Effect of snow cover on the off-host survival of <i>Dermacentor variabilis</i> (Acari: Ixodidae) larvae
Bibliographic record
Abstract
The geographical range of the American dog tick, Dermacentor variabilis (Say), in Canada continues to expand northwards into areas with colder winter temperatures. Understanding what influences the off-host survival of D. variabilis over winter is important for predicting the northern distributional limit of this species. A field experiment was conducted to determine the effect of snow cover on the off-host survival of unfed D. variabilis larvae from a population situated near the northern distributional limit in Saskatchewan, Canada. Ticks were placed in tubes within 1 of 9 field enclosures (tickaria) in early fall. The 9 tickaria were divided into 3 equal treatment groups: no snow cover, natural snow cover (maximum depth of 25 cm) and extra snow cover (maximum depth of 32 cm). Tick survival was measured in mid-winter and in early spring (i.e., ~17 and ~26 wk after start of experiment). The results showed that snow cover had a significant impact on the relative humidity, but not temperature, in the tickaria. Larvae in tickaria with no snow cover had a higher mortality rate (27%) than larvae in tickaria with natural snow cover (6%) or extra snow cover (4%). Although snow cover enhanced off-host survival, many individuals were able to survive in sub-zero temperatures under leaf litter in the absence of continuous snow cover for a period of 108 days. These findings have implications for the construction of predictive models to determine the northern distributional limits of D. variabilis, a species that is an important vector of several pathogens.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".