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Can mixed pine forests conserve understory richness by improving the establishment of understory species typical of native oak forests? / Daphne Lopez-Marcos 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) . - 13 p. Titre : Can mixed pine forests conserve understory richness by improving the establishment of understory species typical of native oak forests? Type de document : Article/Communication Auteurs : Daphne Lopez-Marcos, Auteur ; Maria-Belen Turrion, Auteur ; Felipe Bravo, Auteur ; Carolina Martinez-Ruiz, Auteur Année de publication : 2020 Article en page(s) : 13 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] échantillonnage de données [Termes descripteurs IGN] Espagne [Termes descripteurs IGN] étage de végétation [Termes descripteurs IGN] forêt de zone humide [Termes descripteurs IGN] forêt tempérée [Termes descripteurs IGN] parcelle forestière [Termes descripteurs IGN] peuplement mélangé [Termes descripteurs IGN] Pinus pinaster [Termes descripteurs IGN] Pinus sylvestris [Termes descripteurs IGN] quercus pyrenaica [Termes descripteurs IGN] régénération (sylviculture) [Termes descripteurs IGN] sous-étage [Vedettes matières IGN] Sylviculture Résumé : (auteur) Key message: A positive effect of mixed pine forests ( Pinus sylvestris L. and Pinus pinaster Ait.) on the understory richness and tree regeneration was observed with respect to monospecific stands. Understory species typical of the native Pyrenean oak forests in the Iberian Peninsula contribute to maintaining high understory richness in such mixed pine forests. Context: The influence of stands characteristics on the understory in mixtures that combine coniferous tree species of the same genus deserves more study since they are frequent in Spain. Aims: To assess the effect of mixed versus monospecific stands of Pinus sylvestris L. and Pinus pinaster Ait. on the main tree species regeneration and understory species composition. Methods: Tree regeneration and understory species composition were inventoried in eighteen forest plots (6 triplets) in North-Central Spain. Each triplet consisted of two plots dominated either by Scots pine or Maritime pine and one mixed plot that contained both species. Results: The basal area (%) of both Pinus species was the only characteristic of the stands that significantly influenced the understory composition and tree regeneration. Characteristic species of humid and temperate zones, including P. sylvestris regeneration, dominated in Scots pine stands, and typical species of well-drained Mediterranean areas, including P. pinaster regeneration, dominated in Maritime pine stands. In mixed stands, the highest regeneration of the native Pyrenean oak with respect to monospecific stands was accompanied by understory species typical of native oak forests that share the same regeneration niche. Conclusion: Mixed pine forests allow the development of understory species better than monospecific forests. Numéro de notice : A2020-067 Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-020-0919-7 date de publication en ligne : 04/02/2020 En ligne : https://doi.org/10.1007/s13595-020-0919-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94579 [article]

Effects of Quercus rubra L. on soil properties and humus forms in 50-year-old and 80-year-old forest stands of Lombardy plain / Chiara Ferré 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) . - 19 p. Titre : Effects of Quercus rubra L. on soil properties and humus forms in 50-year-old and 80-year-old forest stands of Lombardy plain Type de document : Article/Communication Auteurs : Chiara Ferré, Auteur ; Roberto Comolli, Auteur Année de publication : 2020 Article en page(s) : 19 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] boisement artificiel [Termes descripteurs IGN] carbone [Termes descripteurs IGN] conversion forestière [Termes descripteurs IGN] humus [Termes descripteurs IGN] Lombardie [Termes descripteurs IGN] peuplement forestier [Termes descripteurs IGN] peuplement mélangé [Termes descripteurs IGN] quercus (genre) [Termes descripteurs IGN] quercus rubra [Vedettes matières IGN] Ecologie forestière Résumé : (auteur) Key message: Besides the well-known effects on the native plant community, red oak may also impact the soil; the effects of afforestation with red oak involve both organic layers and mineral soil, resulting in changes in organic carbon quantity and quality and in soil acidification. Context: Many alien species have become widespread in Europe; among these, red oak is a common invader of temperate forests. Aims: The effects of substitution of natural mixed forest by red oak forest on humus forms and soil properties were investigated in two paired plots: a 50-year-old (Bosco Vacaressino) and 80-year-old (Bosco Ginestre) forest stand. Methods: Soil sampling was performed from 3 layers at 40 and 49 points in Bosco Vacaressino and Bosco Ginestre respectively to determine humus forms, soil pH, organic carbon stock, carbon-nitrogen ratio (C:N), available phosphorus, and texture. Results: Red oak resulted in a shift from Mull to Moder humus forms; soil acidification, higher C:N ratio, and soil organic carbon stock were observed compared with mixed forests. Conclusion: The major changes were reflected in a change toward less active humus forms; the effects of vegetation conversions were also visible in mineral layers; many of the modifications were more evident with increasing stand age. Numéro de notice : A2020-033 Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-019-0893-0 date de publication en ligne : 10/01/2020 En ligne : https://doi.org/10.1007/s13595-019-0893-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94490 [article]

Artificial neural network models by ALOS PALSAR data for aboveground stand carbon predictions of pure beech stands: a case study from northern of Turkey / Alkan Günlü in Geocarto international, Vol 35 n° 1 ([02/01/2020])  

Public [article]  inGeocarto international > Vol 35 n° 1 [02/01/2020] . - pp 17 - 28 Titre : Artificial neural network models by ALOS PALSAR data for aboveground stand carbon predictions of pure beech stands: a case study from northern of Turkey Type de document : Article/Communication Auteurs : Alkan Günlü, Auteur ; Ilker Erkanli, Auteur Année de publication : 2020 Article en page(s) : pp 17 - 28 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] biomasse aérienne [Termes descripteurs IGN] carbone [Termes descripteurs IGN] Fagus (genre) [Termes descripteurs IGN] image ALOS-PALSAR [Termes descripteurs IGN] peuplement forestier [Termes descripteurs IGN] régression multiple [Termes descripteurs IGN] réseau neuronal artificiel [Termes descripteurs IGN] Turquie Résumé : (auteur) The goal of this study was to estimate aboveground stand carbon (AGSC) of pure beech stands in Turkey with ground measurements as well as topographic information and remote sensing data. For this purpose, 153 sample plots were collected from pure beech stands in study area. The AGSC of each sample plot was computed. Eight texture images (variance, dissimilarity, homogeneity, entropy, contrast, mean, second moment and correlation) with five window sizes (3 × 3, 5 × 5, 7 × 7, 9 × 9 and 11 × 11) generated from ALOS PALSAR L-band satellite image. The AGSC models predicting the relationships between ALOS PALSAR texture values and topographic information, and sample plot AGSC were developed by using multiple linear regressions (MLR). Also, artificial neural networks (ANNs) architectures were trained by comparing various numbers of neurons and activation functions in its network types. Our results revealed the ability of ANNs was better than MLR models to predict AGSC values. Numéro de notice : A2020-017 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1499817 date de publication en ligne : 20/09/2018 En ligne : https://doi.org/10.1080/10106049.2018.1499817 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94410 [article]

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Mapping dead forest cover using a deep convolutional neural network and digital aerial photography / Jean-Daniel Sylvain in ISPRS Journal of photogrammetry and remote sensing, vol 156 (October 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 156 (October 2019) . - pp 14 - 26 Titre : Mapping dead forest cover using a deep convolutional neural network and digital aerial photography Type de document : Article/Communication Auteurs : Jean-Daniel Sylvain, Auteur ; Guillaume Drolet, Auteur ; Nicolas Brown, Auteur Année de publication : 2019 Article en page(s) : pp 14 - 26 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] arbre mort [Termes descripteurs IGN] base de données forestières [Termes descripteurs IGN] classification par réseau neuronal convolutif [Termes descripteurs IGN] couvert forestier [Termes descripteurs IGN] feuillu [Termes descripteurs IGN] forêt boréale [Termes descripteurs IGN] image aérienne [Termes descripteurs IGN] orthoimage [Termes descripteurs IGN] peuplement mélangé [Termes descripteurs IGN] pinophyta [Termes descripteurs IGN] Québec (Canada) [Termes descripteurs IGN] santé des forêts Résumé : (Auteur) Tree mortality is an important forest ecosystem variable having uses in many applications such as forest health assessment, modelling stand dynamics and productivity, or planning wood harvesting operations. Because tree mortality is a spatially and temporally erratic process, rates and spatial patterns of tree mortality are difficult to estimate with traditional inventory methods. Remote sensing imagery has the potential to detect tree mortality at spatial scales required for accurately characterizing this process (e.g., landscape, region). Many efforts have been made in this sense, mostly using pixel- or object-based methods. In this study, we explored the potential of deep Convolutional Neural Networks (CNNs) to detect and map tree health status and functional type over entire regions. To do this, we built a database of around 290,000 photo-interpreted trees that served to extract and label image windows from 20 cm-resolution digital aerial images, for use in CNN training and evaluation. In this process, we also evaluated the effect of window size and spectral channel selection on classification accuracy, and we assessed if multiple realizations of a CNN, generated using different weight initializations, can be aggregated to provide more robust predictions. Finally, we extended our model with 5 additional classes to account for the diversity of landcovers found in our study area. When predicting tree health status only (live or dead), we obtained test accuracies of up to 94%, and up to 86% when predicting functional type only (broadleaf or needleleaf). Channel selection had a limited impact on overall classification accuracy, while window size increased the ability of the CNNs to predict plant functional type. The aggregation of multiple realizations of a CNN allowed us to avoid the selection of suboptimal models and help to remove much of the speckle effect when predicting on new aerial images. Test accuracies of plant functional type and health status were not affected in the extended model and were all above 95% for the 5 extra classes. Our results demonstrate the robustness of the CNN for between-scene variations in aerial photography and also suggest that this approach can be applied at operational level to map tree mortality across extensive territories. Numéro de notice : A2019-316 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.07.010 date de publication en ligne : 02/08/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.07.010 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93353 [article]

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The utility of terrestrial photogrammetry for assessment of tree volume and taper in boreal mixedwood forests / Christopher Mulverhill in Annals of Forest Science [en ligne], Vol 76 n° 3 (September 2019)  

Public [article]  inAnnals of Forest Science [en ligne] > Vol 76 n° 3 (September 2019) . - pp 76 - 83 Titre : The utility of terrestrial photogrammetry for assessment of tree volume and taper in boreal mixedwood forests Type de document : Article/Communication Auteurs : Christopher Mulverhill, Auteur ; Nicholas C. Coops, Auteur ; Piotr Tompalski, Auteur ; Christopher W. Bater, Auteur ; Adam R. Dick, Auteur Année de publication : 2019 Article en page(s) : pp 76 - 83 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes descripteurs IGN] Abies balsamea [Termes descripteurs IGN] Alberta [Termes descripteurs IGN] allométrie [Termes descripteurs IGN] betula papyrifera var. papyrifera [Termes descripteurs IGN] diamètre à hauteur de poitrine [Termes descripteurs IGN] diamètre des arbres [Termes descripteurs IGN] données dendrométriques [Termes descripteurs IGN] forêt boréale [Termes descripteurs IGN] hauteur des arbres [Termes descripteurs IGN] image terrestre [Termes descripteurs IGN] inventaire forestier (techniques et méthodes) [Termes descripteurs IGN] peuplement mélangé [Termes descripteurs IGN] photogrammétrie terrestre [Termes descripteurs IGN] Picea glauca [Termes descripteurs IGN] picea mariana [Termes descripteurs IGN] Pinus contorta [Termes descripteurs IGN] populus tremuloides [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] volume en bois Résumé : (auteur) Key Message: This study showed that digital terrestrial photogrammetry is able to produce accurate estimates of stem volume and diameter across a range of species and tree sizes that showed strong correspondence when compared with traditional inventory techniques. This paper demonstrates the utility of the technology for characterizing trees in complex habitats such as boreal mixedwood forests. Context: Accurate knowledge of tree stem taper and volume are key components of forest inventories to manage and study forest resources. Recent developments have seen the increasing use of ground-based point clouds, including from digital terrestrial photogrammetry (DTP), to provide accurate estimates of these key forest attributes. Aims: In this study, we evaluated the utility of DTP based on a small set of photos (12 per tree) for estimating stem volume and taper on a set of 15 trees from 6 different species (Populus tremuloides, Picea glauca, Pinus contorta latifolia, Betula papyrifera, Picea mariana, Abies balsamea) in a boreal mixedwood forest in Alberta, Canada. Methods: We constructed accurate photogrammetric point clouds and derived taper and volume from three point cloud–based methods, which were then compared with estimates from conventional, field-based measurements. All methods were evaluated for their accuracy based on field-measured taper and volume of felled trees. Results: Of the methods tested, we found that the point cloud–derived diameters in a taper curve matching approach performed the best at estimating diameters at the lowest parts of the stem ( 50% of total height). Using the field-measured DBH and height as inputs to calculate stem volume yielded the most accurate predictions; however, these were not significantly different from the best point cloud-based estimates. Conclusion: The methodology confirmed that using a small set of photographs provided accurate estimates of individual tree DBH, taper, and volume across a range of species and size gradients (10.8–40.4 cm DBH). Numéro de notice : A2019-303 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-019-0852-9 date de publication en ligne : 08/08/2019 En ligne : https://doi.org/10.1007/s13595-019-0852-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93226 [article]

Two contemporary and efficient two-stage sampling methods for estimating the volume of forest stands: a brief overview and unified mathematical description / Aristeidis Georgakis in Open journal of forestry, vol 9 n° 3 (July 2019)  

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A general method for the classification of forest stands using species composition and vertical and horizontal structure / Miquel de Cáceres in Annals of Forest Science [en ligne], vol 76 n° 2 (June 2019)  

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Genetic diversity and structure of Silver fir (Abies alba Mill.) at the south-eastern limit of its distribution range / Maria Teodosiu in Annals of forest research, vol 62 n° 2 (June - December 2019)  

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Estimating architecture-based metabolic scaling exponents of tropical trees using terrestrial LiDAR and 3D modelling / Alvaro Lau in Forest ecology and management, vol 439 (1 May 2019)  

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Model-based investigation on the effects of spatial evenness, and size selection in thinning of Picea abies stands / Peter Fransson in Scandinavian journal of forest research, vol 34 n° 3 (May 2019)  

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Climate change and mixed forests: how do altered survival probabilities impact economically desirable species proportions of Norway spruce and European beech? / Carola Paul in Annals of Forest Science [en ligne], vol 76 n° 1 (March 2019)  

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Single-image photogrammetry for deriving tree architectural traits in mature forest stands: a comparison with terrestrial laser scanning / Kamil Kędra in Annals of Forest Science [en ligne], vol 76 n° 1 (March 2019)  

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Effect of forest structure on stand productivity in Central European forests depends on developmental stage and tree species diversity / Laura Zeller in Forest ecology and management, vol 434 (28 February 2019)  

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Using LiDAR to develop high-resolution reference models of forest structure and spatial pattern / Haley L. Wiggins in Forest ecology and management, vol 434 (28 February 2019)  

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Leaf area density from airborne LiDAR: Comparing sensors and resolutions in a temperate broadleaf forest ecosystem / Aaron G. Kamoske in Forest ecology and management, vol 433 (15 February 2019)  

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