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Record W4407982680 · doi:10.3897/bdj.13.e145637

The stoneflies (Plecoptera) of Arkansas: a checklist compiled from museum specimen data

2025· article· en· W4407982680 on OpenAlexaboutno aff
Lily Hart, R. Edward DeWalt, Phillip Hogan, Scott A. Grubbs, David J. Burton

Bibliographic record

VenueBiodiversity Data Journal · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicFreshwater macroinvertebrate diversity and ecology
Canadian institutionsnot available
Fundersnot available
KeywordsWildlifeGeographyHabitatBiodiversityGlobal biodiversityChecklistEcologyEnvironmental resource managementEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

Background: Stoneflies are well known as indicators of water quality. Their presence in running waters, glacial meltwaters, and large oligotrophic lakes is rapidly declining the world over. In the USA, states partner with the U.S. Fish and Wildlife Service to protect habitat and wildlife through the development of State Wildlife Action Plans (SWAPs). Plants and wildlife species often enter these SWAPs as Species in Greatest Conservation Need (SGCN). Arkansas currently lists nine stonefly species as SGCNs and has funded research on them through SWAP grants. However, these nine species were initially chosen based on the small amount of data from a few papers. A more comprehensive assessment using museum specimen data is necessary to assess completeness of sampling, the relative rarity and endemicity of species, temporal changes in distribution, and the conservation status of species in Arkansas. Herein, we publish a data paper and preliminary dataset comprised of specimen data primarily from the Illinois Natural History Survey Insect Collection, Canadian National Collection, Western Kentucky University, P. N. Hogan Personal Collection, and from existing literature sources. These data are made publicly available by the Global Biodiversity Information Facility (GBIF) to allow for comprehensive assessment of the Arkansas Plecoptera assemblage. More recent occurrence data are needed to accurately assess imperilment of Arkansas stonefly species; these data will be provided through targeted collecting, collaboration with others in Arkansas, and through investigation of additional museum collections. New information: This dataset includes > 3,500 specimen records (ethanol vials or pins with or without catalog numbers) and accounts for 84 stonefly species in Arkansas, six more species than indicated in published records. Perlidae contributed 29 of these species followed distantly by Perlodidae (15), Capniidae (14), Taeniopterygidae (9), Leuctridae (7), Chloroperlidae (5), Nemouridae (4), and Pteronarcyidae (1). A species accumulation curve predicts that sampling of species is nearly complete with a Chao1 estimate of 88.0 ± 3.7 species. Our data demonstrate that 25 species are known from ≤ five records, suggesting that many more than the nine recognized stonefly SGCNs in Arkansas may meet standards for inclusion.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score0.145

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0110.006
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.039
GPT teacher head0.246
Teacher spread0.207 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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