The spatial ecology of Blanding's turtles (Emydoidea blandingii): from local movement patterns, home ranges and microhabitat selection to Ontario-wide habitat suitability modelling
Bibliographic record
Abstract
The Blanding's turtle, a semi-aquatic freshwater species found in North America, is listed as a species at risk in 17 of the 18 state/provincial jurisdictions across its range (NatureServe, 2009). Furthermore, approximately 20% of the global range of the Blanding's turtle is contained in Ontario (COSEWIC, 2005). The purpose of this study was to characterise the spatial ecology of Blanding's turtles in Ontario at multiple spatial scales, from a single island population to Ontario-wide habitat suitability modeling. I followed 38 Blanding's turtles (20 males, 13 gravid females, and 5 non-gravid females) in 2008 and 2009 on Grenadier Island in the St. Lawrence River, Ontario via radio-telemetry. Furthermore, I built habitat suitability models using historical Blanding's turtle records in Ontario and two machine learning algorithms: maximum entropy modeling (MAXENT) and boosted regression trees (BRTs). At the local scale, Blanding's turtles selected colder water with more submerged and floating vegetation and avoided open water. Reproductive class and month did not have a significant effect on the mean daily movement of turtles in May, July, and August. In June, however, gravid females moved significantly more than males. Gravid females also had significantly larger home ranges than both males and non-gravid females. At the landscape level, Blanding's turtle habitat suitability was best predicted by air temperature, wetland area, open water area, cropland area, and road density. Habitat suitability increased with increasing air temperature, wetland area, forested area, alvar area, bedrock outcrop area, and decreased with increasing cropland area, pastures and field area, precipitations, terrain ruggedness, and settlements and developed land. Mean area under the operating curve (AUC) values for habitat suitability models tested on independent data ranged from 0.878 to 0.912. My results highlight the importance of stratifying spatial analyses by reproductive class and time and of including terrestrial habitat in management plans for Blanding's turtles.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".