Ecological drift and the distribution of species diversity
Bibliographic record
Abstract
Ecological drift causes species abundances to fluctuate randomly, lowering diversity within communities and increasing differences among otherwise equivalent communities. Despite broad interest in ecological drift, ecologists have little experimental evidence of its consequences in nature, where competitive forces modulate species abundances. We manipulated drift by imposing 40-fold variation in the size of experimentally assembled annual plant communities and holding their edge-to-interior ratios comparable. Drift over three generations was greater than predicted by neutral models, causing high extinction rates and fast divergence in composition among smaller communities. Competitive asymmetries drove populations of most species to small enough sizes that demographic stochasticity could markedly influence dynamics, increasing the importance of drift in communities. The strong effects of drift occurred despite stabilizing niche differences, which cause species to have greater population growth rates when at low local abundance. Overall, the importance of ecological drift appears greater in non-neutral communities than previously recognized, and varies with community size and the type and strength of density dependence.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.013 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.003 |
| 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; both teacher heads agree on what is shown here.
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".