Forest restoration mitigates drought vulnerability of coast Douglas-fir in a Mediterranean climate
Bibliographic record
Abstract
Multi-year drought and climate change can impact tree growth, especially in California's Mediterranean climate where growing season rainfall is limited or absent. Active forest restoration has the potential to mitigate climate impacts by reducing stand density and conversion towards more resilient species' composition. We used dendrochronology methods to examine climate–growth relationships for coast Douglas-fir ( Pseudotsuga menziesii var. menziesii) trees in mixed multiaged stands near the species’ natural southern range margin. We found positive correlations of ring width with spring–early summer and prior October precipitation and an evapotranspiration index. Additionally, cooler spring temperature was negatively correlated with growth. We also studied tree resistance, resilience, and recovery from two multi-year drought events. Restoration treatments enhanced resistance and resilience to drought relative to trees growing in untreated plots. We did not detect differences in drought resistance and resilience between two common restoration methods, giving managers options for restoration to lessen drought impacts on tree growth.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".