Assessment of the status and viability of a population of moose (<i>Alces alces</i>) at its southern range limit in Ontario
Bibliographic record
Abstract
Factors affecting the distribution and abundance of animals are of substantial interest, and across most of their southern range, populations of moose ( Alces alces (L., 1758)) are declining, presumably because of climate change. Conditions favouring moose population decline versus numerical increase in select areas of the range are not well understood. During 2006–2009, we tested the hypothesis that moose in southern Ontario formed a viable population near the species’ southern range limit, despite occurrence of climate patterns apparently deleterious for population growth. Our study upheld each of our predictions: (i) high pregnancy rate (83.0%) and annual female survival rate (0.899 (0.859, 0.941; 95% CI)), indicating that the population was increasing (λ = 1.16); (ii) female moose having blood-based condition indices within normal range, despite larger than expected home-range size; and (iii) levels of genetic differentiation indicating that the population was part of a larger metapopulation of moose in the region. We surmise that moose in southern Ontario currently are not subject to the prevalent continental decline, likely owing to favourable site-specific climatic conditions. Future research should elaborate on why select southern moose populations are increasing and whether they will ultimately succumb to die off as effects of climate change become increasingly pronounced.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".