Trees dying standing in the northeastern boreal old-growth forests of Quebec: spatial patterns, rates, and temporal variation
Bibliographic record
Abstract
Spatial patterns, rates, and temporal variation of standing-tree mortality were studied in unmanaged boreal old-growth forests of northeastern Quebec. The study was carried out by sampling living and dead trees within 15 transects (400 m long, 40 m wide). The transects lay in stands that were classified according to their species composition in three types: dominated by black spruce, Picea mariana (Mill.) BSP; mixed P. mariana and balsam fir, Abies balsamea (L.) Mill.; and dominated by A. balsamea. Spatial patterns were analysed using Ripley's K function. The year of death was cross-dated using 190 sample discs extracted from dead standing A. balsamea and P. mariana to assess the rates and temporal variation of mortality. The spatial patterns of standing dead trees in P. mariana stands were predominantly clustered. The spatial patterns of large dead trees (>19 cm diameter at breast height (1.3 m height; DBH)) in mixed and A. balsamea-dominated stands were mainly random, with few stands showing clustered patterns. Small dead trees (9–19 cm DBH) in these stands were generally more clustered than larger trees. Tree mortality varied from year to year, though some mortality was observed in all the studied stand types for almost every year. Standing trees that had recently died accounted for 62%, 48%, and 51% of overall mortality in P. mariana-dominated, mixed, and A. balsamea-dominated stands, respectively. The results of this study indicate that mortality of standing trees outside of episodic mortality events (such as insect outbreaks) is an important process in the creation of structural complexity and habitat diversity in these stands.
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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 | 0.003 | 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".