwest USA hydroclimate over the last six glacial-interglacial cycles

2025· article· en· W4416225830 on OpenAlexaff
Kathleen A. Wendt, Stacy Carolin, Christo Buizert, Simon D. Steidle, R. Lawrence Edwards, Gina E. Moseley, Yuri Dublyansky, Hai Cheng, Chengfei He, Christoph Spötl

Bibliographic record

VenueNature Communications · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversity of Toronto
FundersAustrian Science FundNational Natural Science Foundation of ChinaNational Science Foundation
KeywordsVegetation (pathology)Structural basinInterglacialClimate changeGroundwater rechargeNorthern HemisphereCave

Abstract

fetched live from OpenAlex

Abstract The Great Basin in the southwest United States experienced major hydroclimate shifts throughout the Quaternary. Understanding the drivers behind these past changes has become increasingly important for improving future climate projections. Here, we present an absolute-dated δ 18 O and δ 13 C record from Devils Hole cave 2 (southern Nevada) that reveals climate and environmental changes in the southern Great Basin over the last 580,000 years. Water isotope-enabled Earth system simulations and phasing analysis show that temperature-related mechanisms are a primary driver of δ 18 O variability, with additional drivers stemming from processes linked to North American ice sheets. Vegetation density in the highlands of southern Nevada is primarily forced by Northern Hemisphere summer intensity. A rapid decline in primary productivity occurs during warm interglacial periods when local groundwater recharge declines to <50% above modern. Our study sheds new light on the relationship between temperature, moisture balance, and vegetation over the last six glacial-interglacial cycles.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.043
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.298
Teacher spread0.278 · 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 source (direct Gemma or distilled Codex), 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

Explore more

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