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Record W2886125540

THERMAL AND HYDROLOGICAL CONDITIONS OF REPTILE SPECIES-AT-RISK HABITAT ALONG EASTERN GEORGIAN BAY DURING CRITICAL LIFE STAGES

2017· dissertation· en· W2886125540 on OpenAlexfundaboutno aff
Alanna G. Smolarz

Bibliographic record

VenueMacSphere (McMaster University) · 2017
Typedissertation
Languageen
FieldEarth and Planetary Sciences
TopicMarine and environmental studies
Canadian institutionsnot available
FundersU.S. Fish and Wildlife ServiceParks CanadaOntario Ministry of Natural Resources and ForestryMinistry of Natural ResourcesMcMaster UniversityPurdue University
KeywordsGeorgianBayHabitatGeographyOceanographyEnvironmental scienceEcologyGeologyBiology
DOInot available

Abstract

fetched live from OpenAlex

Reptiles are the vertebrate taxon with the highest percentage of at-risk species in Canada, many of which exist at the northern limit of their species’ home range in Ontario. Numerous reptiles are found in the Georgian Bay area; however, factors limiting their distribution in Ontario are poorly understood. It is likely that the thermal and hydrological conditions of a reptile’s critical habitat are contributing factors. Specifically, peatlands serve as ideal hibernacula for the threatened Eastern Massasauga Rattlesnake (Sistrurus catenatus) while moss cushions may provide freshwater turtles, including the threatened Blanding’s Turtle (Emydoidea blandingii) and endangered Spotted Turtle (Clemmys guttata), with nesting opportunities on open rock barrens. Although different in their functional purpose at opposite life stages for two separate orders of reptiles, these ecosystems provide suitable conditions to meet the physiological needs of the reptiles utilizing them. This analysis characterizes the thermal and hydrological conditions of moss-dominated ecosystems from a reptile species-at-risk perspective. The interaction between the water table and the frost line is important when assessing the winter survival of Eastern Massasauga Rattlesnakes hibernating in peatland hummocks. Larger hummocks are more ideal as they have a lower chance of becoming flooded in the winter while still providing protection from the advancing frost line. Ideally, hummocks that are 30-35 cm tall provide the greatest chance of survival when snakes hibernate 20-25 cm below the surface. Subsurface temperatures in relation to snow depth, as it is influenced by tree stand characteristics, was also assessed. This resulted in the conclusion that the presence, absence, timing, and frequency of freeze and thaw events is likely more important than snow depth when it comes to winter survival. Similar to rattlesnake hibernacula, turtle nests can be inundated for extended periods of time or exposed to extreme temperatures which reduces their chance of survival. The water storage dynamics of 22 hillslope and 12 hilltop moss cushions along with the temperature dynamics at nine locations were characterized. Although it was determined hilltop locations had greater water storage capabilities, continuously monitored moss cushions responded very quickly to rainfall events whereby sites were inundated for less than 12 hours. Average subsurface temperatures decreased with depth as did temperature fluctuations, both of which were positively correlated but not significantly affected by canopy openness. However, due to their tendency to grow on flat surfaces, not all moss cushions are suitable nesting sites. Moreover, temperatures that ensure proper development and equal ratios of male-to-female turtles were not achieved suggesting that this is a potential factor limiting the northern distribution of turtles in Ontario. In order to properly asses the vulnerability of these populations to threats including habitat loss and climate change, the habitat requirements of different species at critical life stages needs to be understood. Therefore, conservationists can use this study to implement mitigation strategies that consider impacts on the thermal and hydrological dynamics within reptile habitat.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.176
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.1760.000

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.

Opus teacher head0.012
GPT teacher head0.193
Teacher spread0.181 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2017
Admission routes2
Has abstractyes

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