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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, vol 77 n° 4 (December 2020)
[article]
Titre : Competition overrides climate as trigger of growth decline in a mixed Fagaceae Mediterranean rear-edge forest Type de document : Article/Communication Auteurs : Alvaro Rubio-Cuadrado, Auteur ; J. Julio Camarero, Auteur ; Guillermo G. Gordaliza, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 18 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse diachronique
[Termes IGN] croissance des arbres
[Termes IGN] dendrochronologie
[Termes IGN] densité de la végétation
[Termes IGN] dynamique de la végétation
[Termes IGN] exploitation forestière
[Termes IGN] Fagaceae
[Termes IGN] Fagus sylvatica
[Termes IGN] forêt méditerranéenne
[Termes IGN] gestion forestière
[Termes IGN] modèle de croissance végétale
[Termes IGN] peuplement mélangé
[Termes IGN] Quercus pyrenaica
[Termes IGN] Quercus sessiliflora
[Termes IGN] structure d'un peuplement forestier
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Key message: In recent decades, there has been a decline in growth in a rear-edge broadleaf forest of Fagus sylvatica , Quercus petraea , and Quercus pyrenaica . Although temperatures have been rising due to climate change, the observed decline in growth was mainly attributed to increased density and competition between trees since the cessation of traditional uses such as logging in the 1960s.
Context: In recent decades, two major factors have influenced tree growth in many forests: climate warming, which is associated with aridification and negative growth trends in many Mediterranean forests, and abandonment of forest management, resulting from forest policy in conjunction with rural depopulation in Europe, often leading to an increase in competition and a decrease in growth.
Aims: Here, we study the growth trends in a mixed forest of Fagus sylvatica, Quercus petraea, and Quercus pyrenaica, where the abandonment of traditional uses in the 1960s has been followed by an increase in tree density. In this forest, both F. sylvatica and Q. petraea reach their south-westernmost limits of distribution.
Methods: Using dendrochronological methods and growth modeling, we assess the importance of climate warming on the shifts in competitive growth advantage of these three coexisting tree species and the relative importance of climate and competition on growth trends.
Results: Q. petraea and especially F. sylvatica showed a favorable evolution of their competitive capacity, despite the increase in temperatures that has occurred in the area in recent decades. F. sylvatica presented the lowest sensitivity to climate.
Conclusion: Under the current climate and forest structure conditions, competition is the most limiting factor on tree growth for the two oak species.Numéro de notice : A2020-661 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-020-01004-5 Date de publication en ligne : 01/10/2020 En ligne : https://doi.org/10.1007/s13595-020-01004-5 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96135
in Annals of Forest Science > vol 77 n° 4 (December 2020) . - 18 p.[article]Assessing the effects of thinning on stem growth allocation of individual Scots pine trees / Ninni Saarinen in Forest ecology and management, vol 474 ([15/10/2020])
[article]
Titre : Assessing the effects of thinning on stem growth allocation of individual Scots pine trees Type de document : Article/Communication Auteurs : Ninni Saarinen, Auteur ; Ville Kankare, Auteur ; Tuomas Yrttimaa, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 14 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] croissance des arbres
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] données lidar
[Termes IGN] éclaircie (sylviculture)
[Termes IGN] Finlande
[Termes IGN] gestion forestière
[Termes IGN] image captée par drone
[Termes IGN] Pinus sylvestris
[Termes IGN] reconstruction 3D
[Termes IGN] semis de points
[Termes IGN] troncRésumé : (auteur) Forest management alters the growing conditions and thus further development of trees. However, quantitative assessment of forest management on tree growth has been demanding as methodologies for capturing changes comprehensively in space and time have been lacking. Terrestrial laser scanning (TLS) has shown to be capable of providing three-dimensional (3D) tree stem reconstructions required for revealing differences between stem shapes and sizes. In this study, we used 3D reconstructions of tree stems from TLS and an unmanned aerial vehicle (UAV) to investigate how varying thinning treatments and the following growth effects affected stem shape and size of Scots pine (Pinus sylvestris L.) trees. The results showed that intensive thinning resulted in more stem volume and therefore total biomass allocation and carbon uptake compared to the moderate thinning. Relationship between tree height and diameter at breast height (i.e. slenderness) varied between both thinning intensity and type (i.e. from below and above) indicating differing response to thinning and allocation of stem growth of Scots pine trees. Furthermore, intensive thinning, especially from below, produced less variation in relative stem attributes characterizing stem shape and size. Thus, it can be concluded that thinning intensity, type, and the following growth effects have an impact on post-thinning stem shape and size of Scots pine trees. Our study presented detailed measurements on post-thinning stem growth of Scots pines that have been laborious or impracticable before the emergence of detailed 3D technologies. Moreover, the stem reconstructions from TLS and UAV provided variety of attributes characterizing stem shape and size that have not traditionally been feasible to obtain. The study demonstrated that detailed 3D technologies, such as TLS and UAV, provide information that can be used to generate new knowledge for supporting forest management and silviculture as well as improving ecological understanding of boreal forests. Numéro de notice : A2020-623 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.foreco.2020.118344 Date de publication en ligne : 29/06/2020 En ligne : https://doi.org/10.1016/j.foreco.2020.118344 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96020
in Forest ecology and management > vol 474 [15/10/2020] . - 14 p.[article]See the forest and the trees: Effective machine and deep learning algorithms for wood filtering and tree species classification from terrestrial laser scanning / Zhouxin Xi in ISPRS Journal of photogrammetry and remote sensing, vol 168 (October 2020)
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Titre : See the forest and the trees: Effective machine and deep learning algorithms for wood filtering and tree species classification from terrestrial laser scanning Type de document : Article/Communication Auteurs : Zhouxin Xi, Auteur ; Christopher Hopkinson, Auteur ; Stewart B. Rood, Auteur ; Derek R. Peddle, Auteur Année de publication : 2020 Article en page(s) : pp 1 - 16 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse comparative
[Termes IGN] apprentissage automatique
[Termes IGN] apprentissage profond
[Termes IGN] classification
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] espèce végétale
[Termes IGN] gestion forestière
[Termes IGN] semis de points
[Termes IGN] variation saisonnièreRésumé : (auteur) Determining tree species composition in natural forests is essential for effective forest management. Species classification at the individual tree level requires fine-scale traits which can be derived through terrestrial laser scanning (TLS) point clouds. A generalizable species classification framework also needs to decouple seasonal foliage variation from deciduous species, for which wood filtering is applicable. Different machine learning and deep learning models are feasible for wood filtering and species classification. We investigated 13 machine learning and deep learning classifiers for 9 species, and 15 classifiers for filtering wood points from TLS plot scans. Each classifier was evaluated using the criteria of mean Intersection over Union accuracy (mIoU), training stability and time cost. On average, deep learning classifiers outperformed machine learning classifiers by 10% and 5% in terms of wood and species classification mIoU, respectively. PointNet++ provided the best species classifier, with the highest mIoU (0.906), stability, and moderate time cost. Among wood classifiers, UNet achieved the top mIoU (0.839) while ResNet-50 was recommended for rapid trial and error testing. Across the classifications, the factors of input resolution, attributes and features were also analyzed. Hot zones of species classification with PointNet++ were visualized to indicate how AI interpret species traits. Numéro de notice : A2020-533 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.08.001 Date de publication en ligne : 10/08/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.08.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95718
in ISPRS Journal of photogrammetry and remote sensing > vol 168 (October 2020) . - pp 1 - 16[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2020101 RAB Revue Centre de documentation En réserve L003 Disponible 081-2020103 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2020102 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Carbon stocks, partitioning, and wood composition in short-rotation forestry system under reduced planting spacing / Felipe Schwerz in Annals of Forest Science, vol 77 n° 3 (September 2020)
[article]
Titre : Carbon stocks, partitioning, and wood composition in short-rotation forestry system under reduced planting spacing Type de document : Article/Communication Auteurs : Felipe Schwerz, Auteur ; Durval D. Neto, Auteur ; Braulio O. Caron, Auteur ; et al., Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] biomasse aérienne
[Termes IGN] biomasse forestière
[Termes IGN] Brésil
[Termes IGN] essence d'arbre
[Termes IGN] Eucalyptus grandis
[Termes IGN] gestion forestière
[Termes IGN] plantation forestière
[Termes IGN] puits de carbone
[Vedettes matières IGN] Ecologie forestièreRésumé : (auteur) Key message: The use of reduced planting spacings is an important strategy to increase the carbon storage in the above-belowground biomass and should be recommended for future exploitation of forest energy plantations when the purpose intended is the production of biomass for energy.
Context: Recent concerns about global warming have resulted in more concerted studies on quantifying carbon storage in forest systems. Forest energy plantations play an essential role in the carbon storage.
Aims: We proposed to evaluate the carbon storage and partitioning in short-rotation forest plantations and to characterize the elemental composition and energetic properties of the forest species Eucalyptus grandis W. Hill ex Maiden, Mimosa scabrella Benth, and Ateleia glazioviana Baill, grown under four planting spacings in Southern Brazil.
Methods: A field study was conducted in order to evaluate forest carbon stock and wood composition using samples collected by direct method. The four spacings evaluated were 2.0 × 1.0, 2.0 × 1.5, 3.0 × 1.0, and 3.0 × 1.5 m.
Results: The Eucalyptus grandis stored 327.1 Mg C ha−1 at 2.0 × 1.5-m spacing. When compared with the 3.0 × 1.5-m spacing, we observed a reduction of 29% in carbon stored. All forest species showed higher carbon storage in the following partitioning pattern: trunk>roots>branches>leaves>litter. Forest species energetic properties and elemental composition were not affected by planting spacing. On the other hand, variations according the tree portions were observed. For the carbon stocks in the soil, we observed an average accumulated carbon stock for the forest species studied of 77.4 Mg C ha−1 (0–40 cm).
Conclusion: Forest managers can accelerate growth and increase the forest carbon storage and biomass yield by using reduced planting spacing that are smaller than the current pattern used by the majority of the forest producers, which is 3.0 × 1.5 m. For Eucalyptus grandis and Mimosa scabrella, the planting spacings recommended to produce biomass and improve carbon stocks were 2.0 × 1.5 and 2.0 × 1.0 m, respectively.Numéro de notice : A2020-402 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-020-00974-w Date de publication en ligne : 27/06/2020 En ligne : https://doi.org/10.1007/s13595-020-00974-w Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95450
in Annals of Forest Science > vol 77 n° 3 (September 2020)[article]Evaluating the accuracy of ALS-based removal estimates against actual logging data / Ville Vähä-Konka in Annals of Forest Science, vol 77 n° 3 (September 2020)
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Titre : Evaluating the accuracy of ALS-based removal estimates against actual logging data Type de document : Article/Communication Auteurs : Ville Vähä-Konka, Auteur ; Matti Maltamo, Auteur ; Timo Pukkala, Auteur ; Kalle Kärhä, Auteur Année de publication : 2020 Article en page(s) : 11 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] éclaircie (sylviculture)
[Termes IGN] fiabilité des données
[Termes IGN] Finlande
[Termes IGN] gestion forestière
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] récolte de bois
[Termes IGN] télédétection par lidar
[Termes IGN] télémètre laser aéroporté
[Termes IGN] volume en boisRésumé : (auteur) Key message: We examined the accuracy of the stand attribute data based on airborne laser scanning (ALS) provided by the Finnish Forest Centre. The precision of forest inventory data was compared for the first time with operative logging data measured by the harvester.
Context: Airborne laser scanning (ALS) is increasingly used together with models to predict the stand attributes of boreal forests. The information is updated by growth models. Information produced by remote sensing, model prediction, and growth simulation needs field verification. The data collected by harvesters on logging sites provide a means to evaluate and verify the accuracy of the ALS-based data.
Aims: This study investigated the accuracy of ALS-based forest inventory data provided by the Finnish Forest Centre at the stand level, using harvester data as the reference. Special interest was on timber assortment volumes where the quality reductions of sawlog are model predictions in ALS-based data and true realized reductions in the logging data.
Methods: We examined the accuracy of total volume and timber assortment volumes by comparing ALS-based data and operative logging data measured by a harvester. This was done both for clear cuttings and thinning sites. Accuracy of the identification of the dominant tree species of the stand was examined using the Kappa coefficient.
Results: In clear-felling sites, the total harvest removals based on ALS and model prediction had a RMSE% of 26.0%. In thinning, the corresponding difference in the total harvested removal was 42.4%. Compared to logged volume, ALS-based prediction overestimated sawlog removals in clear cuttings and underestimated pulpwood removals.
Conclusion: The study provided valuable information on the accuracy of ALS-based stand attribute data. Our results showed that ALS-based data need better methods to predict the technical quality of harvested trees, to avoid systematic overestimates of sawlog volume. We also found that the ALS-based estimates do not accurately predict the volume of trees removed in actual thinnings.Numéro de notice : A2020-592 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-020-00985-7 Date de publication en ligne : 27/08/2020 En ligne : https://doi.org/10.1007/s13595-020-00985-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95927
in Annals of Forest Science > vol 77 n° 3 (September 2020) . - 11 p.[article]Ecology and management of northern red oak (Quercus rubra L. syn. Q. borealis F. Michx.) in Europe: a review / Valeriu-Norocel Nicolescu in Forestry, an international journal of forest research, vol 93 n° 4 (July 2020)PermalinkEvaluating the potential of red spruce (Picea rubens Sarg.) to persist under climate change using historic provenance trials in eastern Canada / Wushuang Li in Forest ecology and management, Vol 466 (15 June 2020)PermalinkInfluence of forest management activities on soil organic carbon stocks: A knowledge synthesis / Mathias Mayer in Forest ecology and management, Vol 466 (15 June 2020)PermalinkMapping forest age using National Forest Inventory, airborne laser scanning, and Sentinel-2 data / Johannes Schumacher in Forest ecosystems, vol 7 (2020)PermalinkProfitability of growing Scots pine on cutaway peatlands / Lasse Aro in Silva fennica, vol 54 n° 3 (June 2020)PermalinkShrub biomass estimates in former burnt areas using Sentinel 2 images processing and classification / Jose Aranha in Forests, vol 11 n° 5 (May 2020)PermalinkLa télédétection aéroportée pour la gestion des territoires forestiers de montagne / Jean-Matthieu Monnet in Sciences, eaux & territoires, n° 33 (avril 2020)PermalinkXylem anatomy of Robinia pseudoacacia L. and Quercus robur L. is differently affected by climate in a temperate alluvial forest / Paola Nola in Annals of Forest Science, Vol 77 n° 1 (March 2020)PermalinkPermalinkDisturbance effects on soil carbon and greenhouse gas emissions in forest ecosystems / Scott X. Chang (2020)Permalink