Reintroduction and management of at-risk freshwater turtles in an urban wetland complex in a protected area
Bibliographic record
Abstract
A headstarting program for the Blanding’s turtle (Emydoidea blandingii) was initiated by the Toronto Zoo in 2012 to supplement a functionally extinct population in the Rouge National Urban Park (RNUP) in Toronto, Ontario, Canada. Data collected from multiple years of radio- tracking (2014–2021) and mark-recapture (2018–2021) surveys were used to evaluate the success of the headstarting program. Based on demographic data, survival of headstarted turtles remained high, except during a mass-mortality event when a substantial decline in survival was observed. Male:female sex ratio measured using incubation temperatures shifted from 1:1.5 in captivity to 1:1 in the wild, and size-class distribution of the population remained juvenile- biased. Release methods did not improve post-release outcomes in terms of survival, somatic growth rate, body condition, or movement patterns, and headstarted turtles sustained similar health to wild juvenile conspecifics in other Ontario populations. Headstarted turtles selected hibernacula similar to wild adult conspecifics, and there was weak evidence towards sociality, specifically in terms of familiarity (i.e., individuals from the same release cohort) in overwintering site selection. Demographic data from other resident freshwater turtles indicated that multiple sources of ongoing threats and catastrophes can affect population stability. Headstarting also affected community diversity by shifting species richness and evenness. Overall, Blanding’s turtle headstarting program showed progress, but continued monitoring will be required to determine if headstarting will achieve its desired conservation goals. Conservation actions targeting multiple life-stages of the Blanding’s turtles will be necessary to address root causes of population decline and to ensure that the population will reach a self-sustaining level.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 source (direct Gemma or distilled Codex), 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".