Are nonsocial species more social than we think? Seasonal patterns in sociality in a solitary terrestrial carnivore
Bibliographic record
Abstract
Animal sociality, the extent and manner in which conspecifics associate with each other, ultimately affects an individual's survival and reproductive success. It is shaped by the spatiotemporal configuration and composition of the social units (e.g. individual, pair, group) in a population. Here, we assessed the formation and structure of social networks of a presumed nonsocial species with individual-based movement data of 153 GPS-marked brown bears, Ursus arctos. We explored changes in the frequency of dyadic associations in relation to distinct seasonal patterns (i.e. mating, hyperphagia and hunting seasons) that affect bear behaviour. We found seasonally distinctive frequencies in brown bear associations throughout their active period and that reproduction was the main driver for associations in the population, that is, the highest frequency of associations occurred during the mating season and male–female dyads during the mating season included the majority (73%) of observed associations. We also observed dyadic associations during the hyperphagia and hunting seasons, but found no significant changes in frequency during these seasons. In addition, we found that social structures during both the mating and nonmating periods were nonrandom, that is, dyadic associations occurred more often than expected. Animal sociality is commonly viewed as a classification of social versus nonsocial, but our results suggest that it is rather a dynamic continuum primarily influenced by variation in a species' spatiotemporal configuration (i.e. seasonal movements, social unit structure) and demographic composition (i.e. age, sex). Our results also support the contention that studies focusing on animal sociality should include a sociospatial perspective, as both components are tightly linked. Since sociality can affect individual fitness, and vice versa, advancing the knowledge on assumed ‘solitary’ species is paramount for the conservation and sustainable management of their populations.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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, 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".