Physiologically derived predictions of Douglas-fir site index in British Columbia
Bibliographic record
Abstract
Both the coastal and interior varieties of Douglas-fir (Pseudotsuga menziesii var. menziesii (Mirb.) Franco; Pseudotsuga menziesii var. glauca) are found throughout a wide range of environmental conditions across British Columbia. The species is long-lived and can grow rapidly to standing volumes that approach the highest recorded among temperate conifers. Understanding the growth of the species across British Columbia, and its site index (defined as individual tree height at 50 m) is important for forest managers for both production and conservation objectives. To date, predictions of site index have traditionally been derived from forest inventory using estimates of species, height and age combined with the appropriate height–age model. More recently, process-based modelling has offered a viable alternative approach due to increased computing power, model simplifications and availability of input data. In this paper we applied a physiological forest growth model, 3-PG (Physiological Principles Predicting Growth) to predict and map site index of Douglas-fir across British Columbia at 1-km cell resolution. Our model predictions were scaled-up and compared to independent estimates of average site index for subzones from the British Columbia Biogeoclimatic Ecosystem Classification (BEC) system. Results indicated the 3-PG predictions closely matched those summarized by the BEC sub-zones (r = 0.86, p<0.001, SE = 3.0m). Predicted environmental limitations of growth suggest that the coastal variety of the species is most severely affected by temperature and frost constraints, and in some locations, soil water stress, whereas the interior variety is principally restricted by soil water availability. The proposed modelling approach complements ecological classifications and offers the potential to identify the most favourable sites for management of other native tree species under current and projected climates. Key words: Douglas-fir, site index, physiological modelling, 3-PG model, forest productivity, British Columbia, Canada
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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 | 0.000 | 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) | 0.002 | 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".