A Comparative Health Assessment of Urban and Non-Urban Mule Deer (Odocoileus hemionus) in the Kootenay Region, British Columbia, Canada
Bibliographic record
Abstract
The provincial wildlife management agency, British Columbia Ministry of Forests, Lands, Natural Resource Operations and Rural Development, performed a translocation trial from 2015 to 2017 to control the urban mule deer (Odocoileus hemionus; uMD) overpopulation and supplement the declining non-urban mule deer (nuMD) population in the Kootenay region, British Columbia, Canada.Several local communities are now considering using uMD translocations as a long-term wildlife management method.The aim of this study was to characterize the health risks associated with the translocation initiative by comparing pathogen exposure, body condition scores (BCS) and pregnancy rates of urban and non-urban mule deer (nuMD) and to develop predictive disease models to inform management decisions related to urban deer translocations.Blood samples collected from 200 free-ranging mule deer captured in urban and non-urban environments in the Kootenay region from 2014 to 2017 were tested for exposure to selected pathogens and pregnancy status.Body condition scoring (BCS) and morphometric examinations were performed for each deer.BCS averaged 3.4 on a five-point scale, was greater in nuMD, and significantly differed between years.Antibodies were detected for adenovirus hemorrhagic disease virus (AHDV) (38.4% (uMD 43.7%, nuMD 33.3%)), bluetongue virus (BTV) (0.6% (uMD 1.2%, nuMD 0%)), bovine respiratory syncytial virus (BRSV) (8.4% (uMD 4.6%, nuMD 12.1%)), bovine viral diarrhea virus (BVDV) (1.1% (uMD 0%, nuMD 2.2%)), bovine parainfluenza-3 virus (PI3) (27.0%(uMD 27.6%, nuMD 26.4%)), Neospora caninum (22.1% (uMD 24.4%, nuMD 19.7%)) and Toxoplasma gondii (8.2% (uMD 12.3%, nuMD 3.9%)).No antibodies against epizootic hemorrhagic disease virus were detected.iii Pregnancy rates did not differ between the two deer populations (90.7% (uMD 90.6%, nuMD 90.9%)).Exposure to N. caninum was associated with a reduction in pregnancy rates.uMD were more likely to be exposed to T. gondii than nuMD.Comparison of body condition scores, pregnancy rates and pathogen exposure of uMD and nuMD showed that the health of the two populations did not significantly differ, suggesting that these particular pathogens do not factor in the decline of deer populations nor do they pose a risk of uMD translocations.However, predictive models indicated that exposure to AHDV, BRSV and T. gondii currently differs between deer populations and that uMD translocations would result in an increased risk of AHDV, BRSV and T. gondii transmission.The risk of BRSV and T. gondii transmission under a range of pathogen prevalence conditions was established to be of current concern and the risk of EHDV, BTV, BRSV, BVDV and T. gondii transmission was established to be of potential future concern for either populations.The number of uMD to translocate under the current conditions should be limited to 344 individuals as to minimize the risk of ADHV transmission and its potential negative effects on the nuMD population.Targeted continuous pathogen monitoring was shown to necessitate the sampling of a total of at least 133 individuals to detect realistic outbreaks in all pathogens of concern, including EHDV, BTV, BRSV, BVDV and T. gondii.These results should be considered as part of a formal risk assessment for future uMD translocations in southeastern British Columbia.knowledge, as well as my committee members, Dr.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".