A harmful algal bloom (HAB) pilot project in Oregon is providing officials with an early warning of a severe, recurring threat to both human health and coastal economies.NOS-funded researchers involved with the project demonstrated the vital role of regular sampling of nearshore and offshore waters for HAB species and toxins to help state officials manage recreational shellfisheries, worth $31 million to Oregon's coastal communities.
In July 2010, the pilot project forecasted rising algae cell and toxin levels nearshore, providing state officials advance warning of a coast-wide HAB event and prompting proactive shellfish testing. The prediction was verified when further testing revealed that levels of the HAB toxin domoic acid exceeded regulatory limits in razor clams. The extent of this HAB outbreak forced officials to close razor clam fisheries along roughly two-thirds of Oregon’s coast.
Then, in late August, an advance warning of a second HAB event also proved correct and the state expanded the closure to include mussels. By September, the steady stream of monitoring data provided evidence that both threats had begun to diminish. This gave officials time to safely reopen recreational shellfish harvests in October.
Prior to the pilot project, an increase or decrease of domoic acid or other HAB toxins in shellfish would have been undetected for as long as two weeks. Expanded nearshore HAB monitoring provides shellfish harvesters with greater confidence that the seafood they gather is safe and healthy. Protecting public health from HAB toxins is of highest priority to state officials, but they also recognize that closures negatively impact coastal economies. Coastal managers strive to find ways to mitigate these impacts.
"The regular HAB monitoring program is critical to us because it has given us more lead time to make decisions with greater confidence that ultimately protect public health while minimizing the economic impacts of HAB closures on our valuable recreational shellfisheries," Alex Manderson, Shellfish Specialist with the Oregon Department of Agriculture Food Safety Division.
HAB-related shellfish closures have been a public health concern in Oregon for many decades. Oregon has been testing shellfish for levels of the algal toxin saxitoxin since the 1950s. In the 1990s, domoic acid emerged as a new threat. This toxin has been monitored in Oregon shellfish since 1994 and in nearshore waters since 2005. Consuming contaminated shellfish can cause mild to severe gastrointestinal and neurological symptoms such as vomiting and short-term memory loss. It is important to note that rigorous state shellfish monitoring programs continue to ensure that legally harvested seafood is safe for human consumption. Continual monitoring provides coastal managers with the data they need to protect public health.
In addition to the vital nearshore monitoring of these algal species and HAB toxins, scientists have also been monitoring Oregon’s coastal ocean. Offshore data is another key piece in understanding ocean conditions that are conducive to the formation of toxic algae blooms. The project team integrated offshore and nearshore HAB monitoring data into a comprehensive database that includes environmental conditions, HAB species abundance, and toxin levels.
Like similar efforts in the Gulf of Maine, the project team uses this database to build models to forecast where and when a bloom will begin. The team can then generate a warning (similar to hurricane forecasts) for officials managing the communities and resources most likely to be impacted by the HAB event. The integration of offshore and nearshore HAB monitoring data for Oregon is critical to continue development of these valuable forecast models and further validate their predictions.
This project is funded through NOAA’s national Monitoring and Event Response for Harmful Algal Bloom (MERHAB) program. MERHAB funds state-academic-federal partnerships to address the growing national HAB threat by expanding the number of coastal regions benefiting from advances in algal identification, detection, modeling, and prediction