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Record W2151260052 · doi:10.1890/130145

Amphibians in the climate vise: loss and restoration of resilience of montane wetland ecosystems in the western US

2014· review· en· W2151260052 on OpenAlexafffund
Maureen E. Ryan, Wendy J. Palen, Michael J. Adams, Regina M. Rochefort

Bibliographic record

VenueFrontiers in Ecology and the Environment · 2014
Typereview
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsSimon Fraser University
FundersCanada Research Chairs
KeywordsWetlandHabitatEcologyClimate changeEcosystemEphemeral keyWildlifePredationHabitat destructionEnvironmental scienceFaunaGeographyFisheryBiology

Abstract

fetched live from OpenAlex

Wetlands in the remote mountains of the western US have undergone two massive ecological “experiments” spanning the 20th century. Beginning in the late 1800s and expanding after World War II, fish and wildlife managers intentionally introduced millions of predatory trout (primarily Oncorhynchus spp) into fishless mountain ponds and lakes across the western states. These new top predators, which now occupy 95% of large mountain lakes, have limited the habitat distributions of native frogs, salamanders, and wetland invertebrates to smaller, more ephemeral ponds where trout do not survive. Now a second “experiment” – anthropogenic climate change – threatens to eliminate many of these ephemeral habitats and shorten wetland hydroperiods. Caught between climate‐induced habitat loss and predation from introduced fish, native mountain lake fauna of the western US – especially amphibians – are at risk of extirpation. Targeted fish removals, guided by models of how wetlands will change under future climate scenarios, provide innovative strategies for restoring resilience of wetland ecosystems to climate change.

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: Observational
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.398
Threshold uncertainty score0.395

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.012
GPT teacher head0.240
Teacher spread0.228 · 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
GenreReview

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

Citations79
Published2014
Admission routes2
Has abstractyes

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