Intensive forestry filters understory plant traits over time and space in boreal forests
Bibliographic record
Abstract
Abstract Because of their scarcity, protected areas alone cannot maintain biodiversity. Therefore, it is necessary to create conditions appropriate for plants and wildlife in managed landscapes. We compared the effects of different intensities of forest management on functional responses of vascular understory plants using the fourth-corner method. We analysed functional community composition along a management gradient that spanned semi-natural forests to extensively managed forests (naturally regenerated cuts) to intensively managed forests (planted forests) in Canada. Results showed trait filtering along the gradient of forest management intensity. In natural and extensively managed forests, where forest retention was high in time and space, persistence traits (e.g. perennial geophytes or chamaephytes, non-leafy stem foliage structure) were maintained. At the opposite end of the gradient, in intensively managed plantations where forest retention elements (e.g. amount of dead wood) were reduced, trait filtering led to species associated with colonization, such as tall species with limited lateral extension. These results suggest that intensive forestry conducted over a large extent may change the functional composition of understory plants.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".