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Emily Heaston

Publications and source records attributed to Emily Heaston.

2 recordsLinked to original sources

RoadxStr user’s guide—For collection of road-stream crossing assessment field observations

Intersections of drainage networks and road networks represent a critical nexus between natural waterways and human infrastructure. Managing these systems involves decisions related to management of infrastructure, hydrologic and geomorphic processes, and ecological connectivity. Interactions among these systems influence multiple values, including the intactness of transportation networks, public safety, water quality, and ecosystem function that collectively amount to billions of dollars. Despite the importance of road-stream crossings, there are countless gaps in knowing where and what they are. These gaps limit the degree to which managers can inventory and assess stream and road networks to inform decisions. To address this first-level need, we developed RoadxStr (road-stream crossings): a survey tool that effectively characterizes road-stream crossings across the full stream and drainage network. This document describes the RoadxStr Field Form, available within a mobile application, which is designed for rapid and standardized data collection involving assessment of a road-stream crossing, including the road, crossing structure(s), and the nearby hydrologic channel. This document provides instructions on how to (1) access and download the RoadxStr Field Form within the mobile application service and (2) use and complete a RoadxStr Field Form survey.

Techniques and Methods

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