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Record W4296451115 · doi:10.1139/cjz-2022-0052

Space use and resource selection of Wood Turtles (<i>Glyptemys insculpta</i>) in the northeastern part of its range

2022· article· en· W4296451115 on OpenAlexvenueno aff
Sierra R. Latham, Alexej P. K. Sirén, Leonard R. Reitsma

Bibliographic record

VenueCanadian Journal of Zoology · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicTurtle Biology and Conservation
Canadian institutionsnot available
FundersU.S. Fish and Wildlife ServicePlymouth State University
KeywordsRange (aeronautics)EcologyHabitatHome rangeBiologyExpansiveCanopyEndangered speciesWildlife conservation

Abstract

fetched live from OpenAlex

The threats that affect a species often vary within its geographic range. Wood Turtles ( Glyptemys insculpta (Le Conte, 1830), formerly Clemmys insculpta (Le Conte, 1830)) are a species of concern due to widespread decline from anthropogenic threats. We studied two populations of Wood Turtles from June to September 2019 and 2020 to evaluate how landscape features and vegetative structure influenced space and habitat use and to identify potential risks in the remote, northern parts of its range. We hypothesized that space use would vary due to regional, landscape, and sex-specific differences. Turtles at the conifer-dominated site with higher road density had significantly smaller home ranges than the site with expansive and contiguous floodplains (7.25 ± 1.92 ha and 26.28 ± 6.77 ha, respectively). Females moved farther away from rivers than males (136.00 ± 23.68 m and 69.18 ± 34.81 m, respectively) and made the longest single-event movements. However, movements by males were significantly longer (34.65 ± 1.91 m) than females (23.99 ± 1.03 m) and followed rivers. At finer spatial scales, we found that turtles selected activity areas with complex vegetative structure and a more open canopy. Our study indicates that populations in contiguous forest could be critical to the conservation of Wood Turtles and we discuss management recommendations to reduce potential mortality risks in the northern part of its range.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.155
Threshold uncertainty score0.856

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.187
Teacher spread0.172 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations7
Published2022
Admission routes1
Has abstractyes

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