Relative importance of different secondary successional pathways in an Alaskan boreal forest
Bibliographic record
Abstract
Postfire succession in the Alaskan boreal forest follows several different pathways, the most common being self-replacement and species-dominance relay. In self-replacement, canopy-dominant tree species replace themselves as the postfire dominants. It implies a relatively unchanging forest composition through time maintained by trees segregated within their respective, ecophysiological niches on an environmentally complex landscape. In contrast, species-dominance relay involves the simultaneous, postfire establishment of multiple tree species, followed by later shifts in canopy dominance. It implies that stand compositions vary with time since last fire. The relative frequencies of these and other successional pathways are poorly understood, despite their importance in determining the species mosaic of the present forest and their varying, potential responses to climate changes. Here we assess the relative frequencies of different successional pathways by modeling the relationship between stand type, solar insolation, and altitude; by describing how stand age relates to species composition; and by inferring successional trajectories from stand understories. Results suggest that >70% of the study forest is the product of self-replacement, and tree distributions are controlled mainly by the spatial distribution of solar insolation and altitude, not by time since last fire. As climate warms over the coming decades, deciduous trees will invade cold sites formerly dominated by black spruce, and increased fire frequency will make species-dominance relay even rarer.
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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 | 0.001 | 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".