Environmental, social, and morphological drivers of fission-fusion dynamics in a social ungulate
Bibliographic record
Abstract
Abstract Social groups exist because individuals within the group accrue a net benefit from sharing space. The profitability of sociality, however, varies with ecological context. As ecological context varies, tension emerges among the costs and benefits of social grouping. Fission-fusion societies are fluid in their group dynamics across spatial and temporal contexts, permitting insights into how context affects whether animals choose to join or depart a group. We tested four non-mutually exclusive hypotheses driving variation in fission and fusion in caribou: the risky places, environment heterogeneity, activity budget, and social familiarity hypotheses. The risky places hypothesis predicts animals are unlikely to diffuse when habitats are open and risk of predation is elevated. The habitat heterogeneity hypothesis predicts that fission is more likely in a heterogeneous landscape due to the rising conflicts of interest between group members. The activity budget hypothesis predicts dyads associate by body size due to similar food passage rates. The social cohesion hypothesis predicts that familiar individuals are less likely to fission. We tested the hypotheses using time-to-event (time before fission) analyses and a linear model that assesses spatial, social, and body size relationships among female caribou (n = 22) on Fogo Island, Newfoundland, Canada. Contrary to our prediction for risky places, probability of fission was not influenced by habitat openness. The hypothesis of environmental heterogeneity was partially supported, as caribou remained less cohesive in environments with a higher richness of habitats. No direct evidence emerged to support the activity budget hypothesis. However, it appears that caribou maintain the strongest social bonds among variably sized individuals and these social bonds do decrease the propensity to split. Collectively, our findings showed that social interactions may depend not only on individual identity and characteristics, but also the spatial context in which these interactions occur.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".