Bibliographic record
Abstract
AbstractAllee effects are common to diverse taxa, but their consequences for coexistence are rarely considered by ecologists. Recent research has suggested that Allee effects are incompatible with modern coexistence theory or that their impacts on coexistence are no different from other sources of positive density dependence that generate alternate stable states through priority effects. We use a graphical approach that builds on mathematically robust theory to develop simple conditions for coexistence and alternate stable states when an Allee effect is present. We show that weak Allee effects (those that do not depress population growth rates below zero in the absence of competition) can be integrated with modern coexistence theory but often produce outcomes distinct from other priority effects. This integration allows us to determine how Allee effects alter stabilizing and fitness differences. Importantly, we characterize a high-density criterion for a third alternate stable state that indicates species coexistence even when mutual invasibility is not met. Strong Allee effects (those that preclude invasibility even in the absence of competitors) permit coexistence only when the high-density criterion is satisfied. Our model offers an intuitive extension of modern coexistence theory that accounts for more than two alternative stable states and provides a guide for empirical research on how Allee effects structure ecological diversity.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".