Effects of age, breeding strategy, population density, and number of neighbors on territory size and shape in <i>Passerculus sandwichensis</i> (Savannah Sparrow)
Bibliographic record
Abstract
ABSTRACT The size and shape of an animal’s breeding territory are dynamic features influenced by multiple intrinsic and extrinsic factors and can have important implications for survival and reproduction. Quantitative studies of variation in these territory features can generate deeper insights into animal ecology and behavior. We explored the effect of age, breeding strategy, population density, and number of neighbors on the size and shape of breeding territories in an island population of Passerculus sandwichensis (Savannah Sparrow). Our dataset consisted of 407 breeding territories belonging to 225 males sampled over 11 years. We compared territory sizes to the age of the male territorial holder, the male’s reproductive strategy (monogamy vs. polygyny), the number of birds in the study population (population density), and the number of immediate territorial neighbors (local density). We found substantial variation in territory size, with territories ranging over two orders of magnitude from 57 to 5,727 m2 (0.0057–0.57 ha). Older males had larger territories, polygynous males had larger territories, territories were smaller in years with higher population density, and larger territories were associated with more immediate territorial neighbors. We also found substantial variation in territory shape, from near-circular to irregularly shaped territories. Males with more neighbors had irregularly shaped territories, but shape did not vary with male age, breeding strategy, or population density. For males that lived 2 years or longer, we found strong consistent individual differences in territory size across years, but weaker individual differences in territory shape, suggesting that size has high repeatability whereas shape has low repeatability. Our work provides evidence that songbird territories are highly dynamic, and that their size and shape reflect both intrinsic factors (age and number of breeding partners) and extrinsic factors (population density and number of territorial neighbors).
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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 | 0.001 |
| 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) | 0.002 | 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".