[en] Large tropical trees and a few dominant species were recently identified as the main structuring
elements of tropical forests. However, such result did not translate yet into quantitative approaches which are essential to understand, predict and monitor forest functions and composition over large, often poorly accessible territories. Here we show that the above-ground biomass (AGB) of the whole forest can be predicted from a few large trees and that the relationship is proved strikingly stable in 175 1-ha plots investigated across 8 sites spanning Central Africa. We designed a generic model predicting AGB with an error of 14% when based on only 5% of the stems, which points to universality in forest structural properties. For the first time in Africa, we identified some dominant species that disproportionally contribute to forest AGB with 1.5% of recorded species accounting for over 50% of the stock of AGB. Consequently, focusing on large trees and dominant species provides precise information on the whole forest stand. This offers new perspectives for understanding the functioning of tropical forests and opens new doors for the development of innovative monitoring strategies.
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Bibliography
Lindenmayer, D. B., Laurance, W. F. & Franklin, J. F. Global decline in large old trees. Science. 338, 1305-1306 (2012).
Remm, J. & Lõhmus, A. Tree cavities in forests-The broad distribution pattern of a keystone structure for biodiversity. For. Ecol. Manage. 262, 579-585 (2011).
Bagchi, R. et al. Testing the Janzen-Connell mechanism: pathogens cause overcompensating density dependence in a tropical tree. Ecol. Lett. 13, 1262-1269 (2010).
Harms, K. E., Wright, S. J., Calderón, O., Hernández, A. & Herre, E. A. Pervasive density-dependent recruitment enhances seedling diversity in a tropical forest. Nature 404, 493-495 (2000).
Royer, P. D. et al. Extreme climatic event-triggered overstorey vegetation loss increases understorey solar input regionally: primary and secondary ecological implications. J. Ecol. 99, 714-723 (2011).
Slik, J. W. F. et al. Large trees drive forest aboveground biomass variation in moist lowland forests across the tropics. Glob. Ecol. Biogeogr. 22, 1261-1271 (2013).
Lutz, J. A., Larson, A. J., Swanson, M. E. & Freund, J. A. Ecological importance of large-diameter trees in a temperate mixedconifer forest. PLoS One 7, e36131 (2012).
Stephenson, N. L. et al. Rate of tree carbon accumulation increases continuously with tree size. Nature 507, 90-93 (2014); doi: 10.1038/nature12914.
Sist, P., Mazzei, L., Blanc, L. & Rutishauser, E. Large trees as key elements of carbon storage and dynamics after selective logging in the Eastern Amazon. For. Ecol. Manage. 318, 103-109 (2014).
Chave, J., Riera, B., Dubois, M.-A. & Riéra, B. Estimation of biomass in a neotropical forest of French Guiana : spatial and temporal variability. J. Trop. Ecol. 17, 79-96 (2001).
Réjou-Méchain, M. et al. Local spatial structure of forest biomass and its consequences for remote sensing of carbon stocks. Biogeosciences. 11, 5711-5742 (2014).
Enquist, B. J. & Niklas, K. J. Invariant scaling relations across tree-dominated communities. Nature 410, 655-660 (2001).
Enquist, B. J., West, G. B., Brown, J. H., Enquist, B. J. & Brown, J. H. Extensions and evaluations of a general quantitative theory of forest structure and dynamics. Proc. Natl. Acad. Sci. USA 106, 7040-7045 (2009).
Muller-Landau, H. C. et al. Comparing tropical forest tree size distributions with the predictions of metabolic ecology and equilibrium models. Ecol. Lett. 9, 589-602 (2006).
Coomes, D. A., Duncan, R. P., Allen, R. B. & Truscott, J. Disturbances prevent stem size-density distributions in natural forests from following scaling relationships. Ecol. Lett. 6, 980-989 (2003).
Anderegg, W. R. L., Kane, J. M. & Anderegg, L. D. L. Consequences of widespread tree mortality triggered by drought and temperature stress. Nature Climate Change (2012); doi: 10.1038/nclimate1635.
Ter Steege, H. et al. Hyperdominance in the Amazonian tree flora. Science. 342, 1243092 (2013).
Fauset, S. et al. Hyperdominance in Amazonian forest carbon cycling. Nat. Commun. 6, 6857 (2015).
Grime, J. P. Benefits of plant diversity to ecosystems: immediate, filter and founder effects. J. Ecol. 86, 891-899 (1998).
Malhi, Y., Adu-Bredu, S., Asare, R. A., Lewis, S. L. & Mayaux, P. The past, present and future of Africa's rainforests. Philos. Trans. R. Soc. Lond. B. Biol. Sci. 368, 20120293 (2013).
Stegen, J. C. et al. Variation in above-ground forest biomass across broad climatic gradients. Glob. Ecol. Biogeogr. 20, 744-754 (2011).
White, L. J. T. in African Rain Forest Ecology and Conservation An Interdisciplinary Perspective (eds. Weber, W., Veder, A., Simons Morland, H., White, L. J. T. & Hart, T. B.) 3-29 (Yale University Press, 2001).
Fayolle, A. et al. A new insight in the structure, composition and functioning of central African moist forests. For. Ecol. Manage. 329, 195-205 (2014).
Gonmadje, C. F. et al. Tree diversity and conservation value of Ngovayang's lowland forests, Cameroon. Biodivers. Conserv. 20, 2627-2648 (2011).
Réjou-Méchain, M. et al. Spatial aggregation of tropical trees at multiple spatial scales. J. Ecol. 99, 1373-1381 (2011).
CBFP. The forests of the Congo Basin: state of the forest 2010. (Publications Office of the European Union, 2012); doi: 10.2788/47210.
Bastin, J.-F. et al. Aboveground biomass mapping of African forest mosaics using canopy texture analysis: toward a regional approach. Ecol. Appl. 24, 1984-2001 (2014).
Zolkos, S. G., Goetz, S. J. & Dubayah, R. A meta-analysis of terrestrial aboveground biomass estimation using lidar remote sensing. Remote Sens. Environ. 128, 289-298 (2013).
Chave, J. et al. Tree allometry and improved estimation of carbon stocks and balance in tropical forests. Oecologia 145, 87-99 (2005).
Chave, J. et al. Towards a worldwide wood economics spectrum. Ecol. Lett. 12, 351-366 (2009).
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