Multiple developmental pathways for range-margin <i>Pinus banksiana</i> forests
Bibliographic record
Abstract
Empirical knowledge of forest structure and development in early successional and range-margin populations is often lacking, limiting our ability to effectively model and manage these forests. Such is the case for jack pine (Pinus banksiana Lamb.) in central Minnesota, USA, where it reaches its southwestern range limit. Our objective was to quantify this population’s historical range of variability of structural conditions and developmental pathways. We collected structural, spatial, and dendrochronological data on 0.25 ha plots from 10 jack pine dominated sites that initiated and developed outside of active management. Our results revealed a broad range of structural characteristics and developmental pathways, including rapid and protracted recruitment windows (5–50 years), with subsequent even- and uneven-aged structures, and random and clumped stem spatial arrangements. As such, these mature, early successional forests often displayed a degree of complexity more typically associated with old-growth forests. Our findings suggest that this population, like other southern range-margin populations with mostly nonserotinous cones, historically followed a variety of stand development pathways and did not solely follow the rapid establishment, even-aged pathway often attributed to this forest type. We suggest that even- and uneven-aged silvicultural systems should be used to reflect this historical range of developmental pathways and to increase resilience and adaptability.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".