Initiating the transition from open-canopy lichen woodland to productive forest by transplanting moss, results from a 10-year experiment
Bibliographic record
Abstract
Abstract Background and aims Low productivity open lichen ( Cladonia spp.) woodlands have been rapidly expanding in the closed-crown feather moss ( Pleurozium schreberi (Brid.) Mitt.) boreal forest of eastern Canada. While open-woodland areas are progressing, there is little information on the recoverability of open lichen woodlands back to closed-canopy forests. Methods An experimental set-up using moss transplantation was installed on a poor jack pine ( Pinus banksiana Lamb . ) stand with a lichen ground cover in 2011. Treatments included: 1) lichen cover removed, 2) lichen cover removed and transplantation of a feather moss cover, 3) lichen control, and 4) a natural jack pine site with feather moss cover (moss control). We extracted tree stem increment cores and collected needles and soil samples for nutrient analysis. Results The transplanted-moss treatment can counteract the adverse effects of lichen on jack pine growth. This treatment enhanced foliar nutrition and soil nutrients, especially ammonium (N-NH 4 + ) and nitrate (N-NO 3 − ). With this treatment, the soil conditions (e.g., soil nutrients, soil moisture) and foliar nutrition were closer to that of moss control. Surprisingly, lichen removal treatment did not improve growth and resulted in poorer jack pine growth and harsher soil conditions. Conclusion Feather moss can establish, survive, and remain healthy in an environment previously occupied by lichen. The replacement of lichen by feather moss establishes soil conditions that appear conducive to better tree growth and have the potential of restoring the productivity of boreal forests in open-canopy lichen woodlands.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".