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Rebecca Scully

US Geological Survey
Data Exchange Standard for Integrating Stream Habitat Data from Multiple Monitoring Programs
Monitoring data can provide additional value when integrated with data from other monitoring programs and research projects. The Stream Habitat Metrics Integration Project led by the Pacific Northwest Aquatic Monitoring Partnership (PNAMP) was initiated to integrate metric data from multiple stream tributary habitat monitoring programs within the United States. Stream habitat monitoring programs gather observations and measurements data and distribute information to answer agency-specific management questions about the status and trend of resources within a given geographic range. Additionally, some of these programs publish and share their data. Individual monitoring programs have program-specific storage and analysis capacity, data management history, response design, and spatial design.

To integrate stream habitat data across four programs, PNAMP led a working group of experts from the Bureau of Land Management (BLM) Assessment, Inventory, and Monitoring (AIM) Strategy, United States Forest Service (USFS) Aquatic and Riparian Effectiveness Monitoring Program (AREMP), USFS PacFish/InFish Biological Opinion Monitoring Program (PIBO MP) and Environmental Protection Agency (EPA) National Aquatic Resource Surveys (NARS) National Rivers and Streams Assessment (NRSA). Together we designed a data exchange standard, data structure, controlled vocabularies, data map to translate data from source monitoring, and wrote R code to automate the translation of the data from these sources. The dataset with metadata and metrics from the four programs is published as a relational database, a set of .csv files, and a flat formatted analysis-ready dataset. The data exchange standard is published as a GitLab repository. In this presentation we will outline the process we applied to integrate data, resulting products, lessons learned, and next steps for use of the integrated data to answer management questions outside the original intent of the programs’ data collection effort.