Weighing trees with lasers: reducing uncertainty in tropical forest biomass and allometry
Weighing trees with lasers: reducing uncertainty in tropical forest biomass and allometry
批准号:
NE/N00373X/1
负责人:
Mathias Disney
金额:
$64.34万
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2015
资助国家:
英国
项目状态:
已结题
起止时间:
2015 至 --
中文摘要
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英文摘要
Measuring the volume and structure of a tree accurately allows us to calculate the total above-ground carbon (C) stored in the tree, a very important property. Trees remove CO2 from the atmosphere during photosynthesis and can store this C for decades or even centuries until the tree dies, when some of it is released back to the atmosphere through decomposition. Tropical forests store around half of all above-ground terrestrial C, but are at particular risk due to deforestation and degradation, as well as from changing rainfall and temperature patterns. Surprisingly, our knowledge of tropical forest C stocks is quite poor, and errors in these stocks are large and uncertain. This uncertainty feeds into estimates of CO2 emissions due to deforestation, degradation and land use change. We will address this major uncertainty in the terrestrial C cycle by deploying a new, NERC-funded terrestrial laser scanner (TLS) to scan 1000s of trees in tropical forests on three continents: Amazonia, the Congo Basin and SE Asia. The laser data will allow us to measure 3D tree volume and biomass non-destructively to within a few percent of the best current estimates, made by destructive harvesting and weighing. The current, large uncertainties arise because weighing a tree is extremely difficult: tropical trees may be over 50m tall, and weigh 100 tonnes or more. Harvesting also precludes revisiting trees over time to measure change. In practice, a small sample of trees that have been harvested and weighed are related to easy-to-measure parameters of diameter and height, using empirical 'allometric' (size-to-mass) relationships. These relationships are then used to translate diameter and height measurements made over wider areas into estimates of biomass. Allometry is also the only way to infer biomass at very large (pan-tropical) scales, from remote sensing measurements. Unfortunately, the sample of harvested trees underpinning global allometric relationships is geographically limited, and contains very few large trees. Current estimates of tropical forest C stocks from satellite and ground data, all based on these very limited allometry samples, diverge significantly in size and pattern, leading to heated debate as to why this should be.We hope to settle this debate, given that our lidar-derived estimates of biomass are completely independent of allometry and unbiased in terms of tree size. We will 'weigh' more trees than are currently included in all global pan-tropical allometries and quantify uncertainty in the allometry models. We will also test assumptions made in allometric models regarding tree shape and wood density. Our measurements will also answer fundamental questions about geographical differences in structural characteristics across tropical forests. Our data will be vital for testing new estimates of biomass from remote sensing; the UK-led ESA BIOMASS RADAR and NASA GEDI laser missions will both estimate pan-tropical C stocks by relying on allometric relationships between forest height and biomass. Our work will feed into these two missions through long-standing collaborations with the lead scientists. More generally, the large number of tree measurements we will collect would be of great interest to researchers in tropical ecology, forestry, biodiversity, remote sensing and C mapping, among others.A key aim of the project is to ensure the widest use of our results, by making our data and tools publicly available. We will work with partners to explore routes for commercial developments and input into government policy, particularly relating to forest management and C mapping and mitigation. Lastly, we will make our work accessible through a range of outreach activities, including developing links between a school in the Amazon and UK schools, to raise awareness of scientific, conservation and policy issues surrounding tropical forests.
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Supplementary Material from New insights into large tropical tree mass and structure from direct harvest and terrestrial lidar
补充材料来自直接收获和地面激光雷达对大型热带树木质量和结构的新见解
DOI:
10.6084/m9.figshare.13685849
发表时间:
2021
期刊:
影响因子:
--
作者:
[Burt A]
通讯作者:
Burt A
DOI:
10.3389/ffgc.2020.00012
发表时间:
2020-02-20
期刊:
FRONTIERS IN FORESTS AND GLOBAL CHANGE
影响因子:
3.2
作者:
[Burt, Andrew, Calders, Kim, Disney, Mathias]
通讯作者:
Disney, Mathias
DOI:
10.1098/rsos.201458
发表时间:
2021-02-10
期刊:
Royal Society open science
影响因子:
3.5
作者:
[Burt A, Boni Vicari M, da Costa ACL, Coughlin I, Meir P, Rowland L, Disney M]
通讯作者:
Disney M
New insights into large tropical tree mass and structure from direct harvest and terrestrial lidar
通过直接收获和地面激光雷达对大型热带树木质量和结构的新见解
DOI:
10.1101/2020.09.29.317198
发表时间:
2020
期刊:
影响因子:
--
作者:
[Burt A]
通讯作者:
Burt A
DOI:
10.1111/2041-210x.13121
发表时间:
2019-03-01
期刊:
METHODS IN ECOLOGY AND EVOLUTION
影响因子:
6.6
作者:
[Burt, Andrew, Disney, Mathias, Calders, Kim]
通讯作者:
Calders, Kim
共 8 条
Understanding tree architecture, form and function in the tropics
-
批准号:NE/P011780/1
-
项目类别:Research Grant
-
资助金额:$25.94万
-
财政年份:2017
-
负责人:Mathias Disney
-
依托单位:
GREENHOUSE: Generating Regional Emissions Estimates with a Novel Hierarchy of Observations and Upscaled Simulation Experiments
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批准号:NE/K002554/1
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项目类别:Research Grant
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资助金额:$15.75万
-
财政年份:2013
-
负责人:Mathias Disney
-
依托单位:
国内基金
海外基金
树木抑制户外空气中细菌作用特异性的研究
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批准号:30570346
-
项目类别:面上项目
-
资助金额:8.0万元
-
批准年份:2005
-
负责人:戚继忠
-
依托单位: