A SCOPING REVIEW OF THE RANGIFER TARANDUS INFECTIOUS DISEASE LITERATURE: GAP BETWEEN INFORMATION AND APPLICATION
Bibliographic record
Abstract
The role and impact of infectious diseases in wildlife population dynamics are increasingly recognized, yet disease information is variably incorporated into wildlife management frameworks. This discrepancy is particularly relevant for Rangifer tarandus (caribou or reindeer), a keystone circumarctic species experiencing widespread population declines. The primary objective of this review was to characterize the available peer-reviewed literature on infectious diseases of Rangifer by using a scoping review methodology. Three databases of peer-reviewed literature-Web of Science, BIOSIS previews, and Scopus-were searched and 695 articles met the criteria for initial review. After screening for relevance and language, 349 articles, published between 1967 and 2020, remained. More than half of the excluded articles (181/346; 52%) were left out because they were not published in English; the majority of these excluded articles (120) were in Russian. From the 349 included articles, 137 (39%) pertained to wild (as opposed to semidomesticated or captive) Rangifer populations. Articles on infectious disease in wild Rangifer were published in 40 different journals across various disciplines; the most common journals were disease and parasitology oriented, accounting for 55% of included articles. Most studies were descriptive (87%), followed by experimental (9%). Of the pathogen taxa investigated, helminths were the most common, comprising 35% of articles. Rangifer subspecies were not equally represented in the literature, with barren-ground caribou (R. t. groenlandicus; n=40) and woodland caribou (R. t. caribou; n=39) having the greatest abundance and diversity of infectious disease information available. Few studies explicitly examined individual or population-level impacts of disease, or related disease to vital population rates, and only 27 articles explicitly related results to management or conservation. Findings from this review highlight an unbalanced distribution of studies across Rangifer ecotypes, a preference for dissemination in disease-specialized publication venues, and an opportunity for investigating population-level impacts that may be more readily integrated into caribou conservation frameworks.
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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 | 0.020 | 0.086 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.033 | 0.025 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".