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Pan‐tropical prediction of forest structure from the largest trees

2018; Wiley; Volume: 27; Issue: 11 Linguagem: Inglês

10.1111/geb.12803

1466-8238

Jean‐François Bastin, Ervan Rutishauser, James R. Kellner, Sassan Saatchi, Raphaël Pélissier, Bruno Hérault, Ferry Slik, Jan Bogaert, Charles De Cannière, Andrew R. Marshall, John R. Poulsen, Patricia Alvarez‐Loyayza, Ana Andrade, Albert Angbonga‐Basia, Alejandro Araujo‐Murakami, Luzmila Arroyo, Narayanan Ayyappan, C. P. de Azevedo, Olaf Bánki, Nicolas Barbier, Jorcely Barroso, Hans Beeckman, Robert Bitariho, Pascal Boeckx, Katrin Boehning‐Gaese, Hilandia Brandão, Francis Q. Brearley, Mireille Breuer Ndoundou Hockemba, Roel Brienen, José Luís Camargo, Ahimsa Campos‐Arceiz, Benoît Cassart, Jérôme Chave, Robin L. Chazdon, Georges Chuyong, David B. Clark, Connie J. Clark, Richard Condit, Eurídice N. Honorio Coronado, Priya Davidar, Thalès de Haulleville, Laurent Descroix, Jean‐Louis Doucet, Aurélie Dourdain, Vincent Droissart, Duncan Thomas, Javier Silva Espejo, Santiago Espinosa, Nina Farwig, Adeline Fayolle, Ted R. Feldpausch, António Ferraz, Christine Fletcher, Krisna Gajapersad, Jean‐François Gillet, Iêda Leão do Amaral, Christelle Gonmadje, James Grogan, David J. Harris, Sebastián K. Herzog, Jürgen Homeier, Wannes Hubau, Stephen P. Hubbell, Koen Hufkens, Johanna Hurtado, Narcisse Guy Kamdem, Elizabeth Kearsley, David Kenfack, Michael Kessler, Nicolas Labrière, Yves Laumonier, Susan G. Laurance, Susan G. Laurance, Simon L. Lewis, Moses Libalah, Gauthier Ligot, Jon Lloyd, Thomas Ε. Lovejoy, Yadvinder Malhi, Beatriz Schwantes Marimon, Ben Hur Marimon, 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 A. 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, Plínio Sist, Bonaventure Sonké, José D. Soto, Cíntia 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 van Andel, Rodolfo Vasque, Hans Verbeeck, Vivek Pandi, Jason Vleminckx, Vincent Antoine Vos, Fabien Wagner, Papi Puspa Warsudi, Verginia Wortel, Roderick Zagt, Donatien Zébazé,

Remote Sensing in Agriculture

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 i th 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.