Opposite responses of body condition and fertility in adjacent moose populations
Bibliographic record
Abstract
ABSTRACT Moose (Alces alces) populations exceed 3 individuals/km2 in some wildlife reserves and parks of northeastern Canada. Heavy browsing pressure at such densities is potentially altering the ecological integrity of forests with eventual negative consequences for moose. We hypothesized that regulation by resources would be limited by the capacity of female moose to modulate their reproductive strategies to maintain high fertility despite a decline in body condition. We observed a 20–33% decline in rump fat thickness in males and females, respectively, from the high density Matane Wildlife Reserve in Eastern Québec in October compared to an adjacent population. We also observed a lower mass of the peroneus group of muscles for males (−3%) and prime‐aged females (−8%) in the Matane Wildlife Reserve than in the adjacent population. Females from the Matane Wildlife Reserve population had a lower twinning ovulation rate (1 out of 20 vs. 7 out of 21 ovulating females in the adjacent population) but >15% higher overall ovulation rate. Our results suggest that female moose can maintain high fertility despite a decline in body condition, by reducing their litter size at ovulation and conserving energy to increase the probability of annual reproduction. The adjustment of female reproductive strategies illustrates the plasticity of moose in response to decreasing habitat quality. We conclude that in the absence of specialist predators, equilibrium with forage is unlikely for large herbivores in the short or mid‐term. Active management of moose populations is likely required to maintain the ecological integrity of boreal forests. © 2014 The Wildlife Society.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".