A record of vapour pressure deficit preserved in wood and soil across biomes
Bibliographic record
Abstract
Abstract The drying power of air, or vapour pressure deficit (VPD), is an important measurement of potential plant stress and productivity. Estimates of VPD values of the past are integral for understanding the link between rising modern atmospheric carbon dioxide (pCO2) and global water balance. A geological record of VPD is needed for paleoclimate studies of past greenhouse spikes which attempt to constrain future climate, but at present there are few quantitative atmospheric moisture proxies that can be applied to fossil material. Here we show that VPD leaves a permanent record in the slope (S) of least-squares regressions between stable isotope ratios of carbon and oxygen (13C and 18O) found in cellulose and pedogenic carbonate. Using previously published data collected across four continents we show that S can be used to reconstruct VPD within and across biomes. As one application, we used S to estimate VPD of 0.46 kPa ± 0.26 kPa for cellulose preserved tens of millions of years ago—in the Eocene (45 Ma) Metasequoia from Axel Heiberg Island, Canada—and 0.82 kPa ± 0.52 kPa—in the Oligocene (26 Ma) for pedogenic carbonate from Oregon, USA—both of which are consistent with existing records at those locations. Finally, we discuss mechanisms that contribute to the positive correlation observed between VPD and S, which could help reconstruct past climatic conditions and constrain future alterations of global carbon and water cycles resulting from modern climate change.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.000 | 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".