Response of plant functional groups within plantations and naturally regenerated forests in southern New Brunswick, Canada
Bibliographic record
Abstract
We examined the composition of understory vascular plant species in managed forests to determine how life-history attributes influence plant response to disturbance. Forest types investigated were plantations on old fields (3177 years old, n = 6), plantations on cutover land (1964 years old, n = 8), young forests naturally regenerated after clear-cutting (2766 years old, n = 6), and mature natural forests with no recent harvesting activity (80100 years old, n = 6). Species were categorized by habitat preference (forest, intermediate, disturbed), growth form (12 categories), and life form (15 categories). Forest-habitat species dominated both natural stand types, whereas disturbed-habitat species dominated both plantation types. Mature natural stands contained higher frequency and cover of many herb growth forms, and cutover plantations contained higher values for shrubs. Old-field plantations contained low values for all growth forms. Two life forms, geophytes and rosette hemicryptophytes, were not well represented in either plantation type. All plant functional groups were present in each stand type, suggesting that differences among stand types occur as shifts in the relative abundances of functional groups. We hypothesize that some species may be at risk of local extirpation in plantations because of their limited growth rates and reproductive characteristics.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".