Pan-tropical prediction of forest structure from the largest trees

Bastin, Jean-François, Rutishauser, Ervan, Kellner, James R., Saatchi, Sassan, Pélissier, Raphael, Hérault, Bruno, Slik, Ferry, Bogaert, Jan, De Cannière, Charles, Marshall, Andrew R., Poulsen, John, Alvarez-Loyayza, Patricia, Andrade, Ana, Angbonga-Basia, Albert, Araujo-murakami, Alejandro, Arroyo, Luzmila, Ayyappan, Narayanan, de Azevedo, Celso Paulo, Banki, Olaf, Barbier, Nicolas, Barroso, Jorcely G., Beeckman, Hans, Bitariho, Robert, Boeckx, Pascal, Boehning-Gaese, Katrin, Brandão, Hilandia, Brearley, Francis Q., Breuer Ndoundou Hockemba, Mireille, Brienen, Roel, Camargo, Jose Luis C., Campos-Arceiz, Ahimsa, Cassart, Benoit, Chave, Jerome, Chazdon, Robin, Chuyong, Georges, Clark, David B., Clark, Connie J., Condit, Richard, Honorio Coronado, Euridice, Davidar, Priya, de Haulleville, Thalès, Descroix, Laurent, Doucet, Jean-Louis, Dourdain, Aurelie, Droissart, Vincent, Duncan, Thomas, Silva Espejo, Javier, Espinosa, Santiago, Farwig, Nina, Fayolle, Adeline, Feldpausch, Ted R., Ferraz, Antonio, Fletcher, Christine, Gajapersad, Krisna, Gillet, Jean-François, Amaral, Iêda Leão do, Gonmadje, Christelle, Grogan, James, Harris, David, Herzog, Sebastian K., Homeier, Jürgen, Hubau, Wannes, Hubbell, Stephen P., Hufkens, Koen, Hurtado, Johanna, Kamdem, Narcisse G., Kearsley, Elizabeth, Kenfack, David, Kessler, Michael, Labrière, Nicolas, Laumonier, Yves, Laurance, Susan, Laurance, William F., Lewis, Simon L., Libalah, Moses B., Ligot, Gauthier, Lloyd, Jon, Lovejoy, Thomas E., Malhi, Yadvinder, Marimon, Beatriz S., Marimon Junior, Ben Hur, Martin, Emmanuel H., Matius, Paulus, Meyer, Victoria, Mendoza Bautista, Casimero, Monteagudo-Mendoza, Abel, Mtui, Arafat, Neill, David, Parada Gutierrez, Germaine Alexander, Pardo, Guido, Parren, Marc, Parthasarathy, N., Phillips, Oliver L., Pitman, Nigel C.A., Ploton, Pierre, Ponette, Quentin, Ramesh, B.R., Razafimahaimodison, Jean-Claude, Réjou-Méchain, Maxime, Rolim, Samir Gonçalves, Saltos, Hugo Romero, Rossi, Luiz Marcelo Brum, Spironello, Wilson Roberto, Rovero, Francesco, Saner, Philippe, Sasaki, Denise, Schulze, Mark, Silveira, Marcos, Singh, James, Sist, Plinio, Sonké, Bonaventure, Soto, J. Daniel, de Souza, Cintia Rodrigues, Stropp, Juliana, Sullivan, Martin J.P., Swanepoel, Ben, Steege, Hans ter, Terborgh, John, Texier, Nicolas, Toma, Takeshi, Valencia, Renato, Valenzuela, Luis, Valle Ferreira, Leandro, Cornejo Valverde, Fernando, Van Andel, Tinde R., Vásquez, Rodolfo, Verbeeck, Hans, Vivek, Pandi, Vleminckx, Jason, Vos, Vincent A., Wagner, Fabien H., Warsudi, Papi Puspa, Wortel, Verginia, Zagt, Roderick J., and Zebaze, Donatien (2018) Pan-tropical prediction of forest structure from the largest trees. Global Ecology and Biogeography. (In Press)

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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 above ground 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.

Item ID: 55868
Item Type: Article (Research - C1)
ISSN: 1466-8238
Keywords: carbon, climate change, forest structure, large trees, pan-tropical, REDD+, tropical forest ecology
Copyright Information: © 2018 John Wiley & Sons Ltd
Funders: Fond National pour la Recherche Scientifique, Ecole Régionale Post-Universitaire d'Aménagement et de Gestion Intégrés des Forêts Tropicales, World Wide Fund for Nature (WWF), Belgian Science Policy Office (BELSPO), French Foreign Affairs, Centre de Coopération Internationale en Recherche Agronomique pour le Développement (CIRAD, Coopération et d’Action Culturelle (SCAC), Andrew Mellon Foundation, National Science Foundation (NSF), Conselho Nacional de Desenvolvimento Científico e Tecnológico, Brazil (CNPq), National Academy of Science, USA (USA-NAS), Fundação de Amaparo à Pesquisa do Estado de Mato Grosso (FAPEMAT)
Projects and Grants: WWF ANR-12-EBID-0002, BELSPO COBIMFO project, NSF DEB 0742830, CNPq/FAPEMAT 403725/2012-7, CNPq/FAPEMAT 441244/2016-5, CNPq/FAPEMAT 164131/2013, CNPq-PPBio 457602/2012-0, CNPq/PQ-2, USA-NAS/PEER #PGA-2000005316, FAPEMAT 0589267/2016
Date Deposited: 16 Oct 2018 04:25
FoR Codes: 06 BIOLOGICAL SCIENCES > 0602 Ecology > 060208 Terrestrial Ecology @ 100%
SEO Codes: 96 ENVIRONMENT > 9608 Flora, Fauna and Biodiversity > 960805 Flora, Fauna and Biodiversity at Regional or Larger Scales @ 100%
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