The effects of agricultural intensification on Skylarks(<i>Alauda arvensis</i>): Evidence from monitoring studies in Great Britain
Bibliographic record
Abstract
Declines in a number of farmland bird species in northern Europe have been linked to agricultural intensification. In this paper, we review the evidence for the effects of agricultural intensification on farmland bird populations using monitoring studies on a single well-studied species, the Eurasian Skylark (Alauda arvensis). Between 1970 and 1998, the Skylark population declined by 44% and this decline was greatest on farmland compared to upland or coastal habitats, yet during that time, reproductive performance per individual nesting attempt improved significantly. Skylarks consistently prefer relatively sparse (spring cereals) or structurally complex (fallow "set-aside"') crops, particularly late in the breeding season when crops that are too tall or dense are abandoned. Outside the breeding season, cereal stubble is the most preferred foraging habitat. Intensification has been characterized by decreases in preferred crops (spring cereals and cereal stubble) and an increase in unfavourable habitats (winter cereals, oilseed rape, and intensively managed or grazed grass). Reduction in the number of breeding attempts due to rapid sward development of winter cereals and the lack of suitable alternative habitats is likely to have been an important factor in the Skylark decline. The decline may also have been driven by decreases in survival outside the breeding season. Management regimes that include spring cereals, cereal stubble, and low-intensity grazing are likely to increase Skylark abundance and will benefit a number of other farmland birds. This review highlights the great value of large-scale monitoring schemes in understanding population declines. However, the factors affecting the post-fledging survival of Skylarks and the effects of crop diversity on Skylark abundance remain to be resolved. Key words: agricultural management, cereals, habitat diversity, intensification, population trend, reproductive performance.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".