Habitat Characteristics and Nest Predation do not Explain Clustered Breeding in Least Flycatchers (Empidonax Minimus)
Bibliographic record
Abstract
Abstract Animals often exhibit territorial spatial structure in their breeding habitat. This clustering behavior is not well understood. We reviewed eight hypotheses for clustering and tested two ecological hypotheses for the formation of dense, territorial clusters in the Least Flycatcher (Empidonax minimus), a socially monogamous forest bird. The material resources hypothesis suggests that clustering is a response to habitat heterogeneity in vegetation, food, or both. The predation hypothesis proposes that clustering may reduce nest predation. Univariate and multivariate analyses of 170 vegetation plots from 1997 to 1998 indicated that forest-stand structure and tree species composition could not explain clustering in our population (predictions 1–3). Comparison of mean arthropod biomass inside with arthropod biomass outside two clusters sampled in 1999 using Malaise traps revealed that potential food resources were also unrelated to clustering (prediction 4). Nest predation rates were not correlated with territory position in clusters or with cluster size. In addition, predation rates were similar for clustered and solitary pairs (predictions 5–7). We conclude that habitat characteristics and nest predation do not explain clustered breeding in Least Flycatchers, though further tests of those hypotheses would be helpful. We develop the idea that the pursuit of extrapair copulations may promote clustered breeding. Future studies of territorial spatial structure in Least Flycatchers and other species should consider explanations based on mating behavior concomitant with ecological explanations for clustering.
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) | 0.000 | 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".