Alaskan carbon-climate feedbacks will be weaker than inferred from short-term manipulations: Alaskan Benchmark Data and Model runs

Bouskill, Nick; Riley, William; Mekonnen, Zelalem

doi:10.15485/1670465

Title: Alaskan carbon-climate feedbacks will be weaker than inferred from short-term manipulations: Alaskan Benchmark Data and Model runs

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Abstract

This submission aimed to assess differences in short-term step warming manipulations and long-term chronic response to climate change in Alaskan ecosystems. Briefly, 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 promote a positive feedback to climate change. We show here that the tightly coupled, nonlinear nature of high-latitude ecosystems implies that short-term (< 10 year) warming experiments produce emergent ecosystem carbon stock temperature sensitivities inconsistent with emergent multi-decadal responses. We first demonstrate that a well-tested mechanistic ecosystem model accurately represents observed carbon cycle and active layer depth responses to short-term summer warming in four diverse Alaskan sites. We then show that short-term warming manipulations do not capture the non-linear, long-term dynamics of vegetation, and thereby soil organic matter, that occur in response to thermal, hydrological, and nutrient transformations belowground. Our results demonstrate significant spatial heterogeneity in multi-decadal Arctic carbon cycle trajectories and argue for more mechanistic models to improve predictive capabilities.The model used in the current study is available publicly (https://github.com/jinyun1tang/ECOSYS), and the current submission contains the python/ matlab codes for analyzing output from the model (includng a readme file to explain the codes).more »« less

Authors:

; Riley, William; Mekonnen, Zelalem

Lawrence Berkeley National Laboratory

Publication Date:: Tue Dec 01 00:00:00 EST 2020

Research Org.:: Environmental System Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE) (United States); Next-Generation Ecosystem Experiments (NGEE) Arctic

Sponsoring Org.:: U.S. DOE > Office of Science > Biological and Environmental Research (BER)

Subject:: 54 ENVIRONMENTAL SCIENCES

Keywords:: EARTH SCIENCE > BIOSPHERE > ECOLOGICAL DYNAMICS; EARTH SCIENCE > BIOSPHERE > VEGETATION; EARTH SCIENCE > AGRICULTURE > SOILS > CARBON; EARTH SCIENCE > BIOSPHERE > ECOLOGICAL DYNAMICS > ECOSYSTEM FUNCTIONS > BIOGEOCHEMICAL CYCLES; EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > WATER QUALITY/WATER CHEMISTRY > NUTRIENTS > NITROGEN; EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > WATER QUALITY/WATER CHEMISTRY > NUTRIENTS > PHOSPHOROUS

Geolocation:: 63.0,149.0|63.0,149.0|63.0,149.0|63.0,149.0|63.0,149.063.0,145.0|63.0,145.0|63.0,145.0|63.0,145.0|63.0,145.068.0,149.0|68.0,149.0|68.0,149.0|68.0,149.0|68.0,149.071.0,156.0|71.0,156.0|71.0,156.0|71.0,156.0|71.0,156.0

OSTI Identifier:: 1670465

DOI:: https://doi.org/10.15485/1670465

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                    Bouskill, Nick, Riley, William, and Mekonnen, Zelalem. Alaskan carbon-climate feedbacks will be weaker than inferred from short-term manipulations: Alaskan Benchmark Data and Model runs.  United States: N. p., 2020. 
        Web.  doi:10.15485/1670465.

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                    Bouskill, Nick, Riley, William, & Mekonnen, Zelalem. Alaskan carbon-climate feedbacks will be weaker than inferred from short-term manipulations: Alaskan Benchmark Data and Model runs.  United States.  doi:https://doi.org/10.15485/1670465

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                    Bouskill, Nick, Riley, William, and Mekonnen, Zelalem. 2020.  
"Alaskan carbon-climate feedbacks will be weaker than inferred from short-term manipulations: Alaskan Benchmark Data and Model runs".  United States.  doi:https://doi.org/10.15485/1670465.  https://www.osti.gov/servlets/purl/1670465. Pub date:Tue Dec 01 00:00:00 EST 2020

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@article{osti_1670465,

  title        = {Alaskan carbon-climate feedbacks will be weaker than inferred from short-term manipulations: Alaskan Benchmark Data and Model runs},

  author       = {Bouskill, Nick and Riley, William and Mekonnen, Zelalem},

  abstractNote = {This submission aimed to assess differences in short-term step warming manipulations and long-term chronic response to climate change in Alaskan ecosystems. Briefly, 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 promote a positive feedback to climate change. We show here that the tightly coupled, nonlinear nature of high-latitude ecosystems implies that short-term (< 10 year) warming experiments produce emergent ecosystem carbon stock temperature sensitivities inconsistent with emergent multi-decadal responses. We first demonstrate that a well-tested mechanistic ecosystem model accurately represents observed carbon cycle and active layer depth responses to short-term summer warming in four diverse Alaskan sites. We then show that short-term warming manipulations do not capture the non-linear, long-term dynamics of vegetation, and thereby soil organic matter, that occur in response to thermal, hydrological, and nutrient transformations belowground. Our results demonstrate significant spatial heterogeneity in multi-decadal Arctic carbon cycle trajectories and argue for more mechanistic models to improve predictive capabilities.The model used in the current study is available publicly (https://github.com/jinyun1tang/ECOSYS), and the current submission contains the python/ matlab codes for analyzing output from the model (includng a readme file to explain the codes). The benchmark data, also enclosed, was collected from a range of published and publicly available sources (extracted using GRABIT: https://www.mathworks.com/matlabcentral/fileexchange/7173-grabit). These sources describe warming induced changes in tundra/ boreal ecosystems.},

  doi          = {10.15485/1670465},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Tue Dec 01 00:00:00 EST 2020},

  month        = {Tue Dec 01 00:00:00 EST 2020}

}

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DOI: https://doi.org/10.15485/1670465

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