University of Leicester
bg-15-3377-2018.pdf (6.81 MB)

Canopy area of large trees explains aboveground biomass variations across neotropical forest landscapes

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journal contribution
posted on 2019-07-23, 14:24 authored by V Meyer, S Saatchi, DB Clark, M Keller, G Vincent, A Ferraz, F Espirito-Santo, MVN d'Oliveira, D Kaki, J Chave
Large tropical trees store significant amounts of carbon in woody components and their distribution plays an important role in forest carbon stocks and dynamics. Here, we explore the properties of a new lidar-derived index, the large tree canopy area (LCA) defined as the area occupied by canopy above a reference height. We hypothesize that this simple measure of forest structure representing the crown area of large canopy trees could consistently explain the landscape variations in forest volume and aboveground biomass (AGB) across a range of climate and edaphic conditions. To test this hypothesis, we assembled a unique dataset of high-resolution airborne light detection and ranging (lidar) and ground inventory data in nine undisturbed old-growth Neotropical forests, of which four had plots large enough (1 ha) to calibrate our model. We found that the LCA for trees greater than 27 m (∼ 25–30 m) in height and at least 100 m2 crown size in a unit area (1 ha), explains more than 75 % of total forest volume variations, irrespective of the forest biogeographic conditions. When weighted by average wood density of the stand, LCA can be used as an unbiased estimator of AGB across sites (R2 = 0.78, RMSE = 46.02 Mg ha−1, bias = −0.63 Mg ha−1). Unlike other lidar-derived metrics with complex nonlinear relations to biomass, the relationship between LCA and AGB is linear and remains unique across forest types. A comparison with tree inventories across the study sites indicates that LCA correlates best with the crown area (or basal area) of trees with diameter greater than 50 cm. The spatial invariance of the LCA–AGB relationship across the Neotropics suggests a remarkable regularity of forest structure across the landscape and a new technique for systematic monitoring of large trees for their contribution to AGB and changes associated with selective logging, tree mortality and other types of tropical forest disturbance and dynamics.


The work described in this paper was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration. This work has benefited from Investissement d'Avenir grants managed by the French Agence Nationale de la Recherche (CEBA, ref. ANR-10-LABX-25-01 and TULIP, ref. ANR-10-LABX-0041; ANAEE-France: ANR-11-INBS-0001) and from CNES (TOSCA project; PI T Le Toan). Field and lidar data from the Brazilian sites were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (EMBRAPA), the US Forest Service, and USAID, and the US Department of State. La Selva field work was supported by the US National Science Foundation LTREB Program NSF LTREB 1357177. Data in Chocó are available as part of the Reducing Emissions from Deforestation and forest Degradation (REDD) project. FES was supported by the Natural Environment Research Council (NERC) grants (BIO-RED NE/N012542/1 and AFIRE NE/P004512/1) and Newton Fund (The UK Academies/FAPESP Proc. No.: 2015/50392-8 Fellowship and Research Mobility). The AGB data for Paracou were made available courtesy of CIRAD (Bruno Hérault).



Biogeosciences, 2018, 15 (11), pp. 3377-3390 (14)

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/Organisation/COLLEGE OF SCIENCE AND ENGINEERING/School of Geography, Geology and the Environment


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European Geosciences Union (EGU), Copernicus Publications





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The BCI lidar and forest inventory dataset used in this research are publicly available from the Office of Bioinformatics, Smithsonian Tropical Research Institute (Hubbell et al., 2005). All relevant data are within the paper and its Supplement.. The supplement related to this article is available online at: