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Pan-tropical prediction of forest structure from the largest trees

Bastin, JF and Rutishauser, E and Kellner, JR and Saatchi, S and Pélissier, R and Hérault, B and Slik, F and Bogaert, J and De Cannière, C and Marshall, AR and Poulsen, J and Alvarez-Loyayza, P and Andrade, A and Angbonga-Basia, A and Araujo-Murakami, A and Arroyo, L and Ayyappan, N and de Azevedo, CP and Banki, O and Barbier, N and Barroso, JG and Beeckman, H and Bitariho, R and Boeckx, P and Boehning-Gaese, K and Brandão, H and Brearley, FQ and Breuer Ndoundou Hockemba, M and Brienen, R and Camargo, JLC and Campos-Arceiz, A and Cassart, B and Chave, J and Chazdon, R and Chuyong, G and Clark, DB and Clark, CJ and Condit, R and Honorio Coronado, EN and Davidar, P and de Haulleville, T and Descroix, L and Doucet, JL and Dourdain, A and Droissart, V and Duncan, T and Silva Espejo, J and Espinosa, S and Farwig, N and Fayolle, A and Feldpausch, TR and Ferraz, A and Fletcher, C and Gajapersad, K and Gillet, JF and Amaral, ILD and Gonmadje, C and Grogan, J and Harris, D and Herzog, SK and Homeier, J and Hubau, W and Hubbell, SP and Hufkens, K and Hurtado, J and Kamdem, NG and Kearsley, E and Kenfack, D and Kessler, M and Labrière, N and Laumonier, Y and Laurance, S and Laurance, WF and Lewis, SL and Libalah, MB and Ligot, G and Lloyd, J and Lovejoy, TE and Malhi, Y and Marimon, BS and Marimon Junior, BH and Martin, EH and Matius, P (2018) Pan-tropical prediction of forest structure from the largest trees. Global Ecology and Biogeography, 27 (11). pp. 1366-1383. ISSN 1466-822X

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Abstract

© 2018 John Wiley & Sons Ltd 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.

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