Interactions between seabirds and endemic deer mouse populations on Santa Barbara Island, California
Bibliographic record
Abstract
Nesting seabirds alter habitat and food availability for insular rodent populations; in turn, rodents can reduce seabird nest success by consuming eggs and chicks. Predation by deer mice ( Peromyscus maniculatus elusus Nelson and Goldman, 1931) is considered a significant threat to reproductive success of Xantus’ Murrelet ( Synthliboramphus hypoleucus (Xantus de Vesey, 1860)), a small, burrow-nesting seabird that breeds off the coast of southern California and Baja California. We live-trapped mice in and out of seabird colonies on Santa Barbara Island, California, USA, to determine the effects of seabirds on mouse populations. We used stable isotope analysis to determine if mice fed on murrelet eggs and chicks. Mouse densities increased significantly on all sites from winter to summer, but there were no significant differences in densities between areas with and without seabirds. Although mice were abundant in murrelet colonies, mouse populations appeared to be affected more by habitat factors than seabird populations: areas with greater rock cover supported higher densities, fewer juveniles, and larger adults in winter and spring, whereas grassland sites had high densities and more reproductive adults in summer. We found no evidence of consumption of murrelet chicks or eggs, suggesting that eggs are not a major component of the diet of most mice. However, mice can still have a significant impact on local murrelet productivity because few eggs are laid each season relative to the high numbers of mice present.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".