Résumé

Short-rotation plantations are extending worldwide due to the increased demand for pulp and wood. Reliable estimations of recent expansion of short-rotation plantation areas and associated land use changes are a prerequisite to assess their environmental impact on regional carbon and water cycles, and on climate. A binary classification methodology using MODerate resolution Imaging Spectroradiometer (MODIS) 16-day 250 m NDVI time series was developed and applied to classify Eucalyptus plantations across Brazil. The identification of Eucalyptus plantations specific patterns in the timeserieswas based on the calculation ofmatching functions between theNDVI time series and a ~2 years long reference time series. Among the seven tested matching functions, the bounding envelope
was the most successful. This method was robust to residual noise on the NDVI time series, and a threshold coefficient for the binary classification was adjusted using an omission-commission criteria.With this method, it was possible to detect any presence of Eucalyptus between 2003 and 2009 at monthly time-steps, including the periods of bare soils between two rotations that are typically 6–7 years long. The dates of first afforestation, of clear-cut at the end of a rotation, and of re-planting at the beginning of a new rotation were retrieved from the NDVI time series with a precision of ~66 days. The final almost continuous tri-dimensional map (space and time) was validated with three different datasets, from local to regional data. All three datasets gave similarly high global accuracy statistics, but a global underestimation of Eucalyptus areas compared to large scales census was observed. Discrepancies and way to improve the Eucalyptus area estimates were discussed in this study. The developed methodology could be applied to other short-rotation tree plantations.

Auteurs, date et publication :

Auteurs G. Le Maire , S. Dupuy , Y. Nouvellon , R. Araujo Loos , R. Hakamada

Publication : Remote Sensing of Environment

Date : 2025

Volume : 152

Pages : 136-149

Catégorie(s)

#CIRAD #FORET Itatinga #INRAE

Résumé

Mapping tree mortality rate in a tropical moist forest using multi-temporal LiDAR. Background and aims: Several studies have shown an increase in tree mortality in intact tropical forests in recent decades. However, most studies are based on networks of field plots whose representativeness is debated. We examine the potential of repeated Airborne LiDAR Scanning data to map forest structure change over large areas with high spatial resolution and to detect tree mortality patterns at landscape level. Methods: The study site is a complex forested landscape in French Guiana with varied topographic positions, vegetation structures and disturbance history. We computed a Gap Dynamics Index from Canopy Height Models derived from successive LiDAR data sets (2009, 2015 and 2019) that we compared to field-measured mortality rates (in stem number and basal area loss) obtained from regular monitoring of 74 1.56-ha permanent plots. Results: At the plot level, the relation between gap dynamics and absolute basal area loss rate (combining fallen and standing dead trees) was overall highly significant (R 2 = 0.60) and especially tight for the 59 ha of unlogged forest (R 2 = 0.72). Basal area loss rate was better predicted from gap dynamics than stem loss rate. In particular, in previously logged plots, intense self-thinning of small stems did not translate into detectable gaps, leading to poor predictability of stem mortality by LiDAR in those forests severely disturbed 30 years before. At the landscape scale, LiDAR data revealed spatial patterns of gap creation that persisted over the successive analysis periods. Those spatial patterns were related to local topography and canopy height. High canopy forests and bottomlands were more dynamic, with a higher fraction of canopy affected by gaps per unit time indicating higher basal area loss rates. Conclusion: Gap detection and mapping via multitemporal LiDAR data is poised to become instrumental in characterizing landscape-scale forest response to current global change. Meaningful comparison of gap dynamics across time and space will, however, depend on consistent LiDAR acquisitions characteristics.

Auteurs, date et publication :

Auteurs Claudia Huertas , Daniel Sabatier , Géraldine Derroire , Bruno Ferry , Toby.D. Jackson , Raphaël Pélissier , Grégoire Vincent

Publication : International Journal of Applied Earth Observation and Geoinformation

Date : 2025

Volume : 109

Issue : April

Pages : 102780

Catégorie(s)

#CIRAD #FORET Paracou

Résumé

Abstract

Mapping tropical forest aboveground biomass (AGB) is important for quantifying emissions from land use change and evaluating climate mitigation strategies but remains a challenging problem for remote sensing observations. Here, we evaluate the capability of mapping AGB across a dense tropical forest using tomographic Synthetic Aperture Radar (TomoSAR) measurements at P-band frequency that will be available from the European Space Agency’s BIOMASS mission in 2024. To retrieve AGB, we compare three different TomoSAR reconstruction algorithms, back-projection (BP), Capon, and MUltiple SIgnal Classification (MUSIC), and validate AGB estimation from models using TomoSAR variables: backscattered power at 30 m height, forest height (FH), backscatter power metric (Q), and their combination. TropiSAR airborne campaign data in French Guiana, inventory plots, and airborne LiDAR measurements are used as reference data to develop models and calculate the AGB estimation uncertainty. We used univariate and multivariate regression models to estimate AGB at 4-ha grid cells, the nominal resolution of the BIOMASS mission. Our results show that the BP-based variables produced better AGB estimates compared to their counterparts, suggesting a more straightforward TomoSAR processing for the mission. The tomographic FH and AGB estimation have an average relative uncertainty of less than 10% with negligible systematic error across the entire biomass range (~ 200–500 Mg ha
−1
). We show that the backscattered power at 30 m height at HV polarization is the best single measurement to estimate AGB with significantly better accuracy than the LiDAR height metrics, and combining it with FH improved the accuracy of AGB estimation to less than 7% of the mean. Our study implies that using multiple information from P-band TomoSAR data from the BIOMASS mission provides a new capability to map tropical forest biomass and its changes accurately.

Auteurs, date et publication :

Auteurs Naveen Ramachandran , Sassan Saatchi , Stefano Tebaldini , Mauro Mariotti d’Alessandro , Onkar Dikshit

Publication : Scientific Reports

Date : 2023

Volume : 13

Issue : 1

Pages : 6233

Catégorie(s)

#CIRAD #CNRS #FORET Nouragues #FORET Paracou

Résumé

The preparation of tropical wood surface sections for time‐of‐flight secondary ion mass spectrometry imaging is described, and the use of delayed extraction of secondary ions and its interest for the analysis of vegetal surface are shown. The method has been applied to the study by time‐of‐flight secondary ion mass spectrometry imaging with a resolution of less than one micron of a tropical wood species, Dicorynia guianensis, which is one of the most exploited wood in French Guiana for its durable heartwood. The heartwood of this species exhibits an economical importance, but its production is not controlled in forestry. Results show an increase of tryptamine from the transition zone and a concomitant decrease of inorganic ions and starch fragment ions. These experiments lead to a better understanding of the heartwood formation and the origin of the natural durability of D. guianensis.

Auteurs, date et publication :

Auteurs Quentin P. Vanbellingen , Tingting Fu , Claudia Bich , Nadine Amusant , Didier Stien , Serge Della-Negra , David Touboul , Alain Brunelle

Publication : Journal of Mass Spectrometry

Date : 2016

Volume : 51

Issue : 6

Pages : 412–423

Catégorie(s)

#CIRAD #FORET Paracou

Résumé

This paper introduces the CASINO (CAnopy backscatter estimation, Subsampling, and Inhibited Nonlinear Optimisation) algorithm for above-ground biomass (AGB) estimation in tropical forests using P-band (435 MHz) synthetic aperture radar (SAR) data. The algorithm has been implemented in a prototype processor for European Space Agency's (ESA's) 7th Earth Explorer Mission BIOMASS, scheduled for launch in 2023. CASINO employs an interferometric ground cancellation technique to estimate canopy backscatter (CB) intensity. A power law model (PLM) is then used to model the dependence of CB on AGB for a large number of systematically distributed SAR data samples and a small number of calibration areas with a known AGB. The PLM parameters and AGB for the samples are estimated simultaneously within pre-defined intervals using nonlinear minimisation of a cost function. The performance of CASINO is assessed over six tropical forest sites on two continents: two in French Guiana, South America and four in Gabon, Africa, using SAR data acquired during airborne ESA campaigns and processed to simulate BIOMASS acquisitions. Multiple tests with only two randomly selected calibration areas with AGB > 100 t/ha are conducted to assess AGB estimation performance given limited reference data. At 2.25 ha scale and using a single flight heading, the root-mean-square difference (RMSD) is ≤ 27% for at least 50% of all tests in each test site and using as reference AGB maps derived from airborne laser scanning data. An improvement is observed when two flight headings are used in combination. The most consistent AGB estimation (lowest RMSD variation across different calibration sets) is observed for test sites with a large AGB interval and average AGB around 200–250 t/ha. The most challenging conditions are in areas with AGB < 200 t/ha and large topographic variations. A comparison with 142 1 ha plots distributed across all six test sites and with AGB estimated from in situ measurements gives an RMSD of 20% (66 t/ha).

Auteurs, date et publication :

Auteurs Maciej J. Soja , Shaun Quegan , Mauro M. d’Alessandro , Francesco Banda , Klaus Scipal , Stefano Tebaldini , Lars M. H. Ulander

Publication : Remote Sensing of Environment

Date : 2021

Volume : 253

Pages : 112153

Catégorie(s)

#CIRAD #CNRS #FORET Nouragues #FORET Paracou

Résumé

Somatic mutations potentially play a role in plant evolution, but common expectations pertaining to plant somatic mutations remain insufficiently tested. Unlike in most animals, the plant germline is assumed to be set aside late in development, leading to the expectation that plants accumulate somatic mutations along growth. Therefore, several predictions were made on the fate of somatic mutations: mutations have generally low frequency in plant tissues; mutations at high frequency have a higher chance of intergenerational transmission; branching topology of the tree dictates mutation distribution; and exposure to UV (ultraviolet) radiation increases mutagenesis. To provide insights into mutation accumulation and transmission in plants, we produced two high-quality reference genomes and a unique dataset of 60 high-coverage whole-genome sequences of two tropical tree species, Dicorynia guianensis (Fabaceae) and Sextonia rubra (Lauraceae). We identified 15,066 de novo somatic mutations in D. guianensis and 3,208 in S. rubra, surprisingly almost all found at low frequency. We demonstrate that 1) low-frequency mutations can be transmitted to the next generation; 2) mutation phylogenies deviate from the branching topology of the tree; and 3) mutation rates and mutation spectra are not demonstrably affected by differences in UV exposure. Altogether, our results suggest far more complex links between plant growth, aging, UV exposure, and mutation rates than commonly thought.

Auteurs, date et publication :

Auteurs Sylvain Schmitt , Patrick Heuret , Valérie Troispoux , Mélanie Beraud , Jocelyn Cazal , Émilie Chancerel , Charlotte Cravero , Erwan Guichoux , Olivier Lepais , João Loureiro , William Marande , Olivier Martin-Ducup , Gregoire Vincent , Jérôme Chave , Christophe Plomion , Thibault Leroy , Myriam Heuertz , Niklas Tysklind

Publication : Proceedings of the National Academy of Sciences of the United States of America

Date : 2024

Pages : e2313312121

Catégorie(s)

#CIRAD #FORET Paracou

Résumé

Land biosphere processes are of central importance to the climate system. Specifically, ecosystems interact with the atmosphere through a variety of feedback loops that modulate energy, water, and CO2 fluxes between the land surface and the atmosphere across a wide range of temporal and spatial scales. Human land use and land cover modification add a further level of complexity to land-atmosphere interactions. Dynamic global vegetation models (DGVMs) attempt to capture land ecosystem processes and are increasingly incorporated into Earth system models (ESMs), which makes it possible to study the coupled dynamics of the land biosphere and the climate. In this work we describe a number of modifications to the LPJ-GUESS DGVM, aimed at enabling direct integration into an ESM. These include energy balance closure, the introduction of a sub-daily time step, a new radiative transfer scheme, and improved soil physics. The implemented modifications allow the model (LPJ-GUESS/LSM) to simulate the diurnal exchange of energy, water, and CO2 between the land ecosystem and the atmosphere and thus provide surface boundary conditions to an atmospheric model over land. A site-based evaluation against FLUXNET2015 data shows reasonable agreement between observed and modelled sensible and latent heat fluxes. Differences in predicted ecosystem function between standard LPJ-GUESS and LPJ-GUESS/LSM vary across land cover types. We find that the emerging ecosystem composition and carbon fluxes are sensitive to both the choice of stomatal conductance model and the response of plant water uptake to soil moisture. The new implementation described in this work lays the foundation for using the well-established LPJ-GUESS DGVM as an alternative land surface model (LSM) in coupled land-biosphere-climate studies, where an accurate representation of ecosystem processes is essential.

Auteurs, date et publication :

Auteurs David Martín Belda , Peter Anthoni , David Wårlind , Stefan Olin , Guy Schurgers , Jing Tang , Benjamin Smith , Almut Arneth

Publication : Geoscientific Model Development

Date : 2025

Volume : 15

Issue : 17

Pages : 6709–6745

Catégorie(s)

#CIRAD #FORET Paracou

Résumé

Forest degradation is common in tropical landscapes, but estimates of the extent and duration of degradation impacts are highly uncertain. In particular, selective logging is a form of forest degradation that alters canopy structure and function, with persistent ecological impacts following forest harvest. In this study, we employed airborne laser scanning in 2012 and 2014 to estimate three-dimensional changes in the forest canopy and understory structure and aboveground biomass following reduced-impact selective logging in a site in Eastern Amazon. Also, we developed a binary classification model to distinguish intact versus logged forests. We found that canopy gap frequency was significantly higher in logged versus intact forests even after 8 years (the time span of our study). In contrast, the understory of logged areas could not be distinguished from the understory of intact forests after 6–7 years of logging activities. Measuring new gap formation between LiDAR acquisitions in 2012 and 2014, we showed rates 2 to 7 times higher in logged areas compared to intact forests. New gaps were spatially clumped with 76 to 89% of new gaps within 5 m of prior logging damage. The biomass dynamics in areas logged between the two LiDAR acquisitions was clearly detected with an average estimated loss of −4.14 ± 0.76 MgC ha−1 y−1. In areas recovering from logging prior to the first acquisition, we estimated biomass gains close to zero. Together, our findings unravel the magnitude and duration of delayed impacts of selective logging in forest structural attributes, confirm the high potential of airborne LiDAR multitemporal data to characterize forest degradation in the tropics, and present a novel approach to forest classification using LiDAR data.

Auteurs, date et publication :

Auteurs Ekena Rangel Pinagé , Michael Keller , Paul Duffy , Marcos Longo , Maiza Nara dos-Santos , Douglas C. Morton

Publication : Remote Sensing

Date : 2019

Volume : 11

Issue : 6

Pages : 709

Catégorie(s)

#CIRAD #FORET Paracou

Auteurs, date et publication :

Auteurs Sandra Barantal , Jacques Roy , Nathalie Fromin , Heidy Schimann , Stephan Hättenschwiler

Publication : Oecologia

Date : 2011

Volume : 167

Issue : 1

Pages : 241–252

Catégorie(s)

#CIRAD #FORET Paracou

Résumé

The processes involved in the exchange of water, energy and carbon in terrestrial ecosystems are strongly intertwined. To accurately represent the terrestrial biosphere in land surface models (LSMs), the intrinsic coupling between these processes is required. Soil moisture and leaf area index (LAI) are two key variables at the nexus of water, energy and vegetation. Here, we evaluated two prognostic LSMs (ISBA and ORCHIDEE) and a diagnostic model (based on the LSA SAF, Satellite Application Facility for Land Surface Analysis, algorithms) in their ability to simulate the latent heat flux (LE) and gross primary production (GPP) coherently and their interactions through LAI and soil moisture. The models were validated using in situ eddy covariance observations, soil moisture measurements and remote-sensing-based LAI. It was found that the diagnostic model performed consistently well, regardless of land cover, whereas important shortcomings of the prognostic models were revealed for herbaceous and dry sites. Despite their different architecture and parametrization, ISBA and ORCHIDEE shared some key weaknesses. In both models, LE and GPP were found to be oversensitive to drought stress. Though the simulated soil water dynamics could be improved, this was not the main cause of errors in the surface fluxes. Instead, these errors were strongly correlated to errors in LAI. The simulated phenological cycle in ISBA and ORCHIDEE was delayed compared to observations and failed to capture the observed seasonal variability. The feedback mechanism between GPP and LAI (i.e. the biomass allocation scheme) was identified as a key element to improve the intricate coupling between energy, water and vegetation in LSMs.

Auteurs, date et publication :

Auteurs Jan De Pue , José Miguel Barrios , Liyang Liu , Philippe Ciais , Alirio Arboleda , Rafiq Hamdi , Manuela Balzarolo , Fabienne Maignan , Françoise Gellens-Meulenberghs

Publication : Biogeosciences

Date : 2025

Volume : 19

Issue : 17

Pages : 4361–4386

Catégorie(s)

#CIRAD #FORET Paracou