A heat wave during leaf expansion severely reduces productivity and modifies seasonal growth patterns in a northern hardwood forest
Bibliographic record
Abstract
A useful approach to monitor tree response to climate change and environmental extremes is the recording of long-term time series of stem radial variations obtained with precision dendrometers. Here, we study the impact of environmental stress on seasonal growth dynamics and productivity of yellow birch (Betula alleghaniensis Britton) and sugar maple (Acer saccharum Marsh.) in the Great Lakes, St Lawrence forest region of Ontario. Specifically, we research the effects of a spring heat wave in 2010, and a summer drought in 2012 that occurred during the 2005–14 study period. We evaluated both growth phenology (onset, cessation, duration of radial growth, time of maximum daily growth rate) and productivity (monthly and seasonal average growth rates, maximum daily growth rate, tree-ring width) and tested for differences and interactions among species and years. Productivity of sugar maple was drastically compromised by a 3-day spring heat wave in 2010 as indicated by low growth rates, very early growth cessation and a lagged growth onset in the following year. Sugar maple also responded more sensitively than yellow birch to a prolonged drought period in July 2012, but final tree-ring width was not significantly reduced due to positive responses to above-average temperatures in the preceding spring. We conclude that sugar maple, a species that currently dominates northern hardwood forests, is vulnerable to heat wave disturbances during leaf expansion, which might occur more frequently under anticipated climate change.
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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".