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

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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.

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Notes

  1. The CAL FIRE wildfire risk map (CAL FIRE 2016) suggests a 0.41% average annual wildfire probability for the Northern Sierra Nevada, northern coastal range, and Klamath Mountains, where all California-based IFM projects are located (CARB 2020a). This wildfire risk map and the approach to use a pixel-average as a fireshed-wide annual wildfire probability are widely considered conservative since a pixel-based average might underestimate a fireshed-wide fire risk. A more realistic alternative to fireshed-wide fire risk quantification could be to use the 75th percentile value or the product of the pixel values.

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Acknowledgements

This paper was a direct outcome of the 2015-2019 project: Quantifying ecosystem service benefits of reduced occurrence of significant wildfires. We are grateful for technical feedback from Scott Stephens, John Battles, and Matthew Hurteau on the scientific foundations of the AWE carbon offset methodology. Carmen Tubbesing shared her knowledge on delayed reforestation following high-severity wildfires. Stephen Eubanks and Tad Mason provided valuable inputs on forest restoration treatments and wood products. Shannon Harroun (PCAPCD) reviewed this manuscript for clarity and language.

Funding

Funds were provided by Sierra Pacific Industries, US Forest Service, CAL FIRE, Sacramento Municipal Utility District, Placer County Air Pollution Control District (PCAPCD) and The Coalition of the Upper South Platte (CUSP).

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Authors and Affiliations

  1. Gund Institute for Ecology, University of Vermont, Burlington, VT, USA

    Thomas Buchholz

  2. Spatial Informatics Group LLC (SIG), Pleasanton, CA, USA

    Thomas Buchholz & David Saah

  3. University of New Hampshire, Durham, NH, USA

    John Gunn

  4. Spatial Informatics Group—Natural Assets Laboratory (SIG-NAL), Cumberland, MA, USA

    John Gunn

  5. Placer County Air Pollution Control District, Auburn, CA, USA

    Bruce Springsteen

  6. Department of Geological and Environmental Sciences, Appalachian State University, Boone, NC, USA

    Gregg Marland

  7. Department of Environmental Science, Policy and Management, College of Natural Resources, Berkeley University of California, Berkeley, CA, USA

    Max Moritz

  8. University of San Francisco, San Francisco, CA, USA

    David Saah

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Correspondence to Thomas Buchholz.

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Buchholz, T., Gunn, J., Springsteen, B. et al. Probability-based accounting for carbon in forests to consider wildfire and other stochastic events: synchronizing science, policy, and carbon offsets. Mitig Adapt Strateg Glob Change 27, 4 (2022). https://doi.org/10.1007/s11027-021-09983-0

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