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Figure S1. Land use and risk. The distributions of different land uses are mapped throughout the 6 risk regions. The more developed the land the higher the risk.

Table S1. Each relative risk region was broken down by watersheds within Water Resource Inventory Areas (WRIAs) 10 and 12. Watersheds in Pierce County are identified below for each risk region. Risk regions 1, 4 and 5 had small areas of watersheds overlapping into King County.

Table S2. Summary explanation of model variables, definitions, rankings, and sources for the BN-RRM for the Puyallup River Watershed, examining LID as a management tool to reduce the risk of prespawner mortality in coho salmon.

Table S3. Summary of land use model input ranks and percent land cover for each risk region, including total risk region areas. Road length ranks were determined by natural breaks while commercial property types and other impervious surface ranks were determined by Booth et al. (2002) and Department of Ecology Washington State (2010).

Table S4. Weights and rankings for Migratory Habitat input node. Each region's habitat was assessed based on the total river miles of habitat and the salmon habitat status based on Washington Department of Fish and Wildlife definitions.

Table S5. Summary table for coho salmon spawner returns from Washington Department of Fish and Wildlife (WDFW) data.

Table S6. Summary of risk region node scores. Scores are given for each node, with standard deviations given as calculated from Netica. The overall risk score for each region given in the bottom row for Coho_Fisheries.

Table S7. Summary table of distributions for each node by risk region.

Table S8. Summary table of input parameters with largest contribution to overall risk scores from sensitivity analysis. Note that decision nodes (such as inputs for land use and abundance of low impact development (LID)) were not included in this analysis as Netica software only includes Bayes nets currently in the sensitivity analysis.

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