Potential effects of ozone, climate, and spruce budworm on Douglas-fir growth in the Wasatch Mountains
Bibliographic record
Abstract
This study assessed the potential for ozone injury to vegetation in the central Wasatch Mountains of Utah by determining if Douglas-fir (Pseudotsuga menziesii var. glauca (Beissn.) Franco) experienced reduced growth since the onset of high ozone concentrations. Dendrochronological techniques were used to model Douglas-fir growth in six central Wasatch Mountain stands, where ozone concentrations suggest the possibility of injury to vegetation, and in four Bear River stands, where ozone concentrations are lower than injury thresholds. Previous-year growth, temperature, and Palmer's Z index variables explained 5370% of the variance in annual growth. Reduced Douglas-fir growth, not explained by the model or insect and disease records, occurred after 1970 in the central Wasatch Mountains but not in the Bear River Mountains. Douglas-fir growth in the central Wasatch Mountains was slightly negatively correlated with the previous-year ozone concentrations in nearby Salt Lake valley. Between 1962 and 1973, a fluctuating budworm population due to varying spring precipitation was suggested to have replaced precipitation as the factor limiting tree growth, causing an anomalous negative relationship between precipitation and Douglas-fir growth. Because of a suite of possible factors (e.g., undetected climatic variables, fungal pathogens, competitive interactions) influencing Douglas-fir growth, ozone may be one factor in a larger stressor complex reducing growth.
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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 | 0.000 | 0.000 |
| 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 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".