Kinship, dear enemies, and costly combat: The effects of relatedness on territorial overlap and aggression in a cooperative breeder
Bibliographic record
Abstract
Abstract Many species maintain territories, but the degree of overlap between territories and the level of aggression displayed in territorial conflicts can vary widely, even within species. Greater territorial overlap may occur when neighboring territory holders are close relatives. Animals may also differentiate neighbors from strangers, with more familiar neighbors eliciting less‐aggressive responses during territorial conflicts (the “dear enemy” effect). However, research is lacking in how both kinship and overlap affect territorial conflicts, especially in group‐living species. Here, we investigate kinship, territorial overlap, and territorial conflict in a habituated wild population of group‐living cooperatively breeding birds, the southern pied babbler Turdoides bicolor . We find that close kin neighbors are beneficial. Territories overlap more when neighboring groups are close kin, and these larger overlaps with kin confer larger territories (an effect not seen for overlaps with unrelated groups). Overall, territorial conflict is costly, causing significant decreases in body mass, but conflicts with kin are shorter than those conducted with nonkin. Conflicts with more familiar unrelated neighbors are also shorter, indicating these neighbors are “dear enemies.” However, kinship modulates the “dear enemy” effect; even when kin are encountered less frequently, kin elicit less‐aggressive responses, similar to the “dear enemy” effect. Kin selection appears to be a main influence on territorial behavior in this species. Groups derive kin‐selected benefits from decreased conflicts and maintain larger territories when overlapping with kin, though not when overlapping with nonkin. More generally, it is possible that kinship extends the “dear enemy” effect in animal societies.
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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".