SD3D theme - 3D Structure and Dynamics of Tropical Forests

Description

Background

The structure of tropical forest stands can be seen both as an adaptation to environmental conditions, but also as a marker of this environment and of changes that have occurred. In a context of strong anthropogenic and climatic pressures on ecosystems and biodiversity, the challenge is to better characterize the functional diversity of different types of tropical forests through a better description of forest structure. This is the key to better assess, for example, the role of forests in biogeochemical cycles between land surfaces and the atmosphere (carbon sink/source). Our approach is based on privileged access to field sites in the tropics and know-how in the acquisition of forest data. It is from this field work and the creation of historical databases on study sites that we are attempting to develop measurement methods, 3D structure, dynamic and visualization models of tropical forest stands (mangroves and terra firma) that can account for the complexity and heterogeneity of tropical forest cover at different spatial scales by seeking to understand the origin of the observed changes. As the challenge of characterizing forest structures over large areas and varied environmental situations cannot be satisfied only with forest inventories, we are involved in research projects in remote sensing (radar, optics, lidar) and also in the preparation of future satellite sensors dedicated to the observation of forest characteristics. Practically, at the scale of individuals, including large ones, we are trying to improve measurement protocols to, for example, quantify the volumes of carrier wood, the shape, plasticity and porosity of tree crowns or the arrangement of leaves. At the same time, at the level of forest stands and then at the regional level, we integrate individual characteristics while trying to find emerging properties as a whole through, for example, the analysis of canopies.

Objectives

  •  Establish a current state of often unknown forests over large areas;
  •  Give retrospective assessments on certain regions or forest types with a perspective of several years or even decades to analyse past transformations;
  •  Lay the foundations for evolution scenarios that integrate the knowledge obtained.

Expected Results

  •  New allometric models relevant for the evaluation of aerial biomass based on a better consideration of crown plasticity or even a quantified architectural typology of tropical trees;
  •  Mapping of fine-scale and multi-date forest parameters on dense humid forests and mangroves;
  •  In the context of ecological successions, evaluation of variations in functional strategies with particular attention to the role of intraspecific variation in ecophysiological and architectural traits;
  •  Evaluation of the effect of the variation in frequency of disturbance in systems under high anthropogenic pressure (pastures, tropical forests, road infrastructure, etc.);

Significant events

  •  R. Pélissier guest speaker at the Annual Symposium of the Brazilian National Forest Inventory in 2016;
  •  N. Barbier guest speaker at the 25th Brazilian Symposium on Remote Sensing in 2015 and at the Royal British Society Meeting on Phenology in 2018.

Main funded projects

Acronym Title Duration
FORESTSCANNew technology for characterising forest structure and biomass at ‘Super Sites’ for EO cal/val across the tropics2019 - 2021
PROFEAACPROmouvoir et Formaliser l’Exploitation Artisanale du bois d’œuvre en Afrique Centrale par une approche multi-scalaire : gestion territorialisée de la ressource, gouvernance de la filière, promotion des demandes de sciages légaux2019 - 2023
TALL TREESA 3D perspective on the effects of topography and wind on forest height and dynamics2019 - 2023
CARTO GIZCartographie de l'occupation du sol en appui à l'aménagement au Cameroun2019 - 2019
3DFORMODCombining remote sensing and 3D forest modelling to improve tropical forests monitoring of GHC emissions2018 - 2020
CARTO NHPCCartographie du couvert végétal et de sa dynamique en appui au suivi d'impact du barrage de Nachtigal Amont2018 - 2020
CARTODIV-DENDROLIDARReconnaissance spécifique et cartographie des arbres de la canopée en forêt tropicale ET télédétection individu centrée pour l'évaluation de la ressource en bois d'œuvre en Guyane française2017 - 2020
LEAF EXPVALLeaf ExpVal2017 - 2018
STEMSpatial and temporal dynamics in mangrove carbon pools2016 - 2016
CARBOSHAREASIASharing experience on forest carbon stock assessment and mapping in South Asia2016 - 2017
BIOMAP Intégration de données spatialisées multi-échelles pour la cartographie des types de forêt et de la biomasse en Amapà et Guyane2015 - 2019
FORESTFully Optimised and Reliable Emissions Tool 2014 - 2016
INDESOMangrove & Integrated Coastal Zone Management Application2013 - 2017
EFABControlling for upscaling uncertainty in assessment of forest aboveground biomass in the Western Ghats of India2013 - 2017
STEM-LEAFSTudies based on Experimental and Modelled wavefor for the LEAF (Lidar for Earth And Forests) mission2013 - 2016

Thèses soutenues

  •  Fayad, I. 2015. Estimation of tree height at the regional scale: application to French Guiana. Thesis ED I2S, University of Montpellier. 183 pp. (Co-Director N. Baghdadi & N. Barbier, EADS/Noveltis Industry Exchange). Become: ATER.
  •  Blanchard, E. 2016. Structural diversity of the dense humid forests of the Northern Province of New Caledonia: from tree to landscape. Thesis ED Gaia, Univ. Montpellier. 230 pp. (Co-Director P. Couteron & P. Birnbaum, research contract funding). Become: Post-doctoral fellow at UPR CIRAD Forêt & Sociétés, Montpellier.
  •  Olagoke, A. 2016. Towards a better characterization of morphological plasticity and partitioning of mangrove biomass for the study of mangrove forest dynamics. Thesis in cotutelle, ED Gaia, AgroParisTech and TU Dresden. 171 pp. (Co-Director U. Berger & C. Proisy, European Doctoral Program FONASO). Current Position: post-doc, Univ. Bremen, Germany.
  •  Ploton, P., 2017. Improving tropical forest aboveground biomass estimations: insights from canopy trees structure and spatial organization. Thesis in Co superivised, ED Gaia, AgroParisTech et TU Dresden. 112 pp (Co-dir R. Pélissier & U. Berger, Programme doctoral européen FONASO). Devenir : Post-doctorant UMR AMAP, Montpellier.
  •  Tymen, B. 2015. Determinants of tropical forest structure and dynamics at the landscape scale. Thesis Univ. Toulouse 3. 232 pp. (Co-Director J. Chave & G. Vincent, PhD supervisor). Current Position: High school teacher.
  • Theses in progress

    •  Momo Takoudjou, S. 2015-2019. Use of 3D imagery for indirect and non-destructive estimation of above-ground tree biomass in Cameroon's tropical rainforest. U. Yaoundé 1 (Co-Director B. Sonké & N. Barbier; ARTS-IRD scholarship, Cameroon)
    •  Sagang Takougoum, L. 2018-2021. Study of the dynamics of forest-savannah contact in a tropical wooded savannah ecosystem in the Central Cameroon region. U. Yaoundé 1 (Co-Director N. Barbier & B. Sonké; ARTS-IRD scholarship, NHPC Project, Cameroon)
    •  Mofack, G.II 2018-2021. Effect of architectural types and species on Biomass allometries: case of low and medium altitude semi-deciduous forests in the East Cameroon region. U. Yaoundé 1 (Co-Director B. Sonké, P. Couteron & N. Barbier; NHPC Project, Cameroon)
Main scientific production 2019-2020
Publications HAL de la collection AMAP

2020

Journal articles

ref_biblio
Clément Bourgoin, Julie Betbeder, Pierre Couteron, Lilian Blanc, Hélène Dessard, et al.. UAV-based canopy textures assess changes in forest structure from long-term degradation. Ecological Indicators, Elsevier, 2020, 115, pp.106386. ⟨10.1016/j.ecolind.2020.106386⟩. ⟨hal-02566581⟩
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https://hal.archives-ouvertes.fr/hal-02566581/file/Bourgoin_etal_Preprint_Ecological_Indicators_2020_115.pdf BibTex
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Claire Fortunel, Clement Stahl, Patrick Heuret, Eric Nicolini, Christopher Baraloto. Disentangling the effects of environment and ontogeny on tree functional dimensions for congeneric species in tropical forests. New Phytologist, Wiley, 2020, 226 (2), pp.385-395. ⟨10.1111/nph.16393⟩. ⟨hal-02448421⟩
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Jens Kattge, Gerhard Bonisch, Sandra Díaz, Sandra Lavorel, Iain Colin Prentice, et al.. TRY plant trait database – enhanced coverage and open access. Global Change Biology, Wiley, 2020, 26 (1), pp.119-188. ⟨10.1111/gcb.14904⟩. ⟨hal-02434220⟩
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Moses Libalah Bakonck, Vincent Droissart, Bonaventure Sonké, Nicolas Barbier, Gilles Dauby, et al.. Additive influences of soil and climate gradients drive tree community composition of Central African rainforests. Journal of Vegetation Science, Wiley, In press, ⟨10.1111/jvs.12918⟩. ⟨hal-02885165⟩
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Stephane Momo Takoudjou, Pierre Ploton, Olivier Martin-Ducup, Romain Lehnebach, Claire Fortunel, et al.. Leveraging Signatures of plant functional Strategies in Wood Density Profiles of African Trees to correct Mass estimations from terrestrial Laser Data. Scientific Reports, Nature Publishing Group, 2020, 10 (1), pp.2001. ⟨10.1038/s41598-020-58733-w⟩. ⟨hal-02470476⟩
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https://hal.umontpellier.fr/hal-02470476/file/Momo_etal_Scientific_Reports_2020_10_1.pdf BibTex
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Le Bienfaiteur Sagang Takougoum, Pierre Ploton, Bonaventure Sonké, Hervé Poilvé, Pierre Couteron, et al.. Airborne Lidar Sampling Pivotal for Accurate Regional AGB Predictions from Multispectral Images in Forest-Savanna Landscapes. Remote Sensing, MDPI, 2020, 12 (10), pp.1637. ⟨10.3390/rs12101637⟩. ⟨hal-02619063⟩
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https://hal.umontpellier.fr/hal-02619063/file/SagangT_etal_Remote_sensing_2020_12_10.pdf BibTex
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Robert Schneider, Rafael Calama, Olivier Martin-Ducup. Understanding Tree-to-Tree Variations in Stone Pine (Pinus pinea L.) Cone Production Using Terrestrial Laser Scanner. Remote Sensing, MDPI, 2020, 3D Forest Structure Observation, 12 (1), pp.173. ⟨10.3390/rs12010173⟩. ⟨hal-02459699⟩
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https://hal.umontpellier.fr/hal-02459699/file/remotesensing-12-00173.pdf BibTex
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Di Wang, Stephane Momo Takoudjou, Eric Casella. LeWoS: A universal leaf‐wood classification method to facilitate the 3D modelling of large tropical trees using terrestrial LiDAR. Methods in Ecology and Evolution, Wiley, 2020, 11 (3), pp.376-389. ⟨10.1111/2041-210X.13342⟩. ⟨hal-02516966⟩
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2019

Journal articles

ref_biblio
Mélaine Aubry-Kientz, Vivien Rossi, Guillaume Cornu, Fabien Wagner, Bruno Hérault. Temperature rising would slow down tropical forest dynamic in the Guiana Shield. Scientific Reports, Nature Publishing Group, 2019, 9 (1), ⟨10.1038/s41598-019-46597-8⟩. ⟨hal-02185274⟩
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https://hal.umontpellier.fr/hal-02185274/file/Aubry-Kientz_etal_Scientifc_Reports_2019_9_1.pdf BibTex
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Mélaine Aubry-Kientz, Raphaël Dutrieux, António Ferraz, Sassan Saatchi, Hamid Hamraz, et al.. A Comparative Assessment of the Performance of Individual Tree Crowns Delineation Algorithms from ALS Data in Tropical Forests. Remote Sensing, MDPI, 2019, 11 (9), pp.1086. ⟨10.3390/rs11091086⟩. ⟨hal-02131202⟩
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https://hal.archives-ouvertes.fr/hal-02131202/file/Aubry-Kientz_%26_vincent_etal_Remote_Sens_2019_11_9.pdf BibTex
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J.-B. Féret, G. Le Maire, S. Jay, D. Berveiller, R. Bendoula, et al.. Estimating leaf mass per area and equivalent water thickness based on leaf optical properties: Potential and limitations of physical modeling and machine learning. Remote Sensing of Environment, Elsevier, 2019, 231, pp.110959. ⟨10.1016/j.rse.2018.11.002⟩. ⟨hal-02109661⟩
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Guillaume Giroud, Robert Schneider, Richard Fournier, Joan Luther, Olivier Martin-Ducup. Modeling black spruce wood fiber attributes with terrestrial laser scanning. Canadian Journal of Forest Research, NRC Research Press, 2019, 49 (6), pp.661-669. ⟨10.1139/cjfr-2018-0342⟩. ⟨hal-02140287⟩
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Suzanne Mariëlle Marselis, Hao Tang, John Armston, Katharine Abernethy, Alfonso Alonso, et al.. Exploring the relation between remotely sensed vertical canopy structure and tree species diversity in Gabon. Environmental Research Letters, IOP Publishing, 2019, 14 (9), pp.094013. ⟨10.1088/1748-9326/ab2dcd⟩. ⟨hal-02302269⟩
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https://hal.umontpellier.fr/hal-02302269/file/Marselis_2019_Environ._Res._Lett._14_094013.pdf BibTex
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Maxime Réjou-Méchain, Nicolas Barbier, Pierre Couteron, Pierre Ploton, Grégoire Vincent, et al.. Upscaling Forest Biomass from Field to Satellite Measurements: Sources of Errors and Ways to Reduce Them. Surveys in Geophysics, Springer Verlag (Germany), 2019, 40 (4), pp.881-911. ⟨10.1007/s10712-019-09532-0⟩. ⟨hal-02189103⟩
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Dmitry Schepaschenko, Jérôme Chave, Oliver Phillips, Simon Lewis, Stuart Davies, et al.. The Forest Observation System, building a global reference dataset for remote sensing of forest biomass. Scientific Data , Nature Publishing Group, 2019, 6 (1), ⟨10.1038/s41597-019-0196-1⟩. ⟨hal-02316194⟩
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https://hal.umontpellier.fr/hal-02316194/file/Rejou-mechain_etal_Scientitfic-data_2019_6_1.pdf BibTex
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Nelly Sirri, M. Libalah, Stephane Momo Takoudjou, Pierre Ploton, V. Medjibe, et al.. Allometric Models to Estimate Leaf Area for Tropical African Broadleaved Forests. Geophysical Research Letters, American Geophysical Union, 2019, 46 (15), pp.8985-8994. ⟨10.1029/2019GL083514⟩. ⟨hal-02275384⟩
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Florent Taureau, Marc Robin, Christophe Proisy, François Fromard, Daniel Imbert, et al.. Mapping the Mangrove Forest Canopy Using Spectral Unmixing of Very High Spatial Resolution Satellite Images. Remote Sensing, MDPI, 2019, 11 (3), pp.367. ⟨10.3390/rs11030367⟩. ⟨hal-02102451⟩
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