Application of Population Viability Theory to Moose in Mainland Nova Scotia
Bibliographic record
Abstract
Populations of moose (Alces alces americana) in mainland Nova Scotia, Canada, have been reduced to approximately 1,000 individuals fragmented into a number of isolated populations. Although the data required for a comprehensive population viability assessment (PVA) are not currently available, there are some general rules concerning minimum viable population (MVP) size that may be applied for a preliminary assessment. Genetic evidence suggests that, in general, a genetically effective population (Ne) of 50 individuals is required for short-term persistence and 500 to 5,000 individuals are required for long-term survival. Census population size (N) is generally larger than Ne, and a 10:1 relationship between N and Ne has been roughly established in moose populations elsewhere. Given this relationship, N = 5,000 individuals may be required for long-term viability. Based on current home range size (30-55 km) and population density (0.05/km), the minimum critical area required by a population of this size is estimated to be approximately 100,000200,000 km. Strategies for moose conservation and forest management should concentrate on (1) conducting genetic, population, and habitat analyses to increase understanding of population viability and limiting factors; (2) reestablishing connectedness among discrete populations to form a viable metapopulation; (3) protecting/enhancing habitat to meet the critical requirements of a viable population; and (4) increasing carrying capacity of available habitat to support a greater
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".