Grey Wolf (Canis lupus) Recolonization in Hungary: Does the Predation Risk Affect the Red Deer (Cervus elaphus) Population?
Bibliographic record
Abstract
The populations and distribution areas of large carnivores have declined all over the world due to extirpation and habitat alteration and degradation. However, the grey wolf (Canis lupus) has recovered in Europe in recent decades and has been reappearing in Hungary since the 1990s. Since the dominant prey of this carnivore is the red deer (Cervus elaphus) and the wild boar (Sus scrofa) in Central and Eastern Europe, we aimed to study the impact of wolves on local deer populations. Based on hunters’ opinions, we expected an increasing wolf presence and intense effects of wolves on the stress level and body condition of deer. First, we examined the occupied area by wolf in the North Hungarian Mountains. The distribution map was based on a questionnaire among the game managers. To measure the influence of the reappearing predator population on the red deer individuals, we estimated the body condition (kidney fat and bone marrow index) and stress hormone level of faecal samples. We compared them between the areas colonised by wolves and control sites in the mountains. We revealed an increased distribution area of wolves in the mountains since 2014. The stress hormone level was lower in the wolf-free sites in the case of faeces gathered from the ground, but there was similar amount of cortisol in the samples collected from the hunted animals. The body condition indices were not different between the two area types (average kidney fat index > 100% and almost 100% for the bone marrow fat content). Our results do not support a very intense recent impact of the wolf population on the body condition and stress level of red deer in Hungary.
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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 | 0.001 | 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 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".