Effects of winter food supplementation on reproduction, body mass, and numbers of small mammals in montane Australia
Bibliographic record
Abstract
We used a food-supplementation experiment to test the hypothesis that small-mammal populations are food-limited during winter in southeastern Australia. We trapped small mammals along 120- to 150-m transects at 12 creek and 12 ridgetop sites (representing high- and low-quality habitats) for 2 months prior to winter and 2 months during winter. High-quality food (peanut butter, honey, oats, and dried cat food) was provided ad libitum for 7 weeks during winter at four sites in each habitat. Eight sites were provided with empty feeding tubes and eight were untreated. Seven weeks of food supplementation caused numerical increases of 4.0- and 5.0-fold for the rodents Rattus fuscipes and Rattus lutreolus, respectively. Increases were due largely to immigration, and were only observed in the high-quality creek habitats (R. lutreolus were exclusively captured at creek sites). Food supplementation also led to an increase in body mass and reversed the hiatus in winter breeding for rodents. These results suggest that populations of both species are limited by winter food availability. However, survival rates (indexed from recapture rates) were not affected by food supplementation. Mean body mass of the marsupial Antechinus stuartii also increased with food supplementation, but other demographic parameters showed no response; numbers declined at creek sites after additional food was provided. Trapping-revealed measures of interspecific association showed that A. stuartii avoided areas of high rat numbers after additional food was provided. It is thus likely that interference competition from the much larger and more abundant rodents forced A. stuartii out of the food-supplemented creek sites, hence mediating the direct effects of food supplementation on this species.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".