Tree species richness decreases while species evenness increases with disturbance frequency in a natural boreal forest landscape
Bibliographic record
Abstract
Understanding species diversity and disturbance relationships is important for biodiversity conservation in disturbance-driven boreal forests. Species richness and evenness may respond differently with stand development following fire. Furthermore, few studies have simultaneously accounted for the influences of climate and local site conditions on species diversity. Using forest inventory data, we examined the relationships between species richness, Shannon's index, evenness, and time since last stand-replacing fire (TSF) in a large landscape of disturbance-driven boreal forest. TSF has negative effect on species richness and Shannon's index, and a positive effect on species evenness. Path analysis revealed that the environmental variables affect richness and Shannon's index only through their effects on TSF while affecting evenness directly as well as through their effects on TSF. Synthesis and applications. Our results demonstrate that species richness and Shannon's index decrease while species evenness increases with TSF in a boreal forest landscape. Furthermore, we show that disturbance frequency, local site conditions, and climate simultaneously influence tree species diversity through complex direct and indirect effects in the studied boreal forest.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".