Hydraulic complexity metrics for evaluating in-stream brook trout habitat

A two-dimensional hydraulic model (River2D) was used to investigate the significance of flow complexity on habitat preferences of brook trout (Salvelinus fontinalis) in the high-gradient Staunton River in Shenandoah National Park, Virginia. Two 100-m reaches were modeled where detailed brook trout surveys (10-30-m resolution) have been conducted annually since 1997. Spatial hydraulic complexity metrics including area-weighted circulation and kinetic energy gradients (KEG) were calculated based on modeled velocity distributions. These metrics were compared to fish density in individual habitat complexes (10-30-m subreaches) to evaluate relationships between fish location and average flow complexity. In addition, the fish density was compared to additional habitat variables including percent cascade (CS), pool (PL) and riffle, and in-stream (ISC_N) and riparian cover. There were negative correlations between modeled mean velocity (VEL) and maximum depth (MAXD) and fish density; however, there were no statistically significant correlations between KEGs or area-weighted circulation and fish density. Fish density was negatively correlated to ISC_N and positively correlated to the percent of the channel dominated by protruding boulders (BD) and CS. The structural complexity of cascade habitat and areas with protruding boulders creates complex flow patterns indicating that flow complexity plays an important role in brook trout habitat preferences at the local scale. Linear discriminate analysis was used to further investigate the relationships between habitat variables and fish density. Using backward stepwise variable selection, the final explanatory model contained the BD, ISC_N, MAXD, PL, and VEL variables. These observations indicate that at a coarse spatial scale hydraulic complexity may be an important component in fish habitat preferences; however, other habitat variables cannot be ignored and the hydraulic complexity metrics calculated using 2D modeling results were not explanatory. While spatial hydraulic complexity metrics provide quantifiable measures for evaluating stream restoration project impacts on in-stream habitat quality, the relationships between fish density and hydraulic complexity were not straightforward. This is likely due in part to modeling limitations in this high-gradient complex stream. Further research is needed at a range of spatial scales, stream types, and fish species to fully investigate the use of hydraulic complexity metrics to quantify in-stream habitat.