Centre dedocumentation
scientifique

Unveiling the complex canopy spatial structure of a Mediterranean old-growth beech (Fagus sylvatica L.) forest from UAV observations / Francesco Solano in Ecological indicators, vol 138 (May 2022)  

Public [article]  inEcological indicators > vol 138 (May 2022) . - n° 108807 Titre : Unveiling the complex canopy spatial structure of a Mediterranean old-growth beech (Fagus sylvatica L.) forest from UAV observations Type de document : Article/Communication Auteurs : Francesco Solano, Auteur ; Giuseppe Modica, Auteur ; Salvatore Praticò, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 108807 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] Calabre [Termes IGN] écosystème forestier [Termes IGN] Fagus sylvatica [Termes IGN] forêt ancienne [Termes IGN] forêt méditerranéenne [Termes IGN] forêt primaire [Termes IGN] image à très haute résolution [Termes IGN] image captée par drone [Termes IGN] modèle numérique de surface de la canopée [Termes IGN] orthophotoplan numérique [Termes IGN] photogrammétrie aérienne [Termes IGN] structure spatiale [Termes IGN] structure-from-motion [Termes IGN] surveillance forestière Résumé : (auteur) In front of climate change scenarios and global loss of biodiversity, it is essential to monitor the structure of old-growth forests to study ecosystem status and dynamics to inform future conservation and restoration programmes. We propose an Unmanned Aerial Vehicle (UAV)-based framework to monitor fine-grained forest top canopy structure in a primary old-growth beech (Fagus sylvatica L.) forest in Pollino National Park, Italy, which belongs to the UNESCO World Heritage (UNESCO WH) serial site “Ancient and Primeval beech forests of the Carpathians and other regions of Europe”. Canopy profile, gap properties and their spatial distribution patterns were analysed using the canopy height model (CHM) derived from UAV surveys. Very high-resolution orthomosaic images coupled with direct field measurement data were used to assess gap detection accuracy and CHM validation. Forest canopy properties along with the vertical layering of the canopy were further explored using second-order statistics. The reconstructed canopy profile revealed a bimodal top height frequency distribution. The upper canopy layer (h > 14 m) was the most represented canopy height, with the remaining 50% split between the medium and lowest layer; 551 gaps were identified within 11.5 ha. Gap size varied between 2 m2 and 353 m2, and 19 m2was the mean gap size; the gap size-frequency relationship reflected a power-law probability distribution. About 97 % of the gaps were Numéro de notice : A2022-369 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.ecolind.2022.108807 Date de publication en ligne : 01/04/2022 En ligne : https://doi.org/10.1016/j.ecolind.2022.108807 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100598 [article]

Wood decay detection in Norway spruce forests based on airborne hyperspectral and ALS data / Michele Dalponte in Remote sensing, vol 14 n° 8 (April-2 2022)  

Public [article]  inRemote sensing > vol 14 n° 8 (April-2 2022) . - n° 1892 Titre : Wood decay detection in Norway spruce forests based on airborne hyperspectral and ALS data Type de document : Article/Communication Auteurs : Michele Dalponte, Auteur ; Alvar J. I. Kallio, Auteur ; Hans Ole Ørka, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 1892 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] bois sur pied [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] dépérissement [Termes IGN] données d'entrainement (apprentissage automatique) [Termes IGN] données lidar [Termes IGN] image hyperspectrale [Termes IGN] image infrarouge [Termes IGN] Norvège [Termes IGN] Perceptron multicouche [Termes IGN] Picea abies [Termes IGN] régression linéaire [Termes IGN] régression logistique [Termes IGN] santé des forêts [Termes IGN] semis de points Résumé : (auteur) Wood decay caused by pathogenic fungi in Norway spruce forests causes severe economic losses in the forestry sector, and currently no efficient methods exist to detect infected trees. The detection of wood decay could potentially lead to improvements in forest management and could help in reducing economic losses. In this study, airborne hyperspectral data were used to detect the presence of wood decay in the trees in two forest areas located in Etnedal (dataset I) and Gran (dataset II) municipalities, in southern Norway. The hyperspectral data used consisted of images acquired by two sensors operating in the VNIR and SWIR parts of the spectrum. Corresponding ground reference data were collected in Etnedal using a cut-to-length harvester while in Gran, field measurements were collected manually. Airborne laser scanning (ALS) data were used to detect the individual tree crowns (ITCs) in both sites. Different approaches to deal with pixels inside each ITC were considered: in particular, pixels were either aggregated to a unique value per ITC (i.e., mean, weighted mean, median, centermost pixel) or analyzed in an unaggregated way. Multiple classification methods were explored to predict rot presence: logistic regression, feed forward neural networks, and convolutional neural networks. The results showed that wood decay could be detected, even if with accuracy varying among the two datasets. The best results on the Etnedal dataset were obtained using a convolution neural network with the first five components of a principal component analysis as input (OA = 65.5%), while on the Gran dataset, the best result was obtained using LASSO with logistic regression and data aggregated using the weighted mean (OA = 61.4%). In general, the differences among aggregated and unaggregated data were small. Numéro de notice : A2022-352 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.3390/rs14081892 Date de publication en ligne : 14/04/2022 En ligne : https://doi.org/10.3390/rs14081892 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100541 [article]

Coupling fossil records and traditional discrimination metrics to test how genetic information improves species distribution models of the European beech Fagus sylvatica / Pedro Poli in European Journal of Forest Research, vol 141 n° 2 (April 2022)  

Public [article]  inEuropean Journal of Forest Research > vol 141 n° 2 (April 2022) . - pp - 253–265 Titre : Coupling fossil records and traditional discrimination metrics to test how genetic information improves species distribution models of the European beech Fagus sylvatica Type de document : Article/Communication Auteurs : Pedro Poli, Auteur ; Annie Guiller, Auteur ; Jonathan Lenoir, Auteur Année de publication : 2022 Article en page(s) : pp - 253–265 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] adaptation (biologie) [Termes IGN] bioclimatologie [Termes IGN] distribution spatiale [Termes IGN] espèce végétale [Termes IGN] Europe (géographie politique) [Termes IGN] Fagus sylvatica [Termes IGN] fossile [Termes IGN] génétique forestière [Termes IGN] Holocène [Termes IGN] modèle de simulation [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Species distribution models (SDMs) are widely used to hindcast or forecast suitable habitat conditions during climate change. Although distant populations of a given species may show local adaptations to diverging environmental conditions, traditional SDMs disregard intraspecific variation. Yet, incorporating genetic information into SDMs could improve predictions. Here we aimed at investigating whether genetically informed SDMs would outperform traditional SDMs. Using published information on the spatial genetic structure of the European Beech Fagus sylvatica L. (1753), we built lineage-specific SDMs for each phylogenetic group of the species. We then combined all lineage-specific SDMs into a single genetically informed SDM that we compared against a traditional SDM approach. We finally compared SDMs’ predictions against independent datasets of present-day distribution as well as fossil distribution data from the Mid-Holocene, using six metrics of model performance. We found that aggregating lineage-specific SDMs into a single genetically informed SDM increased model performances to identify suitable areas currently occupied by F. sylvatica. In comparison to a traditional SDM, the genetically informed SDM we built for F. sylvatica assigned higher probabilities of occurrence during the Mid-Holocene at locations where fossil records were found. Aggregating lineage-specific SDMs into a single genetically informed SDM seems to outperform the traditional SDM approach, especially so when the aim is to identify potentially suitable areas of occupancy. This could be particularly useful for the identification of cryptic refugia that remain undetected by traditional SDMs. Genetically informed SDMs have the potential to improve our understanding of species redistribution under climate change. Numéro de notice : A2022-296 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1007/s10342-021-01437-1 Date de publication en ligne : 27/01/2022 En ligne : https://doi.org/10.1007/s10342-021-01437-1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100353 [article]

Data assimilation of growing stock volume using a sequence of remote sensing data from different sensors / Niels Lindgren in Canadian journal of remote sensing, vol 48 n° 2 (April 2022)  

Public [article]  inCanadian journal of remote sensing > vol 48 n° 2 (April 2022) . - pp Titre : Data assimilation of growing stock volume using a sequence of remote sensing data from different sensors Titre original : Assimilation de données de volume de bois à l’aide d’une séquence de données de télédétection provenant de différents capteurs Type de document : Article/Communication Auteurs : Niels Lindgren, Auteur ; Hakan Olsson, Auteur ; Kenneth Nyström, Auteur ; Mattias Nyström, Auteur ; Göran Stahl, Auteur Année de publication : 2022 Article en page(s) : pp Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] Betula (genre) [Termes IGN] capital sur pied [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] étalonnage des données [Termes IGN] filtre de Kalman [Termes IGN] forêt boréale [Termes IGN] Picea abies [Termes IGN] Pinus sylvestris [Termes IGN] Quercus (genre) [Termes IGN] Suède [Termes IGN] volume en bois Résumé : (auteur) Airborne Laser Scanning (ALS) has implied a disruptive transformation of how data are gathered for forest management planning in Nordic countries. We show in this study that the accuracy of ALS predictions of growing stock volume can be maintained and even improved over time if they are forecasted and assimilated with more frequent but less accurate remote sensing data sources like satellite images, digital photogrammetry, and InSAR. We obtained these results by introducing important methodological adaptations to data assimilation compared to previous forestry studies in Sweden. On a test site in the southwest of Sweden (58°27′N, 13°39′E), we evaluated the performance of the extended Kalman filter and a proposed modified filter that accounts for error correlations. We also applied classical calibration to the remote sensing predictions. We evaluated the developed methods using a dataset with nine different acquisitions of remotely sensed data from a mix of sensors over four years, starting and ending with ALS-based predictions of growing stock volume. The results showed that the modified filter and the calibrated predictions performed better than the standard extended Kalman filter and that at the endpoint the prediction based on data assimilation implied an improved accuracy (25.0% RMSE), compared to a new ALS-based prediction (27.5% RMSE). Numéro de notice : A2022-144 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1080/07038992.2021.1988542 Date de publication en ligne : 17/10/2021 En ligne : https://doi.org/10.1080/07038992.2021.1988542 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99985 [article]

Drought impacts in forest canopy and deciduous tree saplings in Central European forests / Mirela Beloiu in Forest ecology and management, vol 509 (April-1 2022)  

Public [article]  inForest ecology and management > vol 509 (April-1 2022) . - n° 120075 Titre : Drought impacts in forest canopy and deciduous tree saplings in Central European forests Type de document : Article/Communication Auteurs : Mirela Beloiu, Auteur ; Reinhold Stahlmann, Auteur ; Carl Beierkuhnlein, Auteur Année de publication : 2022 Article en page(s) : n° 120075 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Bavière (Allemagne) [Termes IGN] bois mort [Termes IGN] canopée [Termes IGN] dendrométrie [Termes IGN] données de terrain [Termes IGN] écosystème forestier [Termes IGN] jeune arbre [Termes IGN] mortalité [Termes IGN] peuplement mélangé [Termes IGN] phénomène climatique extrême [Termes IGN] Pinophyta [Termes IGN] régénération (sylviculture) [Termes IGN] résilience écologique [Termes IGN] sécheresse [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Forests worldwide are increasingly exposed to extreme weather events. Drought deteriorates the health, structure, and functioning of forests, which can lead to reduced diversity, decreased productivity, and increased tree mortality. Therefore, it is an urgent need to assess the impact of drought on tree species. Due to differences in tree physiology, saplings and mature trees are likely to respond specifically to drought conditions. In contrast to mature trees, little is known about the response of saplings to drought. Here, we combine in-situ field measurements for saplings of deciduous tree species with remote sensing for forest canopy to assess drought damage, recovery, and sapling mortality patterns during a centennial drought (2018, 2019) and beyond (2020). We measured 2051 saplings out of 214 plots in Central Germany. Forest canopy health was assessed using 10 × 10 m resolution satellite observations for the same locations. We (1) demonstrate that forest canopy exhibits long-lasting drought-induced effects, (2) show that saplings have a remarkable capacity to recover from drought and survive a subsequent drought, (3) demonstrate that reduced sapling recovery leads to their mortality, (4) reveal that drought damage on saplings increases from pioneer to non-pioneer species, and mortality is ranking from Sorbus aucuparia > Sambucus nigra > Fraxinus excelsior, Acer campestre, Frangula alnus > Ulmus glabra > Carpinus betulus > Betula pendula, Fagus sylvatica > Acer pseudoplatanus > Quercus petraea > Corylus avellana, Crataegus spp., > Prunus avium, Quercus robur; and (5) link drought response to site conditions, indicating that species diversity and winter precipitation as relevant indicators of tree health. If periods of drought become more frequent, as expected, this could negatively impact mid-term forest recovery, alter long-term tree species assemblages and reduce biodiversity and functional resilience of forest ecosystems. We suggest that models of forest response to drought should differentiate between the forest canopy and understory and also consider species-specific responses as we found a broad spectrum of responses within the same plant functional type of deciduous tree species in terms of drought damage and recovery. Numéro de notice : A2022-191 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2022.120075 Date de publication en ligne : 12/02/2022 En ligne : https://doi.org/10.1016/j.foreco.2022.120075 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99947 [article]

Effect of climate change on the growth of tree species: Dendroclimatological analysis / Archana Gauli in Forests, vol 13 n° 4 (April 2022)  

Permalink

Estimation and testing of linkages between forest structure and rainfall interception characteristics of a Robinia pseudoacacia plantation on China’s Loess Plateau / Changkun Ma in Journal of Forestry Research, vol 33 n° 2 (April 2022)  

Permalink

Fertilization modifies forest stand growth but not stand density: consequences for modelling stand dynamics in a changing climate / Hans Pretzsch in Forestry, an international journal of forest research, vol 95 n° 2 (April 2022)  

Permalink

Problems with models assessing influences of tree size and inter-tree competitive processes on individual tree growth: a cautionary tale / P.W. West in Journal of Forestry Research, vol 33 n° 2 (April 2022)  

Permalink

Recent changes in the climate-growth response of European larch (Larix decidua Mill.) in the Polish Sudetes / Malgorzata Danek in Trees, vol 36 n° 2 (April 2022)  

Permalink

Species level classification of Mediterranean sparse forests-maquis formations using Sentinel-2 imagery / Semiha Demirbaş Çağlayana in Geocarto international, vol 37 n° 6 ([01/04/2022])  

Permalink

Are northern German Scots pine plantations climate smart? The impact of large-scale conifer planting on climate, soil and the water cycle / Christoph Leuschner in Forest ecology and management, vol 507 (March-1 2022)  

Permalink

Assessing the dependencies of scots pine (Pinus sylvestris L.) structural characteristics and internal wood property variation / Ville Kankare in Forests, vol 13 n° 3 (March 2022)  

Permalink

Changes of tree stem biomass in European forests since 1950 / Aleksandr Lebedev in Journal of forest science, vol 68 n° 3 (March 2022)  

Permalink

Classification of Eucalyptus plantation Site Index (SI) and Mean Annual Increment (MAI) prediction using DEM-based geomorphometric and climatic variables in Brazil / Aliny Aparecida Dos Reis in Geocarto international, vol 37 n° 5 ([01/03/2022])  

Permalink