Reduced arctic tundra productivity linked with landform and climate change interactions

Lara, Mark J.; Nitze, Ingmar; Grosse, Guido; Martin, Philip; McGuire, A. David

doi:10.1038/s41598-018-20692-8

Title: Reduced arctic tundra productivity linked with landform and climate change interactions

Journal Article · Mon Feb 05 00:00:00 EST 2018 · Scientific Reports

DOI:https://doi.org/10.1038/s41598-018-20692-8· OSTI ID:1624379

Lara, Mark J. ^[1]; Nitze, Ingmar ^[2];

^[2]; Martin, Philip ^[3]; McGuire, A. David ^[4]

Univ. of Illinois at Urbana-Champaign, IL (United States). Dept. of Plant Biology; Univ. of Alaska, Fairbanks, AK (United States). Inst. of Arctic Biology
Alfred Wegener Inst. for Polar and Marine Research, Potsdam (Germany); Univ. of Potsdam (Germany). Inst. of Earth and Environmental Science
US Fish and Wildlife Service, Fairbanks, AK (United States)
Univ. of Alaska, Fairbanks, AK (United States). US Fish and Wildlife Research Unit. Alaska Cooperative Fish and Wildlife Research Unit.

Arctic tundra ecosystems have experienced unprecedented change associated with climate warming over recent decades. Across the Pan-Arctic, vegetation productivity and surface greenness have trended positively over the period of satellite observation. However, since 2011 these trends have slowed considerably, showing signs of browning in many regions. It is unclear what factors are driving this change and which regions/landforms will be most sensitive to future browning. Here we provide evidence linking decadal patterns in arctic greening and browning with regional climate change and local permafrost-driven landscape heterogeneity. We analyzed the spatial variability of decadal-scale trends in surface greenness across the Arctic Coastal Plain of northern Alaska (~60,000km²) using the Landsat archive (1999–2014), in combination with novel 30m classifications of polygonal tundra and regional watersheds, finding landscape heterogeneity and regional climate change to be the most important factors controlling historical greenness trends. Browning was linked to increased temperature and precipitation, with the exception of young landforms (developed following lake drainage), which will likely continue to green. Spatiotemporal model forecasting suggests carbon uptake potential to be reduced in response to warmer and/or wetter climatic conditions, potentially increasing the net loss of carbon to the atmosphere, at a greater degree than previously expected.

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Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). NGEE-Arctic

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 1624379

Journal Information:: Scientific Reports, Vol. 8, Issue 1; ISSN 2045-2322

Publisher:: Nature Publishing GroupCopyright Statement

Country of Publication:: United States

Language:: English

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Vulnerability and resilience of the carbon exchange of a subarctic peatland to an extreme winter event Parmentier, Frans-Jan W.; Rasse, Daniel P.; Lund, Magnus Environmental Research Letters, Vol. 13, Issue 6 https://doi.org/10.1088/1748-9326/aabff3	journal	June 2018
Is arctic greening consistent with the ecology of tundra? Lessons from an ecologically informed mass balance model Rocha, A. V.; Blakely, B.; Jiang, Y. Environmental Research Letters, Vol. 13, Issue 12 https://doi.org/10.1088/1748-9326/aaeb50	journal	December 2018
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Water as a resource, stress and disturbance shaping tundra vegetation Kemppinen, Julia; Niittynen, Pekka; Aalto, Juha Oikos, Vol. 128, Issue 6 https://doi.org/10.1111/oik.05764	journal	January 2019
Regional Patterns and Asynchronous Onset of Ice-Wedge Degradation since the Mid-20th Century in Arctic Alaska Frost, Gerald; Christopherson, Tracy; Jorgenson, M. Remote Sensing, Vol. 10, Issue 8 https://doi.org/10.3390/rs10081312	journal	August 2018
Model Simulation and Prediction of Decadal Mountain Permafrost Distribution Based on Remote Sensing Data in the Qilian Mountains from the 1990s to the 2040s Zhao, Shangmin; Zhang, Shifang; Cheng, Weiming Remote Sensing, Vol. 11, Issue 2 https://doi.org/10.3390/rs11020183	journal	January 2019
Patterns of Arctic Tundra Greenness Based on Spatially Downscaled Solar-Induced Fluorescence Fu, Dongjie; Su, Fenzhen; Wang, Juan Remote Sensing, Vol. 11, Issue 12 https://doi.org/10.3390/rs11121460	journal	June 2019
Tundra landform and vegetation productivity trend maps for the Arctic Coastal Plain of northern Alaska Lara, Mark J.; Nitze, Ingmar; Große, Guido Universität Potsdam https://doi.org/10.25932/publishup-45987	text	January 2020
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