Forward modelling of white spruce radial growth at trailing edge demonstrates high plasticity
Bibliographic record
Abstract
Climate conditions throughout the 21st century across much of western Canada's boreal forest have been drier than normal leading to significant impacts on forest productivity and tree growth. Determining the limiting factors of radial growth in common boreal tree species under current and future conditions is crucial to reconcile how they will continue to respond to climate change. In this study, we used a network of 26 white spruce tree-ring chronologies south of its natural range as an artificially constructed trailing edge to assess climate-growth relationships and limiting factors by identifying seasonal climate relationships and using the Vaganov-Shashkin Lite (VS-Lite) model, respectively. Analysis revealed that white spruce in the study region is positively correlated to precipitation and negatively associated with temperature from the current and previous growing seasons. VS-Lite showed that moisture was the primary limiting factor in growth across the entire study area. The modelled radial growth from the VS-Lite model showed moderate success (14 of 26 site models were significant) and was more variable than measured tree-ring index values. The model systematically overestimated drought-related impacts on radial growth, especially during the middle portion of the growth season (June-August) indicating white spruce likely employs a conservative approach to carbohydrate storage as the region is much more susceptible to moisture deficits. The outcome of our research illustrates that white spruce may be resilient to hotter, drier conditions through environmental plasticity in the Boreal Plains.
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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 | 0.001 | 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 | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".