Effects of intensive harvesting on moose reproduction
Bibliographic record
Abstract
Summary 1. It has been hypothesized that a balanced adult sex ratio is necessary for the full participation of ungulate females in reproduction and therefore high productivity. We tested this general hypothesis by combining two complementary approaches. 2. First, using telemetry (n = 60) and annual aerial censuses between 1995 and 1998, we compared two mooseAlces alcespopulations in Quebec, Canada, one non‐harvested and the other subject to intensive sport harvesting from the end of September to mid‐October. We tested the following predictions for the harvested population: (i) females increase movements and home ranges during the mating period; (ii) the mating system is modified, with the appearance of groups of one male and many females; (iii) subadult males participate in reproduction; (iv) the mating period extends over two to three oestrus cycles; (v) the calving period extends over several months; and (vi) productivity declines. 3. Daily movements and home range sizes during the mating period did not differ between harvested and non‐harvested populations. Most groups observed were male–female pairs. Subadult males (1·5–2·5 years old) were only observed with females in the harvested population. Mating and calving periods did not differ between populations. The proportion of females that gave birth and the number of calves produced were also comparable in the two populations. 4. Secondly, we also assessed the existence of a relationship between population productivity and percentage of males in various management units of the province of Quebec that were characterized by a wide range in sex ratios. Contrary to prediction (vi), the number of calves per 100 adult females was not related to the percentage of adult males in the population. 5. The participation of young adult males (subadults) in reproduction in our harvested population may have compensated for the lower percentage of adult males, and thus productivity was unaffected. We therefore reject the hypothesis that intensive harvesting, at least at the level we observed, affects reproduction and population productivity. 6. As there are some uncertainties regarding the long‐term effects of high hunting pressure, however, managers should favour sex ratios close to levels observed in non‐harvested populations.
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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".