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Record W2974537433 · doi:10.3390/d11090167

Interannual Variation of Benthic Macroinvertebrate Communities at Long-Term Monitoring Sites Impacted by Human Activities: Implications for Bioassessment

2019· article· en· W2974537433 on OpenAlexafffundabout
Almudena L. Idígoras Chaumel, David G. Armanini, John A. Schwindt, Adam G. Yates

Bibliographic record

VenueDiversity · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicFreshwater macroinvertebrate diversity and ecology
Canadian institutionsToronto and Region Conservation AuthorityWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBenthic zoneSTREAMSChironomidaeTaxonEnvironmental scienceEcologySampling (signal processing)Species richnessWatershedVariation (astronomy)Abundance (ecology)InvertebrateRelative species abundanceHydrology (agriculture)BiologyGeology

Abstract

fetched live from OpenAlex

Bioassessment assumes that ecological conditions remain stable in the absence of environmental changes. Evidence suggests this assumption may hold for reference streams, but knowledge gaps remain for impacted streams. Our study quantified interannual variation of benthic macroinvertebrate communities, monitored for at least 14 years in eight impacted streams in the Upper Thames River watershed in Ontario, Canada. Benthic communities exhibited moderate interannual variation in relative abundance of EPT (Ephemeroptera, Plecoptera and Trichoptera) and Chironomidae taxa. Year-to-year changes were reflected in lower community persistence than that observed in studies of reference streams. In contrast, tolerance-based metrics showed minimal interannual variation, suggesting compositional changes were because of taxonomic substitutions, in which one tolerant taxon replaced another. Analyses indicated limited directionality in temporal variation for most bioassessment metrics. An exception was taxa richness, which increased at most sites, possibly because of changes in subsampling. However, no associations between calculated bioassessment metrics and measured environmental factors (stream flow and water chemistry) or sampling procedures were observed. We conclude interannual variation in ecological conditions can be substantial and may not be associated with deterministic factors routinely measured in stream assessments. We recommend increased sampling frequency and traits-based assessment as options for limiting effects of interannual variation on assessment results.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.260
Teacher spread0.234 · 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.

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

Citations6
Published2019
Admission routes3
Has abstractyes

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