Modeling relationships between landscape-level attributes and snorkel counts of chinook salmon and steelhead parr in Idaho
Knowledge of environmental factors impacting anadromous salmonids in their freshwater habitats, particularly at large spatial scales, may be important for restoring them to previously recorded levels in the northwestern United States. Consequently, we used existing data sets and an information-theoretic approach to model landscape-level attributes and snorkel count categories of spring–summer chinook salmon (Oncorhynchus tshawytscha) and steelhead (Oncorhynchus mykiss) parr within index areas in Idaho. Count categories of chinook salmon parr were negatively related to geometric mean road density and positively related to mean annual precipitation, whereas those for steelhead parr were negatively related to percent unconsolidated lithology. Our models predicted that chinook salmon parr would be in low count categories within subwatersheds with >1 km·km–2 geometric mean road densities and (or) <700 mm mean annual precipitation. Similarly, steelhead parr were predicted to be in low count categories in subwatersheds with >30% unconsolidated lithology. These results provide a starting point for fish biologists and managers attempting to map approximate status and quality of rearing habitats for chinook salmon and steelhead at large spatial scales.