Understanding the impact of meningeal worm, Parelaphostrongylus tenuis, on moose populations.
Bibliographic record
Abstract
Periodic declines in moose ( Alces alces ) populations have occurred repeatedly during the past century on the southern fringe of moose range in central and eastern North America. These slow declines, occurring over a number of years, are associated with higher than usual numbers of co-habiting white-tailed deer ( Odocoileus virginianus ). Numerous proximate causes have been hypothesized but none has gained widespread acceptance among cervid managers. However, current knowledge of the nature of moose declines and the biology of meningeal worm ( Parelaphostrongylus tenuis ) makes this parasite the most credible explanation. Other suggested disease-related causes are rejected, including infection with liver flukes ( Fascioloides magna ) because there is no clinical evidence that flukes kill moose. As well, this parasite occurs at only moderate prevalence and intensity in some jurisdictions and is completely absent in others where moose declines are known. Winter ticks ( Dermacentor albipictus ), on the other hand, do kill moose but usually have a distinctly different and more immediate impact on populations. It is recognized that moose, albeit at lower density, can persist for extended periods in the presence of P. tenuis -infected deer at moderate densities. However, it is argued here that parelaphostrongylosis can, when conditions favour sustained high deer densities and enhanced gastropod transmission, cause moose numbers to decline to low numbers or to become locally extinct. Short, mild winters favour deer population growth in areas previously best suited for moose. Wetter and longer snow-free periods increase the numbers and availability of terrestrial gastropod intermediate hosts and the period for parasite transmission. It is hypothesized that these climatic conditions increase rates of meningeal worm transmission to moose and of disease, primarily among younger cohorts. Reports of overtly sick moose are common during declines but may not account for the total mortality and morbidity caused by meningeal worm. Means by which the parasite may lower recruitment and productivity causing slow declines still needs clarification. Managers in areas prone to declines should monitor weather trends, deer numbers, and the prevalence of meningeal worm in deer. Moose recovery will occur only after deer numbers are decidedly reduced, either by appropriate management or a series of severe winters.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".