Family Breakup Dynamics in a Promiscuous Solitary Mammal
Bibliographic record
Abstract
ABSTRACT Family breakup dynamics in mammals can be complex due to competing interests between parents and offspring. Parents need to balance their own as well as their offspring's fitness through either terminating care early or extending care. Yet, males can disrupt this trade‐off as they may force females to focus on future litters by separating or killing offspring, especially in species where sexually selected infanticide occurs. Here, we investigated the family breakup dynamics in brown bears (Ursus arctos) by using GPS relocation data from 144 individuals (114 unique individuals: 23 mothers, 49 offspring, and 42 adult males) in southcentral Sweden. We explored the movement of mothers, their offspring, and adjacent adult males to gain insights into the factors influencing family breakup. Our findings indicate that females with 2‐year‐olds tend to separate before the mating season, whereas females with yearlings typically experience breakups during the mating season. Our results show that females accompanied by yearlings increased their movement speeds 2 weeks before the family breakup. The movement speed of the families that separated was two to three times higher compared to families that remained together. Furthermore, males associated with family groups before and during the mating season. Several associations during the mating season between adult males and family groups occurred on the same day that the family broke up. The increased space use makes the family group more conspicuous on the landscape; this likely increases the detection probability by a male and increases the chance of family breakup. Maternal care tactics can influence both female and offspring fitness, and here we provided additional evidence of the interplay between female and adult male behavior in terminating care in a solitary carnivore.
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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 | 0.000 |
| 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, 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".