Radial growth responses of four oak species to climate in eastern and central North America
Bibliographic record
Abstract
This study characterized associations between climate variables and radial growth of four oak species at sites distributed across central and eastern North America. Tree-ring data were obtained from 24, 29, 33, and 55 sites for Quercus prinus L., Quercus velutina Lam., Quercus macrocarpa Michx., and Quercus stellate Wangenh., respectively. Pearson’s correlation coefficients were computed between radial growth and monthly and seasonal temperature and precipitation. Growth was most strongly and consistently correlated with precipitation and temperature during the early growing season (May to July). Coincident positive correlations with precipitation and negative correlations with temperature indicate that this relationship is mediated by site water balance. The combination of this plausible cause–effect mechanism and extensive spatial replication of these correlations suggest that they reflect cause–effect relationships. Growth of Q. stellata was correlated with precipitation during the dormant season, suggesting that stored soil water is important for growth of this species in the southern Great Plains. Despite substantial spatial variation in temperature and growing-season initiation between sites in Texas and Manitoba, Canada, there was little variation in the phenology of growth–climate associations; growth–climate correlations were strongest during the same May–July period at all sites. Results of this study support the hypothesis that temperate zone ring-porous oak species have similar phenology of growth–climate correlations and can be treated as a biologically meaningful functional group in forest simulation models.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 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 teacher head, 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".