Landscape composition weakly predicts wetland occupancy by Blanding’s turtles ( Emydoidea blandingii Holbrook, 1838)
Bibliographic record
Abstract
Patterns of spatial occurrence in animals are largely a function of landscape composition and configuration. Studying habitat selection at the landscape scale allows the identification of habitat features that favour long-term survival of animal populations. We tested the hypothesis that wetland occupancy by Blanding’s turtles, Emydoidea blandingii, in southern Quebec is related to landscape composition. We conducted visual surveys at 110 wetlands to document occupancy and we measured landscape composition around surveyed wetlands. We used boosted regression trees (BRT) to model the probability of occurrence of Blanding’s turtles based on land use, road density, and wetland size. Blanding’s turtles were more likely to occupy areas with high wetland density, but the BRT model did not fit the presence/absence data well. Therefore, we could not confidently predict wetland occupancy patterns from our six landscape composition variables. Blanding’s turtles in our study area do not seem constrained to high quality sites: turtles occupy areas disturbed by agriculture in a slightly urbanized landscape. Management of the species should focus on protecting sites of documented occurrence with an abundance of wetlands and sufficient suitable habitat to cover seasonal movement patterns.
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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 | 0.000 | 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) | 0.002 | 0.001 |
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; both teacher heads agree on what is shown here.
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".