Demographic processes and behaviour of snapping turtles (Chelydra serpentina) in the context of past catastrophes and ongoing threats
Bibliographic record
Abstract
Lifetime patterns of somatic growth, reproduction, and survival comprise life history, which links \nindividual traits to the vital rates that determine the properties of populations, such as generation \ntime, potential rate of increase, and responses to environmental perturbation. Individual lifehistory traits, such as survival, age at first reproduction, reproductive frequency, and the size and \nnumber of offspring covary along a limited number of dimensions forming the pace-of-life \ncontinuum because they are tightly linked by trade-offs and constraints. Furthermore, variation in \nlife history also covaries with morphological, physiological, and behavioural traits. \nThis dissertation focuses on interconnectedness of life-history traits with social behaviour, \npopulation dynamics, and conservation. The Algonquin long-term field study of Snapping Turtles \n(Chelydra serpentina) provides a unique opportunity to analyze these relationships in a longlived organism with a slow life history by building upon a productive foundation of previous \nresearch. Turtles‘ slow life history, low and variable juvenile recruitment, and reliance on high \nadult survivorship makes them vulnerable to anthropogenic threats resulting in turtles being \ndisproportionately imperilled. \nIn Chapter 1, I analyzed the patterns of abundance and survival during and after a population \ncatastrophe and revealed individuals transitioning between sites in a connected population but no \nrecovery over 23 years. Because of their cryptic behaviour, the mating system of Snapping \nTurtles was poorly known, so in Chapter 2 I quantify sexual size dimorphism and frequency of \nwounds to infer patterns of intraspecific aggression consistent with a mating system mediated by \nmale combat. The third chapter focused on the somatic growth component of life-history by \nrefining growth modelling by developing a model of seasonal variation in growth rates. In \nChapter 4, I examine the demography of Snapping Turtles dispersing across roads by testing \nhypotheses based on the mating system revealed in Chapter 2 using a demographic model \nparameterized with survivorship estimated in Chapter 1 and the growth modeling approach \ndeveloped in Chapter 3. I show that juveniles are overrepresented on roads and face higher \nmortality risk and that the lost reproductive value of juveniles killed on roads contributes \nsubstantially to the overall burden of road mortality in this long-lived species.
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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 | 0.001 |
| 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 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".