The Combined Role of Retention Pattern and Post-Harvest Site Preparation in Regulating Plant Functional Diversity: A Case Study in Boreal Forest Ecosystems
Bibliographic record
Abstract
Changes in the light availability in forests generated by diversified retention patterns (e.g., clear cut, partial harvest) have been shown to strongly filter the plant species present. Modified soil microsite conditions due to post-harvest site preparation (e.g., mechanical site preparation, prescribed fire) might also be an important determinant of plant diversity. The objective here was to detect how retention pattern and post-harvest site preparation act as filters that explain the understory functional diversity in boreal forests. We also assessed whether these effects were dependent on forest attributes (stand type, time since fire, and time since harvest). We retrieved data from seven different studies within 101 sites in boreal forests in Eastern Canada. Our data included forests harvested with two retention patterns: careful logging and clear cut, plus unharvested control forests. Three post-harvest site preparation techniques were applied: plow or disk trenching after careful logging, and prescribed fire after clear cut. We collected trait data (10 traits) representing plant morphology, regeneration strategy, or resource utilization for common species. Our results demonstrated significant variation in functional diversity after harvest. The combined effect of retention pattern and site preparation was the most important factor explaining understory diversity compared to retention pattern only and forest attributes. According to RLQ analysis, harvested forests with site preparation favored traits reflecting resistance or resilience ability after disturbance (clonal guerilla species, geophytes, and species with higher seed weight). Yet harvested forests without site preparation mainly affected understory plant species via their light requirements. Forest attributes did not play significant roles in affecting the relationship between site preparation and functional diversity or traits. Our results indicated the importance of the compounding effects of light variation and soil disturbance in filtering understory diversity and composition in boreal forests. Whether these results are also valid for other ecosystems still needs to be demonstrated.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".