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Record W4402004371 · doi:10.1139/facets-2023-0217

The effect of riffle restoration on the recovery of endangered Nooksack Dace (<i>Rhinichthys cataractae</i> sp. <i>cataractae</i>)

2024· article· en· W4402004371 on OpenAlexafffundvenueabout
John H. Gray, Jordan S. Rosenfeld, Mike Pearson, Kay Colletti, Jeremy A. Ross

Bibliographic record

VenueFACETS · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsSimon Fraser UniversityMinistry of EnvironmentUniversity of British ColumbiaFisheries and Oceans Canada
FundersFisheries and Oceans Canada
KeywordsRiffleEndangered speciesZoologyFisheryBiologyEcologyHabitat

Abstract

fetched live from OpenAlex

The Nooksack Dace ( Rhinichthys cataractae sp. cataractae) is a federally endangered riffle specialist endemic to the lower Fraser Valley of British Columbia, Canada, with historic population declines associated with riffle loss from stream dredging, channelization, and excessive sediment inputs. To assess the effectiveness of riffle restoration as a recovery strategy, gravel and cobble riffles were constructed in two replicate tributaries of the Nooksack River as a before-after-control-impact experiment, measuring dace abundance, substrate composition, and invertebrate biomass before and one year after restoration. Nooksack Dace density increased significantly in cobble (but not gravel) treatments relative to control riffles. Dace abundance was strongly associated with increased availability of interstitial refuges rather than substrate effects on invertebrate prey abundance, suggesting that interstitial space limits adult dace abundance. Young-of-the-year dace were not observed in one of the two restored streams despite riffle restoration, indicating increased dace density due to aggregation in higher-quality restored riffles. This recruitment limitation indicates persistence of a population bottleneck at an early life history stage that is not addressed by successful restoration of adult riffle habitat.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.414
Threshold uncertainty score0.741

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.008
GPT teacher head0.226
Teacher spread0.219 · 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 designNot applicable
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

Citations2
Published2024
Admission routes4
Has abstractyes

Explore more

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