New insights into large tropical tree mass and structure from direct harvest and terrestrial lidar

dc.contributor.authorBurt, Andrew
dc.contributor.authorVicari, Matheus Boni
dc.contributor.authorda Costa, A C L
dc.contributor.authorCoughlin, Ingrid
dc.contributor.authorMeir, Patrick
dc.contributor.authorRowland, Lucy
dc.contributor.authorDisney, Mathias
dc.date.accessioned2023-01-25T04:40:37Z
dc.date.available2023-01-25T04:40:37Z
dc.date.issued2021
dc.date.updated2021-11-28T07:37:47Z
dc.description.abstractA large portion of the terrestrial vegetation carbon stock is stored in the above-ground biomass (AGB) of tropical forests, but the exact amount remains uncertain, partly owing to the lack of measurements. To date, accessible peer-reviewed data are available for just 10 large tropical trees in the Amazon that have been harvested and directly measured entirely via weighing. Here, we harvested four large tropical rainforest trees (stem diameter: 0.6–1.2 m, height: 30–46 m, AGB: 3960–18 584 kg) in intact old-growth forest in East Amazonia, and measured above-ground green mass, moisture content and woody tissue density. We first present rare ecological insights provided by these data, including unsystematic intra-tree variations in density, with both height and radius. We also found the majority of AGB was usually found in the crown, but varied from 42 to 62%. We then compare non-destructive approaches for estimating the AGB of these trees, using both classical allometry and new lidar-based methods. Terrestrial lidar point clouds were collected pre-harvest, on which we fitted cylinders to model woody structure, enabling retrieval of volume-derived AGB. Estimates from this approach were more accurate than allometric counterparts (mean tree-scale relative error: 3% versus 15%), and error decreased when up-scaling to the cumulative AGB of the four trees (1% versus 15%). Furthermore, while allometric error increased fourfold with tree size over the diameter range, lidar error remained constant. This suggests error in these lidar-derived estimates is random and additive. Were these results transferable across forest scenes, terrestrial lidar methods would reduce uncertainty in stand-scale AGB estimates, and therefore advance our understanding of the role of tropical forests in the global carbon cycle.en_AU
dc.description.sponsorshipA.B. and M.D. acknowledge funding from Natural Environment Research Council (NERC) grant no. NE/ N00373X/1 and European Research Council grant no. 757526. A.C.L.d.C. acknowledges funding from Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) grant no. 457914/2013-0/MCTI/CNPq/FNDCT/ LBA/ESECAFLOR. P.M. acknowledges funding from NERC grant no. NE/N006852/1. L.R. acknowledges funding from NERC independent fellowship grant no. NE/N014022/1. M.D. also acknowledges funding from NERC National Centre for Earth Observation (NCEO, NE/R016518/1).en_AU
dc.format.mimetypeapplication/pdfen_AU
dc.identifier.issn2054-5703en_AU
dc.identifier.urihttp://hdl.handle.net/1885/283976
dc.language.isoen_AUen_AU
dc.provenancePublished by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.en_AU
dc.publisherThe Royal Society Publishingen_AU
dc.rights© 2021 The authorsen_AU
dc.rights.licenseCreative Commons Attribution licenceen_AU
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_AU
dc.sourceRoyal Society Open Scienceen_AU
dc.subjecttropical forestsen_AU
dc.subjecttree structureen_AU
dc.subjectabove-ground biomassen_AU
dc.subjectdestructive harvesten_AU
dc.subjectterrestrial lidaren_AU
dc.subjectallometryen_AU
dc.titleNew insights into large tropical tree mass and structure from direct harvest and terrestrial lidaren_AU
dc.typeJournal articleen_AU
dcterms.accessRightsOpen Accessen_AU
local.contributor.affiliationBurt, Andrew, University College Londonen_AU
local.contributor.affiliationVicari, Matheus Boni, University College Londonen_AU
local.contributor.affiliationda Costa, A C L, Universidade Federal do Paraen_AU
local.contributor.affiliationCoughlin, Ingrid, College of Science, ANUen_AU
local.contributor.affiliationMeir, Patrick, College of Science, ANUen_AU
local.contributor.affiliationRowland, Lucy, University of Exeteren_AU
local.contributor.affiliationDisney, Mathias, University College Londonen_AU
local.contributor.authoruidCoughlin, Ingrid, u6565737en_AU
local.contributor.authoruidMeir, Patrick, u4875047en_AU
local.description.notesImported from ARIESen_AU
local.identifier.absfor310800 - Plant biologyen_AU
local.identifier.ariespublicationu9511635xPUB2180en_AU
local.identifier.citationvolume8en_AU
local.identifier.doi10.1098/rsos.201458en_AU
local.publisher.urlhttps://royalsocietypublishing.org/en_AU
local.type.statusPublished Versionen_AU

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