Factors Affecting European Badger Movement Lengths and Propensity
Bibliographic record
Abstract
Understanding the mechanisms underpinning animal movement patterns is one of the key goals of animal ecology. The motivation to move across populations can be driven by a number of factors, including finding new mates, reducing competition or exploiting new resources. The movement ecology of wildlife hosts of zoonotic diseases – e.g. European badger, Meles meles, a reservoir of bovine tuberculosis – is also important when attempting to manage spill-back infection to humans or domestic animals. We studied badger movements, using mark–recapture data (2008–2012) at a large spatial scale (755 km 2 ) in Ireland. We investigated both intrinsic (sex, age-class, or weight at capture) and extrinsic (territory size, group size, or population density) factors that may have affected either movement length or the propensity to move across putative territorial boundaries. We constructed several models using differing metrics of territory size and density, forming a matrix of competing models, from which we assessed similarities and differences. Older badgers tended to make shorter movements relative to other age classes. Movement length increased with greater time intervals between captures. Importantly, there was negative density-dependence with movement length; shorter movements were associated with higher-density areas. The propensity to move across putative territories varied depending on the metrics of territory configuration or badger abundance. Across models, there was a general trend toward lower movement propensity for older badgers and higher densities (or group sizes) and a higher propensity with increasing time between captures. Taken together, our data suggest that there are density-dependent mechanisms affecting movement patterns in badgers within subpopulations. Badgers in higher density areas generally exhibited shorter and less frequent movements than badgers in lower-density areas. However, overall, there was no net tendency for badgers to move into higher- or lower-density areas. These findings help us understand badger movement ecology and will have implications for understanding bovine tuberculosis dynamics across badger 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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".