The minimum founding population in dispersing organisms subject to strong Allee effects
Bibliographic record
Abstract
Summary Dispersal can push population density below strong Allee thresholds ensuring the demise of small founding populations. As a result, for isolated populations of dispersing organisms, the minimum founding population size that enables establishment can be quite different from the Allee threshold. We derive an expression for the minimum founding population size for a general integrodifference equation model of a dispersing population with a strong Allee effect. We demonstrate the utility of the general model by using it to approximate minimum founding populations for the mountain pine beetle. The minimum founding population of the general model increases linearly with the mean squared displacement of the dispersing organism. Transient dynamics of the general model suggest that population density at the point of introduction will often decrease before increasing, even when the minimum founding population size is exceeded. Calculation of minimum founding population sizes may prove useful for predicting invasion success based on propagule size and for maximizing the success of species reintroductions when strong Allee effects exist.
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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 | 0.002 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 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".