The short-term impact of abundant fruit upon deer mouse (<i>Peromyscus maniculatus</i>), southern red-backed vole (<i>Myodes gapperi</i>), and woodland jumping mouse (<i>Napaeozapus insignis</i>) populations
Bibliographic record
Abstract
Fruit has been identified as an important and potentially population-restricting food for southern red-backed voles (Myodes gapperi (Vigors, 1830)), deer mice (Peromyscus maniculatus (Wagner, 1845)), and woodland jumping mice (Napaeozapus insignis (Miller, 1891)). We added domestic dried strawberries (Fragaria × ananassa (Weston) Duchesne ex Rozier (pro sp.)) and European black currants (Ribes nigrum L.), which have native analogues and are preferred foods of these rodents, to white spruce (Picea glauca (Moench) Voss) plantations from May through August 2011 and 2012 to test fruit and fruit-based carbohydrate’s short-term (1–2 years) impact on these rodent populations. We used mark–recapture to estimate density, percentages of population that were juvenile and breeding female, mean home-range size, and body mass during spring and summer of both years, and fecundity via placental scars from euthanized females in summer 2012. Fruit enhancement had no apparent effect on our species’ fecundity, proportion of breeding females or juveniles during spring and summer of either year, nor were there differences among these metrics in spring 2012 following 2011 fruit additions. Overall, there were no impacts to the short-term adult population dynamics for any species during fruit addition. We are led to believe that short-term pulses of fruit and (or) fruit-based carbohydrate abundance do little to influence temperate forest small-mammal populations.
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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 | 0.000 |
| 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) | 0.000 | 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".