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Introduction
Publications
Publications (179)
Key message
Accurate volume estimation in Eucalyptus plantation stands was achieved by a linear model using SPOT and Landsat multispectral imagery, specifically texture indices and pixel-scale NDVI time integrals, which reflect the local plantation growth history. Spatial modelling techniques such as Kriging with External Drift and Generalized Addi...
Realistic representations of plant carbon exchange processes are necessary to understand the growth and productivity of forests and to understand how plants will behave in future climate change scenarios. These processes are known to vary over depending on environmental and genetic factors. Here, we used the model by Farquhar et al. (Plant 149:78–9...
Carbon sequestration by forest plantations, for commercial or restoration purposes, is a nature-based solution to mitigate the impacts of climate change. One of the methodologies suggested by IPCC to quantify carbon sequestration in biomass by forest plantations is to use biomass expansion factors. These factors derive aboveground (BEF) and belowgr...
Sugarcane yield prediction is an important tool to support the sugar-energy sector. This study aimed to create a regional empirical model, using the random forest algorithm, to predict sugarcane yield in the state of Sao Paulo. For this, we used Sentinel-2 imagery (vegetation indices NDVIRE and CIRE, spectral bands Red-edge and near-infrared arrow)...
Increasing tree diversity is considered a key management option to adapt forests to climate change. However, the effect of species diversity on a forest's ability to cope with extreme drought remains elusive. In this study, we assessed drought tolerance (xylem vulnerability to cavitation) and water stress (water potential), and combined them into a...
The Global Ecosystem Dynamics Investigation (GEDI) is a high-resolution lidar instrument, facilitating landscape monitoring through forest structure and biomass assessments. Previous research has mainly focused on estimating forest attributes such as height and biomass from GEDI data. In this comprehensive study, we empirically investigate how Euca...
Climate change disrupts ecosystems and increases extreme weather events. Modeling ecosystem functioning is crucial for effective adaptation strategies. This study focuses on quantifiable vegetation properties, including leaf area index (LAI), chlorophyll content (CHL), leaf mass per area (LMA), and equivalent water thickness (EWT). One of the most...
Intraspecific variability (IV) has been proposed as a new track to explain species coexistence. Previous studies generally assumed that IV results from intrinsic differences between conspecifics that widen species’ fundamental niches and blur differences among species, thus impeding stable coexistence, but also slowing down the rate of competitive...
Potassium (K) availability constrains forest productivity. Brazilian eucalypt plantations are a good example of the K limitation of wood production. Here, we built upon a previously described model (CASTANEA-MAESPA-K) and used it to understand whether the simulated decline in C source under K deficiency was sufficient to explain the K limitation of...
The extent of the potassium (K) limitation of forest productivity is probably more widespread than previously thought, and K limitation could influence the response of forests to future global changes. To understand the effects of K limitation on forest primary production, we have developed the first ecophysiological model simulating the K cycle an...
Intraspecific variability (IV) has been proposed to explain species coexistence in diverse communities. Assuming, sometimes implicitly, that conspecific individuals can perform differently in the same environment and that IV increases niche overlap, previous studies have found contrasting results regarding the effect of IV on species coexistence. W...
Biomass cultivation has a large influence over the resulting bio-based products and is largely influenced by local conditions. Therefore, accounting for spatialization into sustainability assessments under the life-cycle perspective is key. The study aims to integrate satellite image classification for sugarcane areas in the Center-South of Brazil...
Forest landscape restoration (FLR) commitments have been established in the past years to restore over 200 million hectares, as part of the global Bonn Challenge goal, mostly through the implementation of several different restorative practices in degraded lands, ranging from commercial tree monocultures to restoration plantings. The potential of s...
Land use change is one of the most important determinants of carbon storage and dynamics in ecosystems. Areas in the proximity of metropoles undergo land use changes but are poorly studied for their soil and biomass carbon budget, especially in Africa. Close to Benin's economic capital, the Lama territory located on the Allada plateau is subject to...
The extent of the potassium (K) limitation of forest productivity is probably more widespread than previously thought, and K-limitation could influence the response of forests to future global changes. To understand the effects of K-limitation on forest primary production, we have developed the first ecophysiological model simulating the K cycle an...
Potassium availability constrains forest productivity. Brazilian eucalypt plantations are a good example of the K-limitation of wood production. Here, we built upon a previously described model (CASTANEA-MAESPA-K) and used it to understand whether the simulated decline in C-source under K deficiency was sufficient to explain the K-limitation of woo...
Context: Intraspecific variability (IV) has been proposed to explain species coexistence in diverse communities. Assuming, sometimes implicitly, that conspecific individuals can perform differently in the same environment and that IV blurs species differences, previous studies have found contrasting results regarding the effect of IV on species coe...
THIS PREPRINT IS A DUPLICATE OF 10.1101/2022.03.16.484259
Context: Intraspecific variability (IV) has been proposed to explain species coexistence in diverse communities. Assuming, sometimes implicitly, that conspecific individuals can perform differently in the same environment and that IV blurs species differences, previous studies have found co...
Eucalypt is one of the most-planted broadleaf genera around the globe, exhibiting high yield, plasticity and growing capacity on a broad range of environments. The main objective of this study is to present the integration of a specific module for eucalypt short-rotation plantations into ECOSMOS (Ecosystem Model Simulator). Different calibrations a...
Remote sensing techniques can help estimate large sugarcane areas in order to support sustainable planning and management for the sugarcane industry, as well as in the context of environmental monitoring. In this study, four generalized space-time classifiers of high-resolution satellite images were tested in Sao Paulo State (SP) in order to map ou...
Understanding how evolutionary history and the coordination between trait trade-off axes shape the drought tolerance of trees is crucial to predict forest dynamics under climate change. Here, we compiled traits related to drought tolerance and the fast-slow and stature-recruitment trade-off axes in 601 tropical woody species to explore their covari...
The availability of crop type reference datasets for satellite image classification is very limited for complex agricultural systems as observed in developing and emerging countries. Indeed, agricultural land use is very dynamic, agricultural censuses are often poorly georeferenced and crop types are difficult to interpret directly from satellite i...
Full waveform (FW) LiDAR systems have proven their effectiveness to map forest biophysical variables in the last two decades, owing to their ability of measuring, with high accuracy, forest vertical structures. The Global Ecosystem Dynamics Investigation (GEDI) system on board the International Space Station (ISS) is the latest FW spaceborne LiDAR...
Eight years of studying coffee ecophysiology and monitoring ecosystem
services (ES) in a large coffee farm in Costa Rica revealed
several practical recommendations for farmers and policy makers.
The cropping system studied within our collaborative observatory
(Coffee-Flux) corresponds to a coffee-based agroforestry system
(AFS) under the shade of l...
Over the past two decades, spaceborne LiDAR systems have gained momentum in the remote sensing community with their ability to accurately estimate canopy heights and aboveground biomass. This study aims at using the most recent Global Ecosystem Dynamics Investigation (GEDI) LiDAR system data to estimate the stand-scale dominant heights (H<sub>dom</...
The Global Ecosystem Dynamics Investigation LiDAR (GEDI) is a new full waveform (FW) based LiDAR system that presents a new opportunity for the observation of forest structures globally. The backscattered GEDI signals, as all FW systems, are distorted by topographic conditions within their footprint, leading to uncertainties on the measured forest...
The availability of crop type reference datasets for satellite image classification is very limited for complex agricultural systems as observed in developing and emerging countries. Indeed, agricultural land use is very dynamic, agricultural census are often poorly georeferenced, and crop types are difficult to photo-interpret directly from satell...
Fertilization is commonly used to increase growth in forest plantations, but it may also affect tree water relations and responses to drought. Here, we measured changes in biomass, transpiration, sapwood-to-leaf area ratio (As:Al) and sap flow driving force (ΔΨ) during the 6-year rotation of tropical plantations of Eucalyptus grandis under controll...
Sugarcane plays an important role in food and energy production in Brazil and worldwide. The large availability of satellite sensors and advanced techniques for processing data have improved the forecasting sugarcane yield on a local and global scale, but more work is needed on exploiting the synergy between remote sensing, meteorological and agron...
While a recent study showed that significant amounts of the nitrogen (N) requirements of young Eucalyptus trees can be provided by nitrogen-fixing trees (NFTs) in mixed-species plantations through short-term belowground N transfer, the consequences of soil fertility on this facilitation process remain unknown. We assessed the effect of fertilizatio...
Leaf biochemical and structural traits are vegetation characteristics related to various physiological processes. Taking advantage of the physical relationship between optical properties and leaf biochemistry, field-based spectroscopy has allowed for the rapid estimation of leaf biochemical constituents and repeated non-destructive measurements thr...
Cloudy conditions reduce the utility of optical imagery for crop monitoring. New constellations of satellites – including the RADARSAT Constellation Mission (RCM) and Sentinel-1A/B, both available under free and open data policies – can be used to create stacks of dense seasonal C-band Synthetic Aperture Radar (SAR) data. Yet to date, the contribut...
This paper addresses the pixelwise classification problem based on temporal profiles, which are encoded in two-dimensional representations based on Recurrence Plots, Gramian Angular/Difference Fields, and Markov Transition Field. We propose a multi-representational fusion scheme that exploits the complementary view provided by those time series rep...
The trees in agroforestry plots create spatial heterogeneity of high interest for adaptation, mitigation, and the provision of ecosystem services. But to what distance, exactly, from the tree? We tested a novel approach, based upon geostatistics and Unmanned Aerial Vehicle (UAV) sensing, to infer the distance at which a single agroforestry tree aff...
The DynACof model was designed to model coffee agroforestry systems and study the trade-offs to e.g. optimize the system facing climate changes. The model simulates net primary productivity (NPP), growth, yield, mortality, energy and water balance of coffee agroforestry systems according to shade tree species and management. Several plot-scale ecos...
Pixelwise image classification based on time series profiles has been very effective in several applications. In this letter, we investigate recently proposed image-based time series encoding approaches [e.g., Gramian angular summation field/Gramian angular difference field (GASF/GADF) and Markov transition field (MTF)] to support the identificatio...
Free access to the paper for 50 days: https://authors.elsevier.com/a/1YvAs14ynSEen9 -------Cropland maps derived from satellite imagery have become a common source of information to estimate food production, support land use policies, and measure the environmental impacts of agriculture. Cropland classification models are typically calibrated with...
Carbon and water budgets of forest plantations are spatially and temporally variable and hardly empirically predictable. We applied G'DAY, a process-based ecophysiological model, to simulate carbon and water budgets and stem biomass production of Eucalyptus plantations in São Paulo State, Brazil. Our main objective was to assess the drivers of spat...
The DynACof model was designed to model coffee agroforestry systems and study the trade-offs to e.g. optimize the system facing climate changes. The model simulates net primary productivity (NPP), growth, yield, mortality, energy and water balance of coffee agroforestry systems according to shade tree species and management. Several plot-scale ecos...
Agroforestry systems (AFS) are complex to model mainly due to the high spatial variability induced by the shade trees. Recently, the microclimate and light heterogeneity issue in AFS has been addressed using the 3D ecophysiological process-based model MAESPA (Charbonnier et al., 2013; Vezy et al., 2018). MAESPA surpassed the classical sun/shade dic...
Eight years of studying coffee ecophysiology and monitoring ecosystem services (ES) in a large coffee farm in Costa Rica revealed several practical recommendations for farmers and policy makers. The cropping system studied within our collaborative observatory (Coffee-Flux) corresponds to a coffee-based agroforestry system (AFS) under the shade of l...
The monitoring of sugarcane areas is important for sustainable planning and management of the sugarcane industry in Brazil. We developed an operational Object-Based Image Analysis (OBIA) classification scheme, with generalized space-time classifier, for mapping sugarcane areas at the regional scale in São Paulo State (SP). Binary random forest (RF)...
Timely and efficient land-cover mapping is of high interest, especially in agricultural landscapes. Classification based on satellite images over the season, while important for cropland monitoring, remains challenging in subtropical agricultural areas due to the high diversity of management systems and seasonal cloud cover variations. This work pr...
Leaf mass per area (LMA) and leaf equivalent water thickness (EWT) are key leaf functional traits providing information for many applications including ecosystem functioning modeling and fire risk management. In this paper, we investigate two common conclusions generally made for LMA and EWT estimation based on leaf optical properties in the near-i...
Suitable time series representations play an important role in classification tasks. In this letter, we investigate the use of recurrence-plot-(RP)-based representations in the classification of eucalyptus regions in remote sensing images. The proposed framework is composed of three steps. First, time series associated with image pixels are represe...
Extreme climatic events and depletion of phosphorus and potassium reserves threaten the productivity and survival of crops and planted forests. Deep root exploration is crucial for adaptation, as studies in Brazil show Eucalyptus roots reaching up to 17 m. Various methods, including isotopic tracers and modeling, revealed that low-density deep fine...
Global climatic changes may deeply affect the functioning ofEucalyptusplantations, es-pecially through the increase in frequency and duration of droughts and storms. However,the long-term responses of trees to the interactions of the different changing environmentalfactors remain largely unknown. It is therefore crucial to gain knowledge on the dri...
The ongoing introduction of the exotic Grevillea robusta tree species into agroforestry systems (AFS) of the Indian Western Ghats could become a threat to both climate change mitigation and tree diversity conservation.
Here, we quantified carbon (C) storage and shade tree diversity in native forests and coffee AFS under contrasted management (nati...
Although large amounts of potassium (K) are applied in tropical crops and planted forests, little is known about the interaction between K nutrition and water supply regimes on water resources in tropical regions. This interaction is a major issue because climate change is expected to increase the length of drought periods in many tropical regions...
Background and aims
While the role of deep roots in major ecosystem services has been shown for tropical forests, there have been few direct measurements of fine root dynamics at depths of more than 2 m. The factors influencing root phenology remain poorly understood, creating a gap in the knowledge required for predicting the effects of climate ch...
Indonesia is currently one of the regions with the highest transformation rate of land surface worldwide related to the expansion of oil palm plantations and other cash crops replacing forests on large scales. Land cover changes, which modify land surface properties, have a direct effect on the land surface temperature (LST), a key driver for many...
Eight years of monitoring ecophysiology and ecosystem services (ES) in a large coffee farm of Costa Rica yields a range of practical applications for the farmer and stakeholders, thanks to numerous scientific actors and disciplines contributing to our collaborative observatory (Coffee-Flux). • A lot of ecosystem services depend on the soil properti...
Indonesia is currently one of the regions with the highest transformation rate of the land surface worldwide due to the expansion of oil palm plantations and other cash crops replacing forests on large scales. Land cover changes, which modify land surface properties, have a direct effect on the land surface temperature (LST), a key driver for many...
Finding suitable models of canopy reflectance in forward simulation mode is a prerequisite for their use in inverse mode to characterize canopy variables of interest, such as leaf area index (LAI) or chlorophyll content. In this study, the accuracy of the three-dimensional reflectance model DART (Discrete Anisotropic Radiative Transfer) was assesse...
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‐sh...
Climate models predict that the frequency, intensity and duration of drought events will increase in tropical regions. Although water withdrawal from deep soil layers is generally considered to be an efficient adaptation to drought, there is little information on the role played by deep roots in tropical forests. Tropical Eucalyptus plantations man...
Soil organic carbon (SOC) plays an important role in climate change regulation notably through release of CO2 following land use change such a deforestation, but data on stock change levels are lacking. This study aims to empirically assess SOC stocks change between 1991 and 2011 at the landscape scale using easy-to-access spatially-explicit enviro...
Supplementary information from doi: 10.1111/1365-2435.12727
Accurate cropland information is of paramount importance for crop monitoring. This study compares five existing cropland mapping methodologies over five contrasting Joint Experiment for Crop Assessment and Monitoring (JECAM) sites of medium to large average field size using the time series of 7-day 250 m Moderate Resolution Imaging Spectroradiomete...
Many agronomic systems could be at risk considering the shorter-term climate changes but several effects and interactions are still uncertain. Process-based models (PBMs) are generally well suited for predictions under new conditions but their complexity causes high computational demand which limits their application. This is particularly true for...
Understanding the consequences of changes in climatic and biological drivers on tree carbon and water fluxes is essential in forestry. Using a metamodeling approach, sensitivity and uncertainty analyses were carried out for a tree-scale model (MAESPA) to isolate the effects of climate, morphological and physiological traits, and intertree competiti...
In order to quantify the effects of forests to oil palm conversion occurring in the tropics on land–atmosphere carbon, water and energy fluxes, we develop a new perennial crop sub-model CLM-Palm for simulating a palm plant functional type (PFT) within the framework of the Community Land Model (CLM4.5). CLM-Palm is tested here on oil palm only but i...
Understanding how plants are constructed—i.e., how key size dimensions and the amount of mass invested in different tissues varies among individuals—is essential for modeling plant growth, carbon stocks, and energy fluxes in the terrestrial biosphere. Allocation patterns can differ through ontogeny, but also among coexisting species and among speci...
Understanding how plants are constructed—i.e., how key size dimensions and the amount of mass invested in different tissues varies among individuals—is essential for modeling plant growth, carbon stocks, and energy fluxes in the terrestrial biosphere. Allocation patterns can differ through ontogeny, but also among coexisting species and among speci...
Understanding how plants are constructed; i.e., how key size dimensions and the amount of mass invested in different tissues varies among individuals; is essential for modeling plant growth, estimating carbon stocks, and mapping energy fluxes in the terrestrial biosphere. Allocation patterns can differ through ontogeny, but also among coexisting sp...
Fine scale maps of vegetation biophysical variables are useful status indicators for monitoring and managing national parks and endangered habitats. Here, we assess in a comparative way four different retrieval methods for estimating leaf area index (LAI) in grassland: two radiative transfer model (RTM) inversion methods (one based on look-up-table...
