Influence of stocking, site quality, stand age, low-severity canopy disturbance, and forest composition on sub-boreal aspen mixedwood carbon stocks
Bibliographic record
Abstract
Low-severity canopy disturbance presumably influences forest carbon dynamics during the course of stand development, yet the topic has received relatively little attention. This is surprising because of the frequent occurrence of such events and the potential for both the severity and frequency of disturbances to increase as a result of climate change. We investigated the impacts of low-severity canopy disturbance and average insect defoliation on forest carbon stocks and rates of carbon sequestration in mature aspen mixedwood forests of varying stand age (ranging from 61 to 85 years), overstory composition, stocking level, and site quality. Stocking level and site quality positively affected the average annual aboveground tree carbon increment (CAAI), while stocking level, site quality, and stand age positively affected tree carbon stocks (CTREE) and total ecosystem carbon stocks (CTOTAL). Cumulative canopy disturbance (DIST) was reconstructed using dendroecological methods over a 29-year period. DIST was negatively and significantly related to soil carbon (CSOIL), and it was negatively, albeit marginally, related to CTOTAL. Minima in the annual aboveground carbon increment of trees (CAI) occurred at sites during defoliation of aspen (Populus tremuloides Michx.) by forest tent caterpillar (Malacosoma disstria Hubner), and minima were more extreme at sites dominated by trembling aspen than sites mixed with conifers. At sites defoliated by forest tent caterpillar in the early 2000s, increased sequestration by the softwood component (Abies balsamea (L.) Mill. and Picea glauca (Moench) Voss) compensated for overall decreases in CAI by 17% on average. These results underscore the importance of accounting for low-severity canopy disturbance events when developing regional forest carbon models and argue for the restoration and maintenance of historically important conifer species within aspen mixedwoods to enhance stand-level resilience to disturbance agents and maintain site-level carbon stocks.
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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 | 0.001 |
| 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".