Estimating observer error and steelhead redd abundance using a modified Gaussian area-under-the-curve framework

Abstract

This study examined how a suite of habitat and environmental variables relate to the ability of a stream surveyor to identify (observer efficiency) and distinguish (observer accuracy) steelhead (Oncorhynchus mykiss) redds from other stream features. Two existing spawning survey protocols that included one or two redd observers were used to develop models to estimate redd observer error. In most cases, steelhead redd abundances using raw redd counts were underestimated. Mean annual rates of observer efficiency ranged from 0.44 to 0.57, and observer accuracy ranged from 0.67 to 0.83. Regardless of the observer error model used, adjusted annual redd abundance estimates were generally unbiased (range 1.6–0.6 redds). A Gaussian area-under-the-curve methodology that incorporates redd count data and observer error rates was used to generate unbiased estimates of steelhead redd abundance in the Wenatchee (170 redds, coefficient of variation (CV) = 44%) and Methow (106 redds, CV = 41%) rivers. Unbiased estimates of redd abundance will help inform new population viability analyses to better prioritize those populations with the greatest conservation need.