Visual and Olfactory Attributes of Artificial Nests
Bibliographic record
Abstract
Abstract Artificial nests are commonly used to investigate relative rates of nest predation in birds, but several methodological considerations need to be addressed before results from natural and artificial nests can be compared. Using field and laboratory experiments, we examined responses of predators to visual and olfactory cues that were associated with wicker nests and their contents. Avian predators did not discriminate between wicker nests dipped in mud and those covered by a camouflage fabric, whereas mammalian predators showed a weak tendency to depredate camouflaged nests. Nests containing plasticine eggs were depredated more often than nests containing only quail eggs and finch eggs, although no response to number of plasticine eggs in nests was found. The higher predation of nests with plasticine eggs may have resulted because small mammals, relying on olfactory cues, comprised a large portion of the predator assemblage. Field results were supported in tests where captive deer mice (Peromyscus maniculatus) were attracted to assortments of egg types that included plasticine. Time required by captive deer mice to penetrate quail eggs and finch eggs versus plasticine eggs varied as a function of egg size and shell thickness and strength. Overall, domestic finch eggs provided a better alternative to quail eggs because they were small enough to allow detection of predation events by small mammals and did not have an unnatural odor like plasticine. Potential problems with nest concealment, egg visibility, egg odors, and other factors must be resolved to enhance the design and reliability of artificial nest experiments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".