Conservation networks do not match the ecological requirements of amphibians
Bibliographic record
Abstract
Amphibians are among the most threatened taxa as they are highly sensitive to habitat degradation and fragmentation. They are considered as model species to evaluate habitats quality in agricultural landscapes. In France, all amphibian species have a protected status requiring recovery plans for their conservation. Conservation networks combining protected areas and green infrastructure can help the maintenance of their habitats while favouring their movement in fragmented landscapes such as farmlands. Yet, assessing the effectiveness of conservation networks is challenging. Here, we compared the ecological requirements of amphibian species with existing conservation network coverage in a human-dominated region of western France. First, we mapped suitable habitat distributions for nine species of amphibian with varying ecological requirements and mobility. Second, we used stacking species distribution modelling (SSDM) to produce multi-species habitat suitability maps. Then, to identify spatial continuity in suitable habitats at the regional scale, we defined species and multi-species core habitats to perform a connectivity analysis using Circuitscape theory. Finally, we compared different suitability maps with existing conservation networks to assess conservation coverage and efficiency. We highlighted a mismatch between the most suitable amphibian habitats at the regional scale and the conservation network, both for common species and for species of high conservation concern. We also found two bottlenecks between areas of suitable habitat which might be crucial for population movements induced by global change, especially for species associated with hedgerow mosaic landscapes. These bottlenecks were not covered by any form of protection and are located in an intensive farmland context. Synthesis and applications - We advocate the need to better integrate agricultural landscape mosaics into species conservation planning as well as to protect and promote agroecological practices suitable for biodiversity, including mixed and extensive livestock farming. We also emphasize the importance of interacting landscape elements of green infrastructure for amphibian conservation and the need for these to be effectively considered in land-use planning policies.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".