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Record W2136307059 · doi:10.1139/x11-066

Adjacent land-use affects amphibian community composition and species richness in managed forests in New Brunswick, Canada

2011· article· en· W2136307059 on OpenAlexafffundvenueabout
Lee Anne Jacobs, Jeff E. Houlahan

Bibliographic record

VenueCanadian Journal of Forest Research · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife-Road Interactions and Conservation
Canadian institutionsUniversity of New Brunswick
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLithobatesSpecies richnessAmphibianEcologyBiologyNotophthalmus viridescensWetlandCommunity structureRegeneration (biology)

Abstract

fetched live from OpenAlex

Here, we examine the effects of adjacent land use in a managed forest on pond-breeding amphibian species richness and community composition at 34 New Brunswick, Canada, ponds. Amphibian species richness was negatively correlated with the proportion of roads, precommercial thinning, and hardwood forest and positively correlated with the proportion of wetlands in adjacent lands. These land-use effects peak at 180 m from the ponds. Road density was negatively correlated with Lithobates catesbeiana and Lithobates septentrionalis presence. Precommercial thinning was negatively correlated with Ambystoma spp. presence and positively correlated with Anaxyrus americanus presence. Wetlands were positively correlated with L. septentrionalis and Notopthalamus viridescens presence. Correlations were also found between water table height and A. americanus, Lithobates palustris , and Ambystoma spp. presence. In addition, L. catesbeiana and N. viridescens presence–absence was positively correlated with the proportion of mature and overmature forest on the landscape (at scales of 500 and 1000 m, respectively). Lastly, the proportion of regenerating and sapling forest on the landscape was negatively correlated with L. palustris presence–absence but, by contrast, was positively correlated with A. americanus. These results suggest that the effects of adjacent land use may significantly impact amphibian populations in managed eastern Canadian forests.

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)0.001
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 score0.007
Threshold uncertainty score0.317

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.069
GPT teacher head0.269
Teacher spread0.200 · 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

Citations9
Published2011
Admission routes4
Has abstractyes

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