White sturgeon population sizes and dynamics differ throughout the Columbia River Basin.  In every area of the upper Columbia River with severely depleted sturgeon populations, spawning has been documented but young-of-the-year or juvenile fish are rarely collected, suggesting that there may be high levels of mortality during larval and/or early juvenile stages.  The cause of this early mortality is unknown and could be due to a variety of physical or biological factors.  Some river reaches have consistently good spawning success and others have consistently poor or negligible spawning success, thus comparison of physical conditions among reaches should reveal differences between those reaches with consistently good spawning success and those with consistently negligible success.  Thus, we will begin to compare and contrast the physical environment available in reaches that exhibit consistent, inconsistent, and negligible spawning success.  Spatially explicit hydrodynamic modeling in each reach will enable comparisons of physical features such as river depths, channel features, flow velocities including magnitude and variation, and sediments.  Identification of differences in physical habitats among reaches will provide information that managers can use to bring reaches with negligible spawning success to a more desirable state.

Current technologies and computational capabilities allow characterization of riverine habitats in a spatially explicit manner.  A suite of aquatic habitat descriptors including river bed elevations, water velocities, turbulence and hydraulic complexity, sediment composition, and sediment facies can now be assessed via remote sensing technologies and verified with ground-truthing.  As an example, the white sturgeon spawning area in the Kootenai River was recently described using two-dimensional hydrodynamic modeling and substrate characterization.  Geographical Information Systems (GIS) technology enables a broad range of statistical techniques to map and compare discrete spatial areas.  One such statistical technique, the Mahalanobis distance statistic, can be used to provide a measure of similarity (or dissimilarity) to a reference condition.  Very simply, Mahalanobis distance represents the standard squared distance between a set of sample variates and “ideal” habitat.  Since the Mahalanobis distance is measured in terms of standard deviations from the mean of the training samples or “ideal” habitat, one can obtain a statistical measure of how closely the habitats compare.  FRAGSTATS, a computer software program designed to compute a wide variety of landscape metrics for categorical map patterns, will also be used to examine landscape conditions.  By making comparisons of habitat among reaches with differing levels of white sturgeon spawning success, we may discover key differences between reaches that have spawning success and those that don’t.  Managers could then choose to implement actions that move habitats to a more desirable state.  One outcome of this project is to identify that desirable state for white sturgeon migration, spawning and egg incubation, and larvae settling.