Résumé
Tree vigor is often used as a covariate when tree mortality is predicted from tree growth in tropical forest dynamic models, but it is rarely explicitly accounted for in a coherent modeling framework. We quantify tree vigor at the individual tree level, based on the difference between expected and observed growth. The available methods to join nonlinear tree growth and mortality processes are not commonly used by forest ecologists so that we develop an inference methodology based on an MCMC approach, allowing us to sample the parameters of the growth and mortality model according to their posterior distribution using the joint model likelihood. We apply our framework to a set of data on the 20‐year dynamics of a forest in Paracou, French Guiana, taking advantage of functional trait‐based growth and mortality models already developed independently. Our results showed that growth and mortality are intimately linked and that the vigor estimator is an essential predictor of mortality, highlighting that trees growing more than expected have a far lower probability of dying. Our joint model methodology is sufficiently generic to be used to join two longitudinal and punctual linked processes and thus may be applied to a wide range of growth and mortality models. In the context of global changes, such joint models are urgently needed in tropical forests to analyze, and then predict, the effects of the ongoing changes on the tree dynamics in hyperdiverse tropical forests.
Auteurs, date et publication :
Auteurs Mélaine Aubry-Kientz , Vivien Rossi , Jean-Jacques Boreux , Bruno Hérault
Publication : Ecology and Evolution
Date : 2015
Volume : 5
Issue : 12
Pages : 2457–2465
Catégorie(s)
#CIRAD #FORET ParacouRésumé
Synthetic aperture radar tomography (TomoSAR) is an important way of obtaining underlying topography and forest height for long-wavelength datasets such as L-band and P-band radar. It is usual to apply nonparametric spectral estimation methods with a large number of snapshots over forest areas. The nonparametric iterative adaptive approach for amplitude and phase estimation (IAA-APES) can obtain a high resolution; however, it only tends to work well with a small number of snapshots. To overcome this problem, this paper proposes the nonparametric iterative adaptive approach based on maximum likelihood estimation (IAA-ML) for the application over forest areas. IAA-ML can be directly used in forest areas, without any prior information or preprocessing. Moreover, it can work well in the case of a large number of snapshots. In addition, it mainly focuses on the backscattered power around the phase centers, helping to detect their locations. The proposed IAA-ML estimator was tested in simulated experiments and the results confirmed that IAA-ML obtains a higher resolution than IAA-APES. Moreover, six P-band fully polarimetric airborne SAR images were applied to acquire the structural parameters of a forest area. It was found that the results of the HH polarization are suitable for analyzing the ground contribution and the results of the HV polarization are beneficial when studying the canopy contribution. Based on this, the underlying topography and forest height of a test site in Paracou, French Guiana, were estimated. With respect to the Light Detection and Ranging (LiDAR) measurements, the standard deviation of the estimations of the IAA-ML TomoSAR method was 2.11 m for the underlying topography and 2.80 m for the forest height. Furthermore, compared to IAA-APES, IAA-ML obtained a higher resolution and a higher estimation accuracy. In addition, the estimation accuracy of IAA-ML was also slightly higher than that of the SKP-beamforming technique in this case study.
Auteurs, date et publication :
Auteurs Xing Peng , Xinwu Li , Changcheng Wang , Haiqiang Fu , Yanan Du
Publication : Sensors
Date : 2018
Volume : 18
Issue : 8
Catégorie(s)
#CIRAD #FORET ParacouRésumé
Background Managed forests are a major component of tropical landscapes. Production forests as designated by national forest services cover up to 400 million ha, i.e. half of the forested area in the humid tropics. Forest management thus plays a major role in the global carbon budget, but with a lack of unified method to estimate carbon fluxes from tropical managed forests. In this study we propose a new time- and spatially-explicit methodology to estimate the above-ground carbon budget of selective logging at regional scale. Results The yearly balance of a logging unit, i.e. the elementary management unit of a forest estate, is modelled by aggregating three sub-models encompassing (i) emissions from extracted wood, (ii) emissions from logging damage and deforested areas and (iii) carbon storage from post-logging recovery. Models are parametrised and uncertainties are propagated through a MCMC algorithm. As a case study, we used 38 years of National Forest Inventories in French Guiana, northeastern Amazonia, to estimate the above-ground carbon balance (i.e. the net carbon exchange with the atmosphere) of selectively logged forests. Over this period, the net carbon balance of selective logging in the French Guianan Permanent Forest Estate is estimated to be comprised between 0.12 and 1.33 Tg C, with a median value of 0.64 Tg C. Uncertainties over the model could be diminished by improving the accuracy of both logging damage and large woody necromass decay submodels. Conclusions We propose an innovating carbon accounting framework relying upon basic logging statistics. This flexible tool allows carbon budget of tropical managed forests to be estimated in a wide range of tropical regions.
Auteurs, date et publication :
Auteurs Camille Piponiot , Antoine Cabon , Laurent Descroix , Aurélie Dourdain , Lucas Mazzei , Benjamin Ouliac , Ervan Rutishauser , Plinio Sist , Bruno Hérault
Publication : Carbon Balance and Management
Date : 2016
Volume : 11
Issue : 1
Pages : 15
Catégorie(s)
#CIRAD #FORET ParacouAuteurs, date et publication :
Auteurs R.-C. Costa Pinheiro , De Deus Junior J-C , Nouvellon Y , Camargo Campoe O , Stape J-L , Lanzi A-L , Guerrini I-A , Jourdan C , J.-P. Laclau
Publication : Forest Ecology and Management
Date : 2025
Volume : 366
Pages : 143-152
Catégorie(s)
#CIRAD #FORET Itatinga #INRAEAuteurs, date et publication :
Auteurs Pierrette Chagneau , Frédéric Mortier , Nicolas Picard , Jean-Noël Bacro
Publication : Biometrics
Date : 2011
Volume : 67
Issue : 1
Pages : 97–105
Catégorie(s)
#CIRAD #FORET ParacouRésumé
Tropical forest canopies are comprised of tree crowns of multiple species varying in shape and height, and ground inventories do not usually reliably describe their structure. Airborne laser scanning data can be used to characterize these individual crowns, but analytical tools developed for boreal or temperate forests may require to be adjusted before they can be applied to tropical environments. Therefore, we compared results from six different segmentation methods applied to six plots (39 ha) from a study site in French Guiana. We measured the overlap of automatically segmented crowns projection with selected crowns manually delineated on high-resolution photography. We also evaluated the goodness of fit following automatic matching with field inventory data using a model linking tree diameter to tree crown width. The different methods tested in this benchmark segmented highly different numbers of crowns having different characteristics. Segmentation methods based on the point cloud (AMS3D and Graph-Cut) globally outperformed methods based on the Canopy Height Models, especially for small crowns; the AMS3D method outperformed the other methods tested for the overlap analysis, and AMS3D and Graph-Cut performed the best for the automatic matching validation. Nevertheless, other methods based on the Canopy Height Model performed better for very large emergent crowns. The dense foliage of tropical moist forests prevents sufficient point densities in the understory to segment subcanopy trees accurately, regardless of the segmentation method.
Auteurs, date et publication :
Auteurs Mélaine Aubry-Kientz , Raphaël Dutrieux , Antonio Ferraz , Sassan Saatchi , Hamid Hamraz , Jonathan Williams , David Coomes , Alexandre Piboule , Grégoire Vincent
Publication : Remote Sensing
Date : 2019
Volume : 11
Issue : 9
Pages : 1086
Catégorie(s)
#CIRAD #FORET ParacouRésumé
Classifying species into functional groups is a way to understand the functioning of species-rich ecosystems, or to model the dynamics of such ecosystems. Many statistical techniques have been defined to classify species into groups, and a question is whether different techniques bring consistent classifications. In a tropical rain forest in French Guiana, five species classifications have been defined by different authors for the purpose of forest growth modelling but using different data sets and different statistical techniques. The correspondence between the five classifications was measured using four indices that are generalizations of existing indices to compare two classifications. A multiple correspondence analysis was used to identify associations between groups of different classifications. In a second step, two-table multivariate analyses were used to characterize the relationships between species classifications and eight species traits (consisting of seven populational traits and one functional trait). We evidenced a consensus on the potential size of trees: species were similarly clustered by the five classifications along this trait that is correlated to turnover rate. More surprisingly, no consensus was found for growth rate, nor wood density, traits that are correlated with light requirement.
Auteurs, date et publication :
Auteurs Nicolas Picard , Peter Köhler , Frédéric Mortier , Sylvie Gourlet-Fleury
Publication : Ecological Complexity
Date : 2012
Volume : 11
Pages : 75–83
Catégorie(s)
#CIRAD #FORET ParacouRésumé
Productivity of tropical lowland moist forests is often limited by availability and functional allocation of phosphorus (P) that drives competition among tree species and becomes a key factor in determining forestall community diversity. We used non-target 31P-NMR metabolic profiling to study the foliar P-metabolism of trees of a French Guiana rainforest. The objective was to test the hypotheses that P-use is species-specific, and that species diversity relates to species P-use and concentrations of P-containing compounds, including inorganic phosphates, orthophosphate monoesters and diesters, phosphonates and organic polyphosphates. We found that tree species explained the 59% of variance in 31P-NMR metabolite profiling of leaves. A principal component analysis showed that tree species were separated along PC 1 and PC 2 of detected P-containing compounds, which represented a continuum going from high concentrations of metabolites related to non-active P and P-storage, low total P concentrations and high N:P ratios, to high concentrations of P-containing metabolites related to energy and anabolic metabolism, high total P concentrations and low N:P ratios. These results highlight the species-specific use of P and the existence of species-specific P-use niches that are driven by the distinct species-specific position in a continuum in the P-allocation from P-storage compounds to P-containing molecules related to energy and anabolic metabolism.
Auteurs, date et publication :
Auteurs Albert Gargallo-Garriga , Jordi Sardans , Joan Llusià , Guille Peguero , Dolores Asensio , Romà Ogaya , Ifigenia Urbina , Leandro Van Langenhove , Lore T. Verryckt , Elodie A. Courtois , Clément Stahl , Oriol Grau , Otmar Urban , Ivan A. Janssens , Pau Nolis , Miriam Pérez-Trujillo , Teodor Parella , Josep Peñuelas
Publication : Molecules
Date : 2020
Volume : 25
Issue : 17
Pages : 3960