Impact of wildfires on ecosystems and bird communities on designated areas of blanket bog and heath
Bibliographic record
Abstract
Capsule Wildfires on moorland reduced bird species richness and abundance, along with the seedbank and abundance of ground beetles and spiders. The effects were detectable three years after the fires took place.Aims To describe the effects of wildfires during the breeding season on moorland birds, their habitat and ecosystem characteristics, by comparing burnt with adjacent unburnt areas in six designated sites up to three years post-fire.Methods Point counts of birds, vegetation height and cover, soil seedbank and pitfall traps were used to examine differences between areas burnt by wildfires and unburnt areas.Results One year after wildfire, bird species richness was 50% lower and abundance 32% lower on burnt compared to adjacent unburnt areas. Wildfire burnt areas had 80% of the species richness and 94% of the abundance of unburnt areas three years after wildfire. Bird species associated with upland moorland, including European Stonechat Saxicola rubicola, Common Redshank Tringa tetanus and Hen Harrier Circus cyaneus, were recorded exclusively in unburnt areas. Wildfire burnt areas were characterized by habitat generalist species and community composition in burnt areas remained distinct from unburnt areas three years after burning. Heather Calluna vulgaris and Erica spp. regenerated to 59% of the height of heather on unburnt areas three years after burning. Compared to unburnt areas, burnt areas had a reduced seedbank (22% lower), and reduced ground beetle (15% lower) and spider abundance (31% lower).Conclusion The immediate impacts of wildfire may differ from managed fires due to their indiscriminate character, where they occur, extent, duration and temperature. Wildfire incidence is likely to increase in cool temperate areas due to climate change and likely to undermine the characteristic features of designated areas. Research should focus on preventing wildfires, reducing their impact and accelerating the recovery of burnt moorland.
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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".