Mammals and agri‐environment schemes: hare haven or pest paradise?
Bibliographic record
Abstract
1 Agri-environment schemes (AESs) are designed to create landscape-scale improvements in biodiversity. While the specific aims of AESs do not always include the enhancement of species of conservation concern, associated conservation strategies, such as the UK Biodiversity Action Plan, often rest on the assumption that AESs enhance environmental conditions and thereby improve the conservation status of target species. However, there is little evidence for the general efficacy of AESs in this respect. 2 To evaluate the effects of the Environmentally Sensitive Area (ESA) scheme, a widespread AES in Northern Ireland, a spotlight survey of the relative abundance of three mammal species, Irish hare Lepus timidus hibernicus, European rabbit Oryctolagus cuniculus and red fox Vulpes vulpes, was conducted. Of these, the Irish hare is a priority species for conservation action and the focus of a species action plan, while rabbit and fox are commonly considered agricultural pests. The effects of ESA designation and habitat on each species were assessed at 150 ESA and 50 non-ESA sites, matched for landscape characteristics. 3 The ESA scheme had no demonstrable effect on the abundance of Irish hares, and this agri-environment scheme did not target the landscape and habitat variables associated with hares. 4 In contrast, the abundance of rabbits and foxes was significantly greater within ESAs than the wider countryside. Agricultural factors such as reduced livestock stocking density, reduced overgrazing and field boundary enhancements may create more favourable conditions for both species. Aside from the implications for farm economics, the proliferation of rabbit populations within conservation areas may raise issues concerning the grazing of important plant communities, while increases in fox populations may adversely affect ground-nesting birds and other animal species of conservation concern. 5 Synthesis and applications. The abundance of rabbits and foxes corroborates recent work that suggests AESs may benefit common species but can not be relied upon to encourage rarer species. The Irish hare species action plan relies on agri-environment schemes to enhance the species’ status and realize the target of increasing the hare population by 2010 by promoting suitable habitat. However, the ESA scheme is unlikely to help in achieving these objectives. Targeted and evidence-based agri-environment prescriptions are clearly required in order to ensure the realization of species-specific conservation targets.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 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".