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Comparing climate change impact on Arctic tundra over different time periods2 min read

by Christina Procopiou on November 25, 2020

Climate and Ecosystem Sciences Division

Tundra ecosystem, Sarek National Park, Sweden. Ökologix, CC BY-SA 3.0, via Wikimedia Commons

Although climate change is accelerating fastest at high latitudes, it is still uncertain how the carbon cycle within Alaskan tundra soils will respond over different periods of time. Arctic soils house vast stores of carbon, and the response of these ecosystems to warming could determine how much of the greenhouse gas carbon dioxide makes it way to the atmosphere. New EESA research has shown that simulations examining short-term warming in tundra ecosystems, and evaluated against Arctic field experiments, produce responses in the carbon cycle that are inconsistent with modeled ecosystem responses to climate change occurring over decades. 

A paper published last week in the journal Nature Communications describes research led by Berkeley Lab research scientist Nick Bouskill (with co-authors Bill Riley and Zelalem Mekonnen of Berkeley Lab and Robert Grant of the University of Alberta) which found that soil carbon losses occurred at a much higher rate under short-term experimental warming than under decades of warming. The researchers used the land model ecosys to evaluate ecosystem responses to warming across four Alaskan sites over a period of a decade, and over a period of 100 years under expected temperature, precipitation, and carbon dioxide concentrations for the 21st century. 

“Climate warming is occurring fastest at high latitudes. Based on short-term field experiments, this warming is projected to stimulate soil organic matter decomposition, and to promote a positive feedback to climate change,” Bouskill said. “Because Arctic soils sequester carbon dioxide from the atmosphere, it’s essential that climate models accurately account for how various interdependent facets of the tundra ecosystem respond to climate change. Ideally climate modeling should take into account the impacts on microbial communities at different soil depths, and on vegetation growth and productivity.” 

The study results demonstrate that over many decades the rate of soil carbon cycling varies significantly across the Arctic regions evaluated. Further studies are required to improve the ability of climate models’ to predict whether Arctic tundra landscapes remain a carbon sink over multiple decades under climate change.

News & Events

Chun Chang Places Second in Annual Berkeley Lab Pitch Competition3 min read

January 18, 2023

Commercializing Berkeley Lab inventions is an important part of the Lab’s mission, and one that requires strong communication skills. For example, Lab inventors need to be able to pitch their ideas to external partners and potential funders.  The annual Berkeley Lab Pitch Competition occurred on October 27, 2022 and is a part of an entrepreneurship…

EESA Scientists Collaborate With Universities to bring Environmental Science Research Opportunities and Training to Students Underrepresented in STEM3 min read

January 13, 2023

  EESA researchers are collaborators in three of the 41 projects awarded in December by DOE through its Reaching a New Energy Sciences Workforce (RENEW) initiative.  RENEW aims to build foundations for research at institutions that have been historically underrepresented in the Office of Science (SC) research portfolio. The initiative provides opportunities for undergraduate and…

New Report Explores Revolutionary Environmental Artificial Intelligence Infrastructure5 min read

January 10, 2023

In a collaborative effort between the U.S. Department of Energy’s (DOE) Office of Biological and Environmental Research (BER) and DOE’s Advanced Scientific Computing Research (ASCR) program, as well as with community experts, the Artificial Intelligence for Earth System Predictability (AI4ESP) workshop was held from October through December 2021. BER developed the process as the Model-Experiment paradigm, or ModEx, and a report released this fall outlines the key takeaways of last year’s event.

A Q&A With Postdoc Kunxiaoja Yuan3 min read

January 4, 2023

  Kunxiaojia Yuan received her Bachelor’s of Engineering in remote sensing and Ph.D. in geographic information engineering from Wuhan University. She is a postdoctoral researcher in EESA, with a research focus on global carbon, energy, and water cycle analysis and model evaluation using machine learning and causal inference. What motivated you to pursue a postdoc…

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