Pan-tropical prediction of forest structure from the largest trees

Jean François Bastin*, Ervan Rutishauser, James R. Kellner, Sassan Saatchi, Raphael Pélissier, Bruno Hérault, Ferry Slik, Jan Bogaert, Charles De Cannière, Andrew R. Marshall, John Poulsen, Patricia Alvarez-Loyayza, Ana Andrade, Albert Angbonga-Basia, Alejandro Araujo-Murakami, Luzmila Arroyo, Narayanan Ayyappan, Celso Paulo de Azevedo, Olaf Banki, Nicolas BarbierJorcely G. Barroso, Hans Beeckman, Robert Bitariho, Pascal Boeckx, Katrin Boehning-Gaese, Hilandia Brandão, Francis Q. Brearley, Mireille Breuer Ndoundou Hockemba, Roel Brienen, Jose Luis C. Camargo, Ahimsa Campos-Arceiz, Benoit Cassart, Jérôme Chave, Robin Chazdon, Georges Chuyong, David B. Clark, Connie J. Clark, Richard Condit, Euridice N. Honorio Coronado, Priya Davidar, Thalès de Haulleville, Laurent Descroix, Jean Louis Doucet, Aurelie Dourdain, Vincent Droissart, Thomas Duncan, Javier Silva Espejo, Santiago Espinosa, Nina Farwig, Adeline Fayolle, Ted R. Feldpausch, Antonio Ferraz, Christine Fletcher, Krisna Gajapersad, Jean François Gillet, Iêda Leão do Amaral, Christelle Gonmadje, James Grogan, David Harris, Sebastian K. Herzog, Jürgen Homeier, Wannes Hubau, Stephen P. Hubbell, Koen Hufkens, Johanna Hurtado, Narcisse G. Kamdem, Elizabeth Kearsley, David Kenfack, Michael Kessler, Nicolas Labrière, Yves Laumonier, Susan Laurance, William F. Laurance, Simon L. Lewis, Moses B. Libalah, Gauthier Ligot, Jon Lloyd, Thomas E. Lovejoy, Yadvinder Malhi, Beatriz S. Marimon, Ben Hur Marimon Junior, Emmanuel H. Martin, Paulus Matius, Victoria Meyer, Casimero Mendoza Bautista, Abel Monteagudo-Mendoza, Arafat Mtui, David Neill, Germaine Alexander Parada Gutierrez, Guido Pardo, Marc Parren, N. Parthasarathy, Oliver L. Phillips, Nigel C.A. Pitman, Pierre Ploton, Quentin Ponette, B. R. Ramesh, Jean Claude Razafimahaimodison, Maxime Réjou-Méchain, Samir Gonçalves Rolim, Hugo Romero Saltos, Luiz Marcelo Brum Rossi, Wilson Roberto Spironello, Francesco Rovero, Philippe Saner, Denise Sasaki, Mark Schulze, Marcos Silveira, James Singh, Plinio Sist, Bonaventure Sonke, J. Daniel Soto, Cintia Rodrigues de Souza, Juliana Stropp, Martin J.P. Sullivan, Ben Swanepoel, Hans ter Steege, John Terborgh, Nicolas Texier, Takeshi Toma, Renato Valencia, Luis Valenzuela, Leandro Valle Ferreira, Fernando Cornejo Valverde, Tinde R. Van Andel, Rodolfo Vasque, Hans Verbeeck, Pandi Vivek, Jason Vleminckx, Vincent A. Vos, Fabien H. Wagner, Papi Puspa Warsudi, Verginia Wortel, Roderick J. Zagt, Donatien Zebaze

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Aim: Large tropical trees form the interface between ground and airborne observations, offering a unique opportunity to capture forest properties remotely and to investigate their variations on broad scales. However, despite rapid development of metrics to characterize the forest canopy from remotely sensed data, a gap remains between aerial and field inventories. To close this gap, we propose a new pan-tropical model to predict plot-level forest structure properties and biomass from only the largest trees. Location: Pan-tropical. Time period: Early 21st century. Major taxa studied: Woody plants. Methods: Using a dataset of 867 plots distributed among 118 sites across the tropics, we tested the prediction of the quadratic mean diameter, basal area, Lorey's height, community wood density and aboveground biomass (AGB) from the ith largest trees. Results: Measuring the largest trees in tropical forests enables unbiased predictions of plot- and site-level forest structure. The 20 largest trees per hectare predicted quadratic mean diameter, basal area, Lorey's height, community wood density and AGB with 12, 16, 4, 4 and 17.7% of relative error, respectively. Most of the remaining error in biomass prediction is driven by differences in the proportion of total biomass held in medium-sized trees (50–70 cm diameter at breast height), which shows some continental dependency, with American tropical forests presenting the highest proportion of total biomass in these intermediate-diameter classes relative to other continents. Main conclusions: Our approach provides new information on tropical forest structure and can be used to generate accurate field estimates of tropical forest carbon stocks to support the calibration and validation of current and forthcoming space missions. It will reduce the cost of field inventories and contribute to scientific understanding of tropical forest ecosystems and response to climate change.

Original languageEnglish
Pages (from-to)1366-1383
Number of pages18
JournalGlobal Ecology and Biogeography
Volume27
Issue number11
Early online date10 Oct 2018
DOIs
Publication statusPublished - Nov 2018

Keywords

  • carbon
  • climate change
  • forest structure
  • large trees
  • pan-tropical
  • REDD+
  • tropical forest ecology

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