USGS ScienceSearch

Geology topics

Erin K. Dlabola

Publications and source records attributed to Erin K. Dlabola.

2 recordsLinked to original sources

A data exchange standard for wadeable stream habitat monitoring data

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.

Techniques and Methods

Sharing FAIR monitoring program data improves discoverability and reuse

Data resulting from environmental monitoring programs are valuable assets for natural resource managers, decision-makers, and researchers. These data are often collected to inform specific reporting needs or decisions with a specific timeframe. While program-oriented data and related publications are effective for meeting program goals, sharing well-documented data and metadata allows users to research aspects outside initial program intentions. As part of an effort to integrate data from four long-term large-scale US aquatic monitoring programs, we evaluated the original datasets against the FAIR (Findable, Accessible, Interoperable, Reusable) data principles and offer recommendations and lessons learned. Differences in data governance across these programs resulted in considerable effort to access and reuse the original datasets. Requirements, guidance, and resources available to support data publishing and documentation are inconsistent across agencies and monitoring programs, resulting in various data formats and storage locations that are not easily found, accessed, or reused. Making monitoring data FAIR will reduce barriers to data discovery and reuse. Programs are continuously striving to improve data management, data products, and metadata; however, provision of related tools, consistent guidelines and standards, and more resources to do this work is needed. Given the value of these data and the significant effort required to access and reuse them, actions and steps intended on improving data documentation and accessibility are described.

Enviornmental Monitoring and Assessment