The dendroclimatic signal in Douglas-fir and ponderosa pine tree-ring chronologies from the southern Canadian Cordillera
Bibliographic record
Abstract
A network of 53 ring-width chronologies has been developed from low-elevation stands of Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco, n = 40) and ponderosa pine (Pinus ponderosa Dougl. ex P. & C. Laws., n = 13) in the southern Canadian Cordillera. Relationships between the chronologies and monthly, seasonal, and annualized climatic parameters (precipitation, temperature, and Palmer Drought Severity Index (PDSI)) were investigated using correlation analyses. The results indicate that tree growth at the sites is most strongly related to water availability during the growing season months. Although the response of the two species is similar, Douglas-fir show a slightly stronger correlation with seasonalized precipitation for the prior year and early summer whereas ponderosa pine correlate most strongly with current year and late (July) summer precipitation. Maximum correlations for both species occur with annual precipitation totals. The precipitation signal is slightly weaker in the more northerly Douglas-fir chronologies in British Columbia and the higher elevation sites in southwestern Alberta. Correlations with available PDSI records are generally comparable with those from precipitation variables, but the limited number of PDSI records and the availability of more proximal and better correlated precipitation records indicated that annual (summersummer) precipitation totals provide the best possibilities to develop regional, moisture-related proxy climate records from these data. Analysis of earlywood and latewood chronologies for 28 sites (mainly Douglas-fir) indicates that earlywood width is most consistently and strongly correlated with precipitation in the previous summer (July and August), and latewood width is more strongly related to precipitation in the current summer (June and July). The results of these analyses demonstrate considerable potential for reconstructing annual (and (or) summer) precipitation for sites across the region.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 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".