Mahendra Doraisami, Grant M. Domke, Adam R. Martin
{"title":"为多尺度森林碳估算改进木碳组分。","authors":"Mahendra Doraisami, Grant M. Domke, Adam R. Martin","doi":"10.1186/s13021-024-00272-2","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>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.</p><h3>Main text</h3><p>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.</p><h3>Conclusion</h3><p>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.</p></div>","PeriodicalId":505,"journal":{"name":"Carbon Balance and Management","volume":"19 1","pages":""},"PeriodicalIF":3.9000,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://cbmjournal.biomedcentral.com/counter/pdf/10.1186/s13021-024-00272-2","citationCount":"0","resultStr":"{\"title\":\"Improving wood carbon fractions for multiscale forest carbon estimation\",\"authors\":\"Mahendra Doraisami, Grant M. Domke, Adam R. Martin\",\"doi\":\"10.1186/s13021-024-00272-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><p>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.</p><h3>Main text</h3><p>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.</p><h3>Conclusion</h3><p>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.</p></div>\",\"PeriodicalId\":505,\"journal\":{\"name\":\"Carbon Balance and Management\",\"volume\":\"19 1\",\"pages\":\"\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2024-08-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://cbmjournal.biomedcentral.com/counter/pdf/10.1186/s13021-024-00272-2\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Carbon Balance and Management\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://link.springer.com/article/10.1186/s13021-024-00272-2\",\"RegionNum\":3,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Carbon Balance and Management","FirstCategoryId":"89","ListUrlMain":"https://link.springer.com/article/10.1186/s13021-024-00272-2","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Improving wood carbon fractions for multiscale forest carbon estimation
Background
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.
Main text
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.
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 a wider suite of multitiered forest C estimation protocols, models, and studies.
期刊介绍:
Carbon Balance and Management is an open access, peer-reviewed online journal that encompasses all aspects of research aimed at developing a comprehensive policy relevant to the understanding of the global carbon cycle.
The global carbon cycle involves important couplings between climate, atmospheric CO2 and the terrestrial and oceanic biospheres. The current transformation of the carbon cycle due to changes in climate and atmospheric composition is widely recognized as potentially dangerous for the biosphere and for the well-being of humankind, and therefore monitoring, understanding and predicting the evolution of the carbon cycle in the context of the whole biosphere (both terrestrial and marine) is a challenge to the scientific community.
This demands interdisciplinary research and new approaches for studying geographical and temporal distributions of carbon pools and fluxes, control and feedback mechanisms of the carbon-climate system, points of intervention and windows of opportunity for managing the carbon-climate-human system.
Carbon Balance and Management is a medium for researchers in the field to convey the results of their research across disciplinary boundaries. Through this dissemination of research, the journal aims to support the work of the Intergovernmental Panel for Climate Change (IPCC) and to provide governmental and non-governmental organizations with instantaneous access to continually emerging knowledge, including paradigm shifts and consensual views.