Improving wood carbon fractions for multiscale forest carbon estimation

Abstract

Abstract Background Wood carbon fractions (CFs)—the proportion of dry woody biomass comprised of elemental carbon (C)—are a key component of forest C estimation. Traditionally, a generic wood CF of 50% has been assumed in forest C estimation analyses and protocols, but in recent decades, studies have specifically quantified differences in wood CFs across several different forest biomes and taxonomic divisions (angiosperms vs gymnosperms), negating the need for generic wood CF assumptions. The Intergovernmental Panel on Climate Change (IPCC), in its 2006 “Guidelines for National Greenhouse Gas Inventories”, published its own multitiered system of protocols for estimating forest C stocks, which included wood CFs that were 1) based on the best available literature (at the time) and 2) a significant improvement over the generic 50% wood CF assumption. However, a considerable number of new studies on wood CFs have been published since 2006, which allow for more accurate, robust, and spatially- and taxonomically- specific wood CFs for use in forest C estimation. Main text Despite the availability of large wood CF datasets and evidence that suggests that using data-driven wood CFs may help correct nontrivial errors in forest C stock estimates, the IPCC did not update its recommended wood CFs in its most recent refinement to the 2006 guidelines. In this commentary, we argue that the IPCC’s recommended wood CFs differ substantially from, and are less robust, than wood CFs derived from recently published data-rich studies, and may lead to nontrivial errors in forest C estimates, particularly for countries that rely heavily on Tier 1 methods and recommended wood CFs, i.e., countries of the Global South, many of which are heavily forested. Using our previous studies on this topic, we propose an alternative set of refined wood CFs for use in multiscale forest C estimation studies and protocols. Additionally, we propose a novel decision-making framework for integrating species- and location-specific wood CFs into forest C estimation models. Conclusion The refined wood CFs that we present in this commentary may be used by the IPCC to update its recommended wood CFs for use in forest C estimation. Additionally, we propose a novel decision-making framework for integrating data-driven wood CFs into multitiered forest C estimation protocols and studies.