Landscape-level conservation of freshwater turtles
Bibliographic record
Abstract
In Ontario, 7 of the 8 native species of freshwater turtles are listed as at-risk. Protection of species-at-risk requires delineation and identification of their critical habitat to enable the proposal of conservation strategies. Because of pre-existing development and limited resources for conservation, it is difficult to protect land required for species’ survival especially when faced with multiple threats such as habitat loss, degradation, and fragmentation, invasive species, and a changing climate. To improve conservation strategies, we must understand how turtle populations use a variety of different landscapes at a range of spatial scales. The goals of this thesis were to develop and assess landscape-level conservation strategies for imperiled freshwater turtles. I first determined that Blanding's turtles (Emydoidea blandingii) require inland and coastal wetlands, a suitable upland matrix and connecting corridors. Since turtles overwinter for majority of the year, I determined suitable thermal parameters of occupied sites, revealing suitable water temperatures range from 0.44° C to 3.68° C and slowly decline throughout the overwintering period. Using a landscape-level approach, my models support that habitat in Georgian Bay is in good condition; 64% of evaluated islands support habitat for Blanding’s turtles and majority of surveyed coastal wetlands support eastern musk turtles (Sternotherus odoratus). In particular, coastal wetlands with higher proportions of forest cover, lower densities of roads, buildings, and docks, and more variable bathymetric slopes provide more suitable habitat. In addition to anthropogenic stressors, invasive species pose a threat to turtles and their habitat. I provided the first quantitative evidence of the negative consequences of Phragmites australis invasion on availability of habitat for turtles. Since roads are a ubiquitous feature in our landscape, I evaluated strategies aimed at limiting their negative effects on at-risk reptiles. A decade-long dataset of road mortality reveals the ineffectiveness of partial fencing as a mitigation strategy. I recommend emphasis on fence integrity and continuity, limiting impact of edge effects, and conducting a comprehensive monitoring program. Finally, long-term changes in a protected landscape are evaluated and results indicate habitat succession and invasive species can negatively affect habitat suitability, and protection of land alone does not necessarily equate to protection of sensitive herpetofauna. My research integrates geographic information systems and remote sensing to advance our understanding of landscape requirements for turtles and will inform future conservation strategies aimed at mitigating threats to imperiled freshwater 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 | 0.000 | 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) | 0.210 | 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".