NOAA PMEL, University of Washington and OptoKnowledge Systems, Inc. (OKSI) successfully conducted the first deep water test of a new methane analyzer to measure the concentration and carbon isotope ratio of methane near Axial Seamount. This new instrument can collect data that will improve scientists’ understanding of carbon cycling, greenhouse gasses, and sub-seafloor chemosynthetic reactions.

After 3 years of testing and development, the analyzer was mounted on the remotely operated vehicle Jason and coupled to PMEL’s hydrothermal fluid and particle sampler (HFS) during a recent cruise on the Research Vessel Thompson.  The methane analyzer combines a novel laser absorption spectroscopy gas sensor with a membrane-free approach to water sampling. While the research cruise had to be cut short, the team successfully was able to collect valuable data and coordinate samples for cross-calibration during one ROV dive.

While collecting data with the methane analyzer, researchers simultaneously sampled the same fluid in gas-tight samplers attached to the fluid manifold and in custom samplers that are part of the HFS. Methane concentrations analyzed onboard the R/V Thompson by gas chromatography on fluid samples from HFS piston and bag samplers agree well with the in-situ methane concentrations determined by the analyzer. 

Ultimately, the instrument worked well on the ROV and it is expected that the methane spectrometer will have many useful applications.

Learn more about this technology development and methane work on PMEL’s Earth Ocean Interactions research page. 

Instrument Development:

The methane analyzer was developed by OKSI with initial funding from the NOAA Small Business Innovation Research (SBIR) Program. The SBIR Program, also known as America’s Seed Fund, awards seed funding to U.S. small businesses to support high-risk, high-reward research and development of new technologies. In 2016, OKSI received a NOAA SBIR Phase I award to develop an instrument that could analyze underwater gasses, specifically methane and its isotopes. The company was awarded follow-on Phase II funding in 2017. 

The effort has since transformed into a Phase III collaboration with PMEL. OKSI and NOAA PMEL were funded in 2019 through a National Ocean Partnership Program (NOPP) grant with NOAA Ocean Exploration support to continue development of the methane spectrometer and deploy it in deep water. In 2021, PMEL and OKSI successfully completed shallow-water methane concentration measurements in Puget Sound. The Puget Sound test showed that the instrument can take measurements of methane concentration in-situ and report those measurements in real-time to an operator on board a ship with an update rate approximately every 6 minutes.

More About the Sensor: 

For the new spectrometer instrument, it is important to verify that the in-situ measurements agree with established discrete sampling and analysis for methane concentration and carbon isotope ratio. The PMEL hydrothermal fluid sampler, first developed in 1998, will deliver warm hydrothermal fluids from diffuse vents with elevated methane concentrations to the methane spectrometer and simultaneously take coordinated discrete samples for laboratory analysis of concentration and carbon isotope ratio to cross-calibrate the in-situ measurements from the methane sampler. Tamara Baumberger is collecting samples in specialized gas-tight samplers for carbon isotope and methane concentration analysis.

March 31, 2022: The Kuroshio Extension Observatory (KEO) moored buoy was successfully deployed by NOAA PMEL and partners, renewing an ongoing OceanSITES time series that began almost 18 years ago. First deployed in 2004, its time series was disrupted by the COVID pandemic. KEO collects vital data in the Kuroshio Extension recirculation gyre, a region known to affect the development of storms over the North Pacific before they reach the United States.

The deployment was just in time for KEO to capture the air-sea interaction process underneath an intense atmospheric river that connected the western Pacific to the east and brought stormy weather and heavy precipitation to the Pacific Northwest. 

KEO carries sensors for NOAA PMEL and partners from Japan and US academic institutions that measure surface air-sea heat and momentum fluxes, along with various oceanographic variables in the upper 525 meters and near the seafloor. New this year, the KEO-2022 mooring includes dissolved oxygen sensors, a nitrate sensor, and a testbed for new biodegradable “plastic-alternative” materials from the Japan Agency for Marine-Earth Science and Technology (JAMSTEC), the University of Washington-Applied Physics Lab’s bubble and acoustic observations, and a moored CO2 system. 

KEO will also play a critical role in the Japanese national program “Middle-latitude atmosphere-ocean interaction hotspot in a changing climate system” (HotSpot-2), as an ocean observatory by providing a reliable platform for new sensors and the long-term, large-scale context of intensive field campaign observations.

Learn more about the research part of the Ocean Climate Stations program: https://www.pmel.noaa.gov/ocs/KEO 

This work is funded by NOAA’s Global Ocean Monitoring and Observing Program to sustain in situ global ocean observations and information in support of research, monitoring, and prediction.

February 1 - March 7: NOAA PMEL scientists join NOAA Fisheries and an international team of researchers aboard the NOAA R/V Shimada to provide expertise in physical oceanography and lead hydrographic data collection, nutrient sampling, analysis and processing. EcoFOCI is taking part in the International Year of the Salmon expedition to help detect and monitor changes both within Pacific salmon and their respective ecosystems, especially in the Gulf of Alaska.  

Pacific salmon are a uniquely important resource for countries across the North Pacific yet there are major scientific gaps in our understanding of the ocean phase of the salmon life cycle. This cruise will collect vital data to improve that understanding and aid in forecasting and management of salmon. 

The expedition will include as many as five research vessels to conduct the largest ever pan-Pacific, epipelagic ecosystem survey during winter, focused on understanding salmon and their ecosystems. The 2022 Expedition will involve a full ecosystem survey with pelagic trawling and detailed sampling of marine life in the upper ocean and will include research on physical, biological and chemical oceanography. Novel technologies such as gliders, environmental DNA and genetic stock identification will be used to enhance research efforts. This collaborative international effort spanning the entire North Pacific includes scientists from Canada, Japan, the Republic of Korea, the Russian Federation, and the United States. 

The data collected by PMEL will provide key baseline and comparative data to the overall pan-Pacific collaboration focused on salmon recovery. During the expedition, PMEL will collect samples from over 30 CTD stations, deploy satellite-tracked drifters and several Argo floats, and collect carbon dioxide, nutrient and salinity measurements from an on-board flow-through system. 

The research cruise will extend from 1 February to 7 March in the central to western Gulf of Alaska. More about the expedition: https://yearofthesalmon.org/2022expedition/

Follow along with the expedition on the blog and more details online: https://www.fisheries.noaa.gov/west-coast/2022-pan-pacific-winter-high-seas-expedition 

A research team led by NOAA’s Cooperative Institute for Marine Ecosystem and Resource Studies at Oregon State University has developed an automated method that can accurately identify calls from a family of fishes.

The method takes advantage of data collected by underwater microphones known as hydrophones and provides an efficient and inexpensive way to understand changes in the marine environment due to climate change and other human-caused influences, said researchers from Oregon State’s Cooperative Institute for Marine Ecosystem and Resource Studies.

The findings were published in the journal Marine Ecology Progress Series.

Hydrophones are increasingly being deployed in the world’s oceans. They offer advantages over other types of monitoring because they work at night, in low-visibility conditions and over long periods of time. But techniques to efficiently analyze data from hydrophones are not well developed.

This new research led by Jill Munger when she was an undergraduate student, begins to change that. Munger came to Oregon State having worked more than 20 years in the corporate world. An avid scuba diver, she wanted to study the ocean. She received a fellowship from CIMERS to research underwater acoustics with Joe Haxel, who at the time was at the Hatfield Marine Science Center in Newport working with National Oceanic and Atmospheric Administration’s Pacific Marine Environmental Lab’s acoustic program.

Haxel handed her a hard drive with 18,000 hours of acoustic data collected over 39 months in a tropical reef region within the National Park of American Samoa. American Samoa is a U.S. territory in the western Pacific Ocean.

The data was collected via a 12-station hydrophone array maintained by NOAA and the National Park Service that is distributed throughout the world in water controlled by the United States. The hydrophones were designed and built by NOAA and CIMERS researchers at Hatfield Marine Science Center.

Munger decided to focus on calls from damselfish, in part, because they are distinctive. They grind their teeth to create pops, clicks and chirps associated with aggressive behavior and nest defense. She compared the sound to purring kittens. Quickly, it became apparent to her that manually listening to the recordings was not going to work.

“This is such a slow and tedious process,” she remembered thinking. “I have all this data, and I am just looking at a tiny, tiny portion of it. What’s happening in all the other parts that I haven’t had a chance to listen to?”

A conversation with her brother, Daniel Herrera, a machine learning engineer, sparked an idea. Could they use machine learning to automate the analysis of the data?

Machine learning algorithms build a model based on sample data, known as training data, to make predictions or decisions without being explicitly programmed to do so.

Machine learning techniques have been used to automate processing of large amounts of data from passive acoustic monitoring devices that collected sound data from birds, bats and marine mammals. The techniques have been used for fish calls, but it is an underdeveloped area of science, Munger said.

In this case, the machine learning sample or training data was 400 to 500 damselfish calls Munger identified by manually listening to the hydrophone recordings. With that start, Herrera, a co-author of the paper, built a machine learning model that accurately identified 94% of damselfish calls. 

“We built a machine learning model on a relatively small set of training data and then applied it to an enormous set of data,” Munger said. “The implications for monitoring the environment are huge.”

Munger, who now works in the lab of Scott Heppell, an associate professor in Oregon State’s Department of Fisheries, Wildlife, and Conservation Sciences in the College of Agricultural Sciences, believes machine learning will increasingly be used by scientists to monitor many species of fish in the ocean because it requires relatively little effort.

“The benefit to observing fish calls over a long period of time is that we can start to understand how it’s related to changing ocean conditions, which influence our nation’s living marine resources,” Munger said. “For example, damselfish call abundance can be an indicator of coral reef health.”

Munger received input from National Park Service staff on the biology of the damselfish and the reef habitats in close proximity to the hydrophone.

Other co-authors of the paper are Haxel, Heppell, and Samara Haver, all of Oregon State; Lynn Waterhouse, formerly of John G. Shedd Aquarium in Chicago; Megan McKenna, formerly of Natural Sounds and Night Skies Division, National Park Service, Fort Collins, Colorado; and Jason Gedamke and Robert Dziak of NOAA’s Office of Science and Technology, Silver Spring, Maryland, and Pacific Marine Environmental Laboratory, Newport, respectively.

The following article was written by Sean Nealon at Oregon State University and adapted for NOAA PMEL. The Oregon State University news release is available online.