The fall and rise of bison populations in Wood Buffalo National Park: 1971 to 2003
Bibliographic record
Abstract
Two hypotheses have been proposed to explain the decline of bison (Bison bison (L., 1758)) abundance in Wood Buffalo National Park (WBNP). The "disease–predation" hypothesis proposes that tuberculosis (Mycobacterium bovis (Karlson and Lessel 1970)) and brucellosis (Brucella abortus (Schmidt 1901)) reduce bison survival and reproduction, resulting in a low-density, predator-regulated equilibrium. The "habitat dispersion hypothesis" proposes that bison in one area of WBNP, the Peace–Athabasca Delta (Delta), have an increased risk of predation because they are concentrated in large meadows with high temporal and spatial predictability. We incorporate bison census data, calf and yearling segregation counts, reproductive rates, adult survival rates, and adult disease incidence in a stochastic population model to show that the historical decline of bison in WBNP would have occurred regardless of disease prevalence. Our model shows that survival of juveniles, the age class that is least susceptible to disease effects, was likely an important determinant of historical changes in population size. We also demonstrate that the population decline was most pronounced in the Delta and that juvenile survival was lower in the Delta, despite evidence that disease incidence was lower in the Delta than in the rest of WBNP. Lastly, the current population trend in WBNP is one of rapid increase, even in the presence of disease.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".