Feedback effects of chronic browsing on life-history traits of a large herbivore
Bibliographic record
Abstract
1. Increasing ungulate populations are affecting vegetation negatively in many areas, but few studies \nhave assessed the long-term effects of overbrowsing on individual life-history traits of ungulates. \n2. Using an insular population of white-tailed deer (Odocoileus virginianus Zimmermann; \nAnticosti, Québec, Canada) introduced in 1896, and whose density has remained high since the first \nevidence of severe browsing in the 1930s, we investigated potential feedbacks of long-term and \nheavy browsing on deer life-history traits. \n3. We assessed whether chronic browsing contributed to a decline of the quality of deer diet in early \nautumn during the last 25 years, and evaluated the impacts of reduced diet quality on deer body \ncondition and reproduction. \n4. Rumen nitrogen content declined 22% between two time periods, 1977–79 and 2002–04, \nindicating a reduction in diet quality. \n5. After accounting for the effects of year within the time period, age and date of harvest in autumn, \npeak body mass of both sexes declined between the two time periods. At the end of November, males \nwere on average 12% heavier and adult does 6% heavier in 1977–79 than in 2002–04. Hind foot \nlength did not vary between time periods. \n6. The probability of conception increased 15% between the two time periods, but litter size at \novulation declined 7%, resulting in a similar total number of ovulations in 2002–04 and in 1977–79. \n7. Our results suggest that following a decline in diet quality, white-tailed deer females modified \ntheir life-history strategies to maintain reproduction at the expense of growth. \n8. Deer appear to tolerate drastic reductions in diet quality by modifying their life history traits, \nsuch as body mass and reproduction, before a reduction in density is observed. Such modifications \nmay contribute to maintain high population density of large herbivores following population irruption.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".