Th-141-18
The Columbia Habitat Monitoring Program: Applying Twenty-First Century Technology to Solve Fish Management Questions at Multiple Scales

Sarah M. Walker , Terraqua Inc, Wauconda, WA
Chris Beasley , Quantitative Consultants, Inc., Boise, ID
Boyd Bouwes , Watershed Solutions Inc.
Nick Bouwes , Department of Watershed Sciences, Utah State University, Logan, UT
Andrew Hill , Ecological Research Inc
Chris Jordan , Conservation Biology Division, NOAA-NWFSC, Corvallis, OR
Mike Ward , Terraqua INC., Wauconda, WA
Joe Wheaton , Utah State University
Carol J. Volk , Integrated Status and Effectiveness Monitoring Program, South Fork Research, Inc, North Bend, WA
The Columbia Habitat Monitoring Program (Bonneville Power Administration Project 2011-006; CHaMP) was explicitly designed to help address the recovery of ESA-listed salmonid populations in freshwater tributaries across the Columbia River Basin. CHaMP’s unique protocol focuses solely on metrics with presumed direct linkages to salmonid population responses; requires a comprehensive topographic habitat survey via total station or other instrument; and uses custom applications and tools to standardize crew field data capture, ensure metric quality control, and simplify production of a Digital Elevation Model (DEM) for each site. Results from 2011-2013 show our metrics are robust and capable of being used alone for indicator development, or in combination to support multivariate fish-habitat relationship model outputs (e.g., Habitat Suitability Indices). We have found the DEM format to be extremely valuable: it can be leveraged with existing geodatabases, used to replicate other monitoring programs’ survey cross-sections, and multiple DEMs can be used together to quantitatively estimate physical habitat change at a site and to evaluate potential response under different restoration scenarios. To move beyond the site-scale, CHaMP metrics can be used with globally available attributes to produce continuous displays of metrics and indicators across watersheds, and to extrapolate information to unsampled areas of interest.