Modelling climate effects on diameter growth of red pine trees in boreal Ontario, Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The climate is changing and these changes may affect tree growth. Diameter growth models are one of the essential inputs for many growth and yield projection systems. Therefore, diameter growth models that can be used to estimate inside bark diameter at breast height (DBH) for red pine plantations in a changing climate were developed. One hundred and fifty red pine (Pinus resinosa Ait.) trees were sampled from 30 even-aged monospecific plantations (sites) (5 trees/site) across Ontario, Canada. Stem analysis data collected from these trees was used to develop and evaluate the growth models using a mixed effects modeling approach. Site and climate effects on diameter growth were examined by incorporating site and climate variables in the models. Including climate variables improved the fit statistics. Inside bark DBHs were predicted for 4 geographic areas of Ontario for the period 2021 to 2080. Three emissions trajectories known as representative concentration pathways (RCPs), each reflecting different levels of heat at the end of the century (i.e., 2.6, 4.5, and 8.5 W m−2), were evaluated. At the end of the 2021 to 2080 growth period, projected diameters were wider by 11% and 23% for trees in the southeastern and southwestern parts, respectively, and narrower by 6% for those in the central west part of Ontario (under all climate change scenarios relative to those under a no change scenario). However, no pronounced difference in projected diameters was evident for trees in the far west part of the province regardless of climate change scenario (relative to the no change scenario). In the absence of climate data, the model fitted without climate variables can be used to estimate inside bark DBH.
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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 it