Seasonal habitat selection and ranging of domestic cats (Felis catus) in rural and urban environments
Bibliographic record
Abstract
Abstract Domestic cats ( Felis catus ) thrive at high densities alongside humans in urban and rural environments and are responsible for excessive wildlife predation worldwide. As urbanisation and farmland expands, and domestic cats inevitably reach previously unoccupied habitats, management plans will rely on understanding cat ranging behaviours. Cat movements and habitat selection may differ depending on their surroundings, and consequently, we sought to assess how male and female cat behaviours varied during different seasons in urban, suburban, and rural environments. In cities and farmland in the UK, the location of 56 owned cats (26 F:30 M) was recorded every 5 min for a total of 5237 h using GPS collars (454 ± 25 fixes over c. 4 days per individual). Urban and rural cats exhibited similar patterns of home ranges, maximum distances travelled from their owner’s house, and habitat selection, where they selected for built-up areas with good cover and avoided open spaces. Cats spent an average of 75% of their time outside their owners’ house or garden and therefore had great potential to encounter wild prey. Males in rural areas were almost twice as active than other males but all exhibited crepuscular activity patterns compared to cathemeral or diurnal females. In summer, cats had smaller home ranges and were more nocturnal, poentially concentrating their impacts around core areas during hotter months. Similarities in cat ranging behaviours across the urban–rural gradient suggest management plans can be equally applied in areas alongside cities as well as farmland. Buffer or exclusion zones of 750 m around protected areas would exclude 95% of cats, but specialised management, such as periodic confinement during specific active periods, could prove effective during vulnerable prey species’ breeding seasons. These findings improve our understanding of how cat ranging is affected by urbanisation under seasonal variation, and can be used to tailor management strategies as new species and populations are exposed to domestic cat predation.
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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 | 0.000 |
| 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 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".