Spatial and biological oceanographic insights into the massive fish-killing bloom of the haptophyte Chrysochromulina leadbeateri in northern Norway.

A bloom of the fish-killing haptophyte Chrysochromulina leadbeateri in northern Norway during May and June 2019 was the most harmful algal event ever recorded in the region, causing massive mortalities of farmed salmon. Accordingly, oceanographic and biodiversity aspects of the bloom were studied in unprecedented detail, based on metabarcoding and physico-chemical and biotic factors related with the dynamics and distribution of the bloom. Light- and electron-microscopical observations of nanoplankton samples from diverse locations confirmed that C. leadbeateri was dominant in the bloom and the primary cause of associated fish mortalities. Cell counts by light microscopy and flow cytometry were obtained throughout the regional bloom within and adjacent to five fjord systems. Metabarcoding sequences of the V4 region of the 18S rRNA gene from field material collected during the bloom and a cultured isolate from offshore of Tromsøy island confirmed the species identification. Sequences from three genetic markers (18S, 28S rRNA gene and ITS region) verified the close if not identical genetic similarity to C. leadbeateri from a previous massive fish-killing bloom in 1991 in northern Norway. The distribution and cell abundance of C. leadbeateri and related Chrysochromulina species in the recent incident were tracked by integrating observations from metabarcoding sequences of the V4 region of the 18S rRNA gene. Metabarcoding revealed at least 14 distinct Chrysochromulina variants, including putative cryptic species. C. leadbeateri was by far the most abundant of these species, but with high intraspecific genetic variability. Highest cell abundance of up to 2.7 × 107 cells L - 1 of C. leadbeateri was found in Balsfjorden; the high cell densities were associated with stratification near the pycnocline (at ca. 12 m depth) within the fjord. The cell abundance of C. leadbeateri showed positive correlations with temperature, negative correlation with salinity, and a slightly positive correlation with ambient phosphate and nitrate concentrations. The spatio-temporal succession of the C. leadbeateri bloom suggests independent initiation from existing pre-bloom populations in local zones, perhaps sustained and supplemented over time by northeastward advection of the bloom from the fjords.

Imaging Technologies Build Capacity and Accessibility in Phytoplankton Species Identification Expertise for Research and Monitoring: Lessons Learned During the COVID-19 Pandemic.

As primary producers, phytoplankton play an integral role in global biogeochemical cycles through their production of oxygen and fixation of carbon. They also provide significant ecosystem services, by supporting secondary production and fisheries. Phytoplankton biomass and diversity have been identified by the Global Ocean Observing System (GOOS) as Essential Ocean Variables (EOVs), properties that need to be monitored to better understand and predict the ocean system. Phytoplankton identification and enumeration relies on the skills and expertise of highly trained taxonomic analysts. The training of new taxonomic analysts is intensive and requires months to years of supervised training before an analyst is able to independently and consistently apply identification skills to a sample. During the COVID-19 pandemic, access to laboratories was greatly restricted and social distancing requirements prevented supervised training. However, access to phytoplankton imaging technologies such as the Imaging FlowCytobot (IFCB), FlowCam, and PlanktoScope, combined with open online taxonomic identification platforms such as EcoTaxa, provided a means to continue monitoring, research, and training activities remotely when in-person activities were restricted. Although such technologies can not entirely replace microscopy, they have a great potential for supporting an expansion in taxonomic training, monitoring, surveillance, and research capacity. In this paper we highlight a set of imaging and collaboration tools and describe how they were leveraged during laboratory lockdowns to advance research and monitoring goals. Anecdotally, we found that the use of imaging tools accelerated the training of new taxonomic analysts in our phytoplankton analysis laboratory. Based on these experiences, we outline how these technologies can be used to increase capacity in taxonomic training and expertise, as well as how they can be used more broadly to expand research opportunities and capacity.

The Development and Deployment of a Programmable Water Sampling System Using an Autonomous Surface Vehicle

During January and February, 2021, SeaSatellites Inc, (Seasats) in collaboration with the Scripps Ecological Observatory at Scripps Institution of Oceanography, conducted a series of sea trials to demonstrate the capability of collecting ocean water samples using a newly developed Programmable Water Sampling System (ProWaSS) that had been integrated into a solar/battery powered 3m (9.0ft) Seasats Autonomous Surface Vehicle. During the past decade there has been a steady growth in the number of autonomous surface vehicles being deployed to conduct a variety of missions ranging in duration of only a few hours to multiple days, weeks and in some cases multiple months. For many, the idea of deploying an autonomous surface vehicle for extended periods of time, in all- weather conditions while still performing the allotted tasks is a welcomed option. Alleviating the need to go to sea for long periods and now having seen the impact of the Covid-19 pandemic curtailing crewed ship activities, the autonomous surface and subsurface vehicle option has proven invaluable. Collecting water samples for microbial and eDNA analysis is key to better understanding the health of marine ecosystems. For example, knowing the location and density of organisms capable of producing a harmful algal bloom (HAB) is critical to predicting their landfall on beaches where they impact the health and safety of humans and marine wildlife with a potential for substantial financial loss due to closure of recreational and commercial enterprises on our coasts. One way to provide an early warning of HABs landing on coastal beaches is through regular offshore water sampling at HAB initiation sites. This can sometimes be challenging due to rough seas and the unavailability or expense of vessels. The Seasats autonomous surface vehicle equipped with a Programmable Water Sampling System (ProWaSS) allows sampling to commence when other types of sampling are difficult or impossible or crewed vessels are unavailable or operationally prohibited. Trials of the ProWaSS demonstrated the ability to repeatedly collect water samples at pre-determined GPS waypoints offshore of Scripps Pier, return to the pier where the Seasats vehicle was quickly and easily recovered and the samples sent to the laboratory for analysis. This paper and presentation describe the Seasats vehicle and the ProWaSS and presents the results of the water sample analysis provided by Dr Jeff Bowman and Elizabeth Connors from the Scripps Institution of Oceanography, La Jolla, CA, and proposed further development to expand the ProWaSS to accommodate additional water samples and the inclusion of data from CTD and fluorometer sensors. © 2021 MTS.