Modélisation de l'influence de la démographie foliaire sur les données de télédétection par DART et PROSPECT-D

International audienceThe seasonality of Amazon forest productivity and photosynthetic activity has recently been investigated under a new perspective by a series of publications. The debate about possible factors explaining this seasonality is vivid, and the possibility of several hypotheses has been tested, including canopy phenology and leaf demography, and changes in illumination geometry combined with the complex 3D structure of the canopy. A manifold of measurements and techniques have been used to test these hypotheses, including field observations of leaf demography from ground measured litterfall and phenocam, airborne and satellite remote sensing and 3 dimensional radiative transfer modeling. Our study explores the relative influence of leaf demography and illumination geometry on remotely sensed data. To achieve this, we take advantage of the latest advances in the domain of physical modeling at both leaf and canopy scale. The leaf optical properties model PROSPECT-D was used to model leaf optical properties at various growth stages based on field observations and theoretical leaf biochemical composition during its development and senescence. The 3-dimensional radiative transfer model DART was used to simulate various levels of complexity of canopy covers, from a turbid layer to complex canopy derived from airborne LiDAR acquisitions. Data for leaf demography and ontogeny taken from recent publications was used and integrated into canopy simulations corresponding to year-long observations. Data acquisitions were performed in the frame of the HyperTropik project (funded by CNES) and our results focus on analyzing the influence of separated and combined factors on various spectral attributes, including Enhanced vegetation index and hyperspectral metrics.La saisonnalité de la productivité et l'activité photosynthétique de la forêt amazonienne ont récemment été étudiées sous une nouvelle perspective par une série de publications. Le débat sur les facteurs possibles expliquant cette saisonnalité est ouvert, et la possibilité de plusieurs hypothèses a été testée, y compris la phénologie de la canopée et la démographie foliaire, et les changements de la géométrie d'éclairage combinée avec la structure 3D complexe de la canopée. Une multiplicité de mesures et de techniques ont été utilisées pour tester ces hypothèses, y compris les observations sur le terrain de la démographie foliaire de la chute de litière mesurée au sol et du phénocam, de la télédétection aéroportée et satellite et de la modélisation par transfert radiatif en trois dimensions. Notre étude explore l'influence relative de la démographie foliaire et de la géométrie de l'éclairage sur les données de télédétection. Pour ce faire, nous tirons parti des dernières avancées dans le domaine de la modélisation physique à la fois à l'échelle des feuilles et de la canopée. Le modèle de propriétés optiques des feuilles PROSPECT-D a été utilisé pour modéliser les propriétés optiques des feuilles à différents stades de croissance sur la base d'observations sur le terrain et de la composition biochimique théorique des feuilles pendant son développement et sa sénescence. Le modèle de transfert radiatif en trois dimensions DART a été utilisé pour simuler divers niveaux de complexité des couvertures de la canopée, d’une couche turbide à une représentation complexe dérivée d’acquisitions LiDAR. Les données sur la démographie foliaire et sur l'ontogenèse prises à partir de publications récentes ont été utilisées et intégrées dans des simulations de couvertures correspondant à des observations d'une année. Les acquisitions de données ont été effectuées dans le cadre du projet HyperTropik (financé par le CNES) et nos résultats se concentrent sur l'analyse de l'influence de facteurs séparés et combinés sur divers attributs spectraux, y compris l'indice de végétation amélioré EVI et les mesures hyperspectrales

Estimating leaf mass per area and equivalent water thickness based on leaf optical properties: potential and limitations of physical modeling and machine learning.

International audienc

Evaluation of the potential of MODIS satellite data to predict vegetation phenology in different biomes: An investigation using ground-based NDVI measurements

Vegetation phenology is the st udy of the timing of seasonal events that are considered to be the result of adaptive responses to climate variations on short and long time scales. In the field of remote sensing of vegetation phenology, phenologicalmetrics are derived fromtime series of optical data. For that purpose, considerable effort has been specifically focused on developing noise reduction and cloud-contaminated data removal techniques to improve the quality of remotely-sensed time series. Comparative studies between time series composed of satellite data acquired under clear and cloudy conditions and fromradiometric data obtainedwith high accuracy fromground-basedmeasurements constitute a direct and effective way to assess the operational use and limitations of remote sensing for predicting the main plant phenological events. In the present paper, we sought to explicitly evaluate the potential use of MODerate resolution Imaging Spectroradiometer (MODIS) remote sensing data for monitoring the seasonal dynamics of different types of vegetation cover that are representative of the major terrestrial biomes, including temperate deciduous forests, evergreen forests, African savannah, and crops. After cloud screening and filtering, we compared the temporal patterns and phenological metrics derived from in situ NDVI time series and from MODIS daily and 16-composite products. We also evaluated the effects of residual noise and the in uence of data gaps in MODIS NDVI time series on the identification of the most relevant metrics for vegetation phenology monitoring. The results show that the in exion points of a model fitted to a MODIS NDVI time series allow accurate estimates of the onset of greenness in the spring and the onset of yellowing in the autumn in deciduous forests (RMSE<oneweek). Phenologicalmetrics identical to those providedwith theMODIS Global Vegetation Phenology product (MDC12Q2) are less robust to data gaps, and they can be subject to large biases of approximately twoweeks or more during the autumn phenological transitions. In the evergreen forests, in situ NDVI time series describe the phenology with high fidelity despite small temporal changes in the canopy foliage. However, MODIS is unable to provide consistent phenological patterns. In crops and savannah, MODIS NDVI time series reproduce the general temporal patterns of phenology, but significant discrepancies appear between MODIS and ground-based NDVI time series during very localized periods of time depending on the weather conditions and spatial heterogeneity within the MODIS pixel. In the rainforest, the temporal pattern exhibited by a MODIS 16-day composite NDVI time series ismore likely due to a pattern of noise in the NDVI data structure according to both rainy and dry seasons rather than to phenological changes. More investigations are needed, but in all cases, this result leads us to conclude that MODIS time series in tropical rainforests should be interpreted with great caution

Host selection and utilisation of Sonchus oleraceus (Asteraceae) by Helicoverpa armigera (Lepidoptera : Noctuidae): A genetic analysis

The cotton bollworm (Helicoverpa armigera) prefers the common sowthistle (Sonchus oleraceus L.) to cotton (Gossypium hirsutum L.), sorghum (Sorghum bicolor L.) and maize (Zea mays L.) for oviposition in the field in Australia. Using the common sowthistle and cotton as host plants, we carried out this study to evaluate genetic variation in both oviposition preference and larval growth and genetic correlation between maternal preference and larval performance. There was a significant genetic component of phenotypic variation in both characters, and the heritability of oviposition preference was estimated as 0.602. Helicoverpa armigera larvae survived slightly better and grew significantly faster on common sowthistle than on cotton, but genetic correlation between maternal preference and larval growth performance was not detectable. Instead, larval growth performance on the two hosts changed with families, which renders the interaction between family and host plant significant. As a result, the genetic correlation between mean values of larval growth across the two host species was not different from zero. These results are discussed in the context of the relationship between H. armigera and the common sowthistle and the polyphagous behaviour of this insect in general

Foraging behaviour of Helicoverpa armigera first instar larvae on crop plants of different developmental stages

Understanding how insect pests forage on their food plants can help optimize management strategies. Helicoverpa armigera (Hubner) (Lep., Noctuidae) is a major polyphagous pest of agricultural crops worldwide. The immature stages feed and forage on crops at all stages of plant development, damaging fruiting and non-fruiting structures, yet very little is known about the influence of host type or stage on the location and behaviour of larvae. Through semi-continuous observation, we evaluated the foraging (movement and feeding) behaviours of H. armigera first instar larvae as well as the proportion of time spent at key locations on mungbean [Vigna radiata (L.) Wilczek] and pigeon pea [Cajanus cajan (L.) Millspaugh] of differing developmental stages: seedling- and mature (flowering/pod fill)-stage plants. Both host type and age affected the behaviour of larvae. Larvae spent more time in the upper parts of mature plants than on seedlings and tended to stay at the top of mature plants if they moved there. This difference was greater in pigeon pea than in mungbean. The proportion of time allocated to feeding on different parts of a plant differed with host and age. More feeding occurred in the top of mature pigeon pea plants but did not differ between mature and seedling mungbean plants. The duration of key behaviours did not differ between plant ages in either crop type and was similar between hosts although resting bouts were substantially longer on mungbeans. Thus a polyphagous species such as H. armigera does not forage in equivalent ways on different hosts in the first instar stage