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Record W2958302734 · doi:10.11646/zoosymposia.14.1.19

<p class="HeadingRunIn"><strong>Discovery, dispersal, and genetic diversity of <em>Rhyacophila lobifera</em> Betten, 1934 (Trichoptera: Rhyacophilidae) in southeast Michigan, USA</strong></p>

2019· article· en· W2958302734 on OpenAlexaboutno aff
Abigail Fusaro, B. McCulloch, Sally Petrella, VELON WILLIS

Bibliographic record

VenueZoosymposia · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicFreshwater macroinvertebrate diversity and ecology
Canadian institutionsnot available
Fundersnot available
KeywordsBiological dispersalGeographyWatershedPopulationRange (aeronautics)EcologyGenetic diversityBiologyDemography

Abstract

fetched live from OpenAlex

Rhyacophila lobifera Betten, 1934 has been previously documented in the upper Midwest states of Ohio, Indiana, and Illinois, and the province of Ontario. Here we report on the diversity of this species in the Rouge and Huron River watersheds using DNA barcode-verified identifications to confirm the first known Michigan record of this species, with collection from the lower Rouge River in 2003 and again in 2008. Since first detection, we document that the range of R. lobifera in the Rouge River watershed has expanded to include at least one additional site on the Lower Branch and five sites on the Middle Branch (Johnson Creek), as well three sites in the neighboring Huron River watershed. Our sequence analysis of the mitochondrial COI barcode gene region suggests a fine scale population structure in these watersheds, with haplotype partitioning congruent with proposed dispersal patterns based on first records at each site. Ranking as a 4 on the Hilsenhoff's biotic index—an intermediate level of water quality tolerance, discovery of R. lobifera in an urbanized southeast Michigan watershed is not unexpected, but population genetic patterns lend insight into its recent range expansion.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.436
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0000.002
Open science0.0020.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.004

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 head0.187
Teacher spread0.180 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2019
Admission routes1
Has abstractyes

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