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Leaf area is a key structural characteristic of forest canopies because of the role of leaves in controlling many biological and physical processes occurring at the biosphere-atmosphere transition. High pulse density Airborne Laser Scanning (ALS) holds promise to provide spatially resolved and accurate estimates of plant area density (PAD) in forested landscapes, a key step in understanding forest functioning: phenology, carbon uptake, transpiration, radiative balance etc. Inconsistencies between different ALS sensors is a barrier to generating globally harmonised PAD estimates. The basic assumption on which PAD estimation is based is that light attenuation is proportional to vegetation area density. This study shows that the recorded extinction strongly depends on target detectability which is influenced by laser characteristics (power, sensitivity, wavelength). Three different airborne laser scanners were flown over a wet tropical forest at the Paracou research station in French Guiana. Different sensors, flight heights and transmitted power levels were compared. Light attenuation was retrieved with an open source ray-tracing code (http://amapvox.org). Direct comparison revealed marked differences (up-to 25% difference in profile-averaged light attenuation rate and 50% difference at particular heights) that could only be explained by differences in scanner characteristics. We show how bias which may occur under various acquisition conditions can generally be mitigated by a sensor intercalibration. Alignment of light weight lidar attenuation profiles to ALS reference attenuation profiles is not always satisfactory and we discuss what are the likely sources of discrepancies. Neglecting the dependency of apparent light attenuation on scanner properties may lead to biases in estimated vegetation density commensurate to those affecting light attenuation estimates. Applying intercalibration procedures supports estimation of plant area density independent of acquisition characteristics.

Made available in DSpace on 2021-06-25T10:32:16Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-01-01 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 controlled conditions for throughfall and potassium (K) fertilization. K fertilization increased final tree height by 8 m. Throughfall exclusion scarcely affected tree functioning because of deep soil water uptake. Tree growth increased in K-supplied plots and remained stable in K-depleted plots as tree height increased, while growth per unit leaf area increased in all plots. Stand transpiration and hydraulic conductance standardized per leaf area increased with height in K-depleted plots, but remained stable or decreased in K-supplied plots. Greater Al in K-supplied plots increased the hydraulic constraints on water use. This involved a direct mechanism through halved As:Al in K-supplied plots relative to K-depleted plots, and an indirect mechanism through deteriorated water status in K-supplied plots, which prevented the increase in ΔΨ with tree height. K fertilization in tropical plantations reduces the hydraulic compensation to growth, which could increase the risk of drought-induced dieback under climate change. CIRAD UMR Eco&Sols Eco&Sols Univ Montpellier CIRAD INRAe IRD Montpellier SupAgro Department of Forest Sciences Universidade de São Paulo “Luiz de Queiroz” College of Agriculture (USP-ESALQ) Center of Nuclear Energy in Agriculture Universidade de São Paulo (USP-CENA) Edafotec SL NIPE UNICAMP Bordeaux Sciences Agro UMR INRAe-ISPA 1391 Nicholas School of the Environment Duke University Ecologie Systématique Evolution Univ. Paris-Sud CNRS AgroParisTech Université Paris-Saclay School of Agricultural Sciences UNESP—São Paulo State University School of Agricultural Sciences UNESP—São Paulo State University

The data presented in this data paper describe the early growth of cover crop cultivated in growth chamber under non-limiting conditions. Seventeen species of four botanical groups were described after one month of growth. Traits related to plant growth and leaf area development were measured (five traits) and calculated (eight traits). This data set is made available to enable comparisons between dataset, extended analysis and meta-analysis on cover crop traits. The data presented in this article were used on the research article entitled “Leaf area development strategies of cover plants used in banana plantations identified from a set of plant traits’ [1]. Keywords: Cover crops, Plant growth, Leaf area, Leaf traits, Plant traits

[Departement_IRSTEA]Territoires [TR1_IRSTEA]SYNERGIE [Axe_IRSTEA]TETIS-ATTOS; International audience; 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 assessed for canopies of different genotypes of Eucalyptus, having distinct biophysical and biochemical characteristics, to improve the knowledge on how these characteristics are influencing the reflectance signal as measured by passive orbital sensors. The first step was to test the model suitability to simulate reflectance images in the visible and near infrared. We parameterized DART model using extensive measurements from Eucalyptus plantations including 16 contrasted genotypes. Forest inventories were conducted and leaf, bark, and forest floor optical properties were measured. Simulation accuracy was evaluated by comparing the mean top of canopy (TOC) bidirectional reflectance of DART with TOC reflectance extracted from a Pleiades very high resolution satellite image. Results showed a good performance of DART with mean reflectance absolute error lower than 2%. Intergenotype reflectance variability was correctly simulated, but the model did not succeed at catching the slight spatial variation for a given genotype, excepted when large gaps appeared due to tree mortality. The second step consisted of sensitivity analysis to explore which biochemical or biophysical characteristics influenced more the canopy reflectance between genotypes. Perspectives for using DART model in inversion mode in these ecosystems were discussed. [ABSTRACT FROM PUBLISHER]

The phylloplane is the first contact surface between Theobroma cacao and the fungus Moniliophthora perniciosa, which causes witches’ broom disease (WBD). We evaluated the index of short glandular trichomes (SGT) in the cacao phylloplane and the effect of irrigation on the disease index of cacao genotypes with or without resistance to WBD, and identified proteins present in the phylloplane. The resistant genotype CCN51 and susceptible Catongo presented a mean index of 1,600 and 700 SGT cm−2, respectively. The disease index in plants under drip irrigation was reduced by approximately 30% compared with plants under sprinkler irrigation prior to inoculation. Leaf water wash (LWW) of the cacao inhibited the germination of spores by up to 98%. Proteins from the LWW of CCN51 were analyzed by two-dimensional sodium dodecyl sulfate polyacrylamide gel electrophoresis followed by tandem mass spectrometry. The gel showed 71 spots and identified a total of 42 proteins (28 from the plant and 14 from bacteria). Proteins related to defense and synthesis of defense metabolites and involved in nucleic acid metabolism were identified. The results support the hypothesis that the proteins and water-soluble compounds secreted to the cacao phylloplane participate in the defense against pathogens. They also suggest that SGT can contribute to the resistance of cacao.

In addition to timber and non-timber forest products, tropical forests host the largest amount of terrestrial carbon in the world, thus its importance for reducing the effects of climate change. This carbon is generally estimated as aboveground biomass (AGB) because about half of the organic matter is carbon. Therefore, estimating AGB trough differentapproaches and the calibration of relationships between AGB and dendrometric parameters (allometric equations) are of great importance for the estimation carbon stock. From a functional perspective, data from AGB and leaf (e.g. leaf area) ameliorates our understanding of the functioning of tropical forests and their interactions with the atmosphere. However, destructive data sampling commonly used is cumbersome to implement and presents significant uncertainty. This leads to a considerable deficit of accurate data. Studies carried intemperate forests show that using terrestrial LiDAR technologies (TLS) may provide a solution to the limitations of destructive sampling. The TLS produce a tridimensional points cloud which describes with a high precision structures within their natural environment.Therefore, the overall goal of this thesis is to evaluate the potential of using TLS data reducing the lack of quality data observed in the Congo Basin. Here we used TLS data to: i) establish AGB and height-diameter (HD) allometric models ; ii) evaluate the potential impact of vertical variation of wood density (WD) on AGB estimates derived from TLS data ; and finally, iii) ameliorate LA estimation of trees and calibrate allometric model for the prediction of this area using data which derived from LiDAR data.At the local scale, (semi-deciduous forest of south East Cameroon), two datasets were collected. The first has 61 trees and opposes TLS data to destructive data. The second dataset collected in quadrats within plots had 712 trees and opposed TLS data to classic field inventory data. At the regional scale (forest from the Congo Basin), a uniform destructivesampling realized on 821 trees permitted us to obtain WD data, volume data and AGB for each compartment. Thanks to an automatic method of topology reconstruction and the geometry of trees (Quantitative Structure Model QSM) based on the adjustment of cylinders in the points cloud, we compared dendrometric parameters i.e. volumes, AGB and allometricmodels resulting from TLS data to those derived from the destructive and inventory sampling method.It appears that, the TLS estimates wood volume with great precision (88%) and low bias (4.6%). Related to this, the AGB allometric model (R²=95%) established from TLS data is statistically similar to the one obtained with destructive data (R²=98%). Nevertheless, theselast results depend on the manual editing of QSM for some compartments of the tree because obtained AGB with raw QSM (without manual edition) lead to a different allometry (R²=93%). Despite these results, comparing total tree height data collected in plots scalerevealed that there is an average difference of 3 meters between total height derived from TLS and those collected from classical inventory. Using these two datasets separately led to the selection of a similar HD predictive model ; but the AGB estimated with predicted heights byinventory method is systematic underestimation of 10% per ha. The principal component analysis of WD by the different compartments helped in discriminating tree mayor types of WD vertical gradients: constant, decreasing, and increasing. These vertical gradients areconserved within species and are strongly correlated to species guilds, the basal density (WDStu) and the density issued of global databases (GWD). Thus, neglecting the existence of these gradients during the conversion of volumes derived from TLS to AGB leads to an individual bias (rising up to 73%) and an average bias of 8.12%. But using an unbiased estimator of WD defined in this work limits the bias to 0.75% with the WDStu and 1.19% with the GWD. Apart from these results on the AGB, manual segmentation between wood and trees realized before the automatic adjustment of the QSM made it possible to use thevoxelization technique on the leaves points cloud. This is with the aim of subdividing the tree crown in cubic volumes (voxels) to estimate the LA. Comparing LA derived from TLS to those obtained with the destructive method revealed that commonly using the spherical distribution as the “typical” angular distribution of leaves led to a fairly high average bias ofLA (17.28 %) against 6.5% when the distribution is computed per tree. This estimated leaf area (LA) is strongly correlated with DBH (r = 0.88) and AGB (r = 0.97). Linear models established between these variables produced R² ranging from 72 to 95%, illustrating a strong intensity of the link between LA and these two variables.To conclude, using TLS data would facilitate the implementation of international programs whose objective to achieve Tier III levels of accuracy necessary in estimating carbon stocks as recommended by the Intergovernmental Panel on Climate change., Outre le bois et les produits forestiers non ligneux, les forêts tropicales hébergent la plus grande quantité de carbone aérien au monde d’où son importance pour la réduction des effets du changement climatique. Ce carbone est généralement estimé sous forme de biomasse aérienne (AGB) car environ la moitié de la matière organique est constituée de carbone. Ainsi, l’estimation de l’AGB au travers de différentes approches et la calibration des relations entre l’AGB et les paramètres dendrométriques (équations allométriques) sont d’une grande importance pour l’estimation des stocks de carbone. D’un point de vue fonctionnel, les données d’AGB ainsi que des données foliaires (e.g surface foliaire) permettent d’améliorer la compréhension du fonctionnement des forêts tropicales et leurs interactions avec l'atmosphère. Cependant, la collecte des données destructives est très lourde à mettre en oeuvre et présente une incertitude importante. Cela conduit à un déficit considérable de données de qualité. Or, des études initiées en forêts tempérées montrent que l’utilisation de la technologie LiDAR terrestre (TLS) apporterait une solution aux limites de la collecte destructive. En effet, cet instrument produit une représentation tridimensionnelle de l’environnement scanné sous forme de nuage de points. L’objectif général de la présente thèse est d’évaluer le potentiel de l’usage des données TLS sur la réduction du déficit de données de qualité observée dans le bassin du Congo. Ainsi, il a été question : i) d’établir les modèles allométriques d’AGB et des hauteursdiamètres (HD) ; ii) d’évaluer l’impact potentiel des variations verticales de densité spécifique du bois (GWD) sur les estimations d’AGB dérivées des données TLS ; et enfin, iii) d’améliorer les estimations de surface foliaire (LA) et calibrer un modèle allométrique de prédiction de cette surface basée sur les données dérivées du LiDAR terrestre.A l’échelle locale (forêt semi-décidue du Sud-est du Cameroun), deux jeux de données ont été collectés. Le premier est constitué de 61 arbres et oppose les données TLS à celles destructives. Le second, collecté dans des quadrats de parcelles, est constitué de 712 arbres et oppose les données TLS à celles d’inventaires floristiques classiques. A l’échelle régionale (forêts du bassin du Congo) un échantillonnage destructif uniforme réalisé sur 821 arbres a permis d’obtenir les données de WD, de volume et d’AGB par compartiment. Grâce à une méthode automatique de reconstruction de la topologie et de la géométrie des arbres (Modèle de Structure Quantitatif : QSM) basée sur l’ajustement de cylindres dans le nuage de points, nous avions pu comparer les paramètres dendrométriques, les volumes, l’AGB et les modèles allométriques (d’AGB et HD) issus des données TLS à ceux dérivés de la méthode destructive et inventaire.Il en ressort que le TLS estime avec une précision de 88 % et un biais très faible de 4,6 % les volumes des arbres. Associé à cela, le modèle allométrique d’AGB (R²=95 %) établi grâce aux données TLS est statistiquement identique à celui obtenu avec les données destructives (R²=98 %). Toutefois, ce dernier résultat repose sur l’édition manuelle des QSM pour certains compartiments de l’arbre car l’AGB obtenues avec des QSM bruts (sanscorrection manuelle) conduisent à une allométrie (R²=93 %) différente. Outre ces résultats, la comparaison des données de hauteurs totales collectées dans les parcelles a révélé qu’il existe une différence moyenne de 3 mètres entre les hauteurs totales dérivées du TLS et celles issues de la méthode classique d’inventaire. L’usage séparé de ces deux jeux de données a conduit à la sélection d’un même modèle de prédiction de HD, mais l’AGB estimée avec les hauteurs prédites par la méthode d’inventaire est systématiquement sous-estimé de 10 % par hectare.L’analyse en composante principale de la WD par compartiment a permis de discriminer trois types de grands gradients verticaux de WD à savoir constant, décroissant et croissant. Ces gradients verticaux se conservent remarquablement au sein des espèces et sont fortement corrélés aux tempéraments des espèces, à la densité basale (WDStu) et à la densité issue de la base de données globales (GWD). Ainsi, négliger l’existence de ces gradients au cours de la conversion des volumes dérivées du TLS en AGB conduit à un biais individuel (allant jusqu’à 73 %) et un biais moyen 8,12 %. L’usage d’un estimateur non biaisé de la WD défini dans ce travail permet de limiter ces biais à 0,75 % avec WDStu et 1,19 % avec la GWD. A part ces résultats sur l’AGB, une approche par voxelisation (subdivision de l’espace en cube) du nuage de point de feuille segmenté manuellement a permis l’estimation du LA à l’échelle de l’arbre. La comparaison des LA dérivés du TLS à ceux obtenus avec la méthode destructive révèle que l’usage conventionnelle de la distribution sphérique comme distribution angulaire « type » de feuilles conduit à un biais moyen d’estimation de LA assez élevé (17,28 %) contre 6,5 % lorsque la distribution réelle est obtenue par arbre. Ce LA estimée est fortement corrélé au DBH (r = 0,88) et à l’AGB (r = 0,97). Les modèles linéaire établis entre ces variables a produit des R² allant de 72 à 95 % illustrant une forte intensité de la liaison entre le LA et ces deux variables.En somme, les résultats de ce travail ont permis de mettre en évidence que l’utilisation des données TLS sont une grande plus-value pour la mise en oeuvre des programmes internationaux ayant pour objectif l’atteinte du tiers III de précision nécessaire à l'estimation des stocks de carbone tel que recommandé par le Groupe d’Expert Intergouvernemental sur l’évolution du Climat.

International audience; Breeders select for yield, thereby indirectly selecting for traits that contribute to it. We tested if breeding has affected a range of traits involved in plant architecture and light interception, via the analysis of a panel of 60 maize hybrids released from 1950 to 2015. This was based on novel traits calculated from reconstructions derived from a phenotyping platform. The contribution of these traits to light interception was assessed in virtual field canopies composed of 3D plant reconstructions, with a model tested in a real field. Two categories of traits had different contributions to genetic progress. (a) The vertical distribution of leaf area had a high heritability and showed a marked trend over generations of selection. Leaf area tended to be located at lower positions in the canopy, thereby improving light penetration and distribution in the canopy. This potentially increased the carbon availability to ears, via the amount of light absorbed by the intermediate canopy layer. (b) Neither the horizontal distribution of leaves in the relation to plant rows nor the response of light interception to plant density showed appreciable trends with generations. Hence, among many architectural traits, the vertical distribution of leaf area was the main indirect target of selection.

National audience; Dans le contexte de l’agroécologie, les couverts plurispécifiques augmenteront. Il faut donc repenser certains outils de diagnostic de l’état des couverts, pour la plupart développés pour des couverts monospécifiques. C’est le cas de l’indice de nutrition azotée (INN), classiquement utilisé en agronomie pour diagnostiquer le statut azoté d’un couvert afin d’identifier d’éventuelles situations de carence en azote et, sur cette base, piloter la fertilisation. L’INN est calculé avec la courbe critique de dilution de l’azote qui indique la teneur en azote optimale d’une plante pour maximiser sa croissance. Cette courbe ne peut pas être utilisée pour des plantes de couvert plurispécifique car elle varie en fonction de l’environnement lumineux de la plante. Or, les plantes de couvert plurispécifique n’ont pas toutes le même accès à la lumière. Nous avons cherché à identifier une nouvelle formalisation de la courbe critique, stable quel que soit l’environnement lumineux de la plante. Des expérimentations en serre ont permis de soumettre 8 espèces végétales à 4 niveaux d’azote et 2 niveaux de rayonnement pour reproduire différents accès à l’azote et à la lumière. La biomasse et la teneur en azote des feuilles, des tiges et des racines et la surface foliaire ont été mesurées à 4 dates. Nous avons identifié que le ratio Quantité d'azote des parties aériennes/biomasse des feuilles est un bon indicateur du statut azoté de la plante. Pour une plante de couvert plurispécifique, la comparaison du ratio à la valeur attendue à nutrition azotée optimale permet de quantifier son statut azoté.

National audience; Afin de réduire les impacts environnementaux de l’agriculture, les couverts hétérogènes plurispécifiques sont amenés à augmenter. Cette étude, basée sur des expérimentations en serre, vise à repenser l’indice de nutrition azotée (INN), utilisé pour diagnostiquer le statut azoté d’un couvert monospécifique homogène afin d’en piloter la fertilisation azotée. En effet, les formalismes classiquement utilisés pour calculer l’INN varient en fonction de l’environnement lumineux, alors que les plantes des couverts hétérogènes n’ont pas accès au rayonnement lumineux de la même façon. Les résultats ont permis d’identifier que le ratio quantité d’azote aérien / biomasse des feuilles (QNaer/MSF) est un bon indicateur du niveau de nutrition azotée de la plante. De plus, ce ratio est relativement indépendant du rayonnement. Ce nouvel indicateur permet de quantifier le statut azoté d’une plante en comparant la valeur observée QNaer/MSF à la valeur attendue en situation de nutrition azotée optimale.

National audience; Le bilan hydrique des peuplements sera particulièrement impacté par le changement climatique. De nombreux projets du RMT Aforce ont donc envisagé cette question en abordant notamment l'influence de la réduction de la surface foliaire via les éclaircies. Cet article rappelle pourquoi et comment le sylviculteur a intérêt à considérer cette variable d'ajustement.

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International audience; Pruning is an important horticultural practice that generally promotes vegetative growth. However, the precise characterization of vegetative growth after pruning and of the factors affecting it are little known. The objective of this study was to decipher the vegetative response to pruning in a tropical evergreen species, the mango tree. Pruning was characterized by two factors: pruning intensity, defined at the tree scale as the amount of fresh biomass removed per unit volume of canopy, and pruning severity, defined at the axis scale as the distance between the pruning point and the distal end of the axis. Vegetative growth after pruning was broken down into structural (burst rate, vegetative growth intensity, leaf area produced) and temporal (burst date) variables, and the effects of pruning were evaluated on these variables at a local scale on pruned axes and at a distant scale on unpruned axes. Burst rate and leaf area produced increased with pruning intensity (pruned and unpruned axes), pruning severity (pruned axes), axis diameter (pruned and unpruned axes) and proximity to pruned axes (unpruned axes). Vegetative growth intensity increased with pruning severity (pruned axes) and axis diameter (pruned and unpruned axes) but was not affected by pruning intensity. For these three variables, local responses were more important than distant responses. The dynamics of vegetative growth was affected by pruning intensity and severity. Results depicted the complexity of mango tree response to pruning at different scales. As a general rule, more extensive pruning led to larger and more synchronous vegetative growth.

Despite evidence and previous reports on the genotypic variation of apple tree architecture, phenotyping large populations remains challenging. In this study, we used T-LiDAR scanning for evaluating architectural traits on an apple core collection. After the determination of an adequate protocol considering both data acquisition duration and scan resolution, scans were collected on a large number of individuals (around 1000) corresponding to a French core collection of apple varieties, implanted in Montpellier, France. The analysis relied on different methods and software to segment and extract the point clouds corresponding to each tree. The procedure makes it possible to compute descriptors of the tree shape such as the height, convex volume, alpha hull volume, total leaf area and it vertical distribution, and light interception efficiency estimated through the silhouette to leaf area ratio (STAR). Alpha hull volumes were well correlated with in planta measurements such as total leaf area or trunk cross-sectional area emphasizing the relevance of this descriptor. Most descriptors showed high variation and heritability within the population. Highest heritability values were observed for global or integrative traits such as plant volume while lowest heritabilities were observed for more local traits such as leaf area vertical distribution. The estimated variables were then used to define six architectural morphotypes using a clustering method. Differences between groups were first explained by parameters related to the size of the tree and then by differences in STAR values within each group of small and big trees. The present results suggest that T-Lidar scans are relevant for capturing genetic variation of global tree shape within a population with a large diversity and could be extended for phenotypic other architectural traits. In that context, forthcoming works are undergoing for extracting topological traits on the whole population on scans collected in winter conditions.

The detection of plant diseases, including fungi, is a major challenge for reducing yield gaps of crops across the world. We explored the potential of the PROCOSINE radiative transfer model to assess the effect of the fungus Pseudocercospora fijiensis on leaf tissues using laboratory-acquired submillimetre-scale hyperspectral images in the visible and near-infrared spectral range. The objectives were (i) to assess the dynamics of leaf biochemical and biophysical parameters estimated using PROCOSINE inversion as a function of the disease stages, and (ii) to discriminate the disease stages by using a Linear Discriminant Analysis model built from the inversion results. The inversion results show that most of the parameter dynamics are consistent with expectations: for example, the chlorophyll content progressively decreased as the disease spreads, and the brown pigments content increased. An overall accuracy of 78.7% was obtained for the discrimination of the six disease stages, with errors mainly occurring between asymptomatic samples and first visible disease stages. PROCOSINE inversion provides relevant ecophysiological information to better understand how P. fijiensis affects the leaf at each disease stage. More particularly, the results suggest that monitoring anthocyanins may be critical for the early detection of this disease.

International audience; Urban leaf area measurement is crucial to properly determining the effect of urban trees on micro-climate regulation, heat island effect, building cooling, air quality improvement, and ozone formation. Previous works on the leaf area measurement have mainly focused on the stand level, although the presence of individual trees is more common than forests in urban areas. The only feasible ways for an operational non-destructive leaf area measurement, namely, optical indirect methods, are mostly limited in urban areas because light path is constantly intercepted by surrounding buildings or other objects. A terrestrial laser scanner (TLS), which can extract an individual tree by using its unique distance information, provides a possibility for indirectly measuring the leaf area index (LAI) in urban areas. However, indirect LAI measurement theory, which uses the cosine of an observation zenith angle for path-length correction, is incompatible for an individual tree because the representative projected area of LAI changes while the observation zenith angle changes, thus making the results incomparable and ambiguous. Therefore, we modified a path length distribution model for the leaf area measurement of an individual tree by replacing the traditional cosine path length correction for a continuous canopy with real path length distribution. We reconstructed the tree crown envelope from a TLS point cloud and calculated a real path length distribution through laser pulse-envelope intersections. Consequently, leaf area density was separated from the path length distribution model for leaf area calculation. Comparisons with reference measurement for an individual tree showed that the TLS-derived leaf area using the path length distribution is insensitive to the scanning resolution and agrees well with an allometric measurement with an overestimation from 5 m 2 to 18 m 2 (3-10%, respectively). Results from different stations are globally consistent, and using a weighted mean for different stations by sample numbers further improves the universality and efficiency of the proposed method. Further automation of the proposed method can facilitate a rapid and operational leaf area extraction of an individual tree for urban climate modeling.

We aim at extending methodologies based on T-Lidar scans for providing a description of individual apple tree topology and architecture. Experiments were performed on 2- and 3-year-old trees belonging to a core collection of French apple cultivars. In 2016, ten trees were precisely scanned in winter to assess our ability to extract topological traits. In 2017, the whole core-collection was scanned to estimate tree leaf areas at the end of the summer period. Topological reconstructions on 2016 data were performed with Plantscan3D software using existing algorithms whereas an allometric relationship depending on tree alpha hull volumes was used for estimating tree leaf areas on 2017 data. Topological traits extracted from T-LiDAR data were compared to digitizing data of the same trees and the estimated total leaf areas were compared to manual measurements on a sample of twenty trees displaying large variability in vegetative development. In 2016, topological reconstructions gave promising results with R² values higher than 0.90 for the total number of axes and growth units pet tree and for their mean length when T-Lidar were compared to digitizing data. However, a significant number of short axes or growth units were not detected by the T-Lidar. Comparisons between T-LiDAR and digitizing data showed g ood adequacy if axes were classified depending on their branching order suggesting that our method was relevant for evaluating the number of branching points in the structure. Regarding data collected on leafy trees in 2017, the total leaf area estimated from T-LiDAR was also highly correlated (R²= 0.83) with manual measurements. Forthcoming works are undergoing for improving topological reconstruction algorithms in order to extract topological traits and new variables related to vegetative development on the whole population. Nevertheless this first study suggests that this method could be adapted for phenotypic architectural traits on large tree population on which genetic analyses could be performed.

International audience; The coffee tree is an important economic plant for several developing countries. Stem and leaf dry biomass, which are key traits of plant production, are used in functional-structural plant models to simulate plant growth and predict yield. These values are difficult to obtain since they classically rely on time-consuming protocols and require destructive measurements. Measuring stem and leaf dimensions (length and width) to estimate them provides a non-destructive and rapid approach for use in the field. In this study we sought the best allometric relationships existing between stem and leaf dimensions and their corresponding dry mass in order to avoid destructive measurements which are also time-consuming. This was investigated in three coffee species: Coffea canephora, Coffea liberica var. liberica and Coffea liberica var. dewevrei in Ivory Coast. For each species, the internodes and leaves of three axis categories (stem, branch and branchlet) comprising the main compartments were sampled. Two different equations were found to estimate the stem and leaf dry mass whatever the species and the axis categories: (1) a linear equation for the relation between the stem volume (V) and its corresponding dry mass (IWe), IWe = 0.70 × V and (2) a power law for the relation between the leaf area [as the product of length (LL) and width (Wi)] and its dry mass (LWe), LWe = 0.007 (LL × LWi)1.02. Finally, stem and leaf dry mass could be easily obtained without destructive measurements. This method could be applied to estimate the plant total leaf area and the total stem and leaf biomass of a plant in an agroforestry system.

Black leaf streak (BLS), caused by the phytopathogenic fungus Pseudocercospora fijiensis, leads to leaf necrosis and often to a substantial reduction in fruit yield. It also causes the fruit to ripen early by reducing the time between harvest and the beginning of natural ripening, called green life (GL). The usual method of control is by spraying fungicides, but this type of management is challenged worldwide due to the high costs, regulation of products, environmental concerns and the development of resistance. Integrated pest control is an alternative management method based on the combination of agronomic practices that can slow down the development of the epidemic, and limit damage to the fruit. Two experiments were conducted in the Dominican Republic and Martinique, to evaluate the performance of an innovative prototype cropping system with no chemical control. This system is based on optimal growth management, to reduce stress and enhance the leaf emission rate, combined with the systematic removal of necrotic parts of the leaves, which strongly limits ascopore sporulation and reduces the effect of BLS on GL. Depending on the conditions and cycles, the reduction in bunch weight with the prototype system versus chemical control ranged from O to 15%. Bananas were harvested at the same physiological age in the prototype and in the control. The bananas harvested from plants with as low as zero leaves left at harvest retained a good aptitude for conservation, with up to 40 days of GL, on average. The limited impact on fruit weight observed suggests that physiological compensation phenomena through remobilization of resources inside the plant (stem, bunch, suckers) occur. Above all, the removal of necrotic leaves prevented a significant negative effect on early fruit ripening when the bananas were harvested at the correct physiological age, and enabled export of the fruit despite the small number of leaves remaining on the plant at harvest. These results offer perspectives for the development and transfer of alternative practices to chemical control.

© 2018 The Authors Urban trees play a key role in mitigating environmental problems in cities, but they often face harsh environmental conditions as they generally grow in sealed soils that have small rooting space and low water availability. In this context, rapid monitoring and assessment of tree health status is critical to maintain urban trees and secure the provisioning of urban ecosystem services. Across three European cities we selected 187 Tilia tomentosa trees growing under following planting conditions: (i) sealed, trees planted in small soil pits or strips surrounded by highly sealed surfaces (concrete, pavement or asphalt); and (ii) unsealed, trees planted in roomy soil surfaces (e.g. parks). We measured leaf reflectance and fluorescence and derived a set of optical traits from the measurements. We examined whether these non-destructively measured optical traits differ between planting conditions and whether they correlate with leaf functional traits, e.g. specific leaf area (SLA), leaf water content (LWC) and leaf water per area (LWA). Compared to the unsealed trees, sealed trees showed decreased SLA and LWC while increased LWA. Leaf optical traits differed between the unsealed and sealed trees. Highly sealed soils accelerated leaf senescence of the sealed trees compared to the unsealed trees, embodied in the temporal trend of optical traits. Sealed planting conditions negatively affect urban tree health status and phenology. These negative effects can be estimated by leaf optical traits, demonstrating the great potential of optical traits in assessing tree health status. Our findings provide insights into facilitating urban green management using optical traits and remote sensing data. ispartof: ECOLOGICAL INDICATORS vol:95 pages:895-906 status: published

The morphological responses of seedlings of eight African provenances of Vitellaria paradoxa (Shea tree or Karite) to imposed draught stress were compared under nursery experimental conditions. The potted seedlings were subjected to three different watering regimes (87 days after sowing): no water stress (100% of the field capacity, C), moderate water stress (75% of C) and severe water stress (50% of C). Before the application of the stress, we observed genotypical differences in the morphological variables at the scale of leaves and of above-ground parts. The six-month water stress affected aerial growth: all provenances responded to drought by down-regulating growth (in height and in diameter), leaf number and area. Katawki provenance of Uganda performed relatively poorly, possibly of it being a nilotica subspecies, contrary to the others (paradoxa subspecies). There was a lack of correlation between climate of seeds origin, seed characteristics, seeds germination and survival rate of seedlings. The study confirmed the importance of leaf area in the vigor of the initial growth in this species. Thus, Tamale and Karaba provenances performed better than other West African provenances due to their larger leaf area, which was found to be a determining factor of relative growth in height at the seedling stage.

Accurate estimation of the terrestrial latent heat flux (LE) for each plant functional type (PFT) at high spatial and temporal scales remains a major challenge. We developed a satellite-based hybrid algorithm to determine the Priestley–Taylor (PT) parameter for estimating global terrestrial LE across multiple biomes. The hybrid algorithm combines a simple empirical equation with physically based ecophysiological constraints to obtain the sum of the weighted ecophysiological constraints (f(e)) from satellite-based normalized difference vegetation index (NDVI) and ground-measured air temperature (Ta), relative humidity (RH), vapor pressure deficit (VPD) and LE for 2000 to 2009 provided by 240 globally distributed FLUXNET eddy covariance (ECOR) tower sites. Cross-validation analysis indicated that the optimization at a PFT level performed well with a RMSE of less than 0.15 and a R2 between 0.61 and 0.88 for estimated monthly f(e). Cross-validation analysis also revealed good performance of the hybrid-based PT method in estimating seasonal variability with a RMSE of the monthly LE varying from 4.3 W/m2 (for 6 deciduous needleleaf forest sites) to 18.1 W/m2 (for 34 crop sites) and with a R2 of more than 0.67. The algorithm's performance was also good for predicting among-site and inter-annual variability with a R2 of more than 0.78 and 0.70, respectively. We implemented the global terrestrial LE estimation from 2003 to 2005 for a spatial resolution of 0.05°by recalibrating the coefficients of the hybrid algorithm using Modern Era Retrospective Analysis for Research and Applications (MERRA) meteorological data, Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI product and ground-measured LE. This simple but accurate hybrid algorithm provides an alternative method for mapping global terrestrial LE, with a performance generally improved as compared to other satellite algorithms that are not calibrated with tower. The calibrated f(e) differs for different PFTs, and all driving forces of the algorithm can be acquired from satellite and meteorological observations.

Yams are a neglected crop, grown mostly in West Africa by resource-poor farmers. Little is known about the physiology of the crop, and researchers lack practical and efficient tools to conduct growth analysis. The objective of this study was to develop allometric models able to predict yam leaf area and leaf and stem dry mass with acceptable accuracy. The models were calibrated using a data set comprising 10 cultivars belonging to the two main specks ([i]Dioscorea alata[/i] L. and [i]D. rotundata[/i] Poir.) grown at two locations in Guadeloupe (Lesser Antilles) and two locations in Benin (West Africa). The best models were selected based on Akaike's information criteria and validated against independent data sets. A power regression was best for predicting leaf area from leaf measurements while linear relationships were sufficient to predict the relationship between crop leaf area and leaf and stem mass. The use of species-specific models for the estimation of leaf and stem mass significantly improved the models' performance. Models predicting yam leaf area and leaf mass proved to be reliable and accurate (no significant deviation and adjusted R-2 > 0.95). For stem mass, overestimation always occurred during validation (9%). To overcome this discrepancy, a methodology was proposed that allows the user to calibrate the model by tailoring the sampling size to obtain the required precision. The use of the selected models provides a nondestructive and reliable alternative to estimate leaf area and leaf and stem biomass for different cultivars and sites

Dans un contexte de réchauffement global, les études sur l’apparition de la cavitation des arbres sont indispensables pour la compréhension et l’appréhension des mécanismes de tolérance à la sécheresse. Par rapport aux travaux sur la transpiration stomatique, principale responsable de cavitation dans les vaisseaux du xylème, peu de connaissances sont disponibles pour appréhender le rôle de la transpiration résiduelle dans les risques de cavitation après la fermeture stomatique. Les objectifs de cette étude sont de déterminer si la transpiration résiduelle est mesurable de façon gravimétrique et son incidence sur la vulnérabilité des plantes au stress hydrique. Pour ce faire, des plants et des feuilles isolées de Populus tremula x alba en régimes hydriques normal et défavorable et dans deux conditions de défoliation, entiers ou défoliés à moitié, ont été placés sur des balances et leur perte de masse a été enregistrée dans le temps. L’évolution du taux d’embolie a également été mesurée dans le temps pour les deux conditions de défoliation. Il en est ressorti que la méthode gravimétrique permet de visualiser la transpiration résiduelle in vivo dans le temps mais n’est pas suffisamment efficace pour montrer des différences avec des surfaces foliaires changeantes. En revanche, les mesures de taux d’embolie démontrent que la transpiration résiduelle a un rôle dans l’apparition de la cavitation.

Aim: The aim of the survey was to investigate if the grafting type influences the foliar expression of Esca during summer.Methods and Results: Observations were conducted on plots distributed in two French winegrowing regions (two different climatic regions) with two varieties (Cabernet-Sauvignon in the Bordeaux region and Mourvèdre in Provence). Three grafting types were compared: Omega graft, Whip and Tongue graft, and full cleft graft. For both varieties, we found a significant effect of the type of grafting on the foliar development of Esca symptoms. Full cleft grafted plots showed a significantly lower percentage of Esca foliar symptoms than the other two modalities, which were not significantly different from one another. Concerning Omega grafted plots, a significant difference in the rate of Esca foliar symptoms was highlighted compared to full cleft grafted plots, with a higher rate on Omega grafted plots, but these plots were also younger.Conclusions: The study established, for the first time, the difference between full cleft field grafted plots and Omega and Whip and Tongue grafted plots, revealing a higher incidence of Esca on the latter types of grafting.Significance and impact of the study: The spread of mechanical graft could be one of the factors explaining the increasing incidence of Esca in vineyard.

International audience; Leaf expansion depends on both carbon and water availabilities. In cereals, most of experimental effort has focused on leaf elongation, with essentially hydraulic effects. We have tested if evaporative demand and light could have distinct effects on leaf elongation and widening, and if short term effects could translate into final leaf dimensions. For that, we have monitored leaf widening and elongation in a field experiment with temporary shading, and in a platform experiment with 15-min temporal resolution and contrasting evaporative demands. Leaf widening showed a strong (positive) sensitivity to whole-plant intercepted light and no response to evaporative demand. Leaf elongation was (negatively) sensitive to evaporative demand, without effect of intercepted light per se. We have successfully tested resulting equations to predict leaf length and width in an external dataset of 15 field and 6 platform experiments. These effects also applied to a panel of 251 maize hybrids. Leaf length and width presented quantitative trait loci (QTLs) whose allelic effects largely differed between both dimensions but were consistent in the field and the platform, with high QTLxEnvironment interaction. It is therefore worthwhile to identify the genetic and environmental controls of leaf width and leaf length for prediction of plant leaf area.

In this study we present results from a laboratory experiment designed to evaluate the first-order chemical reaction rate (k) of ozone in water films on plant leaves occurring during dew or rain events. Ozone deposition to wet cuticles is indeed known to be a significant pathway of ozone deposition, but the underlying processes are not yet well understood. Leaf infusions obtained by infusing plant leaves with water at room temperature were introduced into a wet effluent denuder fed with a flux of ozone-rich air. Ozone, water vapour concentrations and temperature were measured in both inlet and outlet airflows in order to compute ozone reaction rates kr using an ozone reaction-diffusion model in the water film. Ascorbate solutions were used to validate the set up and led to kr = 3.6 107 M−1 s−1 consistent with the literature. Ozone reaction rates were determined for wheat, beech, oak and pine leaves infusions at several developmental stages were, as well as for rain samples. Leaf infusions reaction rates were between 240 s−1 and 3.4 105 s−1 depending on species and developmental stage, while kr for rain water range from 130 to 830 s−1. Wheat leaves solutions showed significantly (P

Biomass and leaf area equations are often required to assess or model forest productivity, carbon stocks and other ecosystem services. These factors are influenced by climate, age and stand structural attributes including stand density and tree species diversity or species composition. However, such covariates are rarely included in biomass and leaf area equations. We reviewed the literature and built a database of biomass and leaf area equations for 24 European tree species and 3 introduced species. The final dataset contained 973 equations. Most of the equations were site-specific and therefore restricted to the edaphic, climatic and stand structural conditions of the given site. To overcome this limitation, the database was used to develop regional species-specific equations that can be used in a wide range of stands and to quantify the effects of climate, age and stand structure on biomass or leaf area. The analysis showed considerable inter- and intra-specific variability in biomass relationships. The intra-specific variability was related to climate, age or stand characteristics, while the inter-specific variability was correlated with traits such as wood density, specific leaf area and shade tolerance. The analysis also showed that foliage mass is more variable than stem or total aboveground biomass, both within and between species, and these biomass components have contrasting responses to age and changes in stand structure. Despite the large number of published equations, many species are still not well represented. Therefore, generic equations were developed that include species-specific wood density instead of species identity. Further improvements may be possible if future studies quantify the stand structure of individual tree neighbourhoods instead of using the stand means for all trees sampled with the given stand. © 2017 The Authors

The CO2 fertilization effect is a major source of uncertainty in crop models for future yield forecasts, but coordinated efforts to determine the mechanisms of this uncertainty have been lacking. Here, we studied causes of uncertainty among 16 crop models in predicting rice yield in response to elevated [CO2] (E-[CO2]) by comparison to free-air CO2 enrichment (FACE) and chamber experiments. The model ensemble reproduced the experimental results well. However, yield prediction in response to E-[CO2] varied significantly among the rice models. The variation was not random: models that overestimated at one experiment simulated greater yield enhancements at the others. The variation was not associated with model structure or magnitude of photosynthetic response to E-[CO2] but was significantly associated with the predictions of leaf area. This suggests that modelled secondary effects of E-[CO2] on morphological development, primarily leaf area, are the sources of model uncertainty. Rice morphological development is conservative to carbon acquisition. Uncertainty will be reduced by incorporating this conservative nature of the morphological response to E-[CO2] into the models. Nitrogen levels, particularly under limited situations, make the prediction more uncertain. Improving models to account for [CO2] × N interactions is necessary to better evaluate management practices under climate change.

Modification of source–sink ratios in tropical maize through detasseling is an ancestral agronomical practice used for increasing yields under stressful conditions. However, the mechanisms behind such effect are not well understood given the difficulties to determine physiological processes such as photosynthesis and whole-plant transpiration in the field. We have tested the potential ability of kernel δ18O to assess differences in grain yield (GY) through changes in plant transpiration caused by the modification of water availability and source–sink modification treatments, (including removal of the tassel and different numbers of leaves) in three tropical maize hybrids differing in drought tolerance. Drought-tolerant genotypes displayed higher yields and lower kernel δ18O values than the drought-susceptible genotype under both well-watered (WW) and water-stressed (WS) conditions. Detasseling caused a positive increase in GY under well-watered (up to 8%) and water-deficit conditions (up to 36%). Reduction in leaf area (source) through defoliation treatments caused a large impact on GY showing a trade-off between maintaining a photosynthetic versus transpiring leaf area. Thus, while a reasonable reduction in leaf area significantly improved plant water availability (as shown by lower kernel δ18O values) and consequently GY under water deficit (up to 40%), it caused a maximum reduction of 25% in GY under well-watered conditions. Variations in GY were significantly (p < .05) correlated with changes in δ18O under both well-watered (r = −.67) and WS conditions (r = .75 and .82). Our results also reinforce the utility of δ18O measured in mature kernels as a powerful ecophysiological tool for assessing genotypic differences in apical dominance, transpiration and yield under both WW and WS conditions in tropical maize.

Background Plant science uses increasing amounts of phenotypic data to unravel the complex interactions between biological systems and their variable environments. Originally, phenotyping approaches were limited by manual, often destructive operations, causing large errors. Plant imaging emerged as a viable alternative allowing non-invasive and automated data acquisition. Several procedures based on image analysis were developed to monitor leaf growth as a major phenotyping target. However, in most proposals, a time-consuming parameterization of the analysis pipeline is required to handle variable conditions between images, particularly in the field due to unstable light and interferences with soil surface or weeds. To cope with these difficulties, we developed a low-cost, 2D imaging method, hereafter called PYM. The method is based on plant leaf ability to absorb blue light while reflecting infrared wavelengths. PYM consists of a Raspberry Pi computer equipped with an infrared camera and a blue filter and is associated with scripts that compute projected leaf area. This new method was tested on diverse species placed in contrasting conditions. Application to field conditions was evaluated on lettuces grown under photovoltaic panels. The objective was to look for possible acclimation of leaf expansion under photovoltaic panels to optimise the use of solar radiation per unit soil area. Results The new PYM device proved to be efficient and accurate for screening leaf area of various species in wide ranges of environments. In the most challenging conditions that we tested, error on plant leaf area was reduced to 5% using PYM compared to 100% when using a recently published method. A high-throughput phenotyping cart, holding 6 chained PYM devices, was designed to capture up to 2000 pictures of field-grown lettuce plants in less than 2 h. Automated analysis of image stacks of individual plants over their growth cycles revealed unexpected differences in leaf expansion rate between lettuces rows depending on their position below or between the photovoltaic panels. Conclusions The imaging device described here has several benefits, such as affordability, low cost, reliability and flexibility for online analysis and storage. It should be easily appropriated and customized to meet the needs of various users. Electronic supplementary material The online version of this article (10.1186/s13007-017-0248-5) contains supplementary material, which is available to authorized users.

Leaf area index estimates in dense evergreen tropical moist forest almost exclusively rest on indirect methods most of which being of limited accuracy or spatial resolution. In this study we examine the potential of full waveform Aerial Laser Scanning (ALS) to derive accurate spatially explicit estimates of Plant Area Index (PAI). A discrete representation of the forest canopy is introduced in the form of a 3D voxelized space. For each voxel (elementary volume, typically one cubic m) a first estimate of local transmittance of vegetation is computed as the ratio of the sum of energy exiting a voxel to the sum of energy entering the same voxel. A spatially hierarchical model is subsequently applied to refine estimates of individual voxel transmittance. Plant area density (PAD) profiles are then computed from the local transmittance values by applying Beer Lambert's turbid medium approximation. PAI values are obtained from vertical integration of PAD profiles. The model is shown to be robust to low sampling intensity and high occlusion rates. We further compared simulated values of gap fraction obtained by ray tracing for 5 angular sectors with in situ LAI2200 measurements taken at 135 positions in a 0.5 ha forest plot located in the center of the scene. The overall patterns of simulated and measured values (average value per inclination and pattern of variation along a 70 m transect line) were highly consistent. A slight but systematic discrepancy was observed along the inclination gradient, gap fractions derived from ray tracing in the voxelized scene being slightly lower than the measured values. This difference might be the consequence of multiple reflections which have been found to bias gap fractions estimates produced by LAI2200. PAI estimates derived from LAI2200 measurements (either simulated 6.8 or observed 5.9) are much lower than the PAI derived from vertical integration of local PAD (13.6). This large difference reflects the fact that distribution of foliage is strongly spatially structured and that this structural information is not properly accounted for in PAI estimates derived from mean gap fraction per elevation angle. After adjusting local transmittance to match mean LAI 2200 profiles the PAI at plot level was found to be 13.2 m2·m− 2. We conclude that Aerial Laser Scanning can produce accurate maps of Plant Area Index over large areas with unmatched efficacy, accuracy and ease. This should be of major relevance for many forest ecological studies.

Methods are presented testing the suitability of PROSAIL radiative transfer model for analysing HyMap imaging spectroscopy data over grassland. The presented methods include forward modelling and cross-checks of 2D correlation plots. In the forward modelling, it is taken into account that the in situ data are not error free. To increase the predictive power of PROSAIL, a simple and fully automatic feature selection (FS) algorithm is presented identifying and discarding poorly modelled wavebands, yielding more reliable parameter retrievals.