Facilitative interactions between the Eurasian badger (Meles meles), the red fox (Vulpes vulpes), and the invasive raccoon dog (Nyctereutes procyonoides) in Białowieża Primeval Forest, Poland
Bibliographic record
Abstract
Based on radio-tracking of Eurasian badgers ( Meles meles (L., 1758)), red foxes ( Vulpes vulpes (L., 1758)), and raccoon dogs ( Nyctereutes procyonoides (Gray, 1834)) and observations at burrows conducted in Białowieża Primeval Forest (eastern Poland) in 1996–2002, we addressed the hypothesis that facilitative interactions between a native (badger) and an alien (raccoon dog) species contributed to the invasion success of the latter. In winter, 88% of badger setts were occupied by both badgers and raccoon dogs, 4% by badgers and red foxes, and 4% by all three species. In summer, only 20% of badger setts were cohabited by other carnivore species (10% by raccoon dogs and 10% by foxes). Duration of occupation of badger setts by raccoon dogs averaged 117 days (SE = 21 days). Seasonal variation in raccoon dog use of badger setts was explained by changes in ambient temperature: the lower was the temperature, the higher was the rate of sett occupation by raccoon dogs. When wintering in the same sett, badgers and raccoon dogs used different parts of the sett. We conclude that facilitation by badgers (through habitat amelioration and refuge from cold and predation) makes the realized niche of raccoon dogs larger than predicted from their fundamental niche. The facilitating role of badger is stronger in winter, which is a critical period for raccoon dog survival in the temperate and boreal zone.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".