Linking weather conditions and winter tick abundance in moose
Bibliographic record
Abstract
Abstract Climate change may modify species distribution to higher latitudes, resulting in potential changes of parasite diversity and transmission dynamics in areas where animals might not be locally adapted to these new parasite species. In addition, climate change may increase the frequency and severity of infestations of parasites that are already present in a region, by promoting the development and survival of infectious stages. Over the last decades, the number of moose ( Alces americanus ) infested by winter ticks ( Dermacentor albipictus ) has increased in eastern Canada, possibly because milder climatic conditions are increasing winter tick survival. Our main objective was to determine which meteorological variables are more likely to influence winter tick load on moose. We compiled several weather variables that may limit winter tick survival and explored which weather variables, or their interactions, influenced the winter tick load of 4,100 hunted moose from 2013 to 2019 in Québec, Canada along a latitudinal gradient. Winter tick load in fall decreased with the maximum number of consecutive days in spring with average daily temperatures below −15°C and with the number of consecutive days in summer with a relative humidity <80% when snowmelt in spring was earlier. These results suggest that cold temperatures and prolonged periods of low humidity, amplified by early snowmelt, limit the survival of adult female ticks and eggs, thus limiting their subsequent load on moose during the following fall. With climate change, precipitation increases and warm temperatures occur earlier in spring and are more frequent in summer. Our results suggest that climate change may have a positive long‐term influence on winter tick abundance in the environment and thereby increase winter tick load on moose, which could lead to a significant decrease in moose body condition and survival.
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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 | 0.000 | 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) | 0.000 | 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".