Suppr超能文献

基于管理清查数据的非洲湿润热带森林地上生物量分布图。

A map of African humid tropical forest aboveground biomass derived from management inventories.

机构信息

AMAP, Univ Montpellier, IRD, CNRS, INRAE, CIRAD, Montpellier, France.

CIRAD, UPR Forêts et Sociétés, F-34398 Montpellier, France; Université de Montpellier, F-34000, Montpellier, France.

出版信息

Sci Data. 2020 Jul 8;7(1):221. doi: 10.1038/s41597-020-0561-0.

Abstract

Forest biomass is key in Earth carbon cycle and climate system, and thus under intense scrutiny in the context of international climate change mitigation initiatives (e.g. REDD+). In tropical forests, the spatial distribution of aboveground biomass (AGB) remains, however, highly uncertain. There is increasing recognition that progress is strongly limited by the lack of field observations over large and remote areas. Here, we introduce the Congo basin Forests AGB (CoFor-AGB) dataset that contains AGB estimations and associated uncertainty for 59,857 1-km pixels aggregated from nearly 100,000 ha of in situ forest management inventories for the 2000 - early 2010s period in five central African countries. A comprehensive error propagation scheme suggests that the uncertainty on AGB estimations derived from c. 0.5-ha inventory plots (8.6-15.0%) is only moderately higher than the error obtained from scientific sampling plots (8.3%). CoFor-AGB provides the first large scale view of forest AGB spatial variation from field data in central Africa, the second largest continuous tropical forest domain of the world.

摘要

森林生物量是地球碳循环和气候系统的关键,因此在国际气候变化缓解倡议(如 REDD+)的背景下受到了强烈关注。然而,在热带森林中,地上生物量(AGB)的空间分布仍然高度不确定。人们越来越认识到,由于缺乏对大面积和偏远地区的实地观测,进展受到了严重限制。在这里,我们引入了刚果盆地森林 AGB(CoFor-AGB)数据集,该数据集包含了来自五个中非国家 2000 年至 2010 年代初期近 10 万公顷森林管理清查的近 10 万个 1 公里像素的 AGB 估算值及其相关不确定性。一个全面的误差传播方案表明,从大约 0.5 公顷的清查样地得出的 AGB 估算值的不确定性(8.6-15.0%)仅比从科学采样样地获得的误差略高。CoFor-AGB 提供了从中非实地数据中获得的森林 AGB 空间变化的第一个大规模视图,这是世界上第二大连续的热带森林区域。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eac4/7343822/fa1f49c955f6/41597_2020_561_Fig1_HTML.jpg

相似文献

6
Above-ground biomass and structure of 260 African tropical forests.
Philos Trans R Soc Lond B Biol Sci. 2013 Jul 22;368(1625):20120295. doi: 10.1098/rstb.2012.0295. Print 2013.
8
Optimal climate for large trees at high elevations drives patterns of biomass in remote forests of Papua New Guinea.
Glob Chang Biol. 2017 Nov;23(11):4873-4883. doi: 10.1111/gcb.13741. Epub 2017 May 31.
10

本文引用的文献

1
Alarming surge in Amazon fires prompts global outcry.
Nature. 2019 Aug 23. doi: 10.1038/d41586-019-02537-0.
2
Degradation and forgone removals increase the carbon impact of intact forest loss by 626.
Sci Adv. 2019 Oct 30;5(10):eaax2546. doi: 10.1126/sciadv.aax2546. eCollection 2019 Oct.
4
The Importance of Consistent Global Forest Aboveground Biomass Product Validation.
Surv Geophys. 2019;40(4):979-999. doi: 10.1007/s10712-019-09538-8. Epub 2019 May 30.
6
Global land change from 1982 to 2016.
Nature. 2018 Aug;560(7720):639-643. doi: 10.1038/s41586-018-0411-9. Epub 2018 Aug 8.
7
The tropical forest carbon cycle and climate change.
Nature. 2018 Jul;559(7715):527-534. doi: 10.1038/s41586-018-0300-2. Epub 2018 Jul 25.
8
An assessment of forest biomass maps in Europe using harmonized national statistics and inventory plots.
For Ecol Manage. 2018 Feb 1;409:489-498. doi: 10.1016/j.foreco.2017.11.047.
9
21st Century drought-related fires counteract the decline of Amazon deforestation carbon emissions.
Nat Commun. 2018 Feb 13;9(1):536. doi: 10.1038/s41467-017-02771-y.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验