Reconciling links between diversity and population stability across global plant communities
Bibliographic record
Abstract
Maintaining ecological stability is essential for sustaining ecosystem functions and the benefits they provide to society. Ecological theory predicts that plant diversity either stabilizes or destabilizes local populations, while empirical studies report variable effects. We hypothesize that this discrepancy arises to a meaningful extent from differences in the ecological processes captured by various diversity and stability metrics. Analyzing over 8,000 permanent vegetation plots across biomes on five continents, we found a negative (i.e., destabilizing) diversity–stability relationship when using abundance-weighted rather than unweighted measures of population stability, which are more influenced by dominant species. Similarly, cumulative richness—capturing total species occurrence over time and long-term turnover—reveals a stronger destabilizing effect compared to average annual richness. Our findings reveal that, when specific metrics of diversity and stability are considered, increased interspecific coexistence tends to destabilize populations across natural ecosystems worldwide—particularly those of dominant species.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".