MERHAB 2019: Project Summaries
Institutions: Sitka Tribe of Alaska, NOAA, NCCOS Charleston, NWFSC Seattle, Washington Sea Grant
Investigators: Chris Whitehead (lead), Kari Lanphier, Steve Morton, Tod Leighfield, Vera Trainer, Brian Bill, Teri King
The Sitka Tribe of Alaska (STA), founder of Southeast Alaska Tribal Ocean Research (SEATOR), has a vested interest in protecting traditional natural resources and the health of local communities. SEATOR was formed in 2013 to unify Alaska tribes in monitoring harmful algal bloom (HAB) events that pose a health risk to subsistence, recreational, and commercial shellfish harvesters. SEATOR partners include 16 communities between Kodiak, Yakutat, and Metlakatla. Partners collect weekly phytoplankton and shellfish samples at over 52 monitoring sites and have been trained to identify the three main HAB genera in Alaska, including Alexandrium (paralytic shellfish toxins), Pseudo-nitzschia (domoic acid), and Dinophysis (okadaic acid). The Sitka Tribe of Alaska Environmental Research Laboratory (STAERL) uses the receptor binding assay (AOAC Method 2011.27) to determine paralytic shellfish toxin (PST) levels in samples collected by SEATOR partners. STAERL analyzes over 800 shellfish tissue samples each year for PSTs. While Alexandrium HABs and PSTs have long been the primary health risks to shellfish harvesters, domoic acid (DA) and diarrhetic shellfish poisoning (DSP) toxins are emerging as significant new concerns. Based on the observations from phytoplankton monitoring, the goal of the project is to promote shellfish safety in Alaska by also testing samples for ASP and DSP toxins. This project will allow STAERL to build capacity to 1. establish a baseline of DA and DSP toxin values throughout the region, and 2. to transfer the validated technologies to management labs. DSP analyses would use a two-tier approach. STAERL will estimate overall toxicity using a phosphatase inhibition assay in the Sitka laboratory, and NOAA’s Northwest Fisheries Science Center lab (Seattle) will validate the results. All positive samples will be confirmed and analyzed to quantify DSP toxin analogues using Liquid Chromatography Mass Spectroscopy (LC-MS) method at the National Centers for Coastal Ocean Science (NCCOS)
Charleston lab using the recently approved Interstate Shellfish Sanitation Conference (ISSC) LCMS method for DSP. Annual workshops will be held to train Tribal government environmental managers, state resource managers, university staff and students, shellfish industry representatives, community members, and federal entities. This project will also improve SEATOR’s current database and map interface tool (http://www.seator.org/data) which is used by local, regional, and state health departments to develop accurate and specific outreach material and public service announcements to warn shellfish harvesters before, during, and after a HAB event.
Institutions: Bowling Green State University, NOAA, NCCOS, MBio Diagnostics, University of Toledo, LimnoTech, The Ohio State University Stone Laboratory, University of Michigan Cooperative Institute for Great Lakes Research
Investigators: Timothy Davis (lead), Gregory Doucette, Sarah Bickman, Thomas Bridgeman, Ed Verhamme, Justin Chaffin, Thomas Johengen
Collaborators: Steve Morton, John Bratton, Todd Redder, Greg Cutrell, Michael Lochhead
Toxic cyanobacterial harmful algal blooms (CHABs) contribute to economic losses that exceed $2B annually in the U.S. For Lake Erie, the smallest and shallowest of the Laurentian Great Lakes, estimated annual economic losses of $65-71M have been reported for the western basin due to CHABs and this is likely an underestimate because it does not account for the millions of dollars lost due to events like the 2014 Toledo water crisis. Currently, we cannot forecast changes in cyanotoxins, such as microcystins (MC), the most ubiquitous cyanotoxin in the Great Lakes and throughout the world, as well as emerging cyanotoxins of concern for the northeast USA, such as
cylindrospermopsins (CYN). As such, rapid detection technologies and improved monitoring strategies will be crucial in protecting humans from exposure to contaminated drinking and recreational waters in western Lake Erie and other similarly affected water bodies. The primary objective of this MERHAB project is to fully validate and integrate a rapid, portable, quantitative, multiplexed cyanotoxin detection technology into routine monitoring programs, citizen science groups, recreational beach management, and water treatment plants throughout the western Lake Erie to provide water managers with on-the-spot testing of MC and CYN.
For this proposal, a commercially-available MC/CYN HAB Toxin Detection System has been developed by industrial partner, MBio Diagnostics, Inc., for a rapid detection of MC as well as CYN. To fully validate the MBio MC/CYN HAB Toxin Detection System, four programs, University of Michigan Cooperative Institute for Great Lakes Research, University of Toledo, The Ohio State University (OSU), and Bowling Green State University, will incorporate the MC/CYN HAB Toxin Detection System into their routine CHAB monitoring programs. Furthermore, the MC/CYN HAB Toxin Detection System will be evaluated by Toledo and Port Clinton water treatment plant operators. This technology will also be assessed by NOAA’s Phytoplankton Monitoring Network for western Lake Erie and the Lake Erie charter boat captain citizen science initiative that OSU has been leading since 2013. Lastly, Maumee Bay State Park beach managers will integrate the MC/CYN HAB Toxin Detection System into their routine beach monitoring program. These coordinated, concurrent validation efforts will provide robust data to not only validate the MBio instrument against a recognized ‘gold standard’ method, but also to assess the ease of use for water management professionals and citizen scientist organizations. Moreover, to understand how various MC congener ratios may affect the accuracy of the instrument, a subset of field samples will be analyzed using LC-MS/MS. This comparison will provide critical assessment of the MBio instrument’s range of sensitivity for the most common MC congeners.
Finally, a data management system will be developed to provide an easy method for the aforementioned monitoring groups to upload their data through a user-friendly smartphone ‘app’ to a common database system and ultimately to an end-user website, providing a centralized location accessible by other researchers, water plant managers, and the general public.
Institutions: Stony Brook University, University of California at Santa Cruz
Investigators: Christopher J. Gobler (lead), Raphe Kudela (co-lead)
Toxins from harmful cyanobacterial blooms such as microcystin are a threat to the health of animals and humans. There are now data demonstrating that microcystins associated blooms of Microcystis accumulate in shellfish in CA, WA, LA, VA, and NY at concentrations exceeding guidance levels set by some states for food and beyond the estimated tolerable daily intake rate set by US EPA. These results and recent research has demonstrated that microcystin is transported to estuarine and coastal regions where it can bioaccumulate in shellfish, subsequently entering food webs and even causing death in bivalve-consuming marine mammals. Bivalves represent a $2B fishery in the US and oysters, which had high levels of microcystin in NY, are the most valuable US aquacultured shellfish and the second most valuable commercial shellfishery. As organisms that thrive within brackish zones of estuaries, the large majority of US oysters inhabit regions downstream from freshwater bodies that are increasingly prone to microcystin-producing cyanobacterial blooms. Unfortunately, the scope of microcystin contamination of estuarine bivalves is unclear, as are the optimal methods for monitoring and predicting levels of microcystins in bivalves. To address these critical knowledge gaps, the overarching objective of this MERHAB project is to combine and compare traditional and novel microcystin monitoring approaches with bivalve and water column monitoring approaches to assess their collective suitability in detecting and predicting microcystin concentrations within estuarine bivalves. To identify technologies most predictive of microcystin contamination of bivalves, time series sampling across freshwater-to-marine continuums within multiple estuarine ecosystems will be established on the US east and west coasts. For each time series, concentrations of microcystins in bivalves will be measured using liquid chromatograph mass spectrometry (LCMS) and these values will be compared to the newly available Abraxis ELISA for microcystins in bivalves (‘DM’ kit with modified extraction). In tandem, Solid Phase Adsorption Toxin Tracking (SPATT) devices will be deployed and sampled at varying distances between bivalve collection sites and freshwater tributaries suspected of delivering microcystins to each estuarine region. Along the same transects, a suite of water column-based measurements will be made to assess their value in predicting microcystin accumulation in bivalves including microcystins measured by LCMS, ELISA, and new Mbio rapid biosensors, nutrient levels, temperature, salinity, pH, alkalinity, total phytoplankton and total cyanobacteria by a BBE Fluoroprobe and via microscopy, and cyanobacteria potentially producing microcystin by quantitative PCR using Phytoxigene CyanoDTec kits. Rates of microcystin accumulation and depuration will be quantified and statistical models will be developed to identify the environmental factors that forecast and are most predictive of microcystin accumulation in bivalves. An added benefit of this project will be an assessment of new technologies for quantifying or predicting microcystin concentrations in water and bivalves. Our collaborations with federal, state, and local agencies and bivalve farms will facilitate the transitioning of successful approaches to end users. Management-relevant actions of this project will include webinars, fact sheets, presentations of the major findings, and recommendations of this project, as well as training regulatory agencies and bivalve growers in the use of the most effective technologies assessed during this project.
Institutions: University of Washington-Tacoma, University of Alaska Fairbanks, Alaska Sea Grant, NOAA Beaufort Laboratory
Investigators: Cheryl Greengrove (lead), Julie Masura (co-lead), Julie Matweyou (co-lead), Steve Kibler (co-lead)
NOAA is developing Alexandrium bloom forecast products through the HAB Operational Forecasting System to mitigate human health risks and economic effects of shellfish closures during seasonal blooms of Alexandrium catenella in U.S. Atlantic northeast and Pacific northwest states. Forecasting efforts hinge on determination of wintertime abundance of Alexandrium resting cysts in the sediment at bloom locations. The current protocol for cyst enumeration by fluorescent microscopy is laborious, requires highly specific training, and has some uncertainty about the identity of A. catenella resting cysts and their vitality. There is need to streamline cyst quantification to shorten the turnaround time in advance of the spring bloom season. This project will evaluate new quantitative PCR (qPCR) and fluorescent in situ hybridization (FISH) assays for A. catenella cysts using sediment samples from the Gulf of Maine, Puget Sound and Alaska (Kodiak & Kachemak Bay).
The objectives are to build on the species specific PCR assay for A. catenella developed previously by the project team (Vandersea et al. 2017, 2018) to create quantitative molecular assays (PCR and FISH) for quantification of A. catenella resting cysts in sediment samples. The assays will be designed using 2018 samples previously collected from the three locations, and then direct comparison of microscopy-based and molecular-based cyst abundance data will be completed using sediment samples collected after the 2019 and 2020 summer bloom seasons.
Samples collected as part of a collaborative ECOHAB-funded project in southeast Alaska will be added to make the comparison more robust. The new molecular tools will provide cyst abundance data to NOAA’s HAB Operational Forecasting System more quickly, and with less cost than is possible with current microscopy-based counting methods. After validation, the new methods will be shared with other HAB researchers, monitoring organizations and stakeholders in NOAA, the Gulf of Maine, the State of Washington, the temperate Pacific U.S. coast, Alaska and Canada though public presentations, publications, and a training workshop at the 2021 U.S. National HAB Meeting.
Institutions: University of Washington Applied Physics Laboratory, NWFSC, MBARI, CCEHBR, McLane Laboratories, Quileute Natural Resources, NANOOS, OCNMS
Investigators: J. Mickett, S. Moore, N. Adams, J. Birch, G. Doucette, I. Engstrom, J. Hagen, N. Michel-Hart, J. Newton, V. Trainer, J. Waddell
In the Pacific Northwest (PNW), blooms of Pseudo-nitzschia that produce domoic acid (DA) are both a significant human health threat and costly to coastal communities. They have caused prolonged closures of the commercial, subsistence and recreational razor clam fisheries and at times devastated the commercial Dungeness crab fishery, resulting in millions of dollars in lost expenditures and federal fisheries disaster declarations. To assess the risk of DA events and better plan for productive fishing seasons, managers enhance their toolbox with forecasts provided by the PNW Harmful Algal Bloom (HAB) Bulletin. Toxic HABs in this region typically develop offshore; however, the remoteness of the PNW coast and its frequent rough weather conditions make vessel-based offshore monitoring of toxic Pseudo-nitzschia cells challenging and uncertain. This lack of available offshore information can limit both early warning efforts and resource managers’ response to HAB events. The Environmental Sample Processor (ESP) is a powerful technological advancement that enables offshore HAB surveillance without requiring onsite human activity. The ESP autonomously concentrates cells from seawater, applies molecular probes to identify harmful algae and their toxins, and transmits the results to shore so that they can be relayed to end-users in near real-time. The ESP underwent three years of field operations at a site located ~15 miles off the Washington State coast within the flow path of an offshore HAB initiation site and coastal communities, providing data that increased the confidence of HAB forecasts. Building on prior IOOS, MERHAB, ECOHAB and PCMHAB investments, this 5-year targeted MERHAB project will implement a series of essential, mission-enhancing, and cost-saving engineering upgrades to the ESP mooring system to enable more frequent, regular, and reliable offshore monitoring of DA in the PNW. Specific objectives are to: 1) develop a reliable, full-time, two-way communications subsystem for the ESP; 2) resume regular deployments of a real-time ESP mooring system on the Washington shelf; 3) extend the duration of ESP deployments by 50%; 4) increase ESP sample capacity by 50%; and 5) integrate ESP data into forecasting and management products. Significantly, this effort will culminate in uninterrupted ESP deployments from spring to fall (the prime HAB season), with a mid-summer instrument swap, providing near real-time data on DA levels offshore at ~2-day intervals. Efforts will include integrating a satellite modem to back-up the existing cellular modem, reducing biofouling by redesigning key components of the external pump subsystem, reducing power usage through firmware upgrades, and increasing power capacity by adding a third battery pack. Sampling capacity will be increased by modifying the existing ESPs to use lower-profile reaction chambers. The NANOOS “Real-time HABs” website that has previously been used to disseminate ESP observations will be refined through purposeful engagement with end-users, and ESP observations will be seamlessly integrated into the PNW HAB Bulletin. Additionally, new outreach products will be developed to enhance event response, such as alerts sent to a comprehensive distribution list of stakeholders and flow-trajectory predictions provided by the UW Modeling Group.
Institutions: Woods Hole Oceanographic Institution (WHOI), Bowdoin College, Florida Fish and Wildlife Commission, NOAA National Ocean Service, Northeastern Regional Association of Coastal Ocean Observing Systems (NERACOOS), NOAA National Centers for Coastal Ocean Science (NCCOS)
Investigators: Michael Brosnahan (lead), Donald M. Anderson, Mindy Richlen, Bruce Keafer, Collin Roesler, Kate Hubbard, Greg Doucette, J. Ru Morrison, Rick Stumpf, Yizhen Li
Until 2016, the single dominant harmful algal bloom (HAB) threat to New England coastal waters was the dinoflagellate Alexandrium catenella, a species that causes paralytic shellfish poisoning (PSP). This has changed dramatically with the emergence of amnesic shellfish poisoning (ASP) and diarrhetic shellfish poisoning (DSP) syndromes, caused by blooms of Pseudo-nitzschia spp. and Dinophysis spp., respectively, as well as other fin- and shellfish killing species that don’t threaten human health but negatively impact the aquaculture, fishing, and tourism industries. Managers continue to implement rigorous seasonal PSP monitoring but have struggled to develop effective monitoring and decision-making approaches for multiple new threats that span all seasons. This project will create HABON-NE (HAB Observing Network - New England), a framework for aligned academic, industry, state, and federal scientists to deploy - adaptively and continually - a fleet of advanced sensors and sensor platforms. The project would dramatically improve HAB surveillance, help direct state biotoxin testing, and support resource management decision-making. A multi-institutional team of scientists will oversee year-round deployments of sensors and sensor platforms, relocating assets as necessary to meet changing seasonal threats and respond to unexpected ones. Data and analytical products will be shared as they are created through the WHOI HAB Hub (WHHub), an open source, containerized webserver platform for region-scale integration and sharing of rich and diversely sourced HAB observations, model outputs, contextual data, and management actions. The project will also implement and extend a toxicity model that translates high frequency, in situ estimates of cell concentrations into estimates of PSP toxin loads in shellfish. This will include real-time reporting of toxicity estimates derived from sensor data as well as from the output of an existing NOAA forecast model of A. catenella cell concentrations in the Gulf of Maine.
Whenever possible, toxin estimates will be reported with comparisons to state-reported levels at nearby shellfish monitoring stations. The WHHub will enable comparison of diverse data and model estimates from specific areas, time periods, and/or times of year. Resource managers and stakeholders will be engaged throughout the project to share observations, new capabilities, and to solicit input on upcoming deployments, event response actions, and WHHub development. At the project’s conclusion, the webserver, phytoplankton image libraries, classifiers and training sets, and data analysis pipelines will be shared via open source code and data repositories. Transfer of WHHub operation to the Northeast Regional Association for Ocean Observing Systems (NERACOOS) will also be explored and used as a mechanism for documenting code and sharing broadly with researchers and resource managers nationwide.
Institutions: Bigelow Laboratory for Ocean Sciences, Maine Department of Marine Resources
Investigators: Stephen D. Archer, Nicholas R. Record, J. Kohl Kanwit, Jill E. MacLeod
Paralytic shellfish toxins (PSTs) produced by several species of phytoplankton, accumulate in shellfish and present a potentially lethal threat to consumers. Each year extensive blooms of the PST-producing organism, Alexandrium catenella, occur in the Gulf of Maine. The Maine Department of Marine Resources (Maine DMR), New Hampshire Department of Environmental Services and Massachusetts Division of Marine Fisheries use considerable resources to conduct rigorous monitoring programs to ensure the safety of shellfish consumers and support shellfish producers. The shellfish aquaculture and harvesting industries, vital components of a sustainable waterfront economy, are severely disrupted by the dangerous levels of PST-accumulation and requisite closure to harvesting along large stretches of the coast each summer. In March of 2018 there was a NOAA Gulf of Maine Regional HAB Stakeholders Meeting. The goal of the meeting was to review the status of predictions of PST in shellfish. During the meeting it became clear that more targeted forecasts that addressed the development and decline of shellfish toxicity may be of considerable value. In particular, forecasts for individual regions and bays were of interest with predictive timescales ranging from days to several weeks ahead of time. To address this requirement, we developed a machine learning-based forecast capability.
This mathematical approach uses the large dataset generated by the analysis of shellfish as part of the monitoring process carried out in Maine. Maine DMR in close collaboration with Bigelow Laboratory, are the first and only state to introduce a chemical analytical approach, using high performance liquid chromatography (HPLC), for the analysis of PST in shellfish. This replaces the mouse bioassay and has the benefits of being more sensitive and providing information on concentrations of the twelve individual compounds that make up total PST levels. The relative composition of these compounds varies seasonally and geographically. By training the neural network analysis using HPLC-acquired data from 2014 to 2016 and testing it on data from 2017, we have been able to demonstrate very accurate (>95%) forecasts of the PST-levels at individual locations one to two weeks in advance.
Our objectives build on the machine learning predictive capacity by incorporating the forecast as a product of the routine shellfish PST monitoring programs in the Gulf of Maine. This will involve developing an automated data pipeline that takes the HPLC-based PST-toxicity analysis and generates a machine learning-based PST forecast for 30+ specific locations along the Maine coastline. The information for each location, including PST-levels in previous years and the PST forecast, will be communicated via a web-based platform and via customized written reports to end-users. Over the course of the 3-year project, the value of the forecast and communication tools will be refined through a process of thorough testing in real-life applications by the state regulatory managers at Maine DMR and by the shellfish industry, specifically shellfish producers and wholesalers. The project will also explore the value to regulatory bodies of extending the Gulf of Maine coastal forecast to New Hampshire and Massachusetts coastlines by initiating development of the relevant datasets and testing forecast accuracy.
Institutions: University of California Santa Cruz, Northwest Indian College, Central Valley Regional Water Quality Control Board, SCCOOS, CeNCOOS, Lummi Nation
Investigators: Raphael M. Kudela (lead), Melissa Peacock (co-lead), Meredith Howard, Clarissa Anderson, Henry Ruhl, Ben Starkhouse
HABs have emerged as an increasing threat to California Current ecosystem health, with frequent and widespread impacts to both wildlife and humans through direct toxicity, economic loss to fisheries, artisanal harvesting, recreation, and monitoring. While attention has focused on the “traditional” HAB events caused by Pseudo-nitzschia and Alexandrium, there is increasing recognition that the west coast is not immune to numerous other HAB issues. Surveys of wide swaths of California have highlighted the co-occurrence of multiple (order 12) toxin groups but these are severely under-reported threats driven by interactions at the land-sea interface where freshwater and marine toxins mix. A fundamental requirement for monitoring and management of these issues is to develop a more holistic approach to understanding and predicting, i.e. not treating each HAB as an ecologically unique issue. Solid Phase Adsorption Toxin Tracking (SPATT) could be leveraged to address the science/management gap regarding the simultaneous occurrence of multiple toxins. SPATT is well-supported by previous MERHAB and ECOHAB projects and has been widely adopted by agencies and organizations in California and Washington. There are still fundamental issues, including (1) the focus by most researchers and agencies on single-toxin data sets, and (2) the difficulty in standardizing SPATT toxin values. This proposed 5-year effort provides (a) an evaluation of modified SPATT under laboratory and field conditions; (b) development and comparison of methods for analysis of multiple toxins from the same SPATT; (c) analysis of historical SPATT extracts and continuation of existing time-series; (d) development of statistical models linking (multi)toxin data from SPATT to environmental conditions. Years 4-5 will continue the multi-year SPATT times-series, focusing on Monterey Bay, San Francisco Bay, CA, and Bellingham Bay, WA, with the full 5 years of data used to identify environmental drivers of toxicity and trophic transfer. Outcomes include:
- Characterization of multiple toxins, providing quantifiable results comparable to grab samples;
- Development of a 10+ year time-series for Monterey Bay, San Francisco Bay, and Bellingham Bay, leading to multivariate statistical analysis of environmental drivers;
- Addition of SPATT to existing databases, and two community workshops to facilitate uptake and standardization of SPATT within existing monitoring programs.