Estimation de la Biomasse des Arbres et Incertitudes Associées (Revue Bibliographique)
Keywords:
Biomasse, incertitude, équation allométrique, variable dendrométrique, TélédétectionAbstract
La mesure des stocks et flux de carbone forestier est absolument essentielle pour comprendre le rôle que jouent les forêts dans le cycle global du carbone et pour mettre en place des politiques efficaces d’atténuation du réchauffement climatique mondial induit par l’augmentation des gaz à effet de serre d’origine anthropique. Cette revue bibliographique vise à présenter l’état actuel des connaissances sur les incertitudes associées à la quantification du carbone forestier, en particulier dans les forêts tropicales. Plusieurs études montrent que les incertitudes sur les stocks et flux de carbone séquestrés dans les forêts tropicales sont extrêmement larges, estimés respectivement 188 et 272 milliards de tonnes de carbone et entre 0.17 et 1.16 milliards de tonnes de gaz carbonique. Ces énormes incertitudes sont sans doute liées aux méthodes utilisées pour quantifier la biomasse des arbres vivants. La revue bibliographique montre en effet que dans la quasitotalité des études sur le carbone forestier, la biomasse des arbres n’est réellement jamais mesurée sur le terrain, mais plutôt estimés à l’aide des modèles mathématiques ou équations allométriques qui transforment les données d’inventaire forestier en stocks et flux de carbone. L’estimation de carbone comporte en conséquence une incertitude dont l’amplitude pourrait dépendre de : (i) la méthode de collecte des données la biomasse aérienne (ii) la mesure des attributs de taille (diamètre et hauteur) des arbres et traits d’espèces (densité du spécifique du bois, taille de la canopée) lors des inventaires forestiers, (iii) la forme mathématique et qualité d’ajustement des modèles allométriques (erreur propre du modèle) employés, et (iv) possiblement d’une inadéquation entre structure diamétrique des arbres dans les données de calibration des modèles et dans les inventaires forestiers. Toutefois, l’absence d’études ayant mesuré la biomasse totale d’une forêt à une échelle spatiale fixée (exemple 1 ha) ne permet pas actuellement d’évaluer la contribution de chaque source d’erreurs sur l’incertitude totale de l’estimation finale de carbone.
Measuring forest carbon stocks and fluxes is absolutely essential for understanding the role that forests play in the global carbon cycle and for developing effective policies to mitigate global warming induced by increasing greenhouse gases of anthropogenic origin. This bibliographic review aims to present the current state of knowledge on the uncertainties associated with the quantification of forest carbon, particularly in tropical forests. Several studies show that the uncertainties on the carbon stocks and fluxes sequestered in tropical forests are extremely large, estimated respectively at 188 and 272 billion tonnes of CO2and between 0.17 and 1.16 billion tonnes of CO2. These huge uncertainties are probably related to the methods used to quantify the biomass of living trees. The bibliographical review indeed shows that in almost all studies on forest carbon, the biomass of trees is never really measured in the field, but rather estimated using mathematical models or allometric equations which transform the data inventory of carbon stocks and fluxes. The carbon estimate therefore includes an uncertainty, the magnitude of which could depend on: (i) the above-ground biomass data collection method (ii) the measurement of tree size attributes (diameter and height) and tree traits species (specific density of the wood, size of the canopy) during forest inventories, (iii) the mathematical form and quality of adjustment of the allometric models (specific error of the model) used, and (iv) possibly a mismatch between diameter structure of trees in model calibration data and in forest inventories. However, the absence of studies having measured the total biomass of a forest at a fixed spatial scale (example 1 ha) does not currently allow an assessment of the contribution of each source of error to the total uncertainty of the final carbon estimate.
References
Alder, D., and T. J. Synnott. 1992. Permanent sample plot techniques
for mixed tropical forest. Oxford Forestry Institute, University of
Oxford.
Araújo, T. s. M., N. Higuchi, and J. A. de Carvalho Júnior. 1999.
Comparison of formulae for biomass content determination in a
tropical rain forest site in the state of Pará, Brazil. Forest Ecology and
Management 117:43-52.
Bauwens, S., A. Fayolle, S. Gourlet‐Fleury, L. M. Ndjele, C. Mengal,
and P. Lejeune. 2017. Terrestrial photogrammetry: a non‐destructive
method for modelling irregularly shaped tropical tree trunks.
Methods in Ecology and Evolution 8:460-471.
Bauwens, S., P. Ploton, A. Fayolle, G. Ligot, J. J. Loumeto, P.
Lejeune, and S. Gourlet-Fleury. 2021. A 3D approach to model the
taper of irregular tree stems: making plots biomass estimates
comparable in tropical forests. Ecological Applications 31:e02451.
Belyea, H.C. (1931) Forest Measurement. Wiley & Sons, New York,
NY, USA; Chapman & Hall, London, UK.
Blanchard, E., P. Birnbaum, T. Ibanez, T. Boutreux, C. Antin, P.
Ploton, G. Vincent, R. Pouteau, H. Vandrot, and V. Hequet. 2016.
Contrasted allometries between stem diameter, crown area, and tree
height in five tropical biogeographic areas. Trees 30:1953-1968.
Brown, S. 1997. Estimating biomass and biomass change of tropical
forests: a primer. Food & Agriculture Org.
Brown, S., A. J. Gillespie, and A. E. Lugo. 1989. Biomass estimation
methods for tropical forests with applications to forest inventory data.
Forest science 35:881-902.
Burt, A., K. Calders, A. Cuni-Sanchez, J. Gómez-Dans, P. Lewis, S.
L. Lewis, Y. Malhi, O. L. Phillips, and M. Disney. 2020. Assessment
of bias in pan-tropical biomass predictions. Frontiers in Forests and
Global Change 3:12.
Calders, K., G. Newnham, M. Herold, S. Murphy, D. Culvenor, P.
Raumonen, A. Burt, J. Armston, V. Avitabile, and M. Disney. 2013.
Estimating above ground biomass from terrestrial laser scanning in
Australian Eucalypt Open Forest. Pages 90-97 in Proceedings
SilviLaser 2013, 9-11 October, Beijing, China.
Chave, J., R. Condit, S. Aguilar, A. Hernandez, S. Lao, and R. Perez.
Error propagation and scaling for tropical forest biomass
estimates. Philosophical Transactions of the Royal Society of
London. Series B: Biological Sciences 359:409-420.
Chave, J., M. Réjou‐Méchain, A. Búrquez, E. Chidumayo, M. S.
Colgan, W. B. Delitti, A. Duque, T. Eid, P. M. Fearnside, and R. C.
Goodman. 2014. Improved allometric models to estimate the
aboveground biomass of tropical trees. Glob Chang Biol 20:3177-
Clark, D. B., J. R. Kellner, and M. Palmer. 2012. Tropical forest
biomass estimation and the fallacy of misplaced concreteness.
Journal of Vegetation Science 23:1191-1196
Condit, R. 1998. Tropical forest census plots: methods and results
from Barro Colorado Island, Panama and a comparison with other
plots. Springer Science & Business Media.
Dutcă, I., R. Mather, and F. Ioraș. 2020. Sampling trees to develop
allometric biomass models: How does tree selection affect model
prediction accuracy and precision? Ecological Indicators 117:106553.
Fayolle, A., J.-L. Doucet, J.-F. Gillet, N. Bourland, and P. Lejeune.
Tree allometry in Central Africa: Testing the validity of
pantropical multi-species allometric equations for estimating biomass
and carbon stocks. Forest Ecology and Management 305:29-37.
Fayolle, A., A. Ngomanda, M. Mbasi, N. Barbier, Y. Bocko, F.
Boyemba, P. Couteron, N. Fonton, N. Kamdem, J. Katembo, H. J.
Kondaoule, J. Loumeto, H. M. Maïdou, G. Mankou, T. Mengui, G.
Mofack, II, C. Moundounga, Q. Moundounga, L. Nguimbous, N.
Nsue Nchama, D. Obiang, F. Ondo Meye Asue, N. Picard, V. Rossi,
Y.-P. Senguela, B. Sonké, L. Viard, O. D. Yongo, L. Zapfack, and V.
P. Medjibe. 2018. A regional allometry for the Congo basin forests
based on the largest ever destructive sampling. Forest Ecology and
Management 430:228-240.
Gomes, A. C., A. Andrade, J. S. Barreto‐Silva, T. Brenes‐Arguedas,
D. C. López, C. C. de Freitas, C. Lang, A. A. de Oliveira, A. J. Pérez,
and R. Perez. 2013. Local plant species delimitation in a highly
diverse A mazonian forest: do we all see the same species? Journal of
Vegetation Science 24:70-79.
Gonzalez de Tanago, J., A. Lau, H. Bartholomeus, M. Herold, V.
Avitabile, P. Raumonen, C. Martius, R. C. Goodman, M. Disney, and
S. Manuri. 2018. Estimation of above‐ground biomass of large
tropical trees with terrestrial LiDAR. Methods in Ecology and
Evolution 9:223-234.
Goodman, R. C., O. L. Phillips, and T. R. Baker. 2014. The
importance of crown dimensions to improve tropical tree biomass
estimates. Ecological Applications 24:680-698.
Henry, M., A. Besnard, W. Asante, J. Eshun, S. Adu-Bredu, R.
Valentini, M. Bernoux, and L. Saint-André. 2010. Wood density,
phytomass variations within and among trees, and allometric
equations in a tropical rainforest of Africa. Forest Ecology and
Management 260:1375-1388.
Hubau, W., S. L. Lewis, O. L. Phillips, K. Affum-Baffoe, H.
Beeckman, A. Cuní-Sanchez, A. K. Daniels, C. E. Ewango, S.
Fauset, and J. M. Mukinzi. 2020. Asynchronous carbon sink
saturation in African and Amazonian tropical forests. Nature 579:80-
Imani, G., L. Zapfack, J. Kalume, B. Riera, L. Cirimwami, and F.
Boyemba. 2016. Woody vegetation groups and diversity along the
altitudinal gradient in mountain forest: case study of Kahuzi-Biega
National Park and its surroundings, RD Congo. Journal of
Biodiversity and Environmental Sciences 8:134-150.
King, D. A. 1996. Allometry and life history of tropical trees. Journal
of Tropical Ecology 12:25-44.
Larjavaara, M., and H. C. Muller‐Landau. 2013. Measuring tree
height: a quantitative comparison of two common field methods in a
moist tropical forest. Methods in Ecology and Evolution 4:793-801.
Milliken2, W. 1998. Structure and Composition of One Hectare of
Central Amazonian Terra Firme Forest 1. Biotropica 30:530-537.
Mitchard, E. T., S. S. Saatchi, A. Baccini, G. P. Asner, S. J. Goetz, N.
L. Harris, and S. Brown. 2013. Uncertainty in the spatial distribution
of tropical forest biomass: a comparison of pan-tropical maps.
Carbon balance and management 8:1-13.
Momo Takoudjou, S., P. Ploton, B. Sonké, J. Hackenberg, S. Griffon,
F. De Coligny, N. G. Kamdem, M. Libalah, G. I. Mofack, and G. Le
Moguédec. 2018. Using terrestrial laser scanning data to estimate
large tropical trees biomass and calibrate allometric models: A
comparison with traditional destructive approach. Methods in
Ecology and Evolution 9:905-916.
Moundounga Mavouroulou, Q., A. Ngomanda, N. L. Engone Obiang,
J. Lebamba, H. Gomat, G. S. Mankou, J. Loumeto, D. Midoko
Iponga, F. Kossi Ditsouga, R. Zinga Koumba, K. H. Botsika Bobé,
N. Lépengué, B. Mbatchi, and N. Picard. 2014. How to improve
allometric equations to estimate forest biomass stocks? Some hints
from a central African forest. Canadian Journal of Forest Research
:685-691.
Ngomanda, A., Q. M. Mavouroulou, N. L. E. Obiang, D. M. Iponga,
J.-F. Mavoungou, N. Lépengué, N. Picard, and B. Mbatchi. 2012.
Derivation of diameter measurements for buttressed trees, an
example from Gabon. Journal of Tropical Ecology 28:299-302.
Ngomanda, A., N. L. E. Obiang, J. Lebamba, Q. M. Mavouroulou, H.
Gomat, G. S. Mankou, J. Loumeto, D. M. Iponga, F. K. Ditsouga,
and R. Z. Koumba. 2014. Site-specific versus pantropical allometric
equations: which option to estimate the biomass of a moist central
African forest? Forest Ecology and Management 312:1-9.
Niklas, K. J. 1994. Plant allometry: the scaling of form and process.
University of Chicago Press.
Noelke, N., L. Fehrmann, S. J. I Nengah, T. Tiryana, D. Seidel, and
C. Kleinn. 2015. On the geometry and allometry of big-buttressed
trees-a challenge for forest monitoring: new insights from 3Dmodeling
with terrestrial laser scanning. iForest-Biogeosciences and
Forestry 8:574.
Nogueira, E. M., B. W. Nelson, and P. M. Fearnside. 2006. Volume
and biomass of trees in central Amazonia: influence of irregularly
shaped and hollow trunks. Forest Ecology and Management 227:14-
Pan, Y., R. A. Birdsey, J. Fang, R. Houghton, P. E. Kauppi, W. A.
Kurz, O. L. Phillips, A. Shvidenko, S. L. Lewis, and J. G. Canadell.
A large and persistent carbon sink in the world’s forests.
science 333:988-993.
Paul, K. I., P. J. Radtke, S. H. Roxburgh, J. Larmour, R. Waterworth,
D. Butler, K. Brooksbank, and F. Ximenes. 2018. Validation of
allometric biomass models: How to have confidence in the
application of existing models. Forest Ecology and Management
:70-79.
Pelletier, J., D. Martin, and C. Potvin. 2013. REDD+ emissions
estimation and reporting: dealing with uncertainty. Environmental
Research Letters 8:034009.
Picard, N., and S. Gourlet-Fleury. 2008. Manuel de référence pour
l'installation de dispositifs permanents en forêt de production dans le
Bassin du Congo. COMIFAC.
Picard, N., E. Rutishauser, P. Ploton, A. Ngomanda, and M. Henry.
Should tree biomass allometry be restricted to power models?
Forest Ecology and Management 353:156-163.
Pilli, R., T. Anfodillo, and M. Carrer. 2006. Towards a functional and
simplified allometry for estimating forest biomass. Forest Ecology
and Management 237:583-593.
Ploton, P., N. Barbier, S. Takoudjou Momo, M. Réjou-Méchain, F.
Boyemba Bosela, G. Chuyong, G. Dauby, V. Droissart, A. Fayolle,
and R. C. Goodman. 2016. Closing a gap in tropical forest biomass
estimation: taking crown mass variation into account in pantropical
allometries. Biogeosciences 13:1571-1585.
Poorter, L., L. Bongers, and F. Bongers. 2006. Architecture of 54
moist‐forest tree species: traits, trade‐offs, and functional groups.
Ecology 87:1289-1301.
Réjou-Méchain, M., N. Barbier, P. Couteron, P. Ploton, G. Vincent,
M. Herold, S. Mermoz, S. Saatchi, J. Chave, F. de Boissieu, J.-B.
Féret, S. M. Takoudjou, and R. Pélissier. 2019. Upscaling Forest
Biomass from Field to Satellite Measurements: Sources of Errors and
Ways to Reduce Them. Surveys in Geophysics 40:881-911.
Saatchi, S. S., N. L. Harris, S. Brown, M. Lefsky, E. T. Mitchard, W.
Salas, B. R. Zutta, W. Buermann, S. L. Lewis, and S. Hagen. 2011.
Benchmark map of forest carbon stocks in tropical regions across
three continents. Proceedings of the national academy of sciences
:9899-9904.
Shinozaki, K., K. Yoda, K. Hozumi, and T. Kira. 1964. A
quantitative analysis of plant form-the pipe model theory: I. Basic
analyses. Japanese Journal of ecology 14:97-105.
Sileshi, G. W. 2014. A critical review of forest biomass estimation
models, common mistakes and corrective measures. Forest Ecology
and Management 329:237-254.
Slik, J. F., G. Paoli, K. McGuire, I. Amaral, J. Barroso, M. Bastian,
L. Blanc, F. Bongers, P. Boundja, and C. Clark. 2013. Large trees
drive forest aboveground biomass variation in moist lowland forests
across the tropics. Global ecology and biogeography 22:1261-1271.
Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K. Averyt,
M. Tignor, and H. L. Miller. 2007. IPCC, 2007: Climate change
: The physical science basis. Contribution of Working Group I
to the fourth assessment report of the Intergovernmental Panel on
Climate Change. SD Solomon (Ed.).
Tao, S., F. Wu, Q. Guo, Y. Wang, W. Li, B. Xue, X. Hu, P. Li, D.
Tian, and C. Li. 2015. Segmenting tree crowns from terrestrial and
mobile LiDAR data by exploring ecological theories. ISPRS Journal
of Photogrammetry and Remote Sensing 110:66-76.
Ter-Mikaelian, M. T., and M. D. Korzukhin. 1997. Biomass
equations for sixty-five North American tree species. Forest Ecology
and Management 97:1-24.
Trochta, J., M. Krůček, T. Vrška, and K. Král. 2017. 3D Forest: An
application for descriptions of three-dimensional forest structures
using terrestrial LiDAR. PloS one 12:e0176871.
Wassenberg, M., M. Schinker, and H. Spiecker. 2015. Technical
aspects of applying high frequency densitometry: Probe-sample
contact, sample surface preparation and integration width of different
dielectric probes. Dendrochronologia 34:10-18.
West, G. B., J. H. Brown, and B. J. Enquist. 1997. A general model
for the origin of allometric scaling laws in biology. science 276:122-
West, G. B., J. H. Brown, and B. J. Enquist. 1999. A general model
for the structure and allometry of plant vascular systems. Nature
:664-667
Whittaker, R. H., and G. M. Woodwell. 1968. Dimension and
production relations of trees and shrubs in the Brookhaven Forest,
New York. The Journal of Ecology:1-25.
Williamson, G. B., and M. C. Wiemann. 2010. Measuring wood
specific gravity correctly. American Journal of Botany 97:519-524.
Yanai, R. D., C. Wayson, D. Lee, A. Espejo, J. L. Campbell, M. B.
Green, J. M. Zukswert, S. Yoffe, J. Aukema, and A. Lister. 2020.
Improving uncertainty in forest carbon accounting for REDD+
mitigation efforts. Environmental Research Letters 15:124002.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2022 ESI Preprints
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
