Doraisami Mahendra, Domke Grant M, Martin Adam R
Department of Physical and Environmental Sciences, University of Toronto Scarborough, Toronto, ON, Scarborough, M1C 1A4, Canada.
USDA Forest Service, Northern Research Station, St. Paul, MN, USA.
Carbon Balance Manag. 2024 Aug 14;19(1):25. doi: 10.1186/s13021-024-00272-2.
Wood carbon fractions (CFs)-the proportion of dry woody biomass comprised of elemental carbon (C)-are a key component of forest C estimation protocols and studies. Traditionally, a wood CF of 50% has been assumed in forest C estimation protocols, but recent studies have specifically quantified differences in wood CFs across several different forest biomes and taxonomic divisions, 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 (1) were based on the best available literature (at the time) and (2) represented 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, providing more accurate, robust, and spatially- and taxonomically- specific wood CFs for use in forest C estimation.
We argue that the IPCC's recommended wood CFs and those in many other forest C estimation models and protocols (1) differ substantially from, and are less robust than, wood CFs derived from recently published data-rich studies; and (2) may lead to nontrivial errors in forest C estimates, particularly for countries that rely heavily on Tier 1 forest C methods and protocols (e.g., countries of the Global South with large expanses of tropical forests). Based on previous studies on this topic, we propose an alternative set of refined wood CFs for use in multiscale forest C estimation, and propose a novel decision-making framework for integrating species- and location-specific wood CFs into forest C estimation models.
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 a wider suite of multitiered forest C estimation protocols, models, and studies.
木材碳组分（CFs）——即由元素碳（C）构成的干木质生物量的比例——是森林碳估算方案和研究的关键组成部分。传统上，森林碳估算方案中假定木材CF为50%，但最近的研究已经具体量化了几种不同森林生物群落和分类部门的木材CF差异，不再需要通用的木材CF假设。政府间气候变化专门委员会（IPCC）在其2006年《国家温室气体清单指南》中发布了自己的多层森林碳储量估算方案系统，其中包括的木材CF（1）基于当时可得的最佳文献，（2）相较于通用的50%木材CF假设而言有显著改进。然而，自2006年以来发表了大量关于木材CF的新研究，为森林碳估算提供了更准确、可靠且具有空间和分类特异性的木材CF。
我们认为，IPCC推荐的木材CF以及许多其他森林碳估算模型和方案中的CF（1）与最近发表的、数据丰富的研究所得到的木材CF有很大差异，且稳健性较差；（2）可能会导致森林碳估算出现重大误差，特别是对于严重依赖一级森林碳方法和方案的国家（例如拥有大片热带森林的全球南方国家）。基于此前关于该主题的研究，我们提出了一套用于多尺度森林碳估算的改进木材CF，并提出了一个将特定物种和地点的木材CF纳入森林碳估算模型的全新决策框架。
我们在本评论中提出的改进木材CF可被IPCC用于更新其推荐的用于森林碳估算的木材CF。此外，我们提出了一个全新的决策框架，用于将数据驱动的木材CF整合到更广泛的多层森林碳估算方案、模型和研究中。
