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Probability-based accounting for carbon in forests to consider wildfire and other stochastic events: synchronizing science, policy, and carbon offsets

Author

Listed:
  • Thomas Buchholz

    (University of Vermont
    Spatial Informatics Group LLC (SIG))

  • John Gunn

    (University of New Hampshire
    Spatial Informatics Group—Natural Assets Laboratory (SIG-NAL))

  • Bruce Springsteen

    (Placer County Air Pollution Control District)

  • Gregg Marland

    (Appalachian State University)

  • Max Moritz

    (Berkeley University of California)

  • David Saah

    (Spatial Informatics Group LLC (SIG)
    University of San Francisco)

Abstract

Forest carbon offset protocols reward measurable carbon stocks to adhere to accepted greenhouse gas (GHG) accounting principles. This focus on measurable stocks threatens permanence and shifts project-level risks from natural disturbances to an offset registry’s buffer pool. This creates bias towards current GHG benefits, where greater but potentially high-risk stocks are incentivized vs. medium-term to long-term benefits of reduced but more stable stocks. We propose a probability-based accounting framework that allows for more complete risk accounting for forest carbon while still adhering to International Organization for Standardization (ISO) GHG accounting principles. We identify structural obstacles to endorsement of probability-based accounting in current carbon offset protocols and demonstrate through a case study how to overcome these obstacles without violating ISO GHG principles. The case study is the use of forest restoration treatments in fire-adapted forests that stabilize forest carbon and potentially avoid future wildfire emissions. Under current carbon offset protocols, these treatments are excluded since carbon stocks are lowered initially. This limitation is not per se required by ISO’s GHG accounting principles. We outline how real, permanent, and verifiable GHG benefits can be accounted for through a probability-based framework that lowers stressors on a registry’s buffer pool.

Suggested Citation

  • Thomas Buchholz & John Gunn & Bruce Springsteen & Gregg Marland & Max Moritz & David Saah, 2022. "Probability-based accounting for carbon in forests to consider wildfire and other stochastic events: synchronizing science, policy, and carbon offsets," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 27(1), pages 1-21, January.
  • Handle: RePEc:spr:masfgc:v:27:y:2022:i:1:d:10.1007_s11027-021-09983-0
    DOI: 10.1007/s11027-021-09983-0
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    References listed on IDEAS

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