Measurements of resistance and reactance in fish with the use of bioelectrical impedance analysis: sources of error

New technologies can be riddled with unforeseen sources of error, jeopardizing the validity and application of their advancement. Bioelectrical impedance analysis (BIA) is a new technology in fisheries research that is capable of estimating proximate composition, condition, and energy content in fish quickly, cheaply, and (after calibration) without the need to sacrifice fish. Before BIA can be widely accepted in fisheries science, it is necessary to identify sources of error and determine a means to minimize potential errors with this analysis. We conducted controlled laboratory experiments to identify sources of errors within BIA measurements. We concluded that electrode needle location, procedure deviations, user experience, time after death, and temperature can affect resistance and reactance measurements. Sensitivity analyses showed that errors in predictive estimates of composition can be large (>50%) when these errors are experienced. Adherence to a strict protocol can help avoid these sources of error and provide BIA estimates that are both accurate and precise in a field or laboratory setting.

Using wildlife activity and antibiotic resistance analysis to model bacterial water quality in coastal ponds

Models that help predict fecal coliform bacteria (FCB) levels in environmental waters can be important tools for resource managers. In this study, we used animal activity along with antibiotic resistance analysis (ARA), land cover, and other variables to build models that predict bacteria levels in coastal ponds that discharge into an estuary. Photographic wildlife monitoring was used to estimate terrestrial and aquatic wildlife activity prior to sampling. Increased duck activity was an important predictor of increased FCB in coastal ponds. Terrestrial animals like deer and raccoon, although abundant, were not significant in our model. Various land cover types, rainfall, tide, solar irradiation, air temperature, and season parameters, in combination with duck activity, were significant predictors of increased FCB. It appears that tidal ponds allow for settling of bacteria under most conditions. We propose that these models can be used to test different development styles and wildlife management techniques to reduce bacterial loading into downstream shellfish harvesting and contact recreation areas.