Effects of shear on eggs and larvae of striped bass, morone saxatilis, and white perch, M. americana

Shear stress, generated by water movement, can kill fish eggs and larvae by causing rotation or deformation. Through the use of an experimental apparatus, a series of shear (as dynes/cm2)-mortality equations for fixed time exposures were generated for striped bass and white perch eggs and larvae. Exposure of striped bass eggs to a shear level of 350 dynes/cm2 kills 36% of the eggs in 1 min; 69% in 2 min, and 88% in 4 min; exposure of larvae to 350 dynes/cm2 kills 9.3% in 1 min, 30.0% in 2 min, and 68.1% in 4 min. A shear level of 350 dynes/cm2 kills 38% of the white perch eggs in 1 min, 41% in 2 min, 89% in 5 min, 96% in 10 min, and 98% in 20 min. A shear level of 350 dynes/cm2 applied to white perch larvae destroys 38% of the larvae in 1 min, 52% in 2 min, and 75% in 4 min. Results are experimentally used in conjunction with the determination of shear levels in the Chesapeake and Delaware Canal and ship movement for the estimation of fish egg and larval mortalities in the field.

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.