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How much does climate change threaten European forest tree species distributions? / Marcin K. Dyderski in Global change biology, vol 24 n° 3 (March 2018)
[article]
Titre : How much does climate change threaten European forest tree species distributions? Type de document : Article/Communication Auteurs : Marcin K. Dyderski, Auteur ; Sonia Paz, Auteur ; Lee E. Frelich, Auteur ; Andrzej M. Jagodzinski, Auteur Année de publication : 2018 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Abies alba
[Termes IGN] Betula pendula
[Termes IGN] changement climatique
[Termes IGN] distribution spatiale
[Termes IGN] Fagus sylvatica
[Termes IGN] forêt tempérée
[Termes IGN] Fraxinus excelsior
[Termes IGN] gestion forestière
[Termes IGN] habitat (nature)
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] Larix decidua
[Termes IGN] modèle de simulation
[Termes IGN] Picea abies
[Termes IGN] Pinus sylvestris
[Termes IGN] Pseudotsuga menziesii
[Termes IGN] Quercus pedunculata
[Termes IGN] Quercus rubra
[Termes IGN] Quercus sessiliflora
[Termes IGN] Robinia pseudoacacia
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Although numerous species distribution models have been developed, most were based on insufficient distribution data or used older climate change scenarios. We aimed to quantify changes in projected ranges and threat level by the years 2061-2080, for 12 European forest tree species under three climate change scenarios. We combined tree distribution data from the Global Biodiversity Information Facility, EUFORGEN and forest inventories, and we developed species distribution models using MaxEnt and 19 bioclimatic variables. Models were developed for three climate change scenarios – optimistic (RCP2.6), moderate (RCP4.5) and pessimistic (RPC8.5) – using three General Circulation Models, for the period 2061-2080. Our study revealed different responses of tree species to projected climate change. The species may be divided into three groups: “winners” – mostly late-successional species: Abies alba, Fagus sylvatica, Fraxinus excelsior, Quercus robur and Q. petraea; “losers” – mostly pioneer species: Betula pendula, Larix decidua, Picea abies and Pinus sylvestris and alien species – Pseudotsuga menziesii, Q. rubra and Robinia pseudoacacia, which may be also considered as “winners”. Assuming limited migration, most of the species studied would face significant decrease of suitable habitat area. The threat level was highest for species that currently have the northernmost distribution centers. Ecological consequences of the projected range contractions would be serious for both forest management and nature conservation. Numéro de notice : A2018-379 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1111/gcb.13925 En ligne : http://doi.org/10.1111/gcb.13925 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=87220
in Global change biology > vol 24 n° 3 (March 2018)[article]Important LiDAR metrics for discriminating forest tree species in Central Europe / Yifang Shi in ISPRS Journal of photogrammetry and remote sensing, vol 137 (March 2018)
[article]
Titre : Important LiDAR metrics for discriminating forest tree species in Central Europe Type de document : Article/Communication Auteurs : Yifang Shi, Auteur ; Tiejun Wang, Auteur ; Andrew K. Skidmore, Auteur ; Marco Heurich, Auteur Année de publication : 2018 Article en page(s) : pp 163 - 174 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] Allemagne
[Termes IGN] arbre (flore)
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] Europe centrale
[Termes IGN] forêt tempérée
[Termes IGN] morphologie mathématiqueRésumé : (Auteur) Numerous airborne LiDAR-derived metrics have been proposed for classifying tree species. Yet an in-depth ecological and biological understanding of the significance of these metrics for tree species mapping remains largely unexplored. In this paper, we evaluated the performance of 37 frequently used LiDAR metrics derived under leaf-on and leaf-off conditions, respectively, for discriminating six different tree species in a natural forest in Germany. We firstly assessed the correlation between these metrics. Then we applied a Random Forest algorithm to classify the tree species and evaluated the importance of the LiDAR metrics. Finally, we identified the most important LiDAR metrics and tested their robustness and transferability. Our results indicated that about 60% of LiDAR metrics were highly correlated to each other (|r| > 0.7). There was no statistically significant difference in tree species mapping accuracy between the use of leaf-on and leaf-off LiDAR metrics. However, combining leaf-on and leaf-off LiDAR metrics significantly increased the overall accuracy from 58.2% (leaf-on) and 62.0% (leaf-off) to 66.5% as well as the kappa coefficient from 0.47 (leaf-on) and 0.51 (leaf-off) to 0.58. Radiometric features, especially intensity related metrics, provided more consistent and significant contributions than geometric features for tree species discrimination. Specifically, the mean intensity of first-or-single returns as well as the mean value of echo width were identified as the most robust LiDAR metrics for tree species discrimination. These results indicate that metrics derived from airborne LiDAR data, especially radiometric metrics, can aid in discriminating tree species in a mixed temperate forest, and represent candidate metrics for tree species classification and monitoring in Central Europe. Numéro de notice : A2018-080 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.02.002 Date de publication en ligne : 07/02/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.02.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89442
in ISPRS Journal of photogrammetry and remote sensing > vol 137 (March 2018) . - pp 163 - 174[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2018031 RAB Revue Centre de documentation En réserve L003 Disponible 081-2018033 DEP-EXM Revue LASTIG Dépôt en unité Exclu du prêt 081-2018032 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt Predicting temperate forest stand types using only structural profiles from discrete return airborne lidar / Melissa Fedrigo in ISPRS Journal of photogrammetry and remote sensing, vol 136 (February 2018)
[article]
Titre : Predicting temperate forest stand types using only structural profiles from discrete return airborne lidar Type de document : Article/Communication Auteurs : Melissa Fedrigo, Auteur ; Glenn J. Newnham, Auteur ; Nicholas C. Coops, Auteur ; Darius S. Culvenor, Auteur ; Douglas K. Bolton, Auteur ; Craig R. Nitschke, Auteur Année de publication : 2018 Article en page(s) : pp 106 - 119 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse en composantes principales
[Termes IGN] analyse linéaire des mélanges spectraux
[Termes IGN] Australie
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] Eucalyptus (genre)
[Termes IGN] forêt tempérée
[Termes IGN] peuplement forestier
[Termes IGN] prédiction
[Termes IGN] strate végétaleRésumé : (Auteur) Light detection and ranging (lidar) data have been increasingly used for forest classification due to its ability to penetrate the forest canopy and provide detail about the structure of the lower strata. In this study we demonstrate forest classification approaches using airborne lidar data as inputs to random forest and linear unmixing classification algorithms. Our results demonstrated that both random forest and linear unmixing models identified a distribution of rainforest and eucalypt stands that was comparable to existing ecological vegetation class (EVC) maps based primarily on manual interpretation of high resolution aerial imagery. Rainforest stands were also identified in the region that have not previously been identified in the EVC maps. The transition between stand types was better characterised by the random forest modelling approach. In contrast, the linear unmixing model placed greater emphasis on field plots selected as endmembers which may not have captured the variability in stand structure within a single stand type. The random forest model had the highest overall accuracy (84%) and Cohen’s kappa coefficient (0.62). However, the classification accuracy was only marginally better than linear unmixing. The random forest model was applied to a region in the Central Highlands of south-eastern Australia to produce maps of stand type probability, including areas of transition (the ‘ecotone’) between rainforest and eucalypt forest. The resulting map provided a detailed delineation of forest classes, which specifically recognised the coalescing of stand types at the landscape scale. This represents a key step towards mapping the structural and spatial complexity of these ecosystems, which is important for both their management and conservation. Numéro de notice : A2018-074 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.11.018 Date de publication en ligne : 29/12/2017 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.11.018 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89438
in ISPRS Journal of photogrammetry and remote sensing > vol 136 (February 2018) . - pp 106 - 119[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2018021 RAB Revue Centre de documentation En réserve L003 Disponible 081-2018023 RAB Revue Centre de documentation En réserve L003 Disponible 081-2018022 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt Expansion tendancielle du stock de bois dans les forêts françaises (1976–2015) [diaporama] / Jean-Daniel Bontemps (2018)
Titre : Expansion tendancielle du stock de bois dans les forêts françaises (1976–2015) [diaporama] Type de document : Article/Communication Auteurs : Jean-Daniel Bontemps , Auteur ; Anaïs Denardou-Tisserand , Auteur ; Jean-Luc Dupouey, Auteur Editeur : Saint-Mandé : Institut national de l'information géographique et forestière - IGN (2012-) Année de publication : 2018 Conférence : IGN - EcoFor 2018, Colloque 60 ans d’inventaire forestier pour éclairer l’avenir 15/10/2018 16/10/2018 Paris France open access proceedings Importance : 33 p. Format : 21 x 30 cm Langues : Français (fre) Descripteur : [Termes IGN] bois sur pied
[Termes IGN] forêt alpestre
[Termes IGN] forêt de feuillus
[Termes IGN] forêt domaniale
[Termes IGN] forêt privée
[Termes IGN] grande région écologique
[Termes IGN] politique forestière
[Termes IGN] puits de carbone
[Termes IGN] résineux
[Termes IGN] ressources forestières
[Vedettes matières IGN] Inventaire forestierNuméro de notice : C2018-105 Affiliation des auteurs : LIF+Ext (2012-2019) Thématique : FORET Nature : Communication nature-HAL : ComSansActesPubliés-Unpublished DOI : sans En ligne : https://inventaire-forestier.ign.fr/IMG/pdf/02_expansion_foret_metropole_jdbonte [...] Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97509 Realizing mitigation efficiency of European commercial forests by climate smart forestry / Rasoul Yousefpour in Scientific reports, vol 8 (2018)
[article]
Titre : Realizing mitigation efficiency of European commercial forests by climate smart forestry Type de document : Article/Communication Auteurs : Rasoul Yousefpour, Auteur ; Andrey Lessa Derci Augustynczik, Auteur ; Christopher P.O. Reyer, Auteur ; Petra Lasch-Born, Auteur ; Felicitas Suckow, Auteur ; Marc Hanewinkel, Auteur Année de publication : 2018 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] changement climatique
[Termes IGN] croissance des arbres
[Termes IGN] Europe (géographie politique)
[Termes IGN] foresterie
[Termes IGN] forêt boréale
[Termes IGN] forêt tempérée
[Termes IGN] Picea abies
[Termes IGN] Pinus sylvestris
[Termes IGN] puits de carbone
[Termes IGN] ressources forestières
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) European temperate and boreal forests sequester up to 12% of Europe’s annual carbon emissions. Forest carbon density can be manipulated through management to maximize its climate mitigation potential, and fast-growing tree species may contribute the most to Climate Smart Forestry (CSF) compared to slow-growing hardwoods. This type of CSF takes into account not only forest resource potentials in sequestering carbon, but also the economic impact of regional forest products and discounts both variables over time. We used the process-based forest model 4 C to simulate European commercial forests’ growth conditions and coupled it with an optimization algorithm to simulate the implementation of CSF for 18 European countries encompassing 68.3 million ha of forest (42.4% of total EU-28 forest area). We found a European CSF policy that could sequester 7.3–11.1 billion tons of carbon, projected to be worth 103 to 141 billion euros in the 21st century. An efficient CSF policy would allocate carbon sequestration to European countries with a lower wood price, lower labor costs, high harvest costs, or a mixture thereof to increase its economic efficiency. This policy prioritized the allocation of mitigation efforts to northern, eastern and central European countries and favored fast growing conifers Picea abies and Pinus sylvestris to broadleaves Fagus sylvatica and Quercus species. Numéro de notice : A2018-010 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89003
in Scientific reports > vol 8 (2018)[article]Multi-model estimation of understorey shrub, herb and moss cover in temperate forest stands by laser scanner data / Hooman Latifi in Forestry, an international journal of forest research, vol 90 n° 4 (October 2017)PermalinkStrong gradients in forest sensitivity to climate change revealed by dynamics of forest fire cycles in the post Little Ice Age Era / Igor Drobyshev in Journal of geophysical research : Biogeosciences, vol 122 n° 10 (October 2017)PermalinkAdaptive and plastic responses of Quercus petraea populations to climate across Europe / Cuauhtémoc Saenz-Romero in Global change biology, vol 23 n° 7 (July 2017)PermalinkAn integrated airborne laser scanning approach to forest management and cultural heritage issues: a case study at Porolissum, Romania / Anamaria Roman in Annals of forest research, vol 60 n° 1 (January - June 2017)PermalinkAn unsupervised two-stage clustering approach for forest structure classification based on X-band InSAR data — A case study in complex temperate forest stands / Sahra Abdullahi in International journal of applied Earth observation and geoinformation, vol 57 (May 2017)PermalinkEffectiveness of Natura 2000 network in Romanian Alpine Biogeographical Region: an assessment based on forest landscape connectivity / Mihaita Iulian Niculae in Annals of forest research, vol 60 n° 1 (January - June 2017)PermalinkTraitement de données LiDAR pour la modélisation d'indicateurs de biodiversité forestière / Sylvain Jourdana (2017)PermalinkTree diversity effect on dominant height in temperate forest / Patrick Vallet in Forest ecology and management, vol 381 (1 December 2016)PermalinkLand ownership affects diversity and abundance of tree microhabitats in deciduous temperate forests / Franz Johann in Forest ecology and management, vol 380 (15 november 2016)PermalinkDirect measurement of evapotranspiration from a forest using a superconducting gravimeter / Michel Van Camp in Geophysical research letters, vol 43 n° 19 (15 October 2016)Permalink