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Record W1990404080 · doi:10.1155/2012/989872

A Place to Call Home: Amphibian Use of Created and Restored Wetlands

2012· article· en· W1990404080 on OpenAlexaff
Donald J. Brown, Garrett M. Street, Robert W. Nairn, Michael R. J. Forstner

Bibliographic record

VenueInternational Journal of Ecology · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicAmphibian and Reptile Biology
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsWetlandHabitatAmphibianSpecies richnessEcologyAbundance (ecology)Habitat destructionBiologyEnvironmental scienceGeography

Abstract

fetched live from OpenAlex

Loss and degradation of wetland habitats are major contributing factors to the global decline of amphibians. Creation and restoration of wetlands could be a valuable tool for increasing local amphibian species richness and abundance. We synthesized the peer-reviewed literature addressing amphibian use of created and restored wetlands, focusing on aquatic habitat, upland habitat, and wetland connectivity and configuration. Amphibian species richness or abundance at created and restored wetlands was either similar to or greater than reference wetlands in 89% of studies. Use of created and restored wetlands by individual species was driven by aquatic and terrestrial habitat preferences, as well as ability to disperse from source wetlands. We conclude that creating and restoring wetlands can be valuable tools for amphibian conservation. However, the ecological needs and preferences of target species must be considered to maximize the potential for successful colonization and long-term persistence.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.018
GPT teacher head0.256
Teacher spread0.238 · 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 source (direct Gemma or distilled Codex), 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

Citations75
Published2012
Admission routes1
Has abstractyes

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