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Record W2138686993 · doi:10.2193/2006-309

Evaluating Residual Tree Patches as Stepping Stones and Short‐Term Refugia for Red‐Legged Frogs

2007· article· en· W2138686993 on OpenAlexaff
Ann C. Allaye Chan-McLeod, Arnold Moy

Bibliographic record

VenueJournal of Wildlife Management · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicAmphibian and Reptile Biology
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCanopyResidualEcologyTree (set theory)ClearcuttingBiologyTree canopyHabitatAmphibianMathematics

Abstract

fetched live from OpenAlex

Abstract: Temperate pond‐breeding amphibians are vulnerable to forest fragmentation because they must access upland terrestrial sites during the nonbreeding season but are prone to desiccation in hot, dry environments without canopy cover. Harvesting techniques that retain live trees in the cut block are advocated for sustaining forest biodiversity, but the effects of these practices on amphibians are unknown. We studied red‐legged frogs ( Rana aurora ) in movement trials to assess: 1) how short‐term use of residual trees was affected by tree patch size, streams, and neighborhood features; 2) whether residual tree patches were used as stepping stones in negotiating cut blocks; 3) the effects of patch size and patch proximity in altering movement paths; and 4) the effects of retention level and patch size on interpatch distance. Residual tree patches were potentially valuable short‐term refugia but their value was size dependent. Virtually all frogs released at the base of single trees or inside small tree clusters left within 72 hours, but the proportion leaving decreased curvilinearly with increasing patch size. Frogs were less likely to leave tree patches with a running stream or where neighborhood stream density was high. Residual tree patches did not systematically alter movement paths. Frogs intercepted residual tree patches mostly at random and had to be within 5‐20 m of a tree patch before moving to it in greater proportions than expected by chance. However, amphibian movements were biased toward large (0.8 ha) patches and away from small (0.3 ha) patches 50 m away. Our results indicated that residual trees should not be retained singly but should be aggregated in groups between 0.8 ha and 1.5 ha, preferably in stream locations.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.693
Threshold uncertainty score0.456

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.037
GPT teacher head0.325
Teacher spread0.288 · 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

Citations33
Published2007
Admission routes1
Has abstractyes

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