Assessing the impact of current and projected climates on Douglas-Fir productivity in British Columbia, Canada, using a process-based model (3-PG)
Bibliographic record
Abstract
Predicted climate change is expected to significantly affect tree growth in many areas. We used a process-based model (Physiological Principles for Predicting Growth, 3-PG) to evaluate how climatic variation might alter growth of Douglas-fir ( Pseudotsuga menziesii (Mirb.) Franco var. glauca (Beissn.) Franco and Pseudotsuga menziesii (Mirb.) Franco var. menziesii ) across biogeoclimatic zones in British Columbia. The results indicate that there will be significant changes in site index (defined as the height (in metres) of dominant trees at 50 years) over this century. In the interior, a reduction in site index is likely, particularly in stands with mid-range values of site index (25–30 m), with many of the interior bioecoclimatic zones predicted to experience a gradual mean decrease in site index by up to 10%. Individual sites may decrease by as much as 40% from current values. In contrast, site index along the coast overall is predicted to increase to a maximum of 43 m by 2080. In the Coastal Western Hemlock zone, however, mean site index is likely to increase from 26 m to only 34 m. We believe that combining process-based models with fine-spatial resolution climate forecasts offers a viable approach to assess future changes in forest productivity.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".