Response of farmland reptiles to agricultural intensification: Collapse of the common adder <i>Vipera berus</i> and the western green lizard <i>Lacerta bilineata</i> in a hedgerow landscape
Bibliographic record
Abstract
Abstract Agricultural landscapes cover a large portion of the planet and the intensification of farming is a primary cause of biodiversity loss. Changes in agricultural practices have been particularly marked in Western Europe over the last century. Hedgerow landscapes consist of complex mosaics of pastures, ponds, and hedges connected with forest patches that are favourable for biodiversity. Recently, however, these traditional farming landscapes have been profoundly simplified with a massive reduction in hedgerows. Reptiles are currently facing an important global decline, but the impact of the intensification of agricultural practices on their populations remains understudied. We studied the common European adder Vipera berus and the western green lizard Lacerta bilineata in Western France in a hedgerow landscape undergoing agricultural intensification. We first quantified the habitat changes (density of hedgerows and forest edges) from 1950 to 2015. Second, we documented changes in the distribution of V. berus and L. bilineata in the area between two surveys conducted 18 years apart (survey 1: 1994–1997 and survey 2: 2012–2015). The two species were more likely to be found at sites with dense hedgerows and forest edges at the first survey. We detected marked range contractions in the distributions of both species over 18 years (92% and 74%, respectively, for V. berus and L. bilineata). Population monitoring of the adder with capture‐mark‐recapture at two sites revealed marked declines related to the degradation of hedgerows and closure of the forest patches. Our results underline the importance of traditional agricultural landscapes for biodiversity conservation and the value of squamate reptiles as indicator speciesed in such landscapes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".