Cryptogam plant community stability: Warming weakens influences of species richness but enhances effects of evenness
Bibliographic record
Abstract
Community stability is a fundamental factor sustaining ecosystem functioning and is affected by species richness and species evenness. The Arctic is warming more rapidly than other biomes, and cryptogam plant species (specifically lichens and bryophytes in this study) are major contributors to tundra biodiversity and productivity. However, to our knowledge, the impacts of warming on cryptogam community stability and the underlying mechanisms have not been investigated. We conducted a 13-year summer warming experiment in mesic birch hummock tundra vegetation near Daring Lake in the continental interior of low Arctic Canada and recorded patterns of cryptogam species abundance in several different growing seasons. Warming decreased the stability of total community abundance, had no effects on species richness, but increased species evenness and species synchrony. Structural equation model analyses indicated that higher species richness was the principal factor associated with the stronger community abundance stability in the control plots and that this effect was driven primarily by a negative correlation with species synchrony. By contrast, higher species evenness was the principal factor associated with the weakened community abundance stability in the warming plots, and this effect was driven primarily by a positive correlation with species synchrony. Our study suggests that climate warming could reduce cryptogam plant community stability in low Arctic tundra and, therefore, decrease important ecosystem services, including carbon storage and food availability to caribou in northern regions.
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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".