Pan‐tropical prediction of forest structure from the largest trees. Issue 11 (10th October 2018)
- Record Type:
- Journal Article
- Title:
- Pan‐tropical prediction of forest structure from the largest trees. Issue 11 (10th October 2018)
- Main Title:
- Pan‐tropical prediction of forest structure from the largest trees
- Authors:
- 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, Jérôme
Chazdon, Robin
Chuyong, Georges
Clark, David B.
Clark, Connie J.
Condit, Richard
Honorio Coronado, Euridice N.
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
Sonke, 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
Ferreira, Leandro Valle
Valverde, Fernando Cornejo
Van Andel, Tinde R.
Vasque, Rodolfo
Verbeeck, Hans
Vivek, Pandi
Vleminckx, Jason
Vos, Vincent A.
Wagner, Fabien H.
Warsudi, Papi Puspa
Wortel, Verginia
Zagt, Roderick J.
Zebaze, Donatien
… (more) - Abstract:
- 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 theseAbstract: 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. … (more)
- Is Part Of:
- Global ecology & biogeography. Volume 27:Issue 11(2018)
- Journal:
- Global ecology & biogeography
- Issue:
- Volume 27:Issue 11(2018)
- Issue Display:
- Volume 27, Issue 11 (2018)
- Year:
- 2018
- Volume:
- 27
- Issue:
- 11
- Issue Sort Value:
- 2018-0027-0011-0000
- Page Start:
- 1366
- Page End:
- 1383
- Publication Date:
- 2018-10-10
- Subjects:
- carbon -- climate change -- forest structure -- large trees -- pan‐tropical -- REDD+ -- tropical forest ecology
Ecology -- Periodicals
Biogeography -- Periodicals
Biodiversity -- Periodicals
Macroevolution -- Periodicals
577 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1466-8238 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1111/geb.12803 ↗
- Languages:
- English
- ISSNs:
- 1466-822X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4195.390700
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 23831.xml