Climate change and the epidemiology of protostrongylid nematodes in northern ecosystems:<i>Parelaphostrongylus odocoilei</i>and<i>Protostrongylus stilesi</i>in Dall's sheep (<i>Ovis d. dalli</i>)
Bibliographic record
Abstract
We describe the epidemiology of the protostrongylid parasites Parelaphostrongylus odocoilei and Protostrongylus stilesi in Dall's sheep (Ovis dalli dalli) from the Mackenzie Mountains, Northwest Territories, Canada (65 degrees N; 128 degrees W). Peak numbers of 1st-stage larvae of both parasites were shed by Dall's sheep on their winter range from March until May. In larval development experiments in the Mackenzie Mountains, peak numbers of infective 3rd-stage larvae of P. odocoilei were available in gastropod intermediate hosts in August-September. For both protostrongylids, the majority of transmission likely occurs on the winter range, with infection of gastropods when they emerge from hibernation in spring, and infection of Dall's sheep upon their return in fall. We validated a degree-day model for temperature-dependent development of larval P. odocoilei in gastropods, and applied degree-day models to describe and predict spatial and temporal patterns in development of P. odocoilei and P. stilesi in northern North America. Temperature-dependent larval development may currently limit northward range expansion of P. odocoilei into naïve populations of Dall's sheep in the Arctic, but climate warming may soon eliminate such constraints. In Subarctic regions where both P. odocoilei and P. stilesi are endemic, the length of the parasite 'growing season' (when temperatures were above the threshold for larval development) and amount of warming available for parasite development has increased over the last 50 years. Further climate warming and extension of the seasonal window for transmission may lead to amplification of parasite populations and disease outbreaks in host 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".