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Terrestrial laser scanning intensity captures diurnal variation in leaf water potential / S. Junttila in Remote sensing of environment, Vol 255 (March 2021)  

Public [article]  inRemote sensing of environment > Vol 255 (March 2021) . - n° 112274 Titre : Terrestrial laser scanning intensity captures diurnal variation in leaf water potential Type de document : Article/Communication Auteurs : S. Junttila, Auteur ; T. Hölttä, Auteur ; Eetu Puttonen, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 112274 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] Betula (genre) [Termes descripteurs IGN] diagnostic foliaire [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] dynamique de la végétation [Termes descripteurs IGN] Pinus sylvestris [Termes descripteurs IGN] sécheresse [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] stress hydrique [Termes descripteurs IGN] teneur en eau de la végétation [Termes descripteurs IGN] variation diurne Résumé : (auteur) During the past decades, extreme events have become more prevalent and last longer, and as a result drought-induced plant mortality has increased globally. Timely information on plant water dynamics is essential for understanding and anticipating drought-induced plant mortality. Leaf water potential (ΨL), which is usually measured destructively, is the most common metric that has been used for decades for measuring water stress. Remote sensing methods have been developed to obtain information on water dynamics from trees and forested landscapes. However, the spatial and temporal resolutions of the existing methods have limited our understanding of the water dynamics and diurnal variation of ΨL within single trees. Thus, we investigated the capability of terrestrial laser scanning (TLS) intensity in observing diurnal variation in ΨL during a 50-h monitoring period. We aimed to improve the understanding on how large a part of the diurnal variation in ΨL can be captured using TLS intensity observations. We found that TLS intensity at the 905 nm wavelength measured from a static position was able to explain 77% of the variation in ΨL for three trees of two tree species with a root mean square error of 0.141 MPa. Based on our experiment with three trees, a time series of TLS intensity measurements can be used in detecting changes in ΨL, and thus it is worthwhile to expand the investigations to cover a wider range of tree species and forests and further increase our understanding of plant water dynamics at wider spatial and temporal scales. Numéro de notice : A2021-192 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2020.112274 date de publication en ligne : 14/01/2021 En ligne : https://doi.org/10.1016/j.rse.2020.112274 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97113 [article]

Secondary metabolites in leaves of hybrid aspen are affected by the competitive status and early thinning in dense coppices / Linda Rusalepp in Annals of Forest Science [en ligne], vol 78 n° 1 (March 2021)  

Public [article]  inAnnals of Forest Science [en ligne] > vol 78 n° 1 (March 2021) . - n° 1 Titre : Secondary metabolites in leaves of hybrid aspen are affected by the competitive status and early thinning in dense coppices Type de document : Article/Communication Auteurs : Linda Rusalepp, Auteur ; Reimo Lutter, Auteur ; Heiki Hepner, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 1 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] arbre dominant [Termes descripteurs IGN] diagnostic foliaire [Termes descripteurs IGN] éclaircie (sylviculture) [Termes descripteurs IGN] gestion forestière [Termes descripteurs IGN] peuplement mélangé [Termes descripteurs IGN] Populus tremula [Termes descripteurs IGN] taillis [Vedettes matières IGN] Sylviculture Résumé : (auteur) Key message: Non-selective thinning of a hybrid aspen coppice stands via corridor or cross-corridor cutting impacts residual trees differently depending on their competitive status. Suppressed residual trees’ metabolic profile indicates increased stress level, especially after cross-corridor thinning. Context: Early thinning with regular corridor harvests is proposed for the management of post-harvest re-sprouted hybrid aspen (Populus tremula L. × P. tremuloides Michx.) coppice stands. The selection of remaining trees is not size-based and their physiological acclimation to the post-thinning conditions is unknown. Aims: To analyse differences in secondary metabolite profile between thinning treatments and trees competitive status. Methods: We used an HPLC-qTOF mass spectrometer to analyse the leaf extracts of dominant and suppressed trees from stands with different thinning intensities: un-thinned control with basal area of 15.4 ± 1.52 m2 ha−1, corridor thinning with basal area of 8.5 ± 0.46 m2 ha−1 and cross-corridor thinning with basal area of 3.9 ± 0.34 m2 ha−1. Results: Competitive status and thinning treatment both had significant effects on the contents of compounds. Higher exposure to irradiance increased the contents of flavonoids and hydroxycinnamates. Corridor thinning treatments doubled the foliar contents of secondary metabolites and lowered macronutrient contents in competitively suppressed residual trees. Dominant residual trees were not affected in this respect. Conclusion: Forest management practice and competitive status can significantly modify the metabolite profile in tree leaves. After corridor thinning of a young aspen coppice stand, the small-sized residual trees may initially respond with increased allocation to leaf chemical defence rather than to productivity. Numéro de notice : A2021-030 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-020-01014-3 date de publication en ligne : 05/01/2021 En ligne : https://doi.org/10.1007/s13595-020-01014-3 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96722 [article]

A machine learning framework for estimating leaf biochemical parameters from its spectral reflectance and transmission measurements / Bikram Koirala in IEEE Transactions on geoscience and remote sensing, vol 58 n° 10 (October 2020)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 58 n° 10 (October 2020) . - pp 7393 - 7405 Titre : A machine learning framework for estimating leaf biochemical parameters from its spectral reflectance and transmission measurements Type de document : Article/Communication Auteurs : Bikram Koirala, Auteur ; Zohreh Zahiri, Auteur ; Paul Scheunders, Auteur Année de publication : 2020 Article en page(s) : pp 7393 - 7405 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] apprentissage automatique [Termes descripteurs IGN] apprentissage dirigé [Termes descripteurs IGN] biochimie [Termes descripteurs IGN] diagnostic foliaire [Termes descripteurs IGN] feuille (végétation) [Termes descripteurs IGN] indice de végétation [Termes descripteurs IGN] méthode fondée sur le noyau [Termes descripteurs IGN] processus gaussien [Termes descripteurs IGN] réflectance spectrale [Termes descripteurs IGN] régression [Termes descripteurs IGN] teneur en chlorophylle des feuilles Résumé : (auteur) Spectral measurements are commonly applied for the nondestructive estimation of leaf parameters, such as the concentrations of chlorophyll a and b, carotenoid, anthocyanin, brown pigment, leaf water content, and leaf mass per area for the quantification of vegetation physiology. The most popular way to estimate these parameters is by using spectral vegetation indices. The use of biochemical models allows us to use the full wavelength range (400–2500 nm) and to physically interpret the result. However, their performance is usually lower than that of supervised machine learning regression techniques. Machine learning regression techniques, on the other hand, have the disadvantage that the relationship between estimated parameters and the reflectance/transmission spectra is unclear. In this article, a hybrid between a supervised learning method and physical modeling for the estimation of leaf parameters is proposed. In this method, a machine learning regression technique is applied to learn a mapping from the true hyperspectral data set to a data set that follows the PROSPECT model. The PROSPECT model then reveals the actual leaf parameters. Two mapping methods, based on Gaussian processes (GPs) and kernel ridge regression (KRR) are proposed. As an alternative, mapping onto the leaf absorption spectra is proposed as well. The proposed methodology not only estimates the leaf parameters with a lower error but also solves the interpretation problem of the parameters estimated by the advanced machine learning regression techniques. This method is validated on the ANGERS and LOPEX data set. Numéro de notice : A2020-589 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.2982263 date de publication en ligne : 02/04/2020 En ligne : https://doi.org/10.1109/TGRS.2020.2982263 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95919 [article]

Warming effects on morphological and physiological performances of four subtropical montane tree species Authors Authors and affiliations / Yiyong Li in Annals of Forest Science [en ligne], Vol 77 n° 1 (March 2020)  

Public [article]  inAnnals of Forest Science [en ligne] > Vol 77 n° 1 (March 2020) . - 11 p. Titre : Warming effects on morphological and physiological performances of four subtropical montane tree species Authors Authors and affiliations Type de document : Article/Communication Auteurs : Yiyong Li, Auteur ; Yue Xu, Auteur ; Ting Wu, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 11 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] changement climatique [Termes descripteurs IGN] croissance végétale [Termes descripteurs IGN] diagnostic foliaire [Termes descripteurs IGN] effet thermique [Termes descripteurs IGN] forêt tropicale [Termes descripteurs IGN] hauteur des arbres [Termes descripteurs IGN] montagne [Termes descripteurs IGN] morphologie [Termes descripteurs IGN] photosynthèse [Termes descripteurs IGN] stress hydrique [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Key message: In a downward transplantation experiment, warming stimulated growth and photosynthesis of Schima superba Gardn. et Champ., Syzygium rehderianum Merr. et Perry and Itea chinensis Hook. et Arn. via increased stomatal conductance. Warming had no effect on growth of Machilus breviflora (Benth.) Hemsl., indicating species-specific differences in response to warming. Context: Climate change has been shown to shift species composition and community structure in subtropical forests. Thus, understanding the species-specific responses of growth and physiological processes to warming is essential. Aims: To investigate how climate warming affects growth, morphological and physiological performance of co-occurring tree species when they are growing at different altitudes. Methods: Soils and 1-year-old seedlings of four subtropical co-occurring tree species (Schima superba Gardn. et Champ., Syzygium rehderianum Merr. et Perry, Itea chinensis Hook. et Arn. and Machilus breviflora (Benth.) Hemsl.) were transplanted to three altitudes (600 m, 300 m and 30 m a.s.l.), inducing an effective warming of 1.0 °C and 1.5 °C. Growth, morphological, and physiological performances of these seedlings were monitored. Results: When exposed to warmer conditions, aboveground growth of the four species except M. breviflora was strongly promoted, accompanied by increased light-saturated photosynthetic rate and stomatal conductance. Warming also significantly increased concentrations of non-structural carbohydrates in leaves of S. rehderianum and M. breviflora, stems of S. superba and S. rehderianum, and roots of I. chinensis. However, we did not detect any effect of warming on stomatal length and stomatal density. Conclusion: Our results provide evidence that climate warming could have species-specific impacts on co-occurring tree species, which might subsequently shift species composition and forest structure. Numéro de notice : A2020-037 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-019-0910-3 date de publication en ligne : 10/01/2020 En ligne : https://doi.org/10.1007/s13595-019-0910-3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94491 [article]

Application of digital image processing in automated analysis of insect leaf mines / Yee Man Theodora Cho (2020)  

Public Titre : Application of digital image processing in automated analysis of insect leaf mines Type de document : Thèse/HDR Auteurs : Yee Man Theodora Cho, Auteur Editeur : York [Royaume-Uni] : University of York Année de publication : 2020 Importance : 202 p. Format : 21 x 30 cm Note générale : bibliographie PhD thesis, Electronic Engineering, University of York, United Kingdom Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] Acer (genre) [Termes descripteurs IGN] analyse de groupement [Termes descripteurs IGN] apprentissage automatique [Termes descripteurs IGN] Castanea (genre) [Termes descripteurs IGN] classification par Perceptron multicouche [Termes descripteurs IGN] détection de contours [Termes descripteurs IGN] diagnostic foliaire [Termes descripteurs IGN] image hyperspectrale [Termes descripteurs IGN] insecte nuisible [Termes descripteurs IGN] modèle de simulation [Termes descripteurs IGN] segmentation d'image [Termes descripteurs IGN] seuillage [Termes descripteurs IGN] surveillance de la végétation [Termes descripteurs IGN] taxinomie [Termes descripteurs IGN] traitement d'image Résumé : (auteur) Automated species identificationhas become a popular alternative to manual classification in the past few decades, as a result of advancement in digital image processing techniques and machine learning algorithms. This project aims to devise a new approach for the detection of leaf mines and fungal spots from digital images, and to investigate the possibility of monitoring the growth of leaf mines. Leaf-mining insects primarily belong to the orders of moths (Lepidoptera), flies (Diptera) and beetles (Coleoptera); or the suborders of sawflies (Symphyta) and wasps (Apocrita). Every spring and summer the larvae of leaf-mining insects feed on leaf tissues until maturity and vacate the mines as adults. As most species of leaf miners attack garden plants or crops, they are generally regarded as pests, despiterarely causing severe long-term detrimental effect on their host plants. Increase in human activities has led to the spread of these invasive species globally in recent years, and the demand for an effective classification system to monitor their distribution is rising consistently. Samples from three species of leaf-mining insects were included in this project: horse chestnut leaf miner (Cameraria ohridella), apple leaf miner (Lyonetia clerkella), and holly leaf miner (Phytomyza ilicis). Leaves with tar spots (Rhytisma acerinum)were also introduced as variations.The proposed method uses image processing techniques such as thresholding, conversion between colour spaces, edge detection, image segmentation,and morphological operations. This project also explores the use of machine learning algorithmsas analytical monitoring and predictive tools, using the growth of C. ohridellaleaf mines as an example. Note de contenu : 1- Introduction 2- Background 3- Digital image processing 4- Automated classification 5- Implementation 6- Data analysis 7- Conclusion Numéro de notice : 28552 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Thèse étrangère Note de thèse : PhD thesis : Electronic Engineering : University of York : 2020 En ligne : https://etheses.whiterose.ac.uk/27749/1/Cho_105036528_Thesis.pdf Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97414

Effects of stand density on ecosystem properties of subalpine forests in the southern Rocky Mountains, USA / Sharon J. Hall in Annals of Forest Science, vol 67 n° 1 (January-February 2010)  

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Estimation of chlorophyll in Quercus leaves using a portable chlorophyll meter: effects of species and leaf age / Fernando Silla in Annals of Forest Science, vol 67 n° 1 (January-February 2010)  

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Temporal trends in the foliar nutritional status of the French, Walloon and Luxembourg broad-leaved plots of forest monitoring / Mathieu Jonard in Annals of Forest Science, Vol 66 n° 4 (June 2009)  

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Evolution de la nutrition des peuplements : vers une carence générale en phosphore ? / Luc Croisé in Rendez-vous techniques, Hors-série n° 4 (2008)

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Interactive responses of Quercus suber L. seedlings to light and mild water stress: effects on morphology and gas exchange traits / Jaime Puértolas in Annals of Forest Science, Vol 65 n° 6 (September 2008)  

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