Evaluation of bioelectrical impedance analysis and Fulton’s condition factor as nonlethal techniques for estimating short-term responses in postsmolt Atlantic salmon (Salmo salar) to food availabili

We evaluated measures of bioelectrical impedance analysis (BIA) and Fulton’s condition factor (K) as potential nonlethal indices for detecting short-term changes in nutritional condition of postsmolt Atlantic salmon (Salmo salar). Fish reared in the laboratory for 27 days were fed, fasted, or fasted and then refed. Growth rates and proximate body composition (protein, fat, water) were measured in each fish to evaluate nutritional status and condition. Growth rates of fish responded rapidly to the absence or reintroduction of food, whereas body composition (% wet weight) remained relatively stable owing to isometric growth in fed fish and little loss of body constituents in fasted fish, resulting in nonsignificant differences in body composition among feeding treatments. The utility of BIA and Fulton’s K as condition indices requires differences in body composition. In our study, BIA measures were not significantly different among the three feeding treatments, and only on the final day of sampling was K of fasted vs. fed fish significantly different. BIA measures were correlated with body composition content; however, wet weight was a better predictor of body composition on both a content and concentration (% wet weight) basis. Because fish were growing isometrically, neither BIA nor K was well correlated with growth rate. For immature fish, where growth rate, rather than energy reserves, is a more important indicator of fish condition, a nonlethal index that reflects shortterm changes in growth rate or the potential for growth would be more suitable as a condition index than either BIA measures or Fulton�

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.

Measurements of total scattering spectra from bocaccio (Sebastes paucispinis)

Marine sportfishing in southern California is a huge industry with annual revenues totaling many billions of dollars. However, the stocks of lingcod and six rockfish species have been declared overfished by the Pacific Fisheries Management Council. As part of a multifaceted fisheries management plan, marine conservation areas, covering many million square nautical miles, have been mandated. To monitor the recovery of the rockfish stocks in these areas, scientists are faced with the following challenges: 1) multiple species of rockfish exist in these areas; 2) the species reside near or on the bottom at depths of 80 to 300 m; and 3) they are low in numerical density. To meet these challenges, multifrequency echosounders, multibeam sonar, and cameras mounted on remotely operated vehicles are frequently used (Reynolds et al., 2001). The accuracy and precision of these echosounder results are largely dependent upon the accuracy of the species classification and target strength estimation (MacLennan and Simmonds, 1992).