Coherent Region-, Species-, and Frequency-Dependent Local Climate Signals in Northern Hemisphere Tree-Ring Widths*
Bibliographic record
Abstract
Abstract Patterns of correlation between tree rings and local temperature or precipitation are investigated using 762 International Tree-Ring Data Bank standardized ring width site chronology time series, and a gridded dataset of temperature and precipitation. Coherent regional- and, in some cases, hemispheric-scale patterns of correlation are found in the extratropical Northern Hemisphere for both the summer prior to and the summer concurrent with ring width formation across different species and over large distances. Among those chronologies that are primarily linked to temperature, thicker ring widths are generally associated with anomalously cool prior summer temperature and anomalously warm concurrent summer temperature. Reconstructions of local summer temperature using prior, concurrent, and/or subsequent year ring widths as predictors demonstrate that useful climate–growth information generally exists in ring widths that are both concurrent with and subsequent to the summer temperature anomaly. Consistent prior summer temperature–ring width relationships have received relatively little previous attention. Among those chronologies that are primarily linked to precipitation, thicker ring widths are generally associated with high summer precipitation in both the year prior to and the year concurrent with ring formation. The magnitude and spatial consistency of temperature correlations are greater than those for precipitation, at least on the hemispheric scale. These results support and serve to generalize the conclusions of prior regionally restricted and/or species-specific studies relating ring width to energy and/or water limitations. Regional- and hemispheric-scale patterns of ring width–temperature or ring width–precipitation correlations show up more clearly in species-specific and frequency-dependent analyses. Different species respond differently to temperature and precipitation anomalies. Consistent with the hemispheric patterns described above, most standardized ring width time series more faithfully record the high frequency component of the temperature signal than the low frequency component. The potential for enhanced coherence in regionally restricted, species-specific, and frequency-dependent analyses is independently verified by examining the correlation between ring width time series over geographical distance. This broader characterization of relationships between tree-ring widths and local climate provides an objective basis for selecting tree ring or other similarly high-resolution proxy data for regional-, hemispheric-, or global-scale paleoclimate reconstructions.
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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 | 0.001 | 0.002 |
| 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".