Growth responses of riparian <i>Thuja occidentalis</i> to the damming of a large boreal lake
Bibliographic record
Abstract
Growth responses of riparian eastern white cedar trees ( Thuja occidentalis L.) to the double damming of a large lake in the southeastern Canadian boreal forest was analyzed to determine whether the shoreline tree limit is the result of physiological flood stress or mechanical disturbances. The first damming, in 1915, caused a rise in water level of ca. 1.2 m and resulted in the death of the trees that formed the ancient shoreline forest, as well as the wounding and tilting of the surviving trees (by wave action and ice push) that constitute the present forest margin. The second damming, in 1922, did not further affect the water level, but did retard the occurrence of spring high water levels, as well as reduce their magnitude. However, this did not injure or affect the mortality of riparian eastern white cedars. Radial growth was not affected by flooding stress, probably because inundation occurred prior to the start of the growing season (1915–1921) or was of too short duration to adversely affect tree metabolism (after 1921). It follows that (i) the shoreline limit of eastern white cedar is a mechanical rather than a physiological limit, and (ii) disturbance-related growth responses (e.g., ice scars, partial cambium dieback, and compression wood) are better parameters than ring width for the reconstruction of long-term water level increases of natural, unregulated lakes.
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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 | 0.000 |
| 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) | 0.001 | 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".