Table 1.
Summaries of the four classification frameworks applied to streams of the Middle Fork John Day River Basin: River Styles, Natural Channel Classification, Rosgen Classification System, and statistical classification.
Fig 1.
Map of the Middle Fork John Day Basin, Oregon, USA.
The 33 Columbia Habitat Monitoring Program (CHaMP) reaches monitored between 2012–2013 are shown in circles. The National Landcover Dataset is presented as the base map to illustrate biophysical gradients across the watershed. Four photos illustrate the diversity of landscapes encountered across the basin.
Table 2.
Form-based channel metrics included in classification analyses.
Fig 2.
Statistical clustering of reaches using principal components analysis (PCA) based on gradient, D16, D50, D84, bankfull width, bankfull width:depth ratio, and integrated wetted width (i.e. channel width at time of sampling), classified into four discrete groups using partitioning around medoids.
Vectors of stream channel variables are plotted based on the strength of their correlation to the PCA (e.g. longer vectors are more strongly correlated to the channel form variable PCA). The first and second principal components explained 85.6% and 10.9% of the variability in the reach attribute data within the PCA. Point colors represent which cluster each reach was classified into, and representative photographs provide examples of characteristic reach morphology for each cluster.
Table 3.
Analogous reach types between NCC, RSF, RCS, and statistical clustering based on common geomorphic attributes.
Those reach types with good (G) or moderate (M) agreement are included, while those with poor agreement are not shown here, but are noted in Table 4.
Fig 3.
Results of the four classifications.
(A) River Styles, (B) Natural Channel Classes, (C) Rosgen Classification System, and (D) statistical classification with clustering (partitioning around medoids) mapped across the Middle Fork John Day Basin. River Styles and Natural Channel Classes are mapped across the entire stream network, while Rosgen Classification System and statistical classification results are presented only for CHaMP reaches. Full River Style and Natural Channel Class results for CHaMP reaches are presented in Table 4.
Table 4.
Classification results for the four methods compared here.
Fig 4.
Classification results across network and sites.
Percent of total network channel length and percent of CHaMP sites classified into reach types using each classification framework (A-D).
Table 5.
Classification results and agreement for each CHaMP site across the four classification frameworks.
Fig 5.
Illustrative example reaches describing agreement between classification outputs.
Reaches at which the four classifications had poor agreement, moderate agreement, and good agreement in the observed channel planform.
Fig 6.
Dendrogram of clustered reaches based on their classification outputs from each of the four frameworks.
Reaches with a distance of zero that occur on adjacent nodes of the same length are identical. For example, reaches CBW05583-381682 and CBW05583-383986 are identical in how they were classified by all four frameworks. Reaches were clustered using an average linkage clustering algorithm and Gower’s distance matrix.
Fig 7.
Principal coordinates analysis ordination showing reaches’ relative similarity based on the outputs of the four classification frameworks.
Each reach is plotted within each classification output for ease of interpretation. Reaches were grouped within the ordination space using Gower’s distance. Reaches that are more similar to one another are closer together in the ordination space. R2 values correspond to the fit of a given classification framework’s outputs to the ordination of all classification outputs.