Juvenile Anadromous Salmonid Habitat Density Relationships Using Interagency Databases & SSN Models

Year: 2022
Presenter/s: Dan Isaak
Symposium Session: 2022 - 07 Putting the Fish into Fish Habitat Restoration
Topics covered: climate change, fish-cutthroat, fish-salmon, fish-steelhead, modeling, monitoring, and riparian


Significant investments have been made by numerous agencies to monitor anadromous salmonids by conducting thousands of density surveys within streams across the Columbia River Basin. We aggregated these surveys from CRITFC, ODFW, IDFG, USFS, CHaMP, and BioMark for the period of 2000–2018 for Idaho and northeastern Oregon streams into a single database and applied spatial stream network (SSN) models to describe habitat relationships of juvenile Chinook salmon (n = 6,757) and steelhead (n = 7,436). Twenty-eight covariates were assessed, but only seven were statistically significant for Chinook salmon (reach slope, mean summer flow, mean August temperature, baseflow index, riparian canopy density, brook trout density, and inter-annual variation in juvenile densities) and these explained 57% of the variation in densities at the survey sites. The final model for steelhead accounted for 48% of the variation in densities and included six of the same seven covariates as the Chinook salmon model. Response curves describing habitat relationships indicated Chinook salmon densities were highest in medium sized streams with low reach slopes, cool temperatures, higher brook trout densities, and intermediate levels of riparian canopy and baseflows. Conversely, steelhead densities were highest in small streams with greater slopes, warmer temperatures, low brook trout densities, high proportions of watershed conifers, and intermediate levels of riparian canopy. The SSN models were used to create 24 prediction scenarios of juvenile densities for all reaches in the study area networks, and included baseline composite scenarios of average densities for 2000-2018, annual density scenarios, and three future scenarios indicative of climate warming (scenarios available online as ArcGIS shapefile at the StreamNet Data Store: https://app.streamnet.org/datastore_search_classic.cfm). Our results highlight the utility of existing fish density survey data for creating new information when integrated to a consistent database and used with SSN models and other publicly available geospatial resources. The density scenarios can be used with other geospatial resources by conservation planners to display fish densities in areas of interest and allocate restoration accordingly.