Predator Responses to Similarity and Dispersion of Artificial Nest Sites: Implications for the Structure of Boreal Forest Songbird Communities
Bibliographic record
Abstract
Abstract Relatively little is known about the role of predation in shaping patterns of coexistence and nest dispersion of songbird species. It has been hypothesized that predators diversify songbird communities by preying more heavily on individuals and species with greatest similarity in nest-site use. To investigate the importance of predation, we tested how predators responded to assemblages of artificial songbird nests that varied in nest-site placement, vegetation features, and nest dispersion patterns in boreal forest of west-central Alberta, Canada. Variability among nest sites was achieved by deploying wicker nests throughout a gradient of vegetation cover and by deploying nests to simulate two- and three-species assemblages. Two-species assemblages, comprising 20 simulated White-throated Sparrow (Zonotrichia leucophrys) and 3 simulated Hermit Thrush (Catharus guttatus) nests, and three-species assemblages, comprising 10 simulated White-throated Sparrow, 9 simulated Hermit Thrush, and 4 simulated Chipping Sparrow (Spizella passerina) nests, were deployed in eight replicate plots. We hypothesized that predators would be more adept at locating and depredating (1) nests characterized by similar vegetation features in nest patches; (2) nests of similar appearance or nest guild; and (3) clumped versus randomly distributed nests. Contrary to predictions, predation did not increase as variance in vegetation of nest sites decreased across 16 nest-predation plots, nor did variance in vegetation of successful nests increase as predation level increased across 15 nest-predation plots. The addition of one species' nest type to assemblages did not result in lower predation rates. Predators also did not depredate more clumped nests than randomly distributed nests. Overall, predation did not appear to influence patterns of songbird species coexistence or nest dispersion. Abilities of predators to discriminate among less-similar versus more-similar nest sites and nest-dispersion patterns are probably species-specific; that is probably related to the hunting behavior of predators (i.e. use of olfactory and visual cues) and territory size.
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 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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 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".