Allee Effects, Colonization, and Extinction: The Surprising Benefits of Demographic Stochasticity
Bibliographic record
Abstract
Demographic stochasticity and Allee effects are two common mechanisms that increase extinction risk in small populations. High demographic stochasticity produces population fluctuations that cause extinction in small populations. Meanwhile, strong Allee effects create low-density thresholds, where growth rates are negative below the threshold and positive above. We hypothesized that stochastic fluctuations may drive populations over these thresholds, increasing the probability that a population establishes in a habitat. To test this hypothesis, we utilized properties of discrete-time Markov processes and a Ricker model with an Allee effect to quantify colonization and extinction rates. We show that demographic stochasticity can increase colonization rates over a range of carrying capacities in populations with strong Allee effects. In contrast, while higher demographic stochasticity always increases extinction rates of established populations, waiting times to extinction due to demographic stochasticity often exceed thousands of generations, even at relatively small carrying capacities (K=50). Given the frequency of catastrophic disturbances such as fires, extinction rates from demographic stochasticity are near negligible even in small populations with strong Allee effects. Thus, the net effect of demographic stochasticity is often positive. Overall, our study provides novel insights into a mechanism through which demographic stochasticity promotes species persistence.
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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 | 0.000 | 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 | 0.002 |
| 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".