Research Analytics

Researchers are always trying to increase sample sizes, reduce laboratory costs, improve predictive models, track spatial and temporal trends of freshwater and marine species, and utilize data from citizen science organizations. The Analytical Monitoring Program (AMP) provides a solution to all of these.

• Since health and body composition measures only take a few seconds per fish, sample sizes significantly increased. The measurements used to determine which fish are brought back to the laboratory for proximate analysis (e.g., fat and lean fish).
• Proximate analysis costs are ~$110.00 per fish and can take months to complete. CQR measures are instant, and analysis on the dashboard occurs in real-time.
• Sample sizes and sampling robustness often limit predictive models of growth. 
• More data = improved spatial and temporal analysis on the condition, health, and body composition.
• Measures are easy to take with minimal training making this an excellent opportunity to train citizens in science to provide them a means to aid in research. Furthermore, measures can be uploaded anywhere in the world are available for research within the hour. 

The measurable benefit is a simple, easy to use electronic monitoring device that can assess the physiological condition, nutritional status, and body composition of fish in real-time. The machine's simple design and usage will allow anyone to measure, store, and send valuable fisheries data to researchers and managers. Thus, they allow local communities, fishers, and remote peoples to actively participate in fisheries studies while lessening the need and dependency on fishery research agencies to do bulk research. The device will dramatically increase accuracy and sample sizes that can reveal spatial and temporal variation in nutritional status on scales not previously possible. Attempts at assessing body composition or nutritional quality of fishes have focused on simple relationships between length and weight of fish (Anderson et al., 1996; Le Cren, 1951); or more complex laboratory measures of body composition and energy content (Papoutsoglou and Papaparaskeva-Papoutsoglou, 1978; Sutton et al., 2000). Length-weight relationships are easy to obtain, but lack sensitivity specific to an individual's body composition or nutritional status. At the same time, laboratory approaches can provide more detail, but are expensive (> $100.00/fish) and usually require an extended time (6 months – 1 year) for sample analysis. Previous work by Cox and Hartman (2005) provided initial BIA studies of body composition calibration curves 10 for brook trout with R2 scores between predicted and observed values of body composition parameters > 0.95. More recently, Cox and Heintz (2009) expanded BIA usage, creating a nutrition index (phase angle) that reflected nine fish species' nutritional status under varying environmental conditions. BIA has been used in freshwater and marine systems and on a plethora of species (Duncan et al., 2007; Heintz and Cox, 2008; Webster and Hartman, 2007; Willis and Hobday, 2008).