Can redistribution of breeding colonies on a landscape mitigate changing predation danger?
Bibliographic record
Abstract
The reproductive success of colonially breeding species depends in part upon a trade‐off between the benefit of a dilution effect against nestling predation within larger colonies and colony conspicuousness. However, there may be no net survivorship benefit of dilution if smaller colonies are sufficiently inconspicuous. This raises the question about how the size distribution of breeding colonies on a landscape might change as the predation danger for nestlings changes. In southwest British Columbia, Canada, bald eagle Haliaeetus leucocephalus populations have increased exponentially at ∼5% per year in recent decades and prey upon nestlings of colonial breeding great blue herons Ardea herodias faninni . Motivated by field data on reproductive success in relation to colony size, modeling is used to ask under which circumstances trading off a dilution benefit against colony conspicuousness can improve population reproductive success. That is, which colonial nesting distribution, dispersed and cryptic versus clumped and conspicuous, best mitigates predation danger on nestlings? When predators are territorial, the modeling predicts a dispersed nesting strategy as attack rate increases, but not as predator numbers increase. When predators are non‐territorial, the modeling predicts a dispersed nesting strategy as predator numbers and/or attack rates increase. When predators are both territorial and non‐territorial, colonial nesting within a predator's territory improves reproductive success when attack rates are low. This suggests nesting in association with territorial predators may offer decreased levels of predation when compared with nesting amongst non‐territorial predators. Thus a change in the colony size distribution of colonially breeding species might be anticipated on a landscape experiencing a change in predation danger.
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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 | 0.001 | 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".