EN VOGUE: EX-SITU CALIBRATION OF NEXT GENERATION CAMERA TECHNOLOGY TO ASSESS AQUATIC FOOD-WEB STRUCTURE FOR JUVENILE SALMONIDS
Conventional methods of measuring insect drift can become difficult with increasing water velocity due to the accumulation of organic material within nets of a certain mesh size. The processing of multiple net samples can prove to be time consuming and expensive. Together these constraints significantly limit the capacity to sample food-web structure at the necessary temporal and spatial scales within critical habitat for certain size classes of juvenile salmonid. The Scripps Plankton Camera (SPC) employs a 0.137X magnification lens, onboard Odroid – XU4 and LINUX operating system which evaluates particles down to 1mm in length and measure the major axis of the particles within the frame of view of the camera. We utilized an experimental flow-through chamber attached to a variable speed water pump then manipulated frame rate, exposure time, and processing area range to increase resolution of sample particles. We also instituted a PYTHON Image Learning Package to differentiate between insect, detritus, and turbulent bubbles with 85% efficiency. Preliminary results indicate that the development and fine tuning of high resolution photographic technology could prove to be a valuable alternative when sampling insect dispersal in various capacities of lotic environments.
Nicholas Macias (Primary Presenter/Author), University of California, Santa Cruz, firstname.lastname@example.org;