Title
Evaluating the potential of full-waveform lidar for mapping pan-tropical tree species richness
Date Issued
01 October 2020
Access level
open access
Resource Type
journal article
Author(s)
Marselis S.M.
Abernethy K.
Alonso A.
Armston J.
Baker T.R.
Bastin J.F.
Bogaert J.
Boyd D.S.
Boeckx P.
Burslem D.F.R.P.
Chazdon R.
Clark D.B.
Coomes D.
Duncanson L.
Hancock S.
Hill R.
Hopkinson C.
Kearsley E.
Kellner J.R.
Kenfack D.
Labrière N.
Lewis S.L.
Minor D.
Memiaghe H.
Nilus R.
O'Brien M.
Phillips O.L.
Poulsen J.
Tang H.
Verbeeck H.
Dubayah R.
Publisher(s)
Blackwell Publishing Ltd
Abstract
Aim: Mapping tree species richness across the tropics is of great interest for effective conservation and biodiversity management. In this study, we evaluated the potential of full-waveform lidar data for mapping tree species richness across the tropics by relating measurements of vertical canopy structure, as a proxy for the occupation of vertical niche space, to tree species richness. Location: Tropics. Time period: Present. Major taxa studied: Trees. Methods: First, we evaluated the characteristics of vertical canopy structure across 15 study sites using (simulated) large-footprint full-waveform lidar data (22 m diameter) and related these findings to in-situ tree species information. Then, we developed structure–richness models at the local (within 25–50 ha plots), regional (biogeographical regions) and pan-tropical scale at three spatial resolutions (1.0, 0.25 and 0.0625 ha) using Poisson regression. Results: The results showed a weak structure–richness relationship at the local scale. At the regional scale (within a biogeographical region) a stronger relationship between canopy structure and tree species richness across different tropical forest types was found, for example across Central Africa and in South America [R2 ranging from.44–.56, root mean squared difference as a percentage of the mean (RMSD%) ranging between 23–61%]. Modelling the relationship pan-tropically, across four continents, 39% of the variation in tree species richness could be explained with canopy structure alone (R2 =.39 and RMSD% = 43%, 0.25-ha resolution). Main conclusions: Our results may serve as a basis for the future development of a set of structure–richness models to map high resolution tree species richness using vertical canopy structure information from the Global Ecosystem Dynamics Investigation (GEDI). The value of this effort would be enhanced by access to a larger set of field reference data for all tropical regions. Future research could also support the use of GEDI data in frameworks using environmental and spectral information for modelling tree species richness across the tropics.
Start page
1799
End page
1816
Volume
29
Issue
10
Language
English
OCDE Knowledge area
Conservación de la Biodiversidad
Ciencias de las plantas, Botánica
Subjects
Scopus EID
2-s2.0-85088583362
Source
Global Ecology and Biogeography
ISSN of the container
1466822X
Sponsor(s)
This work is supported by NASA Headquarters under the NASA Earth and Space Science Fellowship 414 Program – Grant 80NSSC17K0321; NASA contract #NNL 15AA03C to the University of Maryland for the development and execution of the GEDI mission (Principal Investigator, R. Dubayah); and the NASA New Investigator grant 80NSSC18K0708. We express our sincere gratitude to the following people and institutions for collecting field and lidar data and permitting us to use their data in this research: NASA’s LVIS team, specifically Bryan Blair, Michelle Hofton and David Rabine for collecting airborne lidar data in lsv, cha, lop, mon, mab and rab, Gabon; Agence Nationale des Parcs Nationaux (ANPN) and Agence Gabonaise d'Etudes et d'Observation for logistical support that facilitated both fieldwork and lidar data collection in Gabon, specifically Kathryn Jeffery, Lee White, Flore Koumba Pambo, Josue Edzang Ndong and David Lehmann from ANPN; European Space Agency for funding field data collection in lop through the AfriSAR campaign, ANPN and the University of Stirling at the Station d'Etudes des Gorilles et Chimpanzes field station for hosting, and specifically Carl Ditougou, Pacôme Dimbonda, Arthur Dibambou, Edmond Dimoto, and Napo Milamizokou; NASA for funding field data collection in mon through the AfriSAR campaign and ANPN for hosting it; Nicolas Barbier, Missouri Botanical Garden (Tariq Stevart), Golder Associates, P. Ploton, V. Droissart and Y. Issembe, for field data collection in mab. Shell Gabon and the Smithsonian Tropical Research Institute for funding, and Pulcherie Bissiengou for guiding, field data collection in rab. This is contribution no. 196 of the Gabon Biodiversity Program. We thank Deborah Clark for her efforts in collecting field data in lsv. s11 and s12 field and lidar data sets were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (EMBRAPA), the US Forest Service, and United States Agency for International Development, and the US Department of State. Smithsonian Tropical Research Institute and the Smithsonian the Forest Global Earth Observatory (ForestGEO) Global Earth Observatory Network for funding and publishing field data collection in bci and J. W. Dalling for providing the lidar data in bci, which were funded through National Science Foundation (NSF) grant 0939907. The dan plot is a core project of the Southeast Asia Rain Forest Research Partnership (SEARRP). We thank SEARRP partners, especially Yayasan Sabah, for their support, and HSBC Malaysia and the University of Zurich for funding. We are grateful to the research assistants who are conducting the census, in particular the team leader Alex Karolus, and to Mike Bernados and Bill McDonald for species identifications. We thank Stuart Davies and Shameema Esufali for advice and training. tam plot measurements have been supported by several grants including from Gordon and Betty Moore Foundation #1656 (‘RAINFOR’) to O. L. Phillips and National Geographic. We also thank the JardÃn Botánico de Missouri (Peru) for their field data assistance. We kindly thank Bryan Mark and Horizons Peru for collecting and providing the lidar data over tam. sep plot measurements have been supported by several grants, including the European Research Council (ERC Advanced Grant 291585 – ‘T-FORCES’) and the Natural Environment Research Council (NER/A/S/2000/01002) grants to O. L. Phillips and special thanks go to Lan Qie. Data from RAINFOR, African Tropical Rainforest Observatory Network and tropical forests in the changing earth system (T-FORCES) are curated by ForestPlots.net, a cyber-infrastructure initiative hosted at the University of Leeds that unites permanent plot records and their contributing scientists from the world’s tropical forests. This paper is an outcome of the ForestPlots.net approved research project #60 ‘Towards mapping pan-tropical tree species diversity using GEDI lidar data’. The development of ForestPlots.net was funded by several grants, including NE/B503384/1, NE/N012542/1 BIO-RED, ERC AdG 291585 ‘T-FORCES’, and Gordon and Betty Moore Foundation #1656 (‘RAINFOR’). The collection of field data in yan was done in the framework of the COBIMFO project (Congo Basin integrated monitoring for forest carbon mitigation and biodiversity; contract no. SD/AR/01A) and was funded by the Belgian Science Policy Office (Belspo). The ‘Institut National pour l'Étude et la Recherche Agronomiques’ (INERA) assisted in plot establishment and provided logistical support (Belspo). We thank the World Wildlife Fund for funding and facilitating lidar data collection over yan and mal. Data collection on tree diversity in the Costa Rican sites (cha) was supported by grants from the Andrew W. Mellon Foundation, NSF DEB-0424767, NSF DEB-0639393, NSF DEB-1147429, NASA Terrestrial Ecology Program, and the University of Connecticut Research Foundation.
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