TY - GEN
T1 - Use of Imaging Particle Analyzer (FlowCam®) for characterizing metrics for zooplankton
AU - Nelson, Harry
AU - Broadway, Kyle
AU - Detmer, Thomas
AU - Potter, Cal
AU - Buerkens, Frances
N1 - Conference Proceedings
62nd Annual Conference on Great Lakes Research (IAGLR 2019); 10-14 June 2019, Brockport, New York
PY - 2019
Y1 - 2019
N2 - Evaluations of zooplankton body size, biomass, density, and community composition are critical for understanding ecosystem structure and function. The process of enumerating, identifying, and measuring zooplankton has traditionally been accomplished through microscopy, which can be time intensive and accrue high-cost over time. The development of fully or semi-automated methods are becoming viable and potentially cost effective alternatives to historic approaches. Here we present an approach to studying zooplankton using the imaging particle analyzer FlowCam and FlowCam Macro, along with portions of a study conducted by the Illinois Natural History Survey that compared FlowCam and microscopy for characterizing mesozooplankton body size, biomass, density, and community structure. In the study, estimates of body size varied slightly, but variation was consistent due to varying methods in which size was estimated. A strong relationship was observed in density and community structure estimates between FlowCam and microscopy methods and underestimation from the FlowCam® can be rectified with mathematical equations. Similarly, individual biomass estimation from 2-dimentional profile area derived from FlowCam was similar to estimates from a commonly used length-mass regression model. Under most conditions evaluated, the semi-automated approach yielded an average time savings of 11 minutes per sample compared to the traditional microscopy method.
AB - Evaluations of zooplankton body size, biomass, density, and community composition are critical for understanding ecosystem structure and function. The process of enumerating, identifying, and measuring zooplankton has traditionally been accomplished through microscopy, which can be time intensive and accrue high-cost over time. The development of fully or semi-automated methods are becoming viable and potentially cost effective alternatives to historic approaches. Here we present an approach to studying zooplankton using the imaging particle analyzer FlowCam and FlowCam Macro, along with portions of a study conducted by the Illinois Natural History Survey that compared FlowCam and microscopy for characterizing mesozooplankton body size, biomass, density, and community structure. In the study, estimates of body size varied slightly, but variation was consistent due to varying methods in which size was estimated. A strong relationship was observed in density and community structure estimates between FlowCam and microscopy methods and underestimation from the FlowCam® can be rectified with mathematical equations. Similarly, individual biomass estimation from 2-dimentional profile area derived from FlowCam was similar to estimates from a commonly used length-mass regression model. Under most conditions evaluated, the semi-automated approach yielded an average time savings of 11 minutes per sample compared to the traditional microscopy method.
KW - INHS
UR - http://iaglr.org/conference/proceedings/2019/prof218.html
M3 - Conference contribution
BT - Large Lakes Research: Connecting People & Ideas
ER -