Paleoclimatic Reconstruction Using the Correlation in δ<sup>18</sup>O of Hackberry Carbonate and Environmental Water, North America
Bibliographic record
Abstract
Abstract Celtissp. (commonly known as “hackberry”) fruits were collected from 101 North American sites located in 13 states and one Canadian province between the years of 1979–1994. The biomineralized carbonate endocarp of the hackberry, which is a common botanical fossil found throughout the Quaternary sediments of the Great Plains, was analyzed for its δ18O value and plotted against the δ18O value of site environmental water to demonstrate the potential of the hackberry as a paleoclimate indicator. This correlation was reinforced by intensive studies on extracted tissue-water δ18O value and hackberry endocarp carbonate δ18O value from three trees in Sterling, Colorado. The observed correlation in the large data set between hackberry endocarp carbonate δ18O value and environmental water is [endocarp δ18O=38.56+0.69×environmental water δ18O] (R=0.88;R2=0.78;pvalue<0.0001). The relation of the hackberry carbonate to temperature in the Great Plains was the following: (average daily-maximum growing season temperature [°C])=6.33+0.67 (δ18O of endocarp carbonate) (R=0.73;R2=0.54;pvalue=0.0133). The δ18O value of early Holocene fossil hackberry carbonate in the Pintwater Cave, southern Nevada, suggested precipitation δ18O values more positive than today (∼−4‰ early Holocene vs ∼−9 to −10‰ today). This shift, combined with paleobotanical data, suggests an influx of summer monsoonal moisture to this region in the early Holocene. Alternatively, the more positive δ18O values could be viewed as suggestive of warmer temperatures, although the direct use of Great Plains hackberry/temperature relationships to the Great Basin is of debatable value.
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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".