Scientists can predict carbon transfer in the ocean based on deep-diving tiny organisms
Micro-scale model dynamics. a) Illustration showing micro-scale model dynamics occurring on sinking particles. Primary degraders (red microbes) convert polymeric organic matter (dark blue sphere) into low molecular weight organic matter (LMWOM, light blue) using extracellular enzymes (yellow). The particle-associated community experiences loss due to mortality (gray microbes) and detachment (purple microbes). b) Illustration of water column model dynamics with an emphasis on a single particle (blue sphere) falling through the water column. Each particle is stochastically assigned an initial radius, lability, and set of biological parameter values at the depth of formation (see Methods). The particle-associated microbial dynamics then evolve prognostically for each particle as it sinks through the water column and is consumed by microbial activity. The total particulate organic carbon flux throughout the water column is obtained by summing across all sinking particles. Credit: Nature Communications (2022). DOI: 10.1038/s41467-022-29297-2

The ocean's surface has a big job for the microbes that hitch onto particles. They transfer carbon to the deepest waters of the ocean by riding along until they reach the bottom. The journey can take weeks to months, though estimating the rate has been a challenge.

A USC-led team of international scientists has found that the speed of this carbon transfer is influenced by the size and type ofbacteria that latched onto the particles. Researchers have been able to develop a computer model for estimating carbon transfer, a part of the Earth's natural carbon cycle, in oceans across the globe.

Naomi Levine, an assistant professor of biological sciences, said that the discovery sheds more light on how carbon moves from the atmosphere into the ocean.

Knowing the carbon transfer rate could help scientists better understand how well the Earth is retaining carbon in the deepest parts of its oceans.

This is the first time that we have been able to model ocean-scale carbon-cycle dynamics that account for micro-scale processes that have been observed in the lab.

Scientists are interested in understanding their colonies and survivability because of the large role that microbes play in transferring carbon. Carbon falls deeper into the ocean without them. Levine said that this impacts how much CO 2 stays in the atmosphere.

Some like it hot.

The ocean stores up to 16 times the amount of carbon found in the Earth. Carbon dioxide ends up in the ocean. It drives up ocean surface temperatures and is essential for some life. Increasing CO 2 makes the water more acidic, which can threaten the survival of some organisms in the ocean.

The research team found that the rate of carbon sinking in the ocean and the depth at which the transfer occurs depends on how far down thebacteria travel. The deep ocean is more than 1,000 meters from the surface, and for somebacteria it is a short trip. The potential for carbon to stay in the ocean and return to the atmosphere is raised by healthy colonies ofbacteria.

There is a lot of mortality with thesebacteria. The rate at which they can break these particles down is affected by that.

Scientists can adjust the model to better predict a local rate of carbon transfer or release depending on whether thebacteria are thriving or not.

Levine worked with researchers at the Massachusetts Institute of Technology.

More information: Trang T. H. Nguyen et al, Microbes contribute to setting the ocean carbon flux by altering the fate of sinking particulates, Nature Communications (2022). DOI: 10.1038/s41467-022-29297-2 Journal information: Nature Communications Citation: Scientists can predict carbon transfer in the ocean based on deep-diving tiny organisms (2022, March 31) retrieved 31 March 2022 from https://phys.org/news/2022-03-scientists-carbon-ocean-based-deep-diving.html This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no part may be reproduced without the written permission. The content is provided for information purposes only.