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Diffuse sunlight and cosmic rays: Missing pieces of the forest growth change attribution puzzle? / Jean-Daniel Bontemps in Science of the total environment, vol 806 n°1 (February 2022)  

Public [article]  inScience of the total environment > vol 806 n°1 (February 2022) . - n° 150469 Titre : Diffuse sunlight and cosmic rays: Missing pieces of the forest growth change attribution puzzle? Type de document : Article/Communication Auteurs : Jean-Daniel Bontemps , Auteur ; Henrik Svensmark, Auteur Année de publication : 2022 Projets : 1-Pas de projet / Article en page(s) : n° 150469 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] cerne [Termes IGN] croissance des arbres [Termes IGN] dioxyde de carbone [Termes IGN] modèle de croissance végétale [Termes IGN] modélisation de la forêt [Termes IGN] photosynthèse [Termes IGN] rayonnement cosmique [Termes IGN] rayonnement lumineux [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Forest growth changes have been a matter of intense research efforts since the 1980s. Owing to the variety of their environmental causes – mainly atmospheric CO2 increase, atmospheric N deposition, changes in temperature and water availability, and their interactions – their interpretation has remained challenging. Recent isolated researches suggest further effects of neglected environmental factors, namely changes in the diffuse fraction of light, more efficient to photosynthesis, and galactic cosmic rays (GCR), both emphasized in this Discussion paper. With growing awareness of GCR influence on global cloudiness (the cosmoclimatologic theory by H. Svensmark), GCR may thus cause trends in diffuse-light, and distinguishing between their direct/indirect influences on forest growth remains uncertain. This link between cosmic rays and diffuse sunlight also forms an alternative explanation to the geological evidence of a negative correlation between GCR and atmospheric CO2 concentration over the past 500 Myr. After a careful scrutiny of this literature and of key contributions in the field, we draw research options to progress further in this attribution. These include i) observational strategies intending to build on differences in the spatio-temporal dynamics of environmental growth factors, ranging from quasi-experiments to meta-analyses, ii) simulation strategies intending to quantify environmental factor's effects based on process-based ecosystem modelling, in a context where progresses for accounting for diffuse-light fraction are ongoing. Also, the hunt for tree-ring based proxies of GCR may offer the perspective of testing the GCR hypothesis on fully coupled forest growth samples. Numéro de notice : A2022-001 Affiliation des auteurs : LIF+Ext (2020- ) Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.scitotenv.2021.150469 Date de publication en ligne : 21/09/2021 En ligne : https://doi.org/10.1016/j.scitotenv.2021.150469 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98515 [article]

Improving the Fagacées growth model with an expanded common beech (Fagus sylvatica L.) data series from France and Germany / Gilles Le Moguédec in Annals of Forest Science [en ligne], vol 78 n° 4 (December 2021)  

Public [article]  inAnnals of Forest Science [en ligne] > vol 78 n° 4 (December 2021) . - n° 84 Titre : Improving the Fagacées growth model with an expanded common beech (Fagus sylvatica L.) data series from France and Germany Type de document : Article/Communication Auteurs : Gilles Le Moguédec, Auteur ; Sidonie Artru, Auteur ; Axel Albrecht, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 84 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] allométrie [Termes IGN] Fagus sylvatica [Termes IGN] forêt équienne [Termes IGN] France (administrative) [Termes IGN] hauteur des arbres [Termes IGN] jeu de données [Termes IGN] modèle de croissance végétale [Termes IGN] modélisation de la forêt [Termes IGN] Quercus (genre) [Termes IGN] République fédérale d'Allemagne [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Key message: The Fagacées growth model was originally designed for application in the Northern half of France. It is a robust model with potential applicability to a larger area, though this potential has not yet been verified. We added new data to the original parameterization data set and our results show that the Fagacées formalism can be generalized. Context: The Fagacées growth and yield model was designed for the management of pure even-aged stands of European beech and served as a prototype to build models for other tree species. Aims: The objective of this study was to improve the growth components of the Fagacées model with additional data from North-Western France to South-Western Germany. Material and methods: Our model was calibrated on several forest inventory data sets. The first one (F) is the original data set that was used to elaborate the equations in the Fagacées model. The second one (F+) is the original data set extended with additional measurements on the same sites and on new sites in Northern France. The third (G) adds complementary data from a forest network in Southwestern Germany. The last one (A) is the aggregate of all these data sets. Results: Fitting the original model equations on the extended F+ dataset led us to modify the equation for stand basal area increment. This new equation also fit the German dataset well. The other equations could be applied to all datasets, some with the same parameter values and some after recalibrating according to the dataset. Conclusion: We conclude that the general form of the model’s equations is appropriate for application to other regions, but that a recalibration of the equations is preferable in order to reflect local conditions. The advantage of our approach is that fewer data are required to recalibrate an existing equation than to establish an entirely new one. Numéro de notice : A2021-695 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-021-01086-9 Date de publication en ligne : 20/09/2021 En ligne : https://doi.org/10.1007/s13595-021-01086-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98525 [article]

Radiative transfer modeling in structurally complex stands: towards a better understanding of parametrization / Frédéric André in Annals of Forest Science [en ligne], vol 78 n° 4 (December 2021)  

Public [article]  inAnnals of Forest Science [en ligne] > vol 78 n° 4 (December 2021) . - n° 92 Titre : Radiative transfer modeling in structurally complex stands: towards a better understanding of parametrization Type de document : Article/Communication Auteurs : Frédéric André, Auteur ; Louis de Wergifosse, Auteur ; François de Coligny, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 92 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Belgique [Termes IGN] couvert forestier [Termes IGN] croissance des arbres [Termes IGN] densité du feuillage [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] estimation bayesienne [Termes IGN] Fagus sylvatica [Termes IGN] houppier [Termes IGN] Leaf Mass per Area [Termes IGN] modèle de croissance végétale [Termes IGN] modèle de transfert radiatif [Termes IGN] peuplement mélangé [Termes IGN] photosynthèse [Termes IGN] production primaire brute [Termes IGN] production primaire nette [Termes IGN] Quercus sessiliflora [Termes IGN] structure d'un peuplement forestier [Vedettes matières IGN] Sylviculture Résumé : (auteur) Key message: The best options to parametrize a radiative transfer model change according to the response variable used for fitting. To predict transmitted radiation, the turbid medium approach performs much better than the porous envelop, especially when accounting for the intra-specific variations in leaf area density but crown shape has limited effects. When fitting with tree growth data, the porous envelop approach combined with the more complex crown shape provides better results. When using a joint optimization with both variables, the better options are the turbid medium and the more detailed approach for describing crown shape and leaf area density. Context: Solar radiation transfer is a key process of tree growth dynamics in forest. Aims: Determining the best options to parametrize a forest radiative transfer model in heterogeneous oak and beech stands from Belgium. Methods: Calibration and evaluation of a forest radiative transfer module coupled to a spatially explicit tree growth model were repeated for different configuration options (i.e., turbid medium vs porous envelope to calculate light interception by trees, crown shapes of contrasting complexity to account for their asymmetry) and response variables used for fitting (transmitted radiation and/or tree growth data). Results: The turbid medium outperformed the porous envelope approach. The more complex crown shapes enabling to account for crown asymmetry improved performances when including growth data in the calibration. Conclusion: Our results provide insights on the options to select when parametrizing a forest radiative 3D-crown transfer model depending on the research or application objectives. Numéro de notice : A2021-836 Affiliation des auteurs : non IGN Thématique : FORET/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-021-01106-8 Date de publication en ligne : 26/10/2021 En ligne : https://doi.org/10.1007/s13595-021-01106-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99010 [article]

A CNN-based approach for the estimation of canopy heights and wood volume from GEDI waveforms / Ibrahim Fayad in Remote sensing of environment, vol 265 (November 2021)  

Public [article]  inRemote sensing of environment > vol 265 (November 2021) . - n° 112652 Titre : A CNN-based approach for the estimation of canopy heights and wood volume from GEDI waveforms Type de document : Article/Communication Auteurs : Ibrahim Fayad, Auteur ; Dino Lenco, Auteur ; Nicolas Baghdadi, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 112652 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] Brésil [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] Eucalyptus (genre) [Termes IGN] forme d'onde [Termes IGN] hauteur des arbres [Termes IGN] modèle de croissance végétale [Termes IGN] random-motion-over-ground model [Termes IGN] semis de points [Termes IGN] volume en bois Résumé : (auteur) Full waveform (FW) LiDAR systems have proven their effectiveness to map forest biophysical variables in the last two decades, owing to their ability of measuring, with high accuracy, forest vertical structures. The Global Ecosystem Dynamics Investigation (GEDI) system on board the International Space Station (ISS) is the latest FW spaceborne LiDAR instrument for the continuous observation of Earth's forests. FW systems rely on very sophisticated pre-processing steps to generate a priori metrics in order to leverage their capabilities for the accurate estimation of the aforementioned forest characteristics. The ever-expanding volume of acquired GEDI data, which to date comprises more than 25 billion acquired unfiltered shots, and along with the pre-processed data, amounting to more than 90 TB of data, raises new challenges in terms of adapted preprocessing methods for the suitable exploitation of such a huge and complex amount of LiDAR data. To overcome the issues related to the generation of relevant metrics from GEDI data, we propose a new metric-free approach to estimate canopy dominant heights (Hdom) and wood volume (V) of Eucalyptus plantations over five different regions in Brazil. To avoid metric computation, we leverage deep learning techniques and, more in detail, convolutional neural networks with the aim to analyze the GEDI Level 1B geolocated waveforms. Performance comparisons were conducted between four convolutional neural network (CNN) variants using GEDI waveform data (either untouched, or subsetted) and a metric based Random Forest regressor (RF). Additionally, we tested if our framework can improve the generalization of the models to different distant regions. First, the models were trained using data from all the study regions. Cross validated results showed that the CNN based models compared well against their RF counterpart for both Hdom and V. The RMSE on the estimation of Hdom from the CNN based models varied between 1.54 and 1.94 m with a coefficient of determination (R2) between 0.86 and 0.91, while the RF model produced an accuracy on Hdom estimates of 1.45 m (R2 = 0.92). For V, CNN based estimations ranged from 27.76 to 33.33 m3.ha−1 (R2 between 0.82 and 0.88), while for RF, the RMSE was 27.61 m3.ha−1 (R2 = 0.88). Next, model generalization was assessed by means of a spatial transfer experiment. For Hdom, both the CNN and RF approaches showed similar performances to a global model, however, the CNN based approach showed higher variability on the estimation accuracy, and the variability was related to the forest structure between the trained and tested data (similar tree heights yield better accuracies). For the estimation of V, considering both approaches, the accuracy was dependent on the allometric relationship between Hdom and V in the training and testing regions while lower accuracies on V were obtained when the testing and training regions exhibited a different allometric relationship. Numéro de notice : A2021-869 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2021.112652 Date de publication en ligne : 31/08/2021 En ligne : https://doi.org/10.1016/j.rse.2021.112652 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99118 [article]

Progress on incorporating biodiversity monitoring in REDD+ through national forest inventories / Loïc Gillerot in Global ecology and conservation, vol 32 (December 2021)  

Public [article]  inGlobal ecology and conservation > vol 32 (December 2021) . - n° e01901 Titre : Progress on incorporating biodiversity monitoring in REDD+ through national forest inventories Type de document : Article/Communication Auteurs : Loïc Gillerot, Auteur ; Giorgio Grussu, Auteur ; Rocio Condor-Golec, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° e01901 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] déboisement [Termes IGN] indicateur de biodiversité [Termes IGN] inventaire de la végétation [Termes IGN] inventaire forestier étranger (données) [Termes IGN] inventaire forestier national (données France) [Termes IGN] puits de carbone [Termes IGN] Réduction des émissions dues à la déforestation et la dégradation des forêts, REDD [Termes IGN] surveillance forestière [Termes IGN] télédétection [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) There is a well-documented opportunity and need to incorporate biodiversity conservation priorities into REDD+ (Reducing Emissions from Deforestation and Forest Degradation) initiatives. This requires thorough monitoring of changes to biodiversity at appropriate temporal and spatial scales. A national forest inventory is one of the essential tools used to monitor carbon stock changes but can also be expanded to include biodiversity indicators. Here we analyse the progress and potential of 70 countries in monitoring primarily non-tree biodiversity using national forest inventories. Progress on national forest inventories among countries participating in REDD+ is variable: 11 countries have not started; 26 have started but do not include non-tree biodiversity indicators; the remaining 33 countries do include non-tree biodiversity indicators but use various methodological approaches, levels of detail and taxonomic groups. Very few of these provide comprehensive and accessible manuals or results, highlighting a need for greater transparency. The capacity of countries to fund ongoing national forest inventories is a constraining factor. Remote sensing technologies can help reduce costs for countries with limited monitoring capacity but the need to understand biodiversity variation at finer scales often limits the utility of such methods. Numéro de notice : A2021-866 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET Nature : Article DOI : 10.1016/j.gecco.2021.e01901 Date de publication en ligne : 02/11/2021 En ligne : https://doi.org/10.1016/j.gecco.2021.e01901 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99096 [article]

Beech and hornbeam dominate oak 20 years after the creation of storm-induced gaps / Lucie Dietz in Forest ecology and management, vol 503 (1 January 2022)  

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Factors affecting winter damage and recovery of newly planted Norway spruce seedlings in boreal forests / Jaana Luoranen in Forest ecology and management, vol 503 (1 January 2022)  

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Monitoring leaf phenology in moist tropical forests by applying a superpixel-based deep learning method to time-series images of tree canopies / Guangqin Song in ISPRS Journal of photogrammetry and remote sensing, vol 183 (January 2022)  

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How geographic and climatic factors affect the adaptation of Douglas-fir provenances to the temperate continental climate zone in Europe / Marzena Niemczyk in European Journal of Forest Research, vol 140 n° 6 (December 2021)  

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The Impact of ash dieback on veteran trees in Southwestern Sweden / Vikki Bengtsson in Baltic forestry, vol 27 n° 1 (2021)  

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Estimating timber volume loss due to storm damage in Carinthia, Austria, using ALS/TLS and spatial regression models / Arne Nothdurft in Forest ecology and management, vol 502 (15 december 2021)  

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Modeling post-logging height growth of black spruce-dominated boreal forests by combining airborne LiDAR and time since harvest maps / Batistin Bour in Forest ecology and management, vol 502 (15 december 2021)  

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The efficiency of retention measures in continuous-cover forestry for conserving epiphytic cryptogams: A case study on Abies alba / Stefan Kaufmann in Forest ecology and management, vol 502 (15 december 2021)  

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Automatic tuning of segmentation parameters for tree crown delineation with VHR imagery / Camile Sothe in Geocarto international, Vol 36 n° 19 ([18/10/2021])  

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Mapping canopy heights in dense tropical forests using low-cost UAV-derived photogrammetric point clouds and machine learning approaches / He Zhang in Remote sensing, vol 13 n° 18 (September-2 2021)  

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