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Detecting Environmental Impacts of Invasive Mussel Infestations: Development of an Algae and Zooplankton Database using FlowCam™ Technology

Project ID: 2387
Principal Investigator: Denise Hosler
Research Topic: Water Quality
Priority Area Assignments: 2014 (Zebra and Quagga Mussels), 2015 (Zebra and Quagga Mussels)
Funded Fiscal Years: 2014
Keywords: quagga, zebra, mussel, zooplankton, algae, database, water quality, fisheries, environmental impact.

Research Question

Invasive mussels have a negative impact on a water body's natural biology. Can Reclamation develop a fast and cost effective method to monitor the impact of invasive mussels on the health of the ecosystem? Will the development of a FlowCam™ classification library, filters, and database streamline this monitoring process and provide valuable information on the diversity and abundance of indicator organisms, such as algae and zooplankton?

Need and Benefit

Filter feeding invasive mussels negatively impact aquatic ecosystems by altering the food web. The mussels remove phytoplankton, which is a source of food for zooplankton. Increased filtration subsequently leads to increased light penetration, impacting algae growth and proliferation of aquatic plants. The Bureau of Reclamation purchased a FlowCam™ to build a database of the algae and zooplankton populations in reservoirs sampled for early detection of mussels and to monitor algae and zooplankton population responses to mussel introduction and proliferation. The FlowCam™ takes images of the organisms present in a water sample, and has the capability to identify and catalog the organisms.

Introduction of invasive species can have dramatic effects on the aquatic ecosystem; these effects can only be tracked by the FlowCam™ if the cataloging capabilities are optimized and samples are analyzed. Currently, 3536 water samples have been processed with the FlowCam™ during the 2010 to 2012 sampling seasons. Another 1000 samples will be processed during the 2013 sampling season. Just processing samples without analysis does not provide usable information for water managers. Once statistical filters are developed to identify the organisms and a user-friendly database is created, the population shifts can begin to be monitored. Three to five years of historic data will provide enough information to create the baseline, and at the end of the 2013 sampling season Reclamation will have processed four years of data with the FlowCam™.

Monitoring algae and zooplankton populations will help evaluate the environmental impact of invasive species, such as zebra and quagga mussels. In the future, this monitoring technology could also be beneficial to fisheries managers by helping them determine the best times of year to release fish. FlowCam™ data can help determine when food is plentiful for fish and may decrease the risk of food related fish die-offs. FlowCam™ data combined with benthic surveys would provide a more complete picture of Reclamation water health to limnologists and managers. This database will be beneficial to water management in every state. Historic baselines are important in biology because water health changes over time due to: climate change, invasive species, human impacts, dams, etc. Currently, Reclamation sends zooplankton and algae samples to expert taxonomists who have to identify each individual organism under the microscope; development of FlowCam™ filters, a classification library, and a database should significantly reduce the amount of time and money required for processing these samples.

Contributing Partners

None

Research Products

During fiscal year 2014 a standard operating procedure will be produced describing how to build and use a classification library and statistical filters for the FlowCam™.

During fiscal year 2015 a database will be developed that will be used to store and analyze presence and abundance of indicator zooplankton and algae species. A technical report will be prepared describing the populations of zooplankton and algae species in Reclamation waterways sampled for early detection.

This information was last updated on October 24, 2014
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