Transport infrastructure severely impacts amphibian dispersal regardless of life stage
Bibliographic record
Abstract
Transport infrastructure such as roads has been reported to negatively affect dispersal. Their effects on dispersal are thought to be complex, depending on the characteristics of the structure and the intensity of the traffic using it. In addition, individual factors, such as age, may strongly affect dispersal decisions and success when individuals are confronted with transport infrastructure. Despite the importance of this topic for wildlife conservation, few studies have investigated the effect of transport infrastructure on individuals' dispersal decisions before and after sexual maturity. We examined the effects on two kinds of infrastructure, gravel tracks and paved roads, on the dispersal of an endangered amphibian, the yellow-bellied toad (Bombina variegata). We used capture-recapture data collected during a five-year period on a large, spatially structured population of B. variegata. Our study revealed that emigration rates increased with an individual's age, while dispersal distance decreased. It also showed that both tracks and roads had negative effects on immigration. The negative effect of roads was stronger than that of tracks. We additionally found that the effect of tracks on dispersal slightly decreased with a toad's age. In contrast, the negative effect of roads was severe and relatively similar across age classes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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 teacher head, 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".