Individual and synergistic effects of habitat loss and roads on reptile occupancy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Habitat loss and road mortality pose severe threats to wildlife by reducing available resources, increasing mortality rates, and fragmenting remaining habitat into smaller patches. The combined threats of habitat loss and road mortality may amplify each other to increase extinction risks. Understanding how several threats can act alone or synergistically to affect species is key to implementing recovery actions. We tested how habitat loss and road density affect occupancy probability of reptiles, and how these factors interact, while accounting for the effects of climate on habitat suitability. We built occupancy models using observations of squamates (29,833 observations of 15 species) and turtles (39,925 observations of 7 species) from community science data in the Ontario Reptile and Amphibian Atlas. We predicted that habitat loss and road density would amplify each other and negatively affect occupancy probability. At the scale of our analyses (10 × 10 km squares used in this community science database), habitat loss negatively affected occupancy probability for 19 of 22 species, but the magnitude varied considerably between species. Surprisingly, road density did not affect occupancy of most species. Three species had synergistic effects of habitat loss and road density on occupancy, but the interaction terms had weak predictive power. Overall, habitat loss was a strong predictor of reptile occupancy, but there was not strong evidence that road density or the synergistic effects of habitat loss and road density negatively affected reptile occupancy in our study area. Future research should explore how the relative effects of habitat loss, road density and synergistic effects may differ at other spatial scales. Our results highlight the importance of conserving and restoring habitat to meet conservation goals for reptiles within our study area.
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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 | 0.000 | 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) | 0.000 | 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 it