Process-Based Modeling to Assess the Effects of Recent Climatic Variation on Site Productivity and Forest Function across Western North America
Bibliographic record
Abstract
A process-based forest growth model, 3-PG (Physiological Principles Predicting Growth), parameterized with values of soil properties constrained by satellite-derived estimates of maximum leaf area index (LAImax), was run for Douglas-fir (Pseudotsuga menziesii) to contrast the extent to which site growth potential might vary across western North America between a cool, wet period (1950–1975) and a more recent, generally warmer and drier one (2000–2009). LAImax represents a surrogate for overall site growth potential, as demonstrated from a strong correlation between the two variables, with the latter based on the culmination of mean annual increment estimates made at 3356 ground-based U.S. Forest Service survey plots across the states of Oregon and Washington. Results indicate that since 2000, predicted LAImax has decreased more than 20% in portions of the Southwest USA and for much of the forested area in western Alberta. Similar percentage increases in LAImax were predicted for parts of British Columbia, Idaho and Montana. The modeling analysis included an assessment of changes in seasonal constraints on gross primary production (GPP). A general reduction in limitations caused by spring frost occurred across the entire study area. This has led to a longer growing season, along with notable increases in summer evaporative demand and soil drought for much of the study area away from the maritime influence of the Pacific Ocean.
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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) | 0.000 | 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 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".