Bend-scale geomorphic classification and assessment of the Lower Missouri River from Sioux City, Iowa, to the Mississippi River for application to pallid sturgeon management

Management actions intended to increase growth and survival of pallid sturgeon (Scaphirhynchus albus) age-0 larvae on the Lower Missouri River require a comprehensive understanding of the geomorphic habitat template of the river. The study described here had two objectives relating to where channel-reconfiguration projects should be located to optimize effectiveness. The first objective was to develop a bend-scale (that is, at the scale of individual bends, defined as “cross-over to cross-over”) geomorphic classification of the Lower Missouri River to help in the design of monitoring and evaluation of such projects. The second objective was to explore whether geomorphic variables could provide insight into varying capacities of bends to intercept drifting larvae. The bend-scale classification was based on geomorphic and engineering variables for 257 bends from Sioux City, Iowa, to the confluence with the Mississippi River near St. Louis, Missouri. We used k-means clustering to identify groupings of bends that shared the same characteristics. Separate 3-, 4-, and 6-cluster classifications were developed and mapped. The three classifications are nested in a hierarchical structure. We also explored capacities of bends to intercept larvae through evaluation of linear models that predicted persistent sand area or catch per unit effort (CPUE) of age-0 sturgeon as a function of the same geomorphic variables used in the classification. All highly ranked models that predict persistent sand area contained mean channel width and standard deviation of channel width as significant variables. Some top-ranked models also included contributions of channel sinuosity and density of navigation structures. The sand-area prediction models have r-squared values of 0.648–0.674. In contrast, the highest-ranking CPUE models have r-squared values of 0.011–0.170, indicating much more uncertainty for the biological response variable. Whereas the persistent sand model documents that physical processes of transport and accumulation are systematic and predictable, the poor performance of the CPUE models indicate that additional processes will need to be considered to predict biological transport and accumulation.