Metapopulations, the Inflationary Effect, and Consequences for Public Health
Bibliographic record
Abstract
AbstractThe metapopulation concept offers significant explanatory power in ecology and evolutionary biology. Metapopulations, a set of spatially distributed populations linked by dispersal, and their community and ecosystem level analogs, metacommunity and meta-ecosystem models, tend to be more stable regionally than locally. This fact is largely attributable to the interplay of spatiotemporal heterogeneity and dispersal (the inflationary effect). We highlight this underappreciated (but essential) role of spatiotemporal heterogeneity in metapopulation biology, present a novel expression for quantifying and defining the inflationary effect, and provide a mechanistic interpretation of how it arises and impacts population growth and abundance. We illustrate the effect with examples from infectious disease dynamics, including the hypothesis that policy decisions made during the COVID-19 pandemic generated spatiotemporal heterogeneity that enhanced the spread of disease. We finish by noting how spatiotemporal heterogeneity generates emergent population processes at large scales across many topics in the history of ecology, as diverse as natural enemy-victim dynamics, species coexistence, and conservation biology. Embracing the complexity of spatiotemporal heterogeneity is vital for future research on the persistence of populations.
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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 | 0.005 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".