Résumé
In agroforestry systems, shade trees strongly affect the physiology of the undergrown crop. However, a major paradigm is that the reduction in absorbed photosynthetically active radiation is, to a certain extent, compensated by an increase in light-use efficiency, thereby reducing the difference in net primary productivity between shaded and non-shaded plants. Due to the large spatial heterogeneity in agroforestry systems and the lack of appropriate tools, the combined effects of such variables have seldom been analysed, even though they may help understand physiological processes underlying yield dynamics.
Auteurs, date et publication :
Auteurs Fabien Charbonnier , Olivier Roupsard , Guerric le Maire , Joannès Guillemot , Fernando Casanoves , André Lacointe , Philippe Vaast , Clémentine Allinne , Louise Audebert , Aurélie Cambou , Anne Clément-Vidal , Elsa Defrenet , Remko A. Duursma , Laura Jarri , Christophe Jourdan , Emmanuelle Khac , Patricia Leandro , Belinda E. Medlyn , Laurent Saint-André , Philippe Thaler
Publication : Plant, Cell & Environment
Date : 2025
Volume : 40
Issue : 8
Pages : 1592-1608
Catégorie(s)
#CIRAD #FORET CoffeeFlux #FORET ItatingaAuteurs, date et publication :
Auteurs Ethan E. Butler , Kirk R. Wythers , Habacuc Flores‐Moreno , Daniel M. Ricciuto , Abhirup Datta , Arindam Banerjee , Owen K. Atkin , Jens Kattge , Peter E. Thornton , Madhur Anand , Sabina Burrascano , Chaeho Byun , J.H.C. Cornelissen , Estelle Forey , Steven Jansen , Koen Kramer , Vanessa Minden , Peter B. Reich
Publication : Journal of Geophysical Research: Biogeosciences
Date : 2025
Catégorie(s)
#CIRAD #CNRS #FORET Paracou #FORET PuechabonRésumé
Tropical forests store more than half of the world's forest carbon and are particularly threatened by deforestation and degradation processes, which together represent the second largest source of anthropogenic CO2 emissions. Consequently, tropical forests are the focus of international climate policies (i.e. UN-REDD Programme) aiming at reducing forest-related CO2 emissions. The REDD initiative lies on our ability to map forest carbon stocks (i.e. spatial dynamics) and to detect deforestation and degradations (i.e. temporal dynamics) at large spatial scales (national, forested basin, global), with accuracy and precision. Remote-sensing is as a key tool for this purpose, but the numerous sources of error along the carbon mapping chain and the lack of sensitivity of traditional remote-sensing data to carbon stock variation in carbon-rich tropical forests makes meeting REDD criteria an outstanding challenge. In the present thesis, we assessed carbon (quantified through aboveground biomass, AGB) estimation error at the tree- and plot-level using a widely used pantropical AGB model, and at the landscape-level using a remote sensing method based on canopy texture features from very high resolution (VHR) optical data. Our objective was to better understand and reduce AGB estimation error at each level using information on large canopy tree structure, distribution and spatial organization. Although large trees disproportionally contributed to forest carbon stock and stock growth, they are dramatically under-represented in destructive datasets and subject to a systematic under-estimation error with the pantropical AGB model. We destructively sampled 77 very large tropical trees and assembled a large (pantropical) dataset to study how variation in tree form (through crown sizes and crown mass ratio) contributed to this error pattern. We showed that the source of bias in the pantropical model was a systematic increase in the proportion of tree mass allocated to the crown in canopy trees. An alternative –unbiased– AGB model accounting for this phenomenon was proposed. We also propagated the pantropical model error at the plot-level while explicitly accounting for this size-dependent systematic error and showed that the interaction between forest structure and AGB model error, although often overlooked, might in fact be substantial. We further analyzed the structural properties of crown branching networks in light of the assumptions and predictions of the Metabolic Theory of Ecology, which supports the power-form of the pantropical AGB model. Important deviations were observed, notably from Leonardo's rule (i.e. the principle of area conservation), which, all else being equal, could support the higher proportion of mass in large tree crowns. A second part of the thesis dealt with the extrapolation of field-plot AGB via canopy texture features. Canopy texture properties emerge from the size distribution and spatial organization of apparent (canopy) trees in VHR optical data, notably. A major barrier for the development of a broad-scale forest carbon monitoring method based on canopy texture is that relationships between canopy texture and stand structure parameters (including AGB) vary among forest types and regions of the world. We investigated this discrepancy using a simulation approach: virtual canopy scenes were generated for 279 1-ha plots distributed on contrasted forest types across the tropics. We showed that complementing FOTO texture with additional descriptors of forest structure, notably on canopy openness and heterogeneity (from a lacunarity analysis) and tree slenderness (from a bioclimatic stress proxy) allows developing a consistent, steady inversion frame for forest AGB at large scale. Although the approach we proposed requires further empirical validation, a first case study on a forests mosaic in the Congo basin gave promising results. Overall, this work essentially increases our understanding of mechanisms behind AGB estimation errors at the tree-, plot- and landscape-level. It stresses the need to better account for variation patterns in tree structure (e.g. ontogenetic pattern of carbon allocation) and forest structural organization (across forest types, under different environmental conditions) to improve general AGB models, and in fine our ability to accurately map forest AGB at large scale.
Auteurs, date et publication :
Auteurs Pierre Ploton
Date : 2017
Catégorie(s)
#CIRAD #FORET ParacouRésumé
Potassium (K) is an important limiting factor of tree growth, but little is known of the effects of K supply on the long-distance transport of photosynthetic carbon (C) in the phloem and of the interaction between K fertilization and drought. We pulse-labelled 2-year-old Eucalyptus grandis L. trees grown in a field trial combining K fertilization (+K and −K) and throughfall exclusion (+W and −W), and we estimated the velocity of C transfer by comparing time lags between the uptake of 13CO2 and its recovery in trunk CO2 efflux recorded at different heights. We also analysed the dynamics of the labelled photosynthates recovered in the foliage and in the phloem sap (inner bark extract). The mean residence time of labelled C in the foliage was short (21–31 h). The time series of 13C in excess in the foliage was affected by the level of fertilization, whereas the effect of throughfall exclusion was not significant. The velocity of C transfer in the trunk (0.20–0.82 m h−1) was twice as high in +K trees than in −K trees, with no significant effect of throughfall exclusion except for one +K −W tree labelled in the middle of the drought season that was exposed to a more pronounced water stress (midday leaf water potential of −2.2 MPa). Our results suggest that besides reductions in photosynthetic C supply and in C demand by sink organs, the lower velocity under K deficiency is due to a lower cross-sectional area of the sieve tubes, whereas an increase in phloem sap viscosity is more likely limiting phloem transport under drought. In all treatments, 10 times less 13C was recovered in inner bark extracts at the bottom of the trunk when compared with the base of the crown, suggesting that a large part of the labelled assimilates has been exported out of the phloem and replaced by unlabelled C. This supports the ‘leakage-retrieval mechanism’ that may play a role in maintaining the pressure gradient between source and sink organs required to sustain high velocity of phloem transport in tall trees.
Auteurs, date et publication :
Auteurs D. Epron , O.-M. Rodrigues Cabral , J.-P. Laclau , M. Dannoura , A.-P. Packer , C. Plain , P. Battie Laclau , Z. Moreira Marcelo , P.-C.-O. Trivelin , J.-P. Bouillet , D. Gérant , Y. Nouvellon
Publication : Tree Physiology
Date : 2025
Volume : 36
Issue : 1
Pages : 6-21
Catégorie(s)
#CIRAD #FORET Itatinga #INRAEAuteurs, date et publication :
Auteurs Nicolas Labriere , Shengli Tao , Jerome Chave , Klaus Scipal , Thuy Le Toan , Katharine Abernethy , Alfonso Alonso , Nicolas Barbier , Pulcherie Bissiengou , Tania Casal , Stuart J. Davies , Antonio Ferraz , Bruno Herault , Gaelle Jaouen , Kathryn J. Jeffery , David Kenfack , Lisa Korte , Simon L. Lewis , Yadvinder Malhi , Herve R. Memiaghe
Publication : IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Date : 2025
Catégorie(s)
#ANR-Citation #CIRAD #CNRS #FORET NouraguesRésumé
While future climate scenarios predict declines in precipitations in many regions of the world, little is known of the mechanisms underlying community resilience to prolonged dry seasons, especially in ‘naïve’ Neotropical rainforests. Predictions of community resilience to intensifying drought are complicated by the fact that the underlying mechanisms are mediated by species' tolerance and resistance traits, as well as rescue through dispersal from source patches. We examined the contribution of in situ tolerance-resistance and immigration to community resilience, following drought events that ranged from the ambient norm to IPCC scenarios and extreme events. We used rainshelters above rainwater-filled bromeliads of French Guiana to emulate a gradient of drought intensity (from 1 to 3.6 times the current number of consecutive days without rainfall), and we analysed the post-drought dynamics of the taxonomic and functional community structure of aquatic invertebrates to these treatments when immigration is excluded (by netting bromeliads) or permitted (no nets). Drought intensity negatively affected invertebrate community resistance, but had a positive influence on community recovery during the post-drought phase. After droughts of 1 to 1.4 times the current intensities, the overall invertebrate abundance recovered within invertebrate life cycle durations (up to 2 months). Shifts in taxonomic composition were more important after longer droughts, but overall, community composition showed recovery towards baseline states. The non-random patterns of changes in functional community structure indicated that deterministic processes like environmental filtering of traits drive community re-assembly patterns after a drought event. Community resilience mostly relied on in situ tolerance-resistance traits. A rescue effect of immigration after a drought event was weak and mostly apparent under extreme droughts. Under climate change scenarios of drought intensification in Neotropical regions, community and ecosystem resilience could primarily depend on the persistence of suitable habitats and on the resistance traits of species, while metacommunity dynamics could make a minor contribution to ecosystem recovery. Climate change adaptation should thus aim at identifying and preserving local conditions that foster in situ resistance and the buffering effects of habitat features.
Auteurs, date et publication :
Auteurs Camille Bonhomme , Régis Céréghino , Jean-François Carrias , Arthur Compin , Bruno Corbara , Vincent E. J. Jassey , Joséphine Leflaive , Vinicius F. Farjalla , Nicholas A. C. Marino , Thibaut Rota , Diane S. Srivastava , Céline Leroy
Publication : Journal of Animal Ecology
Date : 2025
Volume : n/a
Issue : n/a
Catégorie(s)
#CIRAD #FORET ParacouRésumé
Terrestrial evapotranspiration (ET) for each plant functional type (PFT) is a key variable for linking the energy, water and carbon cycles of the atmosphere, hydrosphere and biosphere. Process-based algorithms have been widely used to estimate global terrestrial ET, yet each ET individual algorithm has exhibited large uncertainties. In this study, the support vector machine (SVM) method was introduced to improve global terrestrial ET estimation by integrating three process-based ET algorithms: MOD16, PT-JPL and SEMI-PM. At 200 FLUXNET flux tower sites, we evaluated the performance of the SVM method and others, including the Bayesian model averaging (BMA) method and the general regression neural networks (GRNNs) method together with three process-based ET algorithms. We found that the SVM method was superior to all other methods we evaluated. The validation results showed that compared with the individual algorithms, the SVM method driven by towerspecific (Modern Era Retrospective Analysis for Research and Applications, MERRA) meteorological data reduced the root mean square error (RMSE) by approximately 0.20 (0.15) mm/day for most forest sites and 0.30 (0.20) mm/day for most crop and grass sites and improved the squared correlation coefficient (R2) by approximately 0.10 (0.08) (95% confidence) for most flux tower sites. The water balance of basins and the global terrestrial ET calculation analysis also demonstrated that the regional and global estimates of the SVM-merged ET were reliable. The SVM method provides a powerful tool for improving global ET estimation to characterize the long-term spatiotemporal variations of the global terrestrial water budget.
Auteurs, date et publication :
Auteurs Yunjun Yao , Shunlin Liang , Xianglan Li , Jiquan Chen , Shaomin Liu , Kun Jia , Xiaotong Zhang , Zhiqiang Xiao , Joshua B. Fisher , Qiaozhen Mu , Ming Pan , Meng Liu , Jie Cheng , Bo Jiang , Xianhong Xie , Thomas Grünwald , Christian Bernhofer , Olivier Roupsard
Publication : Agricultural and Forest Meteorology
Date : 2025
Volume : 242
Pages : 55-74
Catégorie(s)
#CIRAD #FORET CoffeeFluxRésumé
Abstract. Disturbances can have strong impacts on the dynamics and structure of tropical forests. They often lead to increased tree mortality and affect their behaviour as carbon sinks. In the future, the intensity of disturbances, such as extreme weather events, fires, floods, and biotic agents, will probably even increase, with more serious consequences for tropical forests than we have already observed. However, impacts of altering disturbances on rates of forest biomass loss through tree mortality (hereinafter: biomass mortality) have been little described yet. This complicates progress in quantifying the effects of climate change on forests globally.
This study aims to analyse the consequences of elevated tree mortality on forest dynamics and to provide a methodology that can reduce uncertainties in estimating biomass mortality rates at local and country level. We achieved this by linking benefits of individual-based forest model-ling, statistical linear regression, and remote sensing. We applied an individual-based forest model to investigate the impact of varying disturbance regimes on the succession dynamic of a humid Terra Firma forest at the Paracou study site in French Guiana. By simulating increased tree mortality rates, we were able to investigate their influence on several forest attributes, namely biomass, leaf area index, forest height, gross primary production, net primary production, and biomass mortality. Based on simulations of leaf area index and forest height, we developed a linear multivariate regression model to project biomass mortality.
Our findings demonstrate that severe disturbances altered the succession pattern of the forests in favour of fast-growing species, which changed gross primary production, but net primary production remained stable. We also observed a strong influence on biomass mortality rates as well as observed complex relationships between these rates and single forest attributes (leaf area index, forest height, and biomass). By combining leaf area index and forest height we obtained relationships that allow an estimation of the biomass mortality. Based on these findings, we mapped the biomass mortality for whole French Guiana. We found a nation-wide biomass mortality of 3 % per year (standard deviation = 1.4 % per year).
The approach we describe here, provides a novel methodology for quantifying the spatial-temporal distribution of biomass loss, which has recently been identified as particularly critical for monitoring mortality hot spots. Quantifying biomass mortality rates may help reducing uncertainties in the terrestrial component of the global carbon cycle.
Auteurs, date et publication :
Auteurs Ulrike Hiltner , Andreas Huth , Rico Fischer
Publication : Biogeosciences Discussions
Date : 2020
Pages : 1-23
Catégorie(s)
#CIRAD #FORET ParacouRésumé
The upcoming BIOMASS mission will provide P-band repeat-pass PolInSAR data from space for the improved mapping of global biomass. PolInSAR technique has been widely validated with the potential to invert forest height and estimate forest aboveground biomass (AGB). However, the robustness of PolInSAR-based AGB estimation across different sites still lacks full evaluation, especially for those with a varied forest type, heterogeneity (varied growth ratio between cover and height), and topographic relief. In this study, we concentrated on backscatter decomposition and forest height inversion, and developed a robust AGB estimation method that can be applied to different sites. Two dense and closed tropical forest sites (Paracou and Nouragues) and one open and heterogeneous boreal forest site (Krycklan) were selected as the study areas, and the corresponding airborne PolInSAR, LiDAR, and ground measured AGB data were used for validation and analysis. Results show that ground backscatter has the strongest correlation with AGB in boreal forests, but this correlation cannot be transferred to the tropical forests. Only canopy volume backscatter is almost free from topographic influence, and its relationship with AGB across three sites can be formulated using one exponential equation, producing the best estimation accuracy, with R2 of 0.79 and RMSE of 61.5 tons/ha (relative RMSE of 20.0 %). Multi-baseline PolInSAR retrieved forest height with little bias in spite of the presence of temporal decorrelation. One power equation can be used to correlate PolInSAR forest height with AGB across three different sites, and LOO (leave-one-out) validation shows the R2 of 0.85 and RMSE of 51.8 tons/ha (relative RMSE of 16.9 %). However, the RVoG-inverted PolInSAR FH was found to mainly represent the top forest height for open and heterogeneous forests, which means PolInSAR FH (forest height) lacks consideration for forest horizontal structure (e.g. forest density). In contrast, volume backscatter better captured forest density, and the proposed AGB model that combines PolInSAR FH and volume backscatter further improved the AGB estimation accuracy, especially for open forests: the plot-scale validation from all three sites shows R2 was improved from 0.79 (volume backscatter) and 0.85 (PolInSAR FH) to 0.89, and RMSE decreased from 61.5 and 51.8 to 45.2 (relative RMSE of 14.7 %) tons/ha; for region-scale validation, R2 was improved from 0.77 and 0.83 to 0.89, and RMSE decreased from 64.2 (relative RMSE of 39.0 %) and 54.5 (34.5 %) to 48.1 (29.4 %) tons/ha.
Auteurs, date et publication :
Auteurs Zhanmang Liao , Binbin He , Yue Shi
Publication : International Journal of Applied Earth Observation and Geoinformation
Date : 2022
Volume : 115
Pages : 103088
Catégorie(s)
#CIRAD #CNRS #FORET Nouragues #FORET ParacouRésumé
With the upcoming spaceborne synthetic aperture radar (SAR) missions (BIOMASS, LuTan-1, NISAR, and TanDEM-L), it will become possible to extract vegetation height at a global scale by utilizing spaceborne low-frequency (L- and P-band) polarimetric synthetic aperture radar interferometry (PolInSAR) data. However, in the context of single-baseline parameter retrieval by the random volume over ground (RVoG) model, three main error sources that affect the inversion accuracy should be carefully considered, i.e., the ground scattering contribution, the spatial baseline configuration, and the temporal decorrelation (the main part of non-volume decorrelation). To make the estimation more reliable, several kinds of multibaseline PolInSAR inversion methods have been proposed over the past few years and have achieved improved inversion performances. Dual-baseline inversion effectively avoids the ambiguity of the ground contribution, whereas the performance is highly dependent on the appropriate combination of two spatial baselines as well as the mitigation of the non-volume decorrelation. In this study, we conducted in-depth research into the effect of these influencing factors on dual-baseline inversion, aiming to provide effective guidance on dual-baseline combination selection among multibaseline data. Accordingly, a novel multibaseline inversion scheme (MBLFPI) suitable for low-frequency PolInSAR data is proposed in this paper. The significant advantage of the new method is that the three aforementioned error sources can be taken into account simultaneously, without relying on external data. The proposed scheme was validated using L- and P-band SAR data acquired by the DLR's E-SAR/F-SAR and ONERA's SETHI systems, as well as corresponding light detection and ranging (LiDAR) data collected during the BioSAR-2008, AfriSAR-2016, and TropiSAR-2009 campaigns. A series of experiments was performed to evaluate the applicability and generalizability of the proposed method. The results showed that this innovative scheme produced forest height maps with a root-mean-square error (RMSE) of 2.37 m (R2 = 0.88) and 3.13–4.43 m (R2 = 0.35–0.94) in the L-band and P-band scenarios (boreal and tropical forest), respectively, indicating a significant improvement over the three conventional multibaseline methods and pure dual-baseline inversion. The comprehensive analysis provided in this paper should assist with and provide strong support for SAR system and mission design, and the proposed scheme could be considered a promising way for future spaceborne missions to invert vegetation parameters at a global scale.
Auteurs, date et publication :
Auteurs Yanzhou Xie , Haiqiang Fu , Jianjun Zhu , Changcheng Wang , Qinghua Xie , Jie Wan , Wentao Han
Publication : Remote Sensing of Environment
Date : 2024
Volume : 312
Pages : 114306