We used broad-scale landscape feature variables to model redd densities of spring Chinook salmon (Oncorhynchus tshawytscha) and steelhead trout (Oncorhynchus mykiss) in the Methow River watershed. Redd densities were estimated from redd counts conducted from 2005 to 2007 and 2009 for steelhead trout and 2005 to 2009 for spring Chinook salmon. These densities were modeled using generalized linear mixed models. Variables examined included primary and secondary geology type, habitat type, flow type, sinuosity, and slope of stream channel. In addition, we included spring effect and hatchery effect variables to account for high densities of redds near known springs and hatchery outflows. Variables were associated with National Hydrography Database reach designations for modeling redd densities within each reach. Reaches were assigned a dominant habitat type, geology, mean slope, and sinuosity. The best fit model for spring Chinook salmon included sinuosity, critical slope, habitat type, flow type, and hatchery effect. Flow type, slope, and habitat type variables accounted for most of the variation in the data. The best fit model for steelhead trout included year, habitat type, flow type, hatchery effect, and spring effect. The spring effect, flow type, and hatchery effect variables explained most of the variation in the data. Our models illustrate how broad-scale landscape features may be used to predict spawning habitat over large areas where fine-scale data may be lacking.
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Using broad landscape level features to predict redd densities of steelhead trout (Oncorhynchus mykiss) and Chinook Salmon (Oncorhynchus tshawytscha) in the Methow River watershed, Washington