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Forest Inventories: Discrepancies and Uncertainties

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  • Waggoner, Paul E.

Abstract

Credits for sequestered carbon augment forests’ already considerable value as natural habitat and as producers of timber and biomass, making their accurate inventory more critical than ever before. This article examines discrepancies in inventories of forest attributes and their sources in four variables: area, timber volume per area, biomass per timber volume, and carbon concentration. Documented discrepancies range up to a multibillion-ton difference in the global stock of carbon in trees. Because the variables are multiplied together to estimate an attribute like carbon stock, more precise measurement of the most certain variable improves accuracy little, and a 10 percent error in biomass per timber levers a discrepancy as much as a mistake in millions of hectares. More precise measurements of, say, accessible stands cannot remedy inaccuracies from biased sampling of regional forests. The discrepancies and uncertainties documented here underscore the obligation to improve monitoring of global forests.

Suggested Citation

  • Waggoner, Paul E., 2009. "Forest Inventories: Discrepancies and Uncertainties," RFF Working Paper Series dp-09-29.pdf, Resources for the Future.
    • Handle: RePEc:rff:dpaper:dp-09-29.pdf
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    File URL: http://www.rff.org/RFF/documents/RFF-DP-09-29.pdf
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    References listed on IDEAS

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    1. Unknown, 1962. "Handbook of Agriculture," Indian Journal of Agricultural Economics, Indian Society of Agricultural Economics, vol. 17(2), pages 1-3.
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    Cited by:

    1. Fortmann, Lea & Cordero-Salas, Paula & Sohngen, Brent & Brian, Roe, 2016. "Incentive Contracts for Environmental Services and their Potential in REDD," International Review of Environmental and Resource Economics, now publishers, vol. 9(3-4), pages 363-409, September.
    2. Molly Macauley & Roger Sedjo, 2011. "Forests in climate policy: technical, institutional and economic issues in measurement and monitoring," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 16(5), pages 499-513, June.
    3. Nathan Richardson & Molly Macauley, 2012. "Forest Carbon Economics: What We Know, What We Do Not And Whether It Matters," Climate Change Economics (CCE), World Scientific Publishing Co. Pte. Ltd., vol. 3(04), pages 1-18.
    4. Köhl, Michael & Neupane, Prem Raj & Mundhenk, Philip, 2020. "REDD+ measurement, reporting and verification – A cost trap? Implications for financing REDD+MRV costs by result-based payments," Ecological Economics, Elsevier, vol. 168(C).
    5. Sloggy, Matthew R. & Kling, David M. & Plantinga, Andrew J., 2020. "Measure twice, cut once: Optimal inventory and harvest under volume uncertainty and stochastic price dynamics," Journal of Environmental Economics and Management, Elsevier, vol. 103(C).
    6. Daniel Plugge & Thomas Baldauf & Michael Köhl, 2013. "The global climate change mitigation strategy REDD: monitoring costs and uncertainties jeopardize economic benefits," Climatic Change, Springer, vol. 119(2), pages 247-259, July.
    7. Epede, Mesumbe Bianca & Wang, Daoping, 2022. "Competitiveness and upgrading in global value chains: A multiple-country analysis of the wooden furniture industry," Forest Policy and Economics, Elsevier, vol. 140(C).

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    More about this item

    Keywords

    forest monitoring; Forest Identity; forest carbon; remote sensing;
    All these keywords.

    JEL classification:

    • Q23 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Forestry
    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth
    • Q57 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Ecological Economics

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