Validation and Application of Brook Trout Bioelectrical Impedance Models to Detect Seasonal Changes in Percent Dry Weight and Energy Density

Thursday, September 12, 2013: 3:20 PM
Izard (Statehouse Convention Center)
Andrew W. Hafs , Aquatic Biology, Bemidji State University, Bemidji, MN
Kyle J. Hartman , Division of Forestry and Natural Resources, West Virginia University, Morgantown, WV
Although recent studies have had good success with bioelectrical impedance analysis (BIA) in laboratory settings, field validation is needed and would increase confidence in current methods. One objective of this study was to validate laboratory derived BIA models by using them to predict percent dry weight of brook trout from BIA data collected in the field and establish trends in condition. A second objective was to determine if BIA can be used to measure seasonal changes in energy density. To accomplish these objectives BIA was done on Appalachian brook trout sampled once per month May 2010-April 2011. Large changes in adult body condition (represented by percent dry weight) occurred during the study and these changes were likely related to energy depletion from reproduction and changes in terrestrial invertebrate consumption. When subdermal needle electrodes were used for BIA measurements on adult fish monthly mean condition was predicted with good results (RMSE = 1.20, R2 = 0.71). When external rod electrodes were used similar results occurred (RMSE = 1.27, R2 = 0.70). Prediction of condition for individual fish was unreliable suggesting that more work is needed to control sources of error unexplained in this study such as fish surface temperature. The BIA model for age-0 fish was unable to provide reliable predictions for either individual fish or monthly mean estimates (RMSE = 1.15, R2 = 0.40) due in large part to the small range in measured condition. BIA models will have to improve before higher R2 values can be achieved for age-0 fish in the field. An energy density percent dry weight relationship was established that should allow for more accurate predictions from bioenergetics equations. BIA models were able to predict mean percent dry weight with enough accuracy to allow mean energy density predictions (R2 ≥ 0.91) for use in bioenergetics equations.