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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]

Spruce budworm tree host species distribution and abundance mapping using multi-temporal Sentinel-1 and Sentinel-2 satellite imagery / Rajeev Bhattarai in ISPRS Journal of photogrammetry and remote sensing, Vol 172 (February 2021)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > Vol 172 (February 2021) . - pp 28 - 40 Titre : Spruce budworm tree host species distribution and abundance mapping using multi-temporal Sentinel-1 and Sentinel-2 satellite imagery Type de document : Article/Communication Auteurs : Rajeev Bhattarai, Auteur ; Parinaz Rahimzadeh-Bajgiran, Auteur ; Aaron R. Weiskittel, Auteur Année de publication : 2021 Article en page(s) : pp 28 - 40 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] Abies balsamea [Termes descripteurs IGN] carte de la végétation [Termes descripteurs IGN] classification par forêts aléatoires [Termes descripteurs IGN] défoliation [Termes descripteurs IGN] dégradation de la flore [Termes descripteurs IGN] image multibande [Termes descripteurs IGN] image multitemporelle [Termes descripteurs IGN] image radar moirée [Termes descripteurs IGN] image Sentinel-MSI [Termes descripteurs IGN] image Sentinel-SAR [Termes descripteurs IGN] indice de végétation [Termes descripteurs IGN] insecte phyllophage [Termes descripteurs IGN] Nouveau-Brunswick (Canada) [Termes descripteurs IGN] Picea abies Résumé : (auteur) Spruce budworm (Choristoneura fumiferana; SBW) is the most destructive forest pest of northeastern Canada and United States. SBW occurrence as well as the extent and severity of its damage are highly dependent on the characteristics of the forests and the availability of host species namely, spruce (Picea sp.) and balsam fir (Abies balsamea (L.) Mill.). Remote sensing satellite imagery represents a valuable data source for seamless regional-scale mapping of forest composition. This study developed and evaluated new models to map the distribution and abundance of SBW host species at 20 m spatial resolution using Sentinel-1 synthetic aperture radar (SAR) and Sentinel-2 multispectral imagery in combination with several site variables for a total of 191 variables in northern New Brunswick, Canada using the Random Forest (RF) algorithm. We found Sentinel-2 multi-temporal single spectral bands and numerous spectral vegetation indices (SVIs) yielded the classification of SBW host species with an overall accuracy (OA) of 72.6% and kappa coefficient (K) of 0.65. Incorporating Sentinel-1 SAR data with Sentinel-2 variables coupled with elevation, only marginally improved the performance of the model (OA: 73.0% and K: 0.66). The use of Sentinel-1 SAR data with elevation resulted in a reasonable OA of 57.5% and K of 0.47. These spatially explicit up-to-date SBW host species maps are essential for identifying susceptible forests, monitoring SBW defoliation, and minimizing forest losses from insect impacts at landscape scale in the current SBW outbreak in the region. Numéro de notice : A2021-085 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.11.023 date de publication en ligne : 15/12/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.11.023 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96845 [article]

Individual tree diameter growth modeling system for Dalat pine (Pinus dalatensis Ferré) of the upland mixed tropical forests / Bao Huy in Forest ecology and management, vol 480 (15 January 2021)  

Public [article]  inForest ecology and management > vol 480 (15 January 2021) . - n° 118612 Titre : Individual tree diameter growth modeling system for Dalat pine (Pinus dalatensis Ferré) of the upland mixed tropical forests Type de document : Article/Communication Auteurs : Bao Huy, Auteur ; Le Canh nam, Auteur ; Krishna P. Poudel, Auteur ; Hailemariam Temesgen, Auteur Année de publication : 2021 Article en page(s) : n° 118612 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Végétation [Termes descripteurs IGN] cerne [Termes descripteurs IGN] conservation de la flore [Termes descripteurs IGN] croissance végétale [Termes descripteurs IGN] diamètre à hauteur de poitrine [Termes descripteurs IGN] facteur édaphique [Termes descripteurs IGN] flore endémique [Termes descripteurs IGN] forêt tropicale [Termes descripteurs IGN] modèle de croissance [Termes descripteurs IGN] Pinus (genre) [Termes descripteurs IGN] Viet Nam Résumé : (auteur) Pinus dalatensis Ferré (Dalat pine, or five-needle pine, locally) is an endemic large tree species of Vietnam that has both high timber and non-timber values. It is also a rare tree species listed in the Red List of the International Union for Conservation of Nature (IUCN). The objective of this study was to develop an individual tree diameter growth modeling system to facilitate the sustainable management and conservation of this species. We used Haglöf Sweden ® increment borers to collect tree ring samples from a total of 56 trees resulting in a dataset of 4566 diameter at breast height (dbh, cm) measurements at age (t, year) and obtained the associated ecological environmental factors in three different sites in the Central Highlands, Vietnam. A subset of this dataset (n = 1264) also had the climate data collected over the period of past 32–38 years (from 1980 to 2011 and from 1979 to 2016). Weighted mixed-effects models were used to model Dalat pine trees growth and account for autocorrelation and heteroscedasticity of the dbh measurements. Cross validation over 200 realizations were used to select the best equation form of dbh growth and incorporate the environmental effects and climatic factors that help improve reliability of the models. Under the mixed-effects modeling paradigm, the Mitscherlich equation fitted with random effects of ecological environmental factors (eco-subregions and altitude) and climatic factors (temperature, humidity, and temperature in dry and in rainy seasons) produced the best results. Whereas, under the fixed-effect modeling paradigm, the models that used the exponential function of environmental or climatic factors as the modifiers of an average diameter growth performed the best (Bias = −5.9% and RMSE = 10.0 cm). The models developed in this study will be useful for forecasting growth and for silvicultural planning under shifting environment and climate and are expected to contribute to the sustainable management of this endemic species. Numéro de notice : A2021-063 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.foreco.2020.118612 date de publication en ligne : 08/10/2020 En ligne : https://doi.org/10.1016/j.foreco.2020.118612 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96743 [article]

Examining the effectiveness of Sentinel-1 and 2 imagery for commercial forest species mapping / Mthembeni Mngadi in Geocarto international, vol 36 n° 1 ([01/01/2021])  

Public [article]  inGeocarto international > vol 36 n° 1 [01/01/2021] . - pp 1 - 12 Titre : Examining the effectiveness of Sentinel-1 and 2 imagery for commercial forest species mapping Type de document : Article/Communication Auteurs : Mthembeni Mngadi, Auteur ; John Odindi, Auteur ; Kabir Peerbhay, Auteur ; Onisimo Mutanga, Auteur Année de publication : 2021 Article en page(s) : pp 1 - 12 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte [Termes descripteurs IGN] analyse discriminante [Termes descripteurs IGN] carte forestière [Termes descripteurs IGN] Eucalyptus (genre) [Termes descripteurs IGN] image Sentinel-MSI [Termes descripteurs IGN] image Sentinel-SAR [Termes descripteurs IGN] KwaZulu-Natal (Afrique du Sud) [Termes descripteurs IGN] Pinus (genre) [Termes descripteurs IGN] télédétection spatiale Résumé : (Auteur) The successful launch and operation of the Sentinel satellite platform has provided access to freely available remotely sensed data useful for commercial forest species discrimination. Sentinel – 1 (S1) with a synthetic aperture radar (SAR) sensor and Sentinel – 2 (S2) multi-spectral sensor with additional and strategically positioned bands offer great potential for providing reliable information for discriminating and mapping commercial forest species. In this study, we sought to determine the value of S1 and S2 data characteristics in discriminating and mapping commercial forest species. Using linear discriminant analysis (LDA) algorithm, S2 multi-spectral imagery showed an overall classification accuracy of 84% (kappa = 0.81), with bands such as the red-edge (703.9–740.2 nm), narrow near infrared (835.1–864.8 nm), and short wave infrared (1613.7–2202.4 nm) particularly influential in discriminating individual forest species stands. When Sentinel 2’s spectral wavebands were fused with Sentinel 1’s (SAR) VV and VH polarimetric modes, overall classification accuracies improved to 87% (kappa = 0.83) and 88% (kappa = 0.85), respectively. These findings demonstrate the value of combining Sentinel’s multispectral and SAR structural information characteristics in improving commercial forest species discrimination. These, in addition to the sensors free availability, higher spatial resolution and larger swath width, offer unprecedented opportunities for improved local and large scale commercial forest species discrimination and mapping. Numéro de notice : A2021-050 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1585483 date de publication en ligne : 10/06/2019 En ligne : https://doi.org/10.1080/10106049.2019.1585483 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96719 [article]

From local to global: A transfer learning-based approach for mapping poplar plantations at national scale using Sentinel-2 / Yousra Hamrouni in ISPRS Journal of photogrammetry and remote sensing, vol 171 (January 2021)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 171 (January 2021) . - pp 76 - 100 Titre : From local to global: A transfer learning-based approach for mapping poplar plantations at national scale using Sentinel-2 Type de document : Article/Communication Auteurs : Yousra Hamrouni, Auteur ; Eric Paillassa, Auteur ; Véronique Chéret, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 76 - 100 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] apprentissage automatique [Termes descripteurs IGN] base de données forestières [Termes descripteurs IGN] carte de la végétation [Termes descripteurs IGN] classification par forêts aléatoires [Termes descripteurs IGN] couvert forestier [Termes descripteurs IGN] échantillonnage [Termes descripteurs IGN] France (administrative) [Termes descripteurs IGN] image Sentinel-MSI [Termes descripteurs IGN] mise à jour de base de données [Termes descripteurs IGN] populus (genre) [Termes descripteurs IGN] série temporelle Résumé : (auteur) Reliable estimates of poplar plantations area are not available at the French national scale due to the unsuitability and low update rate of existing forest databases for this short-rotation species. While supervised classification methods have been shown to be highly accurate in mapping forest cover from remotely sensed images, their performance depends to a great extent on the labelled samples used to build the models. In addition to their high acquisition cost, such samples are often scarce and not fully representative of the variability in class distributions. Consequently, when classification models are applied to large areas with high intra-class variance, they generally yield poor accuracies because of data shift issues. In this paper, we propose the use of active learning to efficiently adapt a classifier trained on a source image to spatially distinct target images with minimal labelling effort and without sacrificing the classification performance. The adaptation consists in actively adding to the initial local model new relevant training samples from other areas in a cascade that iteratively improves the generalisation capabilities of the classifier leading to a global model tailored to these different areas. This active selection relies on uncertainty sampling to directly focus on the most informative pixels for which the algorithm is the least certain of their class labels. Experiments conducted on Sentinel-2 time series revealed their high capacity to identify poplar plantations at a local scale with an average F-score ranging from 89.5% to 99.3%. For large area adaptation, the results showed that when the same number of training samples was used, active learning outperformed random sampling by up to 5% of the overall accuracy and up to 12% of the class F-score. Additionally, and depending on the class considered, the random sampling model required up to 50% more samples to achieve the same performance of an active learning-based model. Moreover, the results demonstrate the suitability of the derived global model to accurately map poplar plantations among other tree species with overall accuracy values up to 14% higher than those obtained with local models. The proposed approach paves the way for a national scale mapping in an operational context. Numéro de notice : A2021-013 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.10.018 date de publication en ligne : 20/11/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.10.018 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96417 [article]

Pure and even-aged forestry of fast growing conifers under climate change: on the need of a silvicultural paradigm shift / Clémentine Ols in Environmental Research Letters, vol 16 n° inconnu ([01/01/2021])    

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Spatial characterization and distribution modelling of Ensete ventricosum (wild and cultivated) in Ethiopia / Meron Awoke Eshetae in Geocarto international, vol 36 n° 1 ([01/01/2021])  

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Topographic, edaphic and climate influences on aspen (Populus tremuloides) drought stress on an intermountain bunchgrass prairie / Andrew Neary in Forest ecology and management, vol 479 ([01/01/2021])  

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Turgor – a limiting factor for radial growth in mature conifers along an elevational gradient / Richard L. Peters in New phytologist, vol 229 n° 1 (January 2021)  

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Variations in temperate forest biomass ratio along three environmental gradients are dominated by interspecific differences in wood density / Baptiste Kerfriden in Plant ecology, vol inconnu (January 2021)  

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Climate sensitive single tree growth modeling using a hierarchical Bayes approach and integrated nested Laplace approximations (INLA) for a distributed lag model / Arne Nothdurft in Forest ecology and management, vol 478 ([15/12/2020])  

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Competition overrides climate as trigger of growth decline in a mixed Fagaceae Mediterranean rear-edge forest / Alvaro Rubio-Cuadrado in Annals of Forest Science [en ligne], vol 77 n° 4 (December 2020)  

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Does recent fire activity impact fire-related traits of Pinus halepensis Mill. and Pinus sylvestris L. in the French Mediterranean area? / Bastien Romero in Annals of Forest Science [en ligne], vol 77 n° 4 (December 2020)  

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Improving aboveground biomass estimates by taking into account density variations between tree components / Antoine Billard in Annals of Forest Science [en ligne], vol 77 n° 4 (December 2020)  

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A meta-analysis of changes in soil organic carbon stocks after afforestation with deciduous broadleaved, sempervirent broadleaved, and conifer tree species / Guolong Hou in Annals of Forest Science [en ligne], vol 77 n° 4 (December 2020)  

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