Behavioral dominance interactions between <i>Nicrophorus orbicollis</i> and <i>N. tomentosus</i> burying beetles (Coleoptera: Silphidae)
Bibliographic record
Abstract
Asymmetric interference competition, where one species is behaviorally dominant over another, appears widespread in nature with the potential to structure ecological communities through trade-offs between competitive dominance and environmental tolerance. The details of how species interact and the factors that contribute to behavioral dominance, however, are poorly known for most species, yet such details are important for understanding when and why trade-offs occur. Here, we examine behavioral interactions between two species of burying beetles (Coleoptera: Silphidae) that compete for limited breeding resources (i.e., small vertebrate carcasses) in nature, to identify behaviors involved in interference competition and to test if large body size, species identity, or time of arrival best predict behavioral dominance among species. To test these ideas, we placed same-sex individuals of Nicrophorus orbicollis (early to mid-summer breeder) and N. tomentosus (late summer to fall breeder) into an enclosure together with a 25–30 g mouse carcass ( Mus musculus ). We then video-recorded all behaviors, including neutral and aggressive interactions, for 13 h per trial ( N = 14 trials). For each interaction, we assigned a winner based on which beetle retained its position instead of fleeing or retained possession of the carcass; the overall behavioral dominant was determined as the individual that won the most interactions over the length of the trial. We found that large body size was the best predictor of behavioral dominance. In most interactions, N. orbicollis was larger and dominant over N. tomentosus ; however, when N. tomentosus was larger they outcompeted smaller N. orbicollis , illustrating the importance of body size in aggressive contests. The order of arrival to the carcass (priority effects) did not predict behavioral dominance. The larger size and abundance of N. orbicollis in nature suggest a competitive asymmetry between the species, supporting the idea that N. orbicollis constrains the ability of N. tomentosus to breed earlier in the summer.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
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) | 0.001 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".