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  4. Multi-stressor Predictive Models of Invertebrate Condition in the Corn Belt, U.S.A.

Multi-stressor Predictive Models of Invertebrate Condition in the Corn Belt, U.S.A.

Dates

Start Date
2013-06-01
End Date
2013-09-30
Publication Date

Citation

Waite, Ian, and Van Metre, P.C., 2017, Multi-stressor Predictive Models of Invertebrate Condition in the Corn Belt, U.S.A.: U.S. Geological Survey data release, https://doi.org/10.5066/F71V5C57.

Summary

The data set includes the macroinvertebrate metrics calculated by IDAS software (Cuffney 2003, USGS OFR 03-172) for the Midwest Stream Quality Assessment (MSQA). Invert data is taxonomic data that has been summarized into variables called metrics that summarize various components of the taxonomic data. The original taxonomic data comes from USGS BioData.

Contacts

Point of Contact :
Ian Waite
Originator :
Ian Waite, Peter C. Van Metre
Metadata Contact :
Ian Waite
Distributor :
Pete Van Metre or Daniel Bottom
USGS Mission Area :
Water Resources
SDC Data Owner :
Oregon Water Science Center

Attached Files

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Multi_stressor_Predictive_Models_of_Invertebrate_Condition_in_the_Corn_Belt_U_S_A_.xml
Original FGDC Metadata
View 		17.88 KB application/fgdc+xml
MSQA_Invert Metrics Reduced_Top 6.csv 13.75 KB text/csv

Purpose

The data were collected from 99 streams in 11 different States in the Midwest as part of USGS MSQA project. The data is bioassessment of these streams using the ecological data (macroinvertebrate metrics) as indicators of the stream condition and to relate these data to various environmental stressors (nutrients, contaminants, sediment and flow alteration) to gain better understanding of the causes of impairment.

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Communities

  • National Water-Quality Assessment Project
  • USGS Data Release Products

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Type Scheme Key
DOI https://www.sciencebase.gov/vocab/category/item/identifier doi:10.5066/F71V5C57

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