Evidence map›Paper›PMID 37379936›Full record

ArticleThe Science of the total environment2023

Development of national stressor-specific genus sensitivity values.

Michael B Griffith

Abstract read
In one paragraph

Article in The Science of the total environment, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

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5 · Who and what money

Authors and funding

1 author.

Michael B GriffithU.S. Environmental Protection Agency, Office of Research and Development, Center for Environmental Monitoring and Modelling, 26 Martin Luther King Drive West, Cincinnati, OH 45168, United States of America. Electronic address: griffith.michael@epa.gov.

Funding

Intramural EPA EPA999999
6 · The paper itself

Abstract

Effective water quality management is based on associations between at least two pieces of information: a stressor and a response. However, assessments are hindered by the lack of pre-developed stressor-response associations. To remedy this, I developed genus stressor-specific sensitivity values (SVs) for up to 704 genera to estimate a sensitive genera ratio (SGR) metric for as many as 34 common stream stressors. The SVs were estimated from a large, paired macroinvertebrate and environmental data set for the contiguous United States. Environmental variables measuring potential stressors were selected that were generally uncorrelated and usually had several thousand station observations. I calculated relative abundance weighted averages (WA) for each genus and environmental variable meeting data requirements in a calibration data set. Each environmental variable was split into 10 intervals along each stressor gradient. Genera were assigned an SV from 1 to 10 based on the interval consistent with the WA for each environmental parameter. Using the calibration derived SVs, SGRs were calculated for the calibration and a validation subsets. SGRs are the number of genera with SV ≤ 5 divided by the total number of genera in a sample. In general, as stress increased, the SGR (range: 0-1) decreased for many environmental variables, but for five environmental variables, the decrease was not consistent. The 95 % confidence intervals of the mean of the SGRs were greater for least disturbed stations compared to all other stations for 23 of the remaining 29 environmental variables. Regional performance of SGRs was evaluated by subdividing the calibration data set into West, Central, and East subsets and recalculating SVs. SGR mean absolute errors were smallest in the East and Central regions. These stressor-specific SVs expand the available tools for assessing stream biological impairments from commonly encountered environmental stressors.

Indexed as

Environmental MonitoringWater QualityAnimalsCalibrationEcosystemInvertebratesUnited StatesEnvironmental variablesMacroinvertebratesSensitivityStressor-response relationshipsWeighted averaging

Identifiers

PMID37379936
PMCPMC10527857

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.