Disturbance effects on species diversity and functional diversity in riparian and upland plant communities
Bibliographic record
Abstract
Understanding disturbance effects on species diversity and functional diversity is fundamental to conservation planning but remains elusive. We quantified species richness, diversity, and evenness and functional richness, diversity, and evenness of riparian and upland plants along 24 small streams subjected to a range of anthropogenic disturbances in the boreal forest of northwestern Ontario, Canada. We included a total of 36 functional traits related to productivity, competitive ability, reproduction, disturbance tolerance, life history, and tolerance to habitat instability. Using nested ANOVA, we examined the response of diversity indices to disturbance and whether it followed the intermediate disturbance hypothesis (IDH) and varied with habitat stability. We found that, like species richness and diversity, functional richness and diversity reached peaks at moderate disturbance intensity; functional diversity followed the predictions of the IDH. Second, disturbance–habitat-stability coupling has very little effect on overall species and functional diversity, but the effect on particular life forms and functions may be significant. Since species richness and diversity patterns are context and system dependent, our findings should be most applicable to similar temperate riparian systems.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".