Personality, space use and tick load in an introduced population of Siberian chipmunks <i>Tamias sibiricus</i>
Bibliographic record
Abstract
1. Although behaviours can contribute to the heterogeneity in parasite load among hosts, links between consistent individual differences in behaviour and parasitic infection have received little attention. We investigated the role of host activity and exploration on hard tick infestations of marked individuals in a population of Siberian chipmunks Tamias sibiricus introduced in a suburban French forest over 3 years. 2. Individual activity-exploration profiles were assessed from 106 hole-board tests on 73 individuals, and chipmunks' trappability and trap diversity were used respectively as indices of their activity-exploration and space use on a sub-sample of 60 individuals. At each capture, we counted the total number of ticks per head of chipmunk. 3. We found significant and consistent individual differences in activity-exploration, trappability, trap diversity and tick load, and could estimate individual indices for these four variables, corrected for confounding effects of year, season, body mass and sex. 4. Using a path analysis, we found an indirect effect of activity-exploration on tick load: tick load increased with space use, which in turn was positively affected by trappability in the field. Trappability was itself positively related to activity-exploration in the hole board. Habitat type affected tick load, independently of behavioural traits. A second path model revealed a lack of either direct or indirect influence of tick loads on chipmunks' personality and trappability. 5. Our results show that host personality-related patterns in space use can lead to a non-random parasite distribution among hosts.
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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 | 0.000 | 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".