Gap expansion in old‐growth subarctic forests: the climate–pathogen connection
Bibliographic record
Abstract
We tested the hypothesis considering old-growth subarctic woodlands, free of fire, insect and stand-scale blowdown disturbances, to be at equilibrium with the climate. To do so, we explored the status of Hudsonian woodlands based on the natality/mortality ratio. The gap history of the woodland was reconstructed based on mapping and dating of dead gap-spruces (Picea mariana). Among the 25 gaps studied, 763 dead trees and only 14 saplings were recorded. The center of some gaps remained treeless over the last 1000 yr, and gap area doubled over the last 100 yr. The status of the tree population is in a demographic disequilibrium caused by the small replacement of dead spruces in all of the gaps. Episodes of 'mass' mortality occurred during several decades corresponding to years of favorable tree-ring growth. The natural process of gap-filling appears to be ineffective under current conditions. Good tree-ring growth of dying trees suggests abundant precipitation during the mortality episodes, but precipitation appears to be involved indirectly in the mortality process. The main cause of the widespread tree mortality during the last centuries of gap expansion appears to be biotic in origin. The impact of pathogenic fungal disease linked to late-lying snow cover is proposed for the mortality events.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".