Posted in | News | Ecology

Microbial Carbon Use Efficiency is the Key Factor in Determining Soil Carbon Storage

Microbes are by far the most important factor in determining how much carbon is stored in the soil, according to a new study with implications for mitigating climate change and improving soil health for agriculture and food production.

The research is the first to measure the relative importance of microbial processes in the soil carbon cycle. The study's authors found that the role microbes play in storing carbon in the soil is at least four times more important than any other process, including decomposition of biomatter.

That's important information: Earth's soils hold three times more carbon than the atmosphere, creating a vital carbon sink in the fight against climate change.

The study, "Microbial Carbon Use Efficiency Promotes Global Soil Carbon Storage," published May 24 in Nature, describes a novel approach to better understanding soil carbon dynamics by combining a microbial computer model with data assimilation and machine learning, to analyze big data related to the carbon cycle.

The method measured microbial carbon use efficiency, which tells how much carbon was used by microbes for growth versus how much was used for metabolism. When used for growth, carbon becomes sequestered by microbes in cells and ultimately in the soil, and when used for metabolism, carbon is released as a side product in the air as carbon dioxide, where it acts as a greenhouse gas. Ultimately, growth of microbes is more important than metabolism in determining how much carbon is stored in the soil.

"This work reveals that microbial carbon use efficiency is more important than any other factor in determining soil carbon storage," said Yiqi Luo, the Liberty Hyde Bailey Professor in the School of Integrative Plant Science in the College of Agriculture and Life Sciences, and the paper's senior author.

The new insights point agricultural researchers toward studying farm management practices that may influence microbial carbon use efficiency to improve soil health, which also helps ensure greater food security. Future studies may investigate steps to increase overall soil carbon sequestration by microbes. Researchers may also study how different types of microbes and substrates (such as those high in sugars) may influence soil carbon storage.

Soil carbon dynamics have been studied for the last two centuries, but those studies were mainly concerned with how much carbon gets into the soil from leaf litter and roots, and how much is lost to the air in the form of CO2 when organic matter decomposes.​​​​​​​

"But we are the first group that can evaluate the relative importance of microbial processes versus other processes," Luo said.

In an example of cutting-edge digital agriculture, Luo and colleagues made a breakthrough and developed a method to integrate big data into an earth system computer model by using data assimilation and machine learning.

The model revealed that overall carbon use efficiency of microbe colonies was at least four times as important as any of the other components that were evaluated, including decomposition and carbon inputs.

The new process-based model, machine learning approach, which made this result possible for the first time, opens the possibility for applying the method to analyze other types of big data sets.

Feng Tao, a researcher at Tsinghua University, Beijing, is the paper's first author. Xiaomeng Huang, a professor at Tsinghua University, is a corresponding author, along with Luo. Benjamin Houlton, the Ronald P. Lynch Dean of CALS and professor in the departments of Ecology and Evolutionary Biology and of Global Development; and Johannes Lehmann, the Liberty Hyde Bailey Professor in the Soil and Crop Sciences Section of the School of Integrative Plant Science in CALS, are both co-authors.

The study was funded by the National Science Foundation, the National Key Research and Development Program of China and the National Natural Science Foundation of China, among others.

Tell Us What You Think

Do you have a review, update or anything you would like to add to this news story?

Leave your feedback
Your comment type

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.