Submersible robots help us better understand ocean health and carbon flows

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Floating robots could become indispensable in helping us monitor the health of ocean ecosystems and the flow of carbon between the atmosphere and oceans, according to a new study.

Although the microscopic marine plants and animals which make up plankton are the bedrock of ocean ecosystems. While they’re essential for the well-being of everything that swims, they’re also very important for our comfort and well-being, too. Plankton is one of the largest single sources of oxygen on the planet, and it consumes a lot of CO2 to do it. This process is known as marine primary productivity.

Knowing how they’re faring, then, would be a great help. Floating robots can help us out in that regard, according to a new paper.

Floats my boats

“Based on imperfect computer models, we’ve predicted primary production by marine phytoplankton will decrease in a warmer ocean, but we didn’t have a way to make global-scale measurements to verify models. Now we do,” said Monterey Bay Aquarium Research Institute (MBARI) Senior Scientist Ken Johnson, first author of the paper.

Together with former MBARI postdoctoral fellow Mariana Bif, Johnson shows how a fleet of marine robots could completely change our understanding of primary productivity on a global scale. Data from these crafts would allow researchers to more accurately model the flow of carbon between the atmosphere and the ocean, thus improving our understanding of the global carbon cycle.

Furthermore, the duo explains, shifts in phytoplankton productivity can have significant effects on all life on Earth by changing how much carbon oceans absorb, and by altering oceanic food webs. The latter can easily impact human food security, as the oceans are a prime source of food for communities all over the world. In the context of our changing climate, it’s especially important to know with accuracy how much carbon plankton can scrub out of the atmosphere, and what factors influence this quantity.

Part of what makes the ocean such a good carbon sink is that dead organic matter sinks to the bottom. Plankton grows by consuming atmospheric oxygen, and is in turn consumed by other organisms, such as fish. As these eventually die, they sink to the bottom of the sea, where they’re decomposed by bacteria, releasing carbon in the process. However, because this happens at great depths, the carbon is effectively prevented from returning to the atmosphere for very long periods of time. Generally, it seeps into deep-water sediments and stays there for millions of years or more.

That being said, this process is very sensitive to environmental factors such as changes in climate. While we understand that this happens, we’ve not been able to actually monitor how primary productivity is responding to climate change on a global scale, as most of it happens in the depths of the oceans.

“We might expect global primary productivity to change with a warming climate,” explained Johnson. “It might go up in some places, down in others, but we don’t have a good grip on how those will balance.”

“Satellites can be used to make global maps of primary productivity, but the values are based on models and aren’t direct measurements,”

Autonomous robots could help us get the data we need, the study argues. For starters, it’s much easier to build robots that can withstand the humongous pressures of the deep ocean than it is to build equivalent manned submarines. Secondly, robots are mass-producible for relatively little cost. Human crews are expensive and slow to train — they’re also quite limited in availability. Finally, robots can operate for much longer periods of time than human crews, and nobody needs to risk their life in the process.

The authors point to the deployment of Biogeochemical-Argo (BGC-Argo) floats across the globe as a great example of how robots can help monitor primary productivity. These automated floats can measure temperature, salinity, oxygen, pH, chlorophyll, and nutrient content in marine environments, at depths of up to 2,000 meters (6,600 ft). A float can perform its monitoring tasks autonomously, shifting between different depths and supplying live data to researchers onshore. These robots have been deployed in increasing numbers over the past decade, providing reliable — but as of yet, still sparse — measurements of oxygen production across the globe.

Although the data they’ve been feeding us didn’t tell us anything new, it is the first time we’ve been able to quantitatively measure primary productivity directly.

“Oxygen goes up in the day due to photosynthesis, down at night due to respiration—if you can get the daily cycle of oxygen, you have a measurement of primary productivity,” explained Johnson.

In order to confirm that these robots were actually performing their job reliably, the team compared primary productivity estimates computed from the BGC-Argo floats to ship-based sampling data in two regions: the Hawaii Ocean Time-series (HOT) Station and the Bermuda Atlantic Time-series Station (BATS). The data from these two sources matched over several years, proving the reliability of the system.

“We can’t yet say if there is change in ocean primary productivity because our time series is too short,” cautioned Bif. “But it establishes a current baseline from which we might detect future change. We hope that our estimates will be incorporated into models, including those used for satellites, to improve their performance.”

Seeing as we have drones flying about the atmosphere taking pictures of everything and anything, it only makes sense that we’d eventually have some doing the same underwater. I am personally very thrilled to see robots taking on the deepest depths. The ocean is a fascinating place, but I’m also terrified of drowning, so I’ll probably never work up the courage to actually explore it. Hopefully, our automated friends will do the work for us and help us understand what is still a very much unexplored frontier of Earth.

The paper “Constraint on net primary productivity of the global ocean by Argo oxygen measurements” has been published in the journal Nature.

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