The effects of woodland fragmentation and human activity on roe deer distribution in agricultural landscapes
Bibliographic record
Abstract
Landscape structure and human activity influence the distribution and abundance of species. Landscape modifications have resulted in loss of habitat, increased isolation between remnant patches, and increased disturbance. We compare distributions and group sizes of roe deer across four open agricultural landscapes of differing structure. The roe deer, essentially a woodland species, exhibits behavioural plasticity, recently colonising the agricultural plain. Our results suggest that the switch between forest and field behaviour may involve a threshold of landscape geometry concerning woodland connectivity. Where woodland fragments are numerous and widely dispersed, roe deer retain strong links to woodland structures, probably for cover and social reasons. Where remaining woodland is clumped, with little edge, roe deer adopt an open field habit, remaining at a distance from woodland. Average winter group size increased with distance from woodland, resulting in large herds typical of field roe deer populations at the more open sites. In addition, roe deer avoided areas associated with human activity, probably because of associated disturbance, particularly where woodland cover was lacking. Finally, average group size was lower in areas where the level of human activity was high. The behavioural plasticity of this species means that landscape change may not be limiting. Therefore, to predict the effects of landscape modification, models need to incorporate variation in the animallandscape relationship due to behavioural plasticity.
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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 | 0.000 | 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) | 0.000 | 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".