Progress Report to Council Native Corporation

Introduction

We are grateful to conduct our scientific research on lands stewarded by Alaska Native Communities.

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The opportunity to conduct our scientific research on land stewarded by Alaska Native Communities has been invaluable to the NGEE Arctic team and our science. We are grateful for and thank the Council, Sitnasuak, Bering Straits, Mary’s Igloo, and UIC Science Native Corporations for allowing us to conduct research on their lands. We recently submitted a Progress Report on NGEE Arctic science to the Council Native Corporation (CNC); our research has been focused within a large watershed near mile marker 71 on the Council Road outside of Nome, Alaska. The report summarizes our scientific findings to date and explains how these findings have improved a computer model that helps to predict our future climate. We also included links to associated publications and published datasets. For example, research on CNC land by the NGEE Arctic team found that terrain, vegetation, and snowpack are key indicators of permafrost extent and characteristics; that soil physical and chemical characteristics change with soil depth; that microbial production of GHGs carbon dioxide and methane varied with soil pH, water content, and geochemistry; and that tundra plants and soils at the Council 71 study site absorb more carbon dioxide than they release but release more methane than they absorb.

Citation: Iversen CM, Bennett K, Bolton B, Dafflon B, Dengel S, Herndon B, Kumar J, Murphy B, Sulman B, Thomas L, Torn M, Yang D, and the NGEE Arctic Team. 2023. NGEE Arctic Progress Report to the Council Native Corporation

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Map of predicted groupings of plant species (i.e., PFTs) across the Council 71 study site based on airborne synthetic aperture radar (SAR) imagery and machine-learning algorithms. Image credit: Daryl Yang.

Map of predicted groupings of plant species (i.e., PFTs) across the Council 71 study site based on airborne synthetic aperture radar (SAR) imagery and machine-learning algorithms. Image credit: Daryl Yang. 

For more information, please contact:

Colleen Iversen

iversencm@ornl.gov
Project Phase(s)