biodiversity; canopy structure; GEDI; lidar; plant area index; tropical forests; Global and Planetary Change; Ecology, Evolution, Behavior and Systematics; Ecology
Abstract :
[en] 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.
Disciplines :
Environmental sciences & ecology
Author, co-author :
Marselis, Suzanne M. ; Department of Geographical Sciences, University of Maryland, College Park, United States
Abernethy, Katharine; Division of Biological and Environmental Sciences Tropical Ecology and Conservation, University of Stirling, Stirling, United Kingdom ; Institut de Recherche en Ecologie Tropicale (IRET), CENAREST, Libreville, Gabon
Alonso, Alfonso ; Center for Conservation and Sustainability, Smithsonian Conservation Biology Institute, Washington, United States
Armston, John; Department of Geographical Sciences, University of Maryland, College Park, United States
Baker, Timothy R.; School of Geography, University of Leeds, Leeds, United Kingdom
Bastin, Jean-François ; Université de Liège - ULiège > TERRA Research Centre ; CAVELab, Computational and Applied Vegetation Ecology, Department of Environment, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium
Bogaert, Jan ; Université de Liège - ULiège > Département GxABT > Biodiversité et Paysage
Boyd, Doreen S.; School of Geography, University of Nottingham, Nottingham, United Kingdom
Burslem, David F. R. P.; School of Biological Sciences, University of Aberdeen, Aberdeen, United Kingdom
Chazdon, Robin; Department of Ecology and Evolutionary Biology, University of Connecticut, Storrs, United States
Clark, David B.; Department of Biology, University of Missouri-St. Louis, St. Louis, United States
Coomes, David; Department of Plant Sciences, University of Cambridge, Cambridge, United Kingdom
Duncanson, Laura; Department of Geographical Sciences, University of Maryland, College Park, United States
Hancock, Steven; School of Geosciences, University of Edinburgh, Edinburgh, United Kingdom
Hill, Ross; Department of Life and Environmental Science, Bournemouth University, Poole, United Kingdom
Hopkinson, Chris; Department of Geography, University of Lethbridge, Lethbridge, Canada
Kearsley, Elizabeth ; CAVELab, Computational and Applied Vegetation Ecology, Department of Environment, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium
Kellner, James R.; Institute at Brown for Environment and Society, Brown University, Providence, United States ; Department of Ecology and Evolutionary Biology, Brown University, Providence, United States
Kenfack, David; Center for Tropical Forest Science—Forest Global Earth Observatory, Smithsonian Tropical Research Institute, Smithsonian Institution, Washington, United States
Labrière, Nicolas; Laboratoire Evolution et Diversité Biologique, Université Toulouse III Paul Sabatier, Toulouse, France
Lewis, Simon L.; Department of Geography, University College London, London, United Kingdom
Minor, David; Department of Geographical Sciences, University of Maryland, College Park, United States
Memiaghe, Hervé; Institut de Recherche en Ecologie Tropicale (IRET), CENAREST, Libreville, Gabon
Monteagudo, Abel; Pasco, Jardín Botánico de Missouri, Oxapampa, Peru
Nilus, Reuben; Sabah Forestry Department, Forest Research Centre, Sandakan, Malaysia
O'Brien, Michael ; Área de Biodiversidad y Conservación, Universidad Rey Juan Carlos, Móstoles, Madrid, Spain
Phillips, Oliver L.; School of Geography, University of Leeds, Leeds, United Kingdom
Poulsen, John ; Nicolas School of the Environment, Duke University, Durham, United States
Tang, Hao ; Department of Geographical Sciences, University of Maryland, College Park, United States
Verbeeck, Hans; CAVELab, Computational and Applied Vegetation Ecology, Department of Environment, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium
Dubayah, Ralph; Department of Geographical Sciences, University of Maryland, College Park, United States
Gordon and Betty Moore Foundation NSF - National Science Foundation
Funding text :
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, Pac?me 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 Jard?n Bot?nico 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'?tude 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.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 ,,, , and , 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 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 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 . Shell Gabon and the Smithsonian Tropical Research Institute for funding, and Pulcherie Bissiengou for guiding, field data collection in . This is contribution no. 196 of the Gabon Biodiversity Program. We thank Deborah Clark for her efforts in collecting field data in . and 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 and J. W. Dalling for providing the lidar data in , which were funded through National Science Foundation (NSF) grant 0939907. The 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. 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 Jardín 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 . 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 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 and . Data collection on tree diversity in the Costa Rican sites () 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. lsv cha lop mon mab rab lop mon mab rab lsv s11 s12 bci bci dan tam tam sep yan yan mal cha
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