Presented by Chris Scholin and Heidi M. Sosik
Research topic and goals
The goal of harmful algal blooms (HABs) sampling is to analyze the distribution of target species in situ (analyzing samples in real time). Researchers aim to discern how the phytoplankton community's evolution and reaction to the immediate environment work by using in-situ observations.
The intial focus on harmful algal blooms is to:
- Predict the phytoplankton bloom timing and location
- Locate a phytoplankton bloom
- Follow the bloom and observe changes in its size, species composition, rates, and consumers (organisms who feed off the phytoplankton bloom)
- Forecast the location and size of future blooms
Target measurement of harmful algal blooms sampling
How should researchers target a specific area to collect water samples? Specific areas may contain higher concentrations of the phytoplankton community, which is optimal for sampling. Researchers do not have to collect water samples from a large area. Instead, prior observations and modeling point are key to determining optimal sampling locations.
In the case of Florida, there is a need to sample offshore to find phytoplankton blooms. Sampling for HAB species is required from near shore to offshore. Species are often near the ocean's surface ranging anywhere from 1-25m deep. Target species that need to be sampled occur ephemerally and can be patchy.
Most regions approach HAB research and monitoring from coupled observation, modeling and prediction perspective. There are many opportunities for combining molecular analytical detection technology in order to develop an adaptive sampling/response framework for determing optimal sampling locations.
Current automated capacities and future needs
Source: Olson and Sosik 2007
As its name implies, the Imaging FlowCytobot combines flow cytometry with video imaging capability, which allows two-dimensional imaging in flow. This instrument is optimized for analysis of microplankton-sized particles
For those previously unfamiliar with flow cytometry, it allows researchers to count cells, determine their size, and identify them, often to genus level, in order to process thousands of cells very rapidly.
The Imaging CytoBot has observational capabilities combined with automated image classification for enumeration, identification, and cell sizing thousands of individual phytoplankton.
The FlowCytobot has accomplished a number of tasks regarding the anaylsis of HABS and phytoplankton blooms:
- It can identify 27 classes of diatoms
- It can rank diatom groups by biomass
- It can also identify the dinoflagellate population.
- It has identified the Karenia bloom in the Gulf of Mexico
- It can rank diatom groups by biomass
