INFERRING COLONIZATION PROCESSES FROM POPULATION DYNAMICS IN SPATIALLY STRUCTURED PREDATOR–PREY SYSTEMS
Bibliographic record
Abstract
We examine how spatial subdivision of predator–prey systems affects colonization processes in metapopulations. Dynamics of the herbivorous spider mite Tetranychus urticae (prey) and the predatory mite Phytoseiulus persimilis are highly unstable on isolated bean plants (Phaseolus lunatus) and ultimately result in extinction of prey and predators. Assembling a collection of 90 plants without any dispersal barriers (a super-island experiment) does not modify the persistence of the predator–prey system. Subdividing the system into a metapopulation with barriers for dispersal (a collection of eight islands with 10 plants per island) leads to persistence of the predator–prey dynamics for many generations. In this paper, we use the time series of colonization events and prey and predator densities from the super-island and metapopulation experiments to understand how colonization processes of prey and predatory mites are altered by spatial subdivision. Using survival analysis, we estimate how prey and predator colonization probability is affected by densities of the colonist pool at different distances from the target plant. Contrasting the results from the super-island and metapopulation experiments reveals that spatial subdivision affects the discovery rate of prey outbreaks by predatory mites and differentially affects colonization by prey and predators. Prey colonization is primarily determined by local densities of prey in spatially subdivided systems, whereas predator colonization retains primarily “global” influences. Our analysis of colonization processes suggests mechanisms accounting for stability in the metapopulation experiments and provides the quantitative basis for the development of colonization functions to explore these mechanisms in predator–prey models of acarine systems.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".