“The landscape of love”: sex-specific habitat-use during the mating season in a solitary large carnivore
Bibliographic record
Abstract
Context: In mammals, reproductive strategies and movement behavior can differ between sexes, influenced by biological and environmental factors. Whereas males typically adopt a "roam-to-mate" strategy, increasing movement to locate females, females may also adjust their behavior to enhance mating opportunities. Habitat and human disturbance can further shape the spatial structure of mating encounters. Objectives: This study investigates sex-specific habitat use during mating in brown bears. We test (1) which habitats facilitate initial male-female encounters, and (2) how habitat use differs between solitary and consorting individuals, focusing on sex-based differences and responses to anthropogenic features. Methods: We used GPS data from 70 unique adult brown bears (44 females, 26 males) during the mating season in Sweden (2006-2016). We contrasted initial encounter areas of male-female pairs with surrounding available habitat to assess encounter site preferences, accounting for natural and anthropogenic landscape features. Additionally, we compared habitat use for each sex when solitary versus consorting. Results: Bears most often encountered the opposite sex in clearcuts and young forests. When consorting, males moved farther away from anthropogenic areas than when solitary and increased their use of clearcuts, whereas females reduced their use of young and old forests, in contrast to males. Both sexes approached roads more when consorting. Conclusion: This study revealed distinct sex-specific habitat preferences during brown bear consorting behavior, supporting the evidence of female "roam-to-mate" behavior by adjusting to males' habitat use. Our findings emphasize the importance of managing anthropogenic landscapes for conservation efforts, especially if they disrupt mating behaviors. Supplementary Information: The online version contains supplementary material available at 10.1007/s10980-025-02250-6.
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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 | 0.001 | 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, 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".