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Relative influence of stand and site factors on aboveground live-tree carbon sequestration and mortality in managed and unmanaged forests / Christel C. Kern in Forest ecology and management, vol 493 (1st August 2021)  

Public [article]  inForest ecology and management > vol 493 (1st August 2021) . - n° 119266 Titre : Relative influence of stand and site factors on aboveground live-tree carbon sequestration and mortality in managed and unmanaged forests Type de document : Article/Communication Auteurs : Christel C. Kern, Auteur ; Laura S. Kenefic, Auteur ; Christian Kuehne, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 119266 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] arbre mort [Termes IGN] climat [Termes IGN] Etats-Unis [Termes IGN] forêt inéquienne [Termes IGN] gestion forestière [Termes IGN] puits de carbone [Termes IGN] structure d'un peuplement forestier [Termes IGN] teneur en carbone [Vedettes matières IGN] Foresterie Résumé : (auteur) We compiled data from several independent, long-term silvicultural studies on USDA Forest Service experimental forests across a latitudinal gradient in the northeastern and north-central U.S.A. to evaluate factors influencing aboveground live-tree carbon sequestration and mortality. Data represent five sites with more than 70,000 repeated tree records spanning eight decades, five ecoregions, and a range of stand conditions. We used these data to test the relative influence of factors such as climate, treatment history (uneven-aged or no management), species composition, and stand structural conditions on aboveground live-tree carbon sequestration and mortality in repeatedly measured trees. Relative to no management, we found that uneven-aged management tended to have a positive effect on carbon sequestration at low stocking levels and in areas of favorable climate (expressed as a combination of growing season precipitation and annual growing degree days > 5 °C). In addition, losses of carbon from the aboveground live-tree pool due to tree mortality were lower in managed than unmanaged stands. These findings suggest that there may be conditions at which rate of sequestration in living trees is higher in stands managed with uneven-aged silviculture than in unmanaged stands, and that this benefit is greatest where climate is favorable. Numéro de notice : A2021-458 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2021.119266 date de publication en ligne : 28/04/2021 En ligne : https://doi.org/10.1016/j.foreco.2021.119266 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97920 [article]

Detecting structural changes induced by Heterobasidion root rot on Scots pines using terrestrial laser scanning / Timo P Pitkänen in Forest ecology and management, vol 492 (15 July 2021)  

Public [article]  inForest ecology and management > vol 492 (15 July 2021) . - n° 119239 Titre : Detecting structural changes induced by Heterobasidion root rot on Scots pines using terrestrial laser scanning Type de document : Article/Communication Auteurs : Timo P Pitkänen, Auteur ; Tuula Piri, Auteur ; Aleski Lehtonen, Auteur ; Mikko Peltoniemi, Auteur Année de publication : 2021 Article en page(s) : n° 119239 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] arbre mort [Termes IGN] détection de changement [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] données lidar [Termes IGN] Finlande [Termes IGN] Fungi [Termes IGN] houppier [Termes IGN] maladie phytosanitaire [Termes IGN] Pinus sylvestris [Termes IGN] semis de points Résumé : (auteur) Root rot, caused by the decay fungus Heterobasidion annosum, damages both below- and above-ground parts of Scots pines (Pinus Sylvestris L.). The diseased pines are often first characterized by deteriorated crowns and they will eventually be killed by the infection, but the process is gradual and difficult to be observed before the symptoms are severe. We tested the applicability of point cloud data produced by terrestrial laser scanning (TLS) for quantifying the structural differences between the healthy and the diseased trees. This approach was applied in a mature pine stand in southern Finland, which was known to be infected by H. annosum. We first scanned the stand using TLS, and thereafter felled the trees for detailed inspection and classification of the infection status. From the TLS point cloud, we estimated i) crosscut areas within the lowest 1 m of the stem, identifying potential deformations initiated by the fungus, ii) degree of crown deterioration, often providing the first visual signs of the infection at the level of individual trees, and iii) crown occupancy and open space around the trees, prone to be altered by the mycelial spread of the fungus between the adjacent trees. The results indicate that differences in both stem dimensions and crown deterioration can be detected between the healthy and the diseased trees. The diseased trees were found to have a more swollen butt, but no irregularities in circularity of the crosscuts were detected. In terms of vertical point distribution, the diseased trees had point accumulations at substantially greater heights, reflecting easier penetration of laser beams and sparsity of the crown. Regarding to crown occupancy, the diseased trees had more open space around their crowns, but difference to the healthy trees was not statistically significant. According to a simple prediction test based on the calculated features, up to 85% classification accuracy of the infection status was reached. This study is the first indication that TLS can successfully be applied for detecting structural changes of Scots pines connected to Heterobasidion root rot. Our results also show evidence that H. annosum causes butt swelling, which has rarely been reported as a symptom for Scots pines. Numéro de notice : A2021-457 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.foreco.2021.119239 date de publication en ligne : 29/04/2021 En ligne : https://doi.org/10.1016/j.foreco.2021.119239 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97914 [article]

An innovative and automated method for characterizing wood defects on trunk surfaces using high-density 3D terrestrial LiDAR data / Van-Tho Nguyen in Annals of Forest Science [en ligne], vol 78 n° 2 (June 2021)  

Public [article]  inAnnals of Forest Science [en ligne] > vol 78 n° 2 (June 2021) . - Article 32 Titre : An innovative and automated method for characterizing wood defects on trunk surfaces using high-density 3D terrestrial LiDAR data Type de document : Article/Communication Auteurs : Van-Tho Nguyen, Auteur ; Thiéry Constant, Auteur ; Francis Colin, Auteur Année de publication : 2021 Article en page(s) : Article 32 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] analyse comparative [Termes IGN] apprentissage automatique [Termes IGN] détection d'anomalie [Termes IGN] données de terrain [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] écorce [Termes IGN] Fagus sylvatica [Termes IGN] qualité du bois [Termes IGN] Quercus sessiliflora [Termes IGN] segmentation d'image [Termes IGN] télémétrie laser terrestre [Termes IGN] tronc Résumé : (Auteur) We designed a novel method allowing to automatically detect and measure defects on the surface of trunks including branches, branch scars, and epicormics from terrestrial LiDAR data by using only high-density 3D information. We could automatically detect and measure the defects with a diameter as small as 0.5 cm on either oak (Quercus petraea (Matt.) Liebl.) or beech (Fagus sylvatica L.) trees that display either rough or smooth bark. Context : Ground-based light detection and ranging (LiDAR) technology describes standing trees with a high level of detail. This provides an opportunity to assess standing tree quality and to use this information in forest inventory. Assuming the availability of a very high level of detail, we could extract information about the surface defects, mainly inherited from past ramification and having a strong impact on wood quality. Aims : Within the general framework of the development of a computing method able to detect, identify, and quantify the defects on the trunk surface described from 3D data produced by a terrestrial LiDAR, this study focuses on the relevance of the whole process for two tree species with contrasted bark roughness (Quercus petraea (Matt.) Liebl. and Fagus sylvatica L.) in terms of detection, identification of the defects, and comparison with measurements performed manually on the bark surface. Methods : First, a segmentation algorithm detected singularities on the trunk surface. Next, a Random Forests machine learning algorithm identified the most probable defect type and allowed the elimination of false detections. Finally, we estimated the position, horizontal, and vertical dimensions of each defect from 3D data, and we compared them to those observed directly on the trunk by an operator. Results : The defects were detected and classified with a high accuracy with an average F1 score (harmonic mean of precision and recall) of 0.74. There were differences in computed and observed defect areas, but a much closer agreement for the number of defects. Conclusion : The information about the defects present on the trunk surface measured from terrestrial LiDAR data can be used in an automated procedure for grading standing trees or roundwoods. Numéro de notice : A2021-326 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-020-01022-3 date de publication en ligne : 01/04/2021 En ligne : https://doi.org/10.1007/s13595-020-01022-3 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97484 [article]

Characterization of mixed and monospecific stands of Scots pine and Maritime pine: soil profile, physiography, climate and vegetation cover data / Daphne Lopez-Marcos in Annals of Forest Science [en ligne], vol 78 n° 2 (June 2021)  

Public [article]  inAnnals of Forest Science [en ligne] > vol 78 n° 2 (June 2021) . - Article 28 Titre : Characterization of mixed and monospecific stands of Scots pine and Maritime pine: soil profile, physiography, climate and vegetation cover data Type de document : Article/Communication Auteurs : Daphne Lopez-Marcos, Auteur ; Maria-Belen Turrion, Auteur ; Felipe Bravo, Auteur ; Carolina Martinez-Ruiz, Auteur Année de publication : 2021 Article en page(s) : Article 28 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] composition d'un peuplement forestier [Termes IGN] couvert forestier [Termes IGN] données environnementales [Termes IGN] échantillonnage de données [Termes IGN] Espagne [Termes IGN] état du sol [Termes IGN] humidité du sol [Termes IGN] peuplement mélangé [Termes IGN] Pinus pinaster [Termes IGN] Pinus sylvestris [Vedettes matières IGN] Inventaire forestier Résumé : (Auteur) This document provides valuable environmental information about a triplets’ essay of Scots pine and Maritime pine in Spain. The dataset characterizes the soil profile (physicochemical parameters of organic and mineral horizons), climate, physiography, understory and overstory. Numéro de notice : A2021-328 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-021-01042-7 date de publication en ligne : 22/03/2021 En ligne : https://doi.org/10.1007/s13595-021-01042-7 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97489 [article]

Evaluating the performance of hyperspectral leaf reflectance to detect water stress and estimation of photosynthetic capacities / Jingjing Zhou in Remote sensing, vol 13 n° 11 (June-1 2021)  

Public [article]  inRemote sensing > vol 13 n° 11 (June-1 2021) . - n° 2160 Titre : Evaluating the performance of hyperspectral leaf reflectance to detect water stress and estimation of photosynthetic capacities Type de document : Article/Communication Auteurs : Jingjing Zhou, Auteur ; Ya-Hao Zhang, Auteur ; Ze-Min Han, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 2160 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] apprentissage automatique [Termes IGN] Chine [Termes IGN] Citrus (genre) [Termes IGN] classification par forêts aléatoires [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] feuille (végétation) [Termes IGN] image hyperspectrale [Termes IGN] photosynthèse [Termes IGN] réflectance végétale [Termes IGN] rendement agricole [Termes IGN] stress hydrique [Termes IGN] surveillance de la végétation Résumé : (auteur) Advanced techniques capable of early, rapid, and nondestructive detection of the impacts of drought on fruit tree and the measurement of the underlying photosynthetic traits on a large scale are necessary to meet the challenges of precision farming and full prediction of yield increases. We tested the application of hyperspectral reflectance as a high-throughput phenotyping approach for early identification of water stress and rapid assessment of leaf photosynthetic traits in citrus trees by conducting a greenhouse experiment. To this end, photosynthetic CO2 assimilation rate (Pn), stomatal conductance (Cond) and transpiration rate (Trmmol) were measured with gas-exchange approaches alongside measurements of leaf hyperspectral reflectance from citrus grown across a gradient of soil drought levels six times, during 20 days of stress induction and 13 days of rewatering. Water stress caused Pn, Cond, and Trmmol rapid and continuous decline throughout the entire drought period. The upper layer was more sensitive to drought than middle and lower layers. Water stress could also bring continuous and dynamic changes of the mean spectral reflectance and absorptance over time. After trees were rewatered, these differences were not obvious. The original reflectance spectra of the four water stresses were surprisingly of low diversity and could not track drought responses, whereas specific hyperspectral spectral vegetation indices (SVIs) and absorption features or wavelength position variables presented great potential. The following machine-learning algorithms: random forest (RF), support vector machine (SVM), gradient boost (GDboost), and adaptive boosting (Adaboost) were used to develop a measure of photosynthesis from leaf reflectance spectra. The performance of four machine-learning algorithms were assessed, and RF algorithm yielded the highest predictive power for predicting photosynthetic parameters (R2 was 0.92, 0.89, and 0.88 for Pn, Cond, and Trmmol, respectively). Our results indicated that leaf hyperspectral reflectance is a reliable and stable method for monitoring water stress and yield increase, with great potential to be applied in large-scale orchards. Numéro de notice : A2021-440 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs13112160 date de publication en ligne : 31/05/2021 En ligne : https://doi.org/10.3390/rs13112160 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97826 [article]

Improving tree biomass models through crown ratio patterns and incomplete data sources / Maria Menéndez-Miguélez in European Journal of Forest Research, vol 140 n° 3 (June 2021)  

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Individual tree identification using a new cluster-based approach with discrete-return airborne LiDAR data / Haijian Liu in Remote sensing of environment, vol 258 (June 2021)  

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Model-based estimation of forest canopy height and biomass in the Canadian boreal forest using radar, LiDAR, and optical remote sensing / Michael L. Benson in IEEE Transactions on geoscience and remote sensing, vol 59 n° 6 (June 2021)  

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Rapid ecosystem change at the southern limit of the Canadian Arctic, Torngat Mountains National Park / Emma L. Davis in Remote sensing, vol 13 n° 11 (June-1 2021)  

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A deep learning model using satellite ocean color and hydrodynamic model to estimate chlorophyll-a concentration / Daeyong Jin in Remote sensing, vol 13 n°10 (May 2021)  

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Mixture effect on radial stem and shoot growth differs and varies with temperature / Maude Toïgo in Forest ecology and management, vol 488 (15 May 2021)  

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Canopy openness and exclusion of wild ungulates act synergistically to improve oak natural regeneration / Julien Barrere in Forest ecology and management, Vol 487 ([01/05/2021])  

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Inversion of solar-induced chlorophyll fluorescence using polarization measurements of vegetation / Haiyan Yao in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 5 (May 2021)  

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Towards silviculture guidelines to produce large-sized silver birch (betula pendula roth) logs in Western Europe / Héloïse Dubois in Forests, vol 12 n° 5 (May 2021)  

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An iterative-mode scan design of terrestrial laser scanning in forests for minimizing occlusion effects / Linyuan Li in IEEE Transactions on geoscience and remote sensing, vol 59 n° 4 (April 2021)  

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