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A Data Exchange Standard for Wadeable Stream Habitat Monitoring Data

Techniques and Methods 16-B2
Prepared in cooperation with the U.S. Environmental Protection Agency, Bureau of Land Management, and the U.S. Forest Service
By: , , , , , , , , , , and 
https://doi.org/10.3133/tm16B2

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Abstract

Data from wadeable streams collected by monitoring programs are used to assess watershed condition status and trends. Federally managed programs collect a suite of similar habitat measurements using compatible methods and produce individual program datasets for their prescribed geographic and temporal range. We identified four programs that produce similar data: the Bureau of Land Management Assessment, Inventory, and Monitoring lotic division, the U.S. Environmental Protection Agency National Aquatic Resource Surveys National Rivers and Streams Assessment survey section, the Federal interagency Aquatic and Riparian Effectiveness Monitoring Program, and the PacFish/InFish Biological Opinion Monitoring Program. Their datasets answer agency-specific management questions and fulfill reporting requirements, but the datasets are not released in full, or at all, and in some cases, there was no method to integrate data from the four programs to provide data at a larger spatial scale.

The Pacific Northwest Aquatic Monitoring Partnership (PNAMP) led a working group of experts from the four monitoring programs to determine data compatibility, develop a Stream Habitat Metrics Integration (SHMI) data exchange standard, and integrate compatible wadeable stream data. The resulting SHMI data exchange standard contains a data mapping file used to transform data from the source program data to a conformed format based on a controlled vocabulary. After extensive discussions assessing and comparing program collection and analyses methods, the working group found 26 stream habitat metrics to be sufficiently comparable to be integrated into a meaningful dataset. Furthermore, a subset of PIBO MP data previously available only by request and AREMP data available only as a proprietary ESRI ArcGIS geodatabase were made publicly available in non-proprietary formats via the integrated SHMI dataset.

A selection of data from the four programs determined to be compatible among 14 datasets were filtered, transformed, standardized, and combined using R code to create the integrated SHMI dataset containing about 12,000 locations, 19,000 events, and 200,000 measurements from 2000 to 2022.

This report describes the SHMI data exchange standard and its development, the metric compatibility assessment, and the data integration process, so that others may reuse the SHMI data exchange standard and its components as well as the data integration processes.

Suggested Citation

Scully, R.A., Dlabola, E.K., Bayer, J.M., Heaston, E., Courtwright, J., Snyder, M.N., Hockman-Wert, D., Saunders, W.C., Blocksom, K.A., Hirsch, C., and Miller, S.W., 2024, A data exchange standard for wadeable stream habitat monitoring data: U.S. Geological Survey Techniques and Methods, book 16, chap. B2, 28 p., https://doi.org/10.3133/tm16B2.

ISSN: 2328-7055 (online)

Table of Contents

  • Acknowledgements
  • Abstract
  • Introduction
  • Stream Habitat Metrics Integration Project
  • Case Study Results of Integrating Stream Habitat Using the Stream Habitat Metrics Integration Exchange Standard
  • Stream Habitat Metrics Integration Data Exchange Standard
  • Controlled Vocabulary Development
  • Key Considerations When Building Data Exchange Standards and Integrating Datasets
  • Summary
  • References Cited
  • Appendix 1
Publication type Report
Publication Subtype USGS Numbered Series
Title A data exchange standard for wadeable stream habitat monitoring data
Series title Techniques and Methods
Series number 16-B2
DOI 10.3133/tm16B2
Year Published 2024
Language English
Publisher U.S. Geological Survey
Publisher location Reston, VA
Contributing office(s) Forest and Rangeland Ecosystem Science Center
Description Report: vii, 28 p.; Data Release; Software Release
Online Only (Y/N) Y
Google Analytic Metrics Metrics page
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