The Historical Complexity of Tree Height Growth Dynamic Associated with Climate Change in Western North America
Bibliographic record
Abstract
The effect of climate on tree growth has received increased interest in the context of climate change. However, most studies have been limited geographically and with respect to species. Here, sixteen tree species of western North America were used to investigate the response of trees to climate change. Forest inventory data from 36,944 stands established between 1600 and 1968 throughout western North America were summarized. The height growth (top height at a breast-height age of 50 years) of healthy dominant and co-dominant trees was related to annual and summer temperatures, the annual and summer Palmer Drought Severity Indexes (PDSIs), and the tree establishment date (ED). Climate-induced height growth patterns were then tested to determine links to the spatial environment (geographic locations and soil properties), the species’ range (coastal, interior, or both), and traits (shade tolerance and leaf form). Analysis was performed using a linear mixed model (total species) and a general linear model (species scale). Climate change was globally beneficial, except for Alaska yellow-cedar (Chamaecyparis nootkatensis (D. Don) Spach), and growth patterns were magnified for coastal-ranged, high-shade-tolerant, and broadleaf species, and mostly at the northernmost extents of these species’ ranges. Nevertheless, growth patterns were more complex with respect to soil properties. A growth decline for some species was observed at higher latitudes and elevations and was possibly related to increased cloudiness, precipitation, or drought (in interior areas). These results highlight the spatio-temporal complexity of the growth response to recent global climate change.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".