Environmental change shapes understory plant diversity and dominance in boreal forests
Bibliographic record
Abstract
Ongoing environmental change threatens ecosystems worldwide, yet little is known about its effect on understory plant diversity, which underpins ecosystem functioning and sustainability. Here, we use Canada's National Forest Inventory database to evaluate decade-long changes in local plant diversity within understory communities. Species richness of shrubs and bryophytes increases by 8 and 11% per decade, while species evenness of herbs and bryophytes declines by 14 and 8%, respectively. Temporal increases in species richness and declines in species evenness are both associated with rising temperature, nitrogen deposition, water availability, and increased temperature seasonality. Additionally, the proportion of bryophyte biomass increases, whereas that of shrub biomass decreases over time, with the effects of temperature seasonality and water availability on these temporal shifts strongly dependent on overstory basal area. Species richness is positively associated with biomass across shrubs, herbs, and bryophytes, suggesting that changes in diversity alter understory biomass distribution under environmental changes. Contrary to the common view that climate warming uniformly reduces biodiversity, our findings show that understory communities undergo complex and dynamic shifts in plant diversity and composition. We suggest that environmental change-driven shifts in resource availability and heterogeneity may shape understory composition and species dominance, ultimately influencing forest ecosystem function.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".