Blooms of the toxic dinoflagellate, Karenia brevis, threaten human and ecosystem health and local economies around the Gulf of Mexico. Although the blooms mostly prevail on the west coast of Florida, they also occur along the Texas coast. We will investigate the causes of Karenia brevis blooms off the Texas coast with the intent of improving early warning of blooms and their impacts.
Karenia brevis (K. brevis), the “Florida red tide” organism that frequently blooms in some areas of the Gulf of Mexico, produces a suite of neurotoxins. When the toxins are released into the air by wave action near beaches, they cause respiratory irritation and, sometimes, illness in humans. Toxins also accumulate in shellfish, which when consumed cause a debilitating human illness, Neurotoxic Shellfish Poisoning. Intensive monitoring by state public health and resource agencies results in harvesting closures when levels exceed thresholds. Such monitoring ensures safe seafood consumption. Finally, K. brevis causes mass mortality of fish and protected and endangered birds, turtles and mammals. Blooms occur almost annually along the Florida west coast. Along the Texas coast they are more sporadic, but seem to be occurring more often. Early warning allows state managers to better protect public health and helps coastal businesses and the shellfish industry minimize economic impacts.
What We Are Doing
In contrast to the Florida shelf, little is known about the mechanism for K. brevis bloom formation off Texas. Because K. brevis grows slowly, research scientists propose that wind and water movements (convergence and downwelling) physically concentrate Karenia cells near the coast. We tested this hypothesis and use it to improve HAB forecasting in the following steps.
- We investigate the relationship between wind and bloom events for past bloom events using a series of numerical models, from simple correlations to complex three-dimensional hydrodynamic models. The intent is developing a down welling index that we can use to predict the onset of Karenia blooms.
- The predictive ability of the down welling index is being tested in the field in two ways: a) Use of current and historical data from a wide variety of sources, including the Imaging Flow Cytobot, satellite remote sensing, state agency sampling, and the extensive volunteer network; b) When model predictions indicate that a bloom is likely, targeted sampling will be conducted in the area where the bloom is predicted.
- The downwelling index will be incorporated into NOAA’s HAB Forecast System to provide managers with early warning of HAB events.
As part of the field sampling program, cells enumerate with an Imaging Flow Cytobot, which has recently been developed at Woods Hole Oceanographic Institution (WHOI). This automated underwater microscope looks at a very thin stream of water and takes pictures of cells as they pass by a laser in single file. After training, its software can automatically classify and count the different types of phytoplankton cells from the images and send alerts to researchers and state managers when targeted species are observed above threshold levels. This project is part of the Ecology and Oceanography of Harmful Algal Blooms (ECOHAB) program.
The project is led by Lisa Campbell of Texas A&M University, Department of Oceanography. Other project participants include Robert Olson and Heidi Sosik of WHOI, Richard Stumpf of NOAA National Ocean Service, and Robert Hetland, also of Texas A&M University.
Benefits of Our Work
- The project is providing new fundamental knowledge on the mechanism of bloom formation in the western Gulf of Mexico. It will identify the source regions for blooms, which may differ by season.
- Predictive models, incorporating the Downwelling Index, will allow advance warning of HABs that we will disseminate by the NOAA HAB Forecast System for prediction and early warning of HAB events.
- The Imaging Flow Cytobot, located at Port Aransas on the University of Texas-Marine Sciences Institute pier, is a powerful tool for fast identification and counting of HABs. The Cytobot provided researchers and state public health managers with early warning of five new HAB events. This project has continued the development of the Imaging Flow Cytobot, the automated classification software, and an automated early alert system.