Centre Provence-Alpes-Côte d'Azur

Abstract Leaf area index (LAI) is a critical vegetation structural variable and is essential in the feedback of vegetation to the climate system. The advancement of the global Earth Observation has enabled the development of global LAI products and boosted global Earth system modeling studies. This overview provides a comprehensive analysis of LAI field measurements and remote sensing estimation methods, the product validation methods and product uncertainties, and the application of LAI in global studies. First, the paper clarifies some definitions related to LAI and introduces methods to determine LAI from field measurements and remote sensing observations. After introducing some major global LAI products, progresses made in temporal compositing and prospects for future LAI estimation are analyzed. Subsequently, the overview discusses various LAI product validation schemes, uncertainties in global moderate resolution LAI products, and high resolution reference data. Finally, applications of LAI in global vegetation change, land surface modeling, and agricultural studies are presented. It is recommended that (1) continued efforts are taken to advance LAI estimation algorithms and provide high temporal and spatial resolution products from current and forthcoming missions; (2) further validation studies be conducted to address the inadequacy of current validation studies, especially for underrepresented regions and seasons; and (3) new research frontiers, such as machine learning algorithms, light detection and ranging technology, and unmanned aerial vehicles be pursued to broaden the production and application of LAI.

The effects of plants on the biosphere, atmosphere and geosphere are key determinants of terrestrial ecosystem functioning. However, despite substantial progress made regarding plant belowground components, we are still only beginning to explore the complex relationships between root traits and functions. Drawing on the literature in plant physiology, ecophysiology, ecology, agronomy and soil science, we reviewed 24 aspects of plant and ecosystem functioning and their relationships with a number of root system traits, including aspects of architecture, physiology, morphology, anatomy, chemistry, biomechanics and biotic interactions. Based on this assessment, we critically evaluated the current strengths and gaps in our knowledge, and identify future research challenges in the field of root ecology. Most importantly, we found that belowground traits with the broadest importance in plant and ecosystem functioning are not those most commonly measured. Also, the estimation of trait relative importance for functioning requires us to consider a more comprehensive range of functionally relevant traits from a diverse range of species, across environments and over time series. We also advocate that establishing causal hierarchical links among root traits will provide a hypothesis-based framework to identify the most parsimonious sets of traits with the strongest links on functions, and to link genotypes to plant and ecosystem functioning.

In the context of a recent massive increase in research on plant root functions and their impact on the environment, root ecologists currently face many important challenges to keep on generating cutting-edge, meaningful and integrated knowledge. Consideration of the below-ground components in plant and ecosystem studies has been consistently called for in recent decades, but methodology is disparate and sometimes inappropriate. This handbook, based on the collective effort of a large team of experts, will improve trait comparisons across studies and integration of information across databases by providing standardised methods and controlled vocabularies. It is meant to be used not only as starting point by students and scientists who desire working on below-ground ecosystems, but also by experts for consolidating and broadening their views on multiple aspects of root ecology. Beyond the classical compilation of measurement protocols, we have synthesised recommendations from the literature to provide key background knowledge useful for: (1) defining below-ground plant entities and giving keys for their meaningful dissection, classification and naming beyond the classical fine-root vs coarse-root approach; (2) considering the specificity of root research to produce sound laboratory and field data; (3) describing typical, but overlooked steps for studying roots (e.g. root handling, cleaning and storage); and (4) gathering metadata necessary for the interpretation of results and their reuse. Most importantly, all root traits have been introduced with some degree of ecological context that will be a foundation for understanding their ecological meaning, their typical use and uncertainties, and some methodological and conceptual perspectives for future research. Considering all of this, we urge readers not to solely extract protocol recommendations for trait measurements from this work, but to take a moment to read and reflect on the extensive information contained in this broader guide to root ecology, including sections I-VII and the many introductions to each section and root trait description. Finally, it is critical to understand that a major aim of this guide is to help break down barriers between the many subdisciplines of root ecology and ecophysiology, broaden researchers' views on the multiple aspects of root study and create favourable conditions for the inception of comprehensive experiments on the role of roots in plant and ecosystem functioning.

Remote sensing techniques offer a unique solution for mapping stress and monitoring its time-course. This article reviews the main issues to be addressed for quantifying stress level from remote sensing observations, and to mitigate its impact on crop production by managing cultural practices. The case of nitrogen fertilization is used here as a paradigm. The derivation of canopy state variables such as the leaf area index (LAI) and chlorophyll content (C(ab)) is first addressed. It is demonstrated that the inversion of radiative transfer models leads to useful estimates of these variables. However, because of the ill-posed nature of the inverse problem, better accuracy is achieved when using prior information on the distribution of the variables and when multiplying LAI by C(ab) to get canopy level chlorophyll content. This variable, LAIxC(ab) is well suited for quantifying canopy level nitrogen content. It is used for nitrogen stress evaluation by comparison with a reference unstressed situation which is, however, not easy to get in practice. The combination of remote sensing observations with crop models provides an elegant solution for stress quantification through assimilation approaches. It fuses several sources of information within our knowledge of the processes involved and accounts for the environmental budget which can be integrated when making decisions about cultural practices. Conclusions are drawn on the issues related to the retrieval of canopy state variables from remote sensing data, to the link between these observables and crop models, and to the assimilation approaches. Avenues for further research are finally discussed along with the required observation system.

The detection of wheat heads in plant images is an important task for estimating pertinent wheat traits including head population density and head characteristics such as health, size, maturity stage, and the presence of awns. Several studies have developed methods for wheat head detection from high-resolution RGB imagery based on machine learning algorithms. However, these methods have generally been calibrated and validated on limited datasets. High variability in observational conditions, genotypic differences, development stages, and head orientation makes wheat head detection a challenge for computer vision. Further, possible blurring due to motion or wind and overlap between heads for dense populations make this task even more complex. Through a joint international collaborative effort, we have built a large, diverse, and well-labelled dataset of wheat images, called the Global Wheat Head Detection (GWHD) dataset. It contains 4700 high-resolution RGB images and 190000 labelled wheat heads collected from several countries around the world at different growth stages with a wide range of genotypes. Guidelines for image acquisition, associating minimum metadata to respect FAIR principles, and consistent head labelling methods are proposed when developing new head detection datasets. The GWHD dataset is publicly available at http://www.global-wheat.com/and aimed at developing and benchmarking methods for wheat head detection.

Bacterial spores are resistant to physical and chemical insults, which makes them a major concern for public health and industry. Spores help bacteria to survive extreme environmental conditions that vegetative cells cannot tolerate. Spore resistance and dormancy are important properties for applications in medicine, veterinary health, food safety, crop protection and other domains. The resistance of bacterial spores results from a protective multilayered structure and from the unique composition of the spore core. The mechanisms of sporulation and germination, the first stage after breaking of dormancy, and organization of spore structure have been extensively studied in Bacillus species. This review aims to illustrate how far the structure, composition and properties of spores are shaped by the environmental conditions in which spores form. We look at the physiological and molecular mechanisms underpinning how sporulation media and environment deeply affect spore yield, spore properties like resistance to wet heat and physical and chemical agents, germination and further growth. For example, spore core water content decreases as sporulation temperature increases, and resistance to wet heat increases. Controlling the fate of Bacillus spores is pivotal to controlling bacterial risks and process efficiencies in, for example, the food industry, and better control hinges on better understanding how sporulation conditions influence spore properties.

The Copernicus Global Land Service (CGLS) provides global time series of leaf area index (LAI), fraction of absorbed photosynthetically active radiation (fAPAR) and fraction of vegetation cover (fCOVER) data at a resolution of 300 m and a frequency of 10 days. We performed a quality assessment and validation of Version 1 Collection 300 m products that were consistent with the guidelines of the Land Product Validation (LPV) subgroup of the Committee on Earth Observation System (CEOS) Working Group on Calibration and Validation (WGCV). The spatiotemporal patterns of Collection 300 m V1 LAI, fAPAR and fCOVER products are consistent with CGLS Collection 1 km V1, Collection 1 km V2 and Moderate Resolution Imagery Spectroradiometer Collection 6 (MODIS C6) products. The Collection 300 m V1 products have good precision and smooth temporal profiles, and the interannual variations are consistent with similar satellite products. The accuracy assessment using ground measurements mainly over crops shows an overall root mean square deviation of 1.01 (44.3%) for LAI, 0.12 (22.2%) for fAPAR and 0.21 (42.6%) for fCOVER, with positive mean biases of 0.36 (15.5%), 0.05 (10.3%) and 0.16 (32.2%), respectively. The products meet the CGLS user accuracy requirements in 69.1%, 62.5% and 29.7% of the cases for LAI, fAPAR and fCOVER, respectively. The CGLS will continue the production of Collection 300 m V1 LAI, fAPAR and fCOVER beyond the end of the PROBA-V mission by using Sentinel-3 OLCI as input data.

The Global Wheat Head Detection (GWHD) dataset was created in 2020 and has assembled 193,634 labelled wheat heads from 4700 RGB images acquired from various acquisition platforms and 7 countries/institutions. With an associated competition hosted in Kaggle, GWHD_2020 has successfully attracted attention from both the computer vision and agricultural science communities. From this first experience, a few avenues for improvements have been identified regarding data size, head diversity, and label reliability. To address these issues, the 2020 dataset has been reexamined, relabeled, and complemented by adding 1722 images from 5 additional countries, allowing for 81,553 additional wheat heads. We now release in 2021 a new version of the Global Wheat Head Detection dataset, which is bigger, more diverse, and less noisy than the GWHD_2020 version.

AIMS: To study the relationship between sporting activity and alcohol, cigarette and cannabis use among adolescents and young adults, by focusing on elite student athletes (ESAs). DESIGN, SETTING, SUBJECTS: Cross-sectional survey (Spring 2002), in a sample of 460 ESAs (ages 16-24 years) recruited at 40 public centres gathering the young sporting elite from 30 different sports in South-Eastern France, comparison with samples of the general population of adolescents in South-Eastern France. MEASURES: Respondents were asked confidentially by a self-administered questionnaire about their use of licit and illicit drugs, their sporting activity and other aspects of their life-style. FINDINGS: Prevalences of cigarette, alcohol and cannabis use were markedly lower for ESAs than for other adolescents (generally twice or three times as low). Among ESAs, when compared with the practice of an individual sport, the practice of a team sport was correlated positively with alcohol use (OR = 2.7 for girls, OR = 1.8 for boys), and the practice of a sliding sport was correlated positively with cannabis use (for girls: OR = 2.3) and with alcohol use (for boys: 4.3). Girls who entered competition at international level were more prone to smoke cigarettes and cannabis (OR = 6.1 and 2.4, respectively). CONCLUSIONS: As a whole, practising sports as an elite student-athlete can be considered as correlated negatively with cigarette, alcohol and cannabis use. Nevertheless, this relationship depends on the kind of sport practised as well as the level of competition, and further research is needed to understand specific elite athletes' motives for use.

Abstract. A growing number of studies are using specific primary sugar species, such as sugar alcohols or primary saccharides, as marker compounds to characterize and apportion primary biogenic organic aerosols (PBOAs) in the atmosphere. To better understand their annual cycles, as well as their spatiotemporal abundance in terms of concentrations and sources, we conducted a large study focusing on three major atmospheric primary sugar compounds (i.e., arabitol, mannitol, and glucose) measured in various environmental conditions for about 5300 filter samples collected at 28 sites in France. Our results show significant atmospheric concentrations of polyols (defined here as the sum of arabitol and mannitol) and glucose at each sampling location, highlighting their ubiquity. Results also confirm that polyols and glucose are mainly associated with the coarse rather than the fine aerosol mode. At nearly all sites, atmospheric concentrations of polyols and glucose display a well-marked seasonal pattern, with maximum concentrations from late spring to early autumn, followed by an abrupt decrease in late autumn, and a minimum concentration during wintertime. Such seasonal patterns support biogenic emissions associated with higher biological metabolic activities (sporulation, growth, etc.) during warmer periods. Results from a previous comprehensive study using positive matrix factorization (PMF) based on an extended aerosol chemical composition dataset of up to 130 species for 16 of the same sample series have also been used in the present work. The polyols-to-PMPBOA ratio is 0.024±0.010 on average for all sites, with no clear distinction between traffic, urban, or rural typology. Overall, even if the exact origin of the PBOA source is still under investigation, it appears to be an important source of particulate matter (PM), especially during summertime. Results also show that PBOAs are significant sources of total organic matter (OM) in PM10 (13±4 % on a yearly average, and up to 40 % in some environments in summer) at most of the investigated sites. The mean PBOA chemical profile is clearly dominated by contribution from OM (78±9 % of the mass of the PBOA PMF on average), and only a minor contribution from the dust class (3±4 %), suggesting that ambient polyols are most likely associated with biological particle emissions (e.g., active spore discharge) rather than soil dust resuspension.

Context: Agroecology combines agronomic and ecological concepts. It relies on the enhancement of biodiversity and related ecosystem services to support agricultural production. It is dependent on biological interactions for the design and management of agricultural systems in agricultural landscapes. Objectives: We review the role of landscape ecology to understand and promote biodiversity, pest regulation and crop pollination for the designing of "agroecology landscapes". We illustrate the use of landscape ecological methods for supporting agroforestry systems as an example of agroecological development, and we propose pathways to implement agroecology at landscape scale. Methods: The state of the art of how landscape ecology contributes to agroecology development is summarized based on a literature review. Results: Agroecology requires thinking beyond the field scale to consider the positioning, quality and connectivity of fields and semi-natural habitats at larger spatial scales. The spatial and temporal organisation of semi-natural elements and the crop mosaic interact. Understanding this interaction is the pre-requisite for promoting patterns and mechanisms that foster biodiversity and ecosystem service provision. Promoting agroecological practices beyond individual farm borders can be rooted in a bottom-up approach from agroecological lighthouse farms to farm networks to amplify agroecology adoption at the landscape scale. Conclusions: Achieving agricultural landscapes composed of fields and farms following agroecological management requires understanding of biodiversity patterns, biological interactions and mechanisms that determine and boost ecosystem functioning to improve services at landscape scale, involving farmers in a bottom-up and context-specific approach.

Pseudomonas syringae is the most frequently emerging group of plant pathogenic bacteria. Because this bacterium is ubiquitous as an epiphyte and on various substrates in non-agricultural settings, there are many questions about how to assess the risk for plant disease posed by strains in the environment. Although P. syringae is considered to have discrete host ranges in defined pathovars, there have been few reports of comprehensive comparisons of host range potential. Here we present results of host range tests for 134 strains, representing eight phylogroups, from epidemics and environmental reservoirs on 15 to 22 plant species per test conducted in four separate tests to determine the patterns and extent of host range. We sought to identify trends that are indicative of distinct pathotypes and to assess if strains in the P. syringae complex are indeed restricted in their host range. We show that for each test, strains display a diversity of host ranges from very restricted to very broad regardless of the gamut of phylogroups used in the test. Overall, strains form an overlapping continuum of host range potential with equal representation of narrow, moderate and broad host ranges. Groups of distinct pathotypes, including strains with currently the same pathovar name, could not be identified. The absence of groupings was validated with statistical tests for pattern recognition. The extent of host range was positively correlated with the capacity of strains to swarm on semi-solid agar medium and with the abundance of genes in biosynthetic clusters and was inversely correlated with the abundance of genes for proteins with transmembrane domains in their genomes. Our results are consistent with the current paradigm that disease symptoms are the result of multiple molecular interactions between P. syringae and its plant host that are modulated by abiotic and biotic conditions. This leads us to propose that pathovar denominations do not correspond to the underlying biology of P. syringae. A new concept of pathogenicity that accounts for the continuum of pathogenic potential in P. syringae would open new perspectives to understand the evolution of pathogenicity in this bacterium and new insights to anticipate disease and to manage plant health.

OBJECTIVE: Management of nonviral cryoglobulinemia vasculitis has yet to be defined. Rituximab has emerged as a novel and promising therapeutic alternative, but data are scarce. Our objective was to evaluate the safety and efficacy of rituximab in nonviral cryoglobulinemia vasculitis in off-trial real-life patients. METHODS: Prospective data from the French AutoImmunity and Rituximab (AIR) registry, which includes data on patients with autoimmune disorders treated with rituximab in off-label conditions, were analyzed. RESULTS: Twenty-three patients received treatment with rituximab for cryoglobulinemia vasculitis. Tolerance was marked by the occurrence of side effects in almost half of the patients, including severe infections in 6 (26%) of 23, with a rate of 14.1 per 100 patient-years. These infections occurred in a particular subset of patients ages>70 years, with essential type II mixed cryoglobulinemia and renal failure with a glomerular filtration rate of <60 ml/minute, and receiving high-dose corticosteroids. Three of these patients died. In contrast, clinical and immunologic efficacy was noted in all evaluable patients. Clinical relapses occurred in half of the patients after a median time of 13.5 months following rituximab administration, and were more frequent in patients refractory to previous immunosuppressive therapy than in previously untreated patients. CONCLUSION: Data from the AIR registry show a dramatic efficacy and a steroid-sparing effect of rituximab, but also show the occurrence of severe infections in elderly patients with renal failure and high-dose steroids. The role of rituximab in nonviral cryoglobulinemia vasculitis remains to be defined in well-designed randomized controlled trials.

BACKGROUND AND AIMS: Root diameter, especially apical diameter, plays an important role in root development and function. The variation in diameter between roots, and along roots, affects root structure and thus the root system's overall foraging performance. However, the effect of diameter variation on root elongation, branching and topological connections has not been examined systematically in a population of high-order roots, nor along the roots, especially for mature plants grown in the field. METHODS: A method combining both excavation and analysis was applied to extract and quantify root architectural traits of adult, field-grown maize plants. The relationships between root diameter and other root architectural characteristics are analysed for two maize cultivars. KEY RESULTS: The basal diameter of the lateral roots (orders 1-3) was highly variable. Basal diameter was partly determined by the diameter of the bearing segment. Basal diameter defined a potential root length, but the lengths of most roots fell far short of this. This was explained partly by differences in the pattern of diameter change along roots. Diameter tended to decrease along most roots, with the steepness of the gradient of decrease depending on basal diameter. The longest roots were those that maintained (or sometimes increased) their diameters during elongation. The branching density (cm(-1)) of laterals was also determined by the diameter of the bearing segment. However, the location of this bearing segment along the mother root was also involved - intermediate positions were associated with higher densities of laterals. CONCLUSIONS: The method used here allows us to obtain very detailed records of the geometry and topology of a complex root system. Basal diameter and the pattern of diameter change along a root were associated with its final length. These relationships are especially useful in simulations of root elongation and branching in source-sink models.

Simpson-Golabi-Behmel syndrome (SGBS) is a rare X-linked multiple congenital abnormality/intellectual disability syndrome characterized by pre- and post-natal overgrowth, distinctive craniofacial features, macrocephaly, variable congenital malformations, organomegaly, increased risk of tumor and mild/moderate intellectual deficiency. In 1996, Glypican 3 (GPC3) was identified as the major gene causing SGBS but the mutation detection rate was only 28-70%, suggesting either genetic heterogeneity or that some patients could have alternative diagnoses. This was particularly suggested by some reports of atypical cases with more severe prognoses. In the family reported by Golabi and Rosen, a duplication of GPC4 was recently identified, suggesting that GPC4 could be the second gene for SGBS but no point mutations within GPC4 have yet been reported. In the genetics laboratory in Tours Hospital, GPC3 molecular testing over more than a decade has detected pathogenic mutations in only 8.7% of individuals with SGBS. In addition, GPC4 mutations have not been identified thus raising the question of frequent misdiagnosis. In order to better delineate the phenotypic spectrum of SGBS caused by GPC3 mutations, and to try to define specific clinical criteria for GPC3 molecular testing, we reviewed the clinical features of all male cases with a GPC3 mutation identified in the two molecular laboratories providing this test in France (Tours and Paris). We present here the results of the analysis of 42 patients belonging to 31 families and including five fetuses and three deceased neonates.

BACKGROUND: Domestication generally implies a loss of diversity in crop species relative to their wild ancestors because of genetic drift through bottleneck effects. Compared to native Mediterranean fruit species like olive and grape, the loss of genetic diversity is expected to be more substantial for fruit species introduced into Mediterranean areas such as apricot (Prunus armeniaca L.), which was probably primarily domesticated in China. By comparing genetic diversity among regional apricot gene pools in several Mediterranean areas, we investigated the loss of genetic diversity associated with apricot selection and diffusion into the Mediterranean Basin. RESULTS: According to the geographic origin of apricots and using Bayesian clustering of genotypes, Mediterranean apricot (207 genotypes) was structured into three main gene pools: 'Irano-Caucasian', 'North Mediterranean Basin' and 'South Mediterranean Basin'. Among the 25 microsatellite markers used, only one displayed deviations from the frequencies expected under neutrality. Similar genetic diversity parameters were obtained within each of the three main clusters using both all SSR loci and only 24 SSR loci based on the assumption of neutrality. A significant loss of genetic diversity, as assessed by the allelic richness and private allelic richness, was revealed from the 'Irano-Caucasian' gene pool, considered as a secondary centre of diversification, to the northern and southwestern Mediterranean Basin. A substantial proportion of shared alleles was specifically detected when comparing gene pools from the 'North Mediterranean Basin' and 'South Mediterranean Basin' to the secondary centre of diversification. CONCLUSIONS: A marked domestication bottleneck was detected with microsatellite markers in the Mediterranean apricot material, depicting a global image of two diffusion routes from the 'Irano-Caucasian' gene pool: North Mediterranean and Southwest Mediterranean. This study generated genetic insight that will be useful for management of Mediterranean apricot germplasm as well as genetic selection programs related to adaptive traits.

A distinctive variety of A. bisporus has been discovered in several habitats in the low Sonoran Desert of the Coachella Valley of California at elevations below sea level. The tetrasporic character of the basidia is consistently predominant in this local population. The spores of this population tend to be shorter and narrower than those of the bisporic strains. The genotypes of two individuals from this population clearly place them in the species A. bisporus, where they form a cohesive group in species-wide cluster analyses of nuclear genotypic similarity. The relative genetic divergence of this population from others in the species is of a similar order to that observed between other geographically isolated, bisporic populations of the species. The tetrasporic individuals exhibit complete interfertility with several bisporic strains of European and Coastal Californian origin. Because of their basidial and spore morphologies, these mushrooms do not fall within the traditional circumscription of A. bisporus. Varietal status is proposed for these distinctive, tetrasporic members of the species, and A. bisporus var. burnettii is described. Primary habitat of these mushrooms is being destroyed rapidly near our field sites. Geographical range of the variety is unknown.

Summary The packing of elementary particles in soil largely determines the properties that depend on the textural soil pore space, but is studied little. The relations between packing and size and nature of soil particles were studied using fractions of clay, silt and sand, mixed when wet and then dried. Ternary mixtures (clay:silt:sand) were compared with binary mixtures (clay:silt, clay:sand). The pore space of the mixtures was studied using mercury porosimetry and scanning electron microscopy. In all the mixtures the textural pore space was divided into two compartments: (1) lacunar pores due to the presence of skeleton particles and to the shrinkage of the clay phase between these particles, and (2) the clay–fabric pores due to the packing of the clay. In the ternary mixtures, lacunar pores could be divided into two classes: (1) those due to sand particles within the clay–slit phase considered as a single phase, and (2) those due to silt particles within this same phase. For certain mixtures, lacunar pores, referred to as hidden lacunar pores, were not interconnected but were occluded. This occurred both for hidden pores caused by the presence of sand and occluded by the clay–slit phase, and for hidden pores caused by the presence of silt and occluded by the clay phase. The relations between these types of textural pores and the proportions of different size fractions in the mixtures provide guidelines for making optimum use of the particle‐size characteristics of the soil to determine its properties.

Tomato is a widely cultivated crop, which can grow in many environments. However, temperature above 30°C impairs its reproduction, subsequently impacting fruit yield. We assessed the impact of high-temperature stress (HS) in two tomato experimental populations, a multi-parental advanced generation intercross (MAGIC) population and a core-collection (CC) of small-fruited tomato accessions. Both populations were evaluated for 11 traits related to yield components, phenology and fruit quality in optimal and HS conditions. HS significantly impacted all traits in both populations, but a few genotypes with stable yield under HS were identified. A plasticity index was computed for each individual to measure the extent of the heat impact for each trait. Quantitative trait loci (QTL) were detected in control and HS conditions as well as for plasticity index. Linkage and genome-wide association analyses in the MAGIC and CC populations identified a total of 98 and 166 QTLs, respectively. Taking the two populations together, 69 plasticity QTLs (pQTLs) were involved in tomato heat response for 11 traits. The transcriptome changes in the ovary of six genotypes with contrasted responses to HS were studied, and 837 genes differentially expressed according to the conditions were detected. Combined with previous transcriptome studies, these results were used to propose candidate genes for HS response QTLs.

The OLIVE (On Line Interactive Validation Exercise) platform is dedicated to the validation of global biophysical products such as LAI (Leaf Area Index) and FAPAR (Fraction of Absorbed Photosynthetically Active Radiation). It was developed under the framework of the CEOS (Committee on Earth Observation Satellites) Land Product Validation (LPV) sub-group. OLIVE has three main objectives: (i) to provide a consistent and centralized information on the definition of the biophysical variables, as well as a description of the main available products and their performances (ii) to provide transparency and traceability by an online validation procedure compliant with the CEOS LPV and QA4EO (Quality Assurance for Earth Observation) recommendations (iii) and finally, to provide a tool to benchmark new products, update product validation results and host new ground measurement sites for accuracy assessment. The functionalities and algorithms of OLIVE are described to provide full transparency of its procedures to the community. The validation process and typical results are illustrated for three FAPAR products: GEOV1 (VEGETATION sensor), MGVIo (MERIS sensor) and MODIS collection 5 FPAR. OLIVE is available on the European Space Agency CAL/VAL portal), including full documentation, validation exercise results, and product extracts.