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Termes IGN > foresterie > sylviculture
sylviculture
Commentaire :
Arboriculture, Arboriculture forestière, Arbres -- Techniques culturales, Cultures forestières, Forêts -- Techniques culturales, Forêts et sylviculture, Techniques forestières. Agriculture. >> Industrie forestière, Bois, Forêt -- Exploitation, Forêt, Machine forestière. Voir aussi les vedettes commençant par Forêts ; Foresterie ; Sylviculture. >>Terme(s) spécifique(s) : Écorçage, Martelage (sylviculture), Arbre -- Abattage, Déboisement, Déchet d'abattage, Dendrométrie, Inventaire forestier, Route forestière, Station forestière -- Typologie, Sylviculture tropicale, Essartage, Éclaircie (sylviculture), Cloisonnement (sylviculture), Coupe à blanc, Dégagement (sylviculture). Equiv. LCSH : Forest and forestry. |
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Pourquoi la forêt française a besoin d’un traitement de fond / Guillaume Decocq in The Conversation France, vol 2022 ([10/02/2022])
[article]
Titre : Pourquoi la forêt française a besoin d’un traitement de fond Type de document : Article/Communication Auteurs : Guillaume Decocq, Auteur ; Serge Muller, Auteur Année de publication : 2022 Langues : Français (fre) Descripteur : [Termes IGN] adaptation (biologie)
[Termes IGN] Chalara fraxinea
[Termes IGN] dépérissement
[Termes IGN] essence indigène
[Termes IGN] France (administrative)
[Termes IGN] gestion forestière durable
[Termes IGN] mortalité
[Termes IGN] productivité
[Termes IGN] puits de carbone
[Termes IGN] sécheresse
[Termes IGN] sylviculture
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Les conclusions des Assises nationales de la forêt et du bois, lancées par le gouvernement en octobre 2021 avec pour objectif de « penser la forêt française de demain », devraient être rendues dans les prochains jours. Un des axes majeurs de cette réflexion concernait le renforcement de la résilience des forêts et la préservation de la biodiversité.
Car la forêt française est aujourd’hui en crise : depuis deux décennies, on assiste en effet à une mortalité croissante des peuplements forestiers et à une baisse globale de leur productivité. Si la surface boisée en France métropolitaine ne cesse de croître depuis le milieu du XIXe siècle, c’est en raison du boisement – spontané ou artificiel – de terres agricoles, car la superficie occupée par des forêts anciennes, elle, ne cesse de diminuer. Ce « dépérissement », est généralement attribué aux modifications climatiques. Les sécheresses estivales récurrentes fragilisent les arbres et la douceur hivernale favorise les pullulations de bioagresseurs, en particulier les scolytes et les hannetons. Le changement climatique en est sans aucun doute une cause essentielle, mais il est aussi le révélateur d’écosystèmes forestiers fragilisés par des décennies de pratiques sylvicoles focalisées sur la production de bois. Non seulement la forêt française fixe moins de carbone par unité de surface, mais l’exploitation des peuplements dépérissants induit des émissions supplémentaires de CO₂ aggravant l’effet de serre et les changements climatiques associés.Numéro de notice : A2022-214 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET Nature : Article DOI : sans Date de publication en ligne : 20/02/2022 En ligne : https://theconversation.com/pourquoi-la-foret-francaise-a-besoin-dun-traitement- [...] Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100083
in The Conversation France > vol 2022 [10/02/2022][article]Afforestation with Pinus nigra Arn ssp salzmannii along an elevation gradient: controlling factors and implications for climate change adaptation / Manuel Esteban Lucas-Borja in Trees, vol 36 n° 1 (February 2022)
[article]
Titre : Afforestation with Pinus nigra Arn ssp salzmannii along an elevation gradient: controlling factors and implications for climate change adaptation Type de document : Article/Communication Auteurs : Manuel Esteban Lucas-Borja, Auteur ; Xin Jing, Auteur ; David Candel-Perez, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 93 - 102 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] afforestation
[Termes IGN] bassin méditerranéen
[Termes IGN] Espagne
[Termes IGN] gradient d'altitude
[Termes IGN] mortalité
[Termes IGN] Pinus nigra salzmannii
[Termes IGN] plantation forestière
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Spanish black pine (Pinus nigra Arn ssp. salzmannii) is the most widely distributed pine species in mountain areas of the Mediterranean Basin and is commonly used for afforestation in endangered and degraded areas. Despite its importance, little is known regarding the factors driving seedling survival for this species, which may hamper afforestation success in Mediterranean areas. In this study, we assessed the effects of seed origin and plantation site along a natural gradient with contrasting elevation and climatic conditions in a Mediterranean forest in Central-Eastern Spain. Our results showed: (1) higher seedling survival rates when seed origin differed from plantation site (25.3 ± 5.4%) compared to same origin and plantation site (5.3 ± 2.7%); (2) higher survival probability (~ 20%) for high and medium elevation seeds (colder and wetter locations) compared to the warmer and drier low elevation sites (15%); (3) higher seedling survival (~ 40%) at higher elevation sites compared to low-elevation sites ( Numéro de notice : A2021-975 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1007/s00468-021-02184-x Date de publication en ligne : 22/07/2021 En ligne : http://dx.doi.org/10.1007/s00468-021-02184-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100418
in Trees > vol 36 n° 1 (February 2022) . - pp 93 - 102[article]An open science and open data approach for the statistically robust estimation of forest disturbance areas / Saverio Francini in International journal of applied Earth observation and geoinformation, vol 106 (February 2022)
[article]
Titre : An open science and open data approach for the statistically robust estimation of forest disturbance areas Type de document : Article/Communication Auteurs : Saverio Francini, Auteur ; Ronald E. McRoberts, Auteur ; Giovanni d' Amico, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 102663 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] changement climatique
[Termes IGN] coupe rase (sylviculture)
[Termes IGN] détection de changement
[Termes IGN] estimation statistique
[Termes IGN] Fagus sylvatica
[Termes IGN] Google Earth Engine
[Termes IGN] image Sentinel-MSI
[Termes IGN] Italie
[Termes IGN] méthode robuste
[Termes IGN] perturbation écologique
[Termes IGN] Quercus cerris
[Termes IGN] Quercus pedunculata
[Termes IGN] Quercus pubescens
[Termes IGN] Quercus sessiliflora
[Termes IGN] surveillance forestièreRésumé : (auteur) Forest disturbance monitoring is critical for understanding forest-related greenhouse gas emissions and for determining the role of forest management in mitigating climate change. Multiple algorithms for the automated mapping of forest disturbance using remotely sensed imagery have been developed and applied; however, variability in natural and anthropogenic disturbance phenomena, as well as image acquisition conditions, can result in maps that may be incomplete or that contain inaccuracies that prevent their use for directly estimating areas of disturbance. To reduce errors in reporting disturbance areas, stratified estimators can be applied to obtain statistically robust area estimates, while simultaneously circumventing the need to conduct a complete census or in situations where such a census may not be possible. We present a semi-automated procedure for implementation in Google Earth Engine, 3I3D-GEE, for regional to global mapping of forest disturbance (including clear-cut harvesting, fire, and wind damage) and sample-based estimation of related areas using data from the processing capacity of Google Earth Engine. Documentation for the application is also provided in Appendix A. Using Sentinel-2 (S2) imagery, our procedure was applied and tested for 2018 in Italy for which the approximately 11 million ha of forests (mostly Q. pubescens, Q. robur, Q. cerris, Q. petraea, and Fagus sylvatica) serve as an appropriate case study because national statistics on forest disturbance areas are not available. To decrease the overall standard errors of the area estimates, the sampling intensities in areas where greater variability in the form of greater commission and omission errors are expected can be increased. To this end, we augmented the predicted forest disturbance map with a buffer class consisting of a two-pixel buffer (20 m) on each side of the disturbance class boundary. We selected a reference sample of 19,300 points: a simple random sample of 9,300 points from the buffer and simple random samples of 5000 from each of the undisturbed and disturbed classes. The reference sample was photointerpreted using fine resolution orthophotos (30 cm) and S2 imagery. While the estimate of the disturbed area obtained by adding the areas of pixels classified as disturbed was 41,732 ha, the estimate obtained using the unbiased stratified estimator was 27% greater at 57,717716 ha. Regarding map accuracy, we found several omission errors in the buffer (53.4%) but none (0%) in the undisturbed map class. Similarly, among the 1035 commission errors, the majority (7 4 4) were in the buffer class. The methods presented herein provide a useful tool that can be used to estimate areas of forest disturbance, which many nations must report as part of their commitment to international conventions and treaties. In addition, the information generated can support forest management, enabling the forest sector to monitor stand-replacing forest harvesting over space and time. Numéro de notice : A2022-072 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.jag.2021.102663 En ligne : https://doi.org/10.1016/j.jag.2021.102663 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99437
in International journal of applied Earth observation and geoinformation > vol 106 (February 2022) . - n° 102663[article]How much does it take to be old? Modelling the time since the last harvesting to infer the distribution of overmature forests in France / Lucie Thompson in Diversity and distributions, vol 28 n° 2 (February 2022)
[article]
Titre : How much does it take to be old? Modelling the time since the last harvesting to infer the distribution of overmature forests in France Type de document : Article/Communication Auteurs : Lucie Thompson, Auteur ; Eugénie Cateau, Auteur ; NIcolas Debaive, Auteur ; frédéric Bray, Auteur ; André Torre, Auteur ; Patrick Vallet, Auteur ; Yoan Paillet, Auteur Année de publication : 2022 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] âge du peuplement forestier
[Termes IGN] forêt tempérée
[Termes IGN] France métropolitaine
[Termes IGN] inventaire forestier national (données France)
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Aim : The distribution of overmature forests in metropolitan France is poorly known, with only a few well-studied prominent sites, and has never been evaluated countrywide. Here, we modelled French forest reserves' time since the last harvesting operation—a proxy for forest maturity—then inferred the current statistical distribution of overmature forests (i.e., forests over 50 years without harvesting) in France.
Location : Metropolitan France.
Methods : We used inventories from forest reserves and managed forests to calibrate a generalised linear mixed model explaining the time since the last harvesting with selected structural attributes and environmental variables. We then projected this model on the independent National Forest Inventory dataset. We thus obtained an updated estimation of the proportion and a rough distribution of overmature forest stands in metropolitan France.
Results : We found that high basal area of very large trees, high volumes of standing and downed deadwood, high diversity of tree-related microhabitats and more marginally diversity of decay stages best characterised the time since the last harvesting. Volumes of stumps and high density of coppices translating legacy of past forest management also distinguished more overmature plots. Our projection yielded an estimated 3% of French forests over 50 years without harvesting mostly located in more inaccessible areas (i.e., mountainous areas).
Main conclusions : Our study showed that the time since the last harvesting could be derived from a combination of key structural attributes characterising overmature temperate forests. It gives the first robust statistical estimate of the proportion of overmature forests in France and may serve to report on their status. Our method could be extended in countries with accessible National Forest Inventory and calibration data, thus producing indicators at an international level.Numéro de notice : A2022-074 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET Nature : Article DOI : 10.1111/ddi.13436 Date de publication en ligne : 08/12/2021 En ligne : https://doi.org/10.1111/ddi.13436 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99373
in Diversity and distributions > vol 28 n° 2 (February 2022)[article]Mapping burn severity in the western Italian Alps through phenologically coherent reflectance composites derived from Sentinel-2 imagery / Donato Morresi in Remote sensing of environment, vol 269 (February 2022)
[article]
Titre : Mapping burn severity in the western Italian Alps through phenologically coherent reflectance composites derived from Sentinel-2 imagery Type de document : Article/Communication Auteurs : Donato Morresi, Auteur ; Raffaella Marzano, Auteur ; Emanuele Lingua, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 112800 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] carte de la végétation
[Termes IGN] cartographie des risques
[Termes IGN] détection de changement
[Termes IGN] forêt alpestre
[Termes IGN] image multibande
[Termes IGN] image Sentinel-MSI
[Termes IGN] incendie de forêt
[Termes IGN] phénologie
[Termes IGN] Piémont (Italie)
[Termes IGN] réflectance spectrale
[Termes IGN] risque naturel
[Termes IGN] variation saisonnière
[Termes IGN] zone sinistréeRésumé : (auteur) Deriving burn severity from multispectral satellite data is a widely adopted approach to infer the degree of environmental change caused by fire. Burn severity maps obtained by thresholding bi-temporal indices based on pre- and post-fire Normalized Burn Ratio (NBR) can vary substantially depending on temporal constraints such as matched acquisition and optimal seasonal timing. Satisfying temporal requirements is crucial to effectively disentangle fire and non-fire induced spectral changes and can be particularly challenging when only a few cloud-free images are available. Our study focuses on 10 wildfires that occurred in mountainous areas of the Piedmont Region (Italy) during autumn 2017 following a severe and prolonged drought period. Our objectives were to: (i) generate reflectance composites using Sentinel-2 imagery that were optimised for seasonal timing by embedding spatial patterns of long-term land surface phenology (LSP); (ii) produce and validate burn severity maps based on the modelled relationship between bi-temporal indices and field data; (iii) compare burn severity maps obtained using either a pair of cloud-free Sentinel-2 images, i.e. paired images, or reflectance composites. We proposed a pixel-based compositing algorithm coupling the weighted geometric median and thematic spatial information, e.g. long-term LSP metrics derived from the MODIS Collection 6 Land Cover Dynamics Product, to rank all the clear observations available in the growing season. Composite Burn Index data and bi-temporal indices exhibited a strong nonlinear relationship (R2 > 0.85) using paired images or reflectance composites. Burn severity maps attained overall classification accuracy ranging from 76.9% to 83.7% (Kappa between 0.61 and 0.72) and the Relative differenced NBR (RdNBR) achieved the best results compared to other bi-temporal indices (differenced NBR and Relativized Burn Ratio). Improvements in overall classification accuracy offered by the calibration of bi-temporal indices with the dNBR offset were limited to burn severity maps derived from paired images. Reflectance composites provided the highest overall classification accuracy and differences with paired images were significant using uncalibrated bi-temporal indices (4.4% to 5.2%) while they decreased (2.8% to 3.2%) when we calibrated bi-temporal indices derived from paired images. The extent of the high severity category increased by ~19% in burn severity maps derived from reflectance composites (uncalibrated RdNBR) compared to those from paired images (calibrated RdNBR). The reduced contrast between healthy and burnt conditions associated with suboptimal seasonal timing caused an underestimation of burnt areas. By embedding spatial patterns of long-term LSP metrics, our approach provided consistent reflectance composites targeted at a specific phenological stage and minimising non-fire induced inter-annual changes. Being independent from the multispectral dataset employed, the proposed pixel-based compositing approach offers new opportunities for operational change detection applications in geographic areas characterised by persistent cloud cover. Numéro de notice : A2022-095 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.rse.2021.112800 Date de publication en ligne : 22/11/2021 En ligne : https://doi.org/10.1016/j.rse.2021.112800 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99534
in Remote sensing of environment > vol 269 (February 2022) . - n° 112800[article]Monthly mapping of forest harvesting using dense time series Sentinel-1 SAR imagery and deep learning / Feng Zhao in Remote sensing of environment, vol 269 (February 2022)PermalinkPlanning of commercial thinnings using machine learning and airborne Lidar data / Tauri Arumäe in Forests, vol 13 n° 2 (February 2022)PermalinkRelationships between species richness and ecosystem services in Amazonian forests strongly influenced by biogeographical strata and forest types / Gijs Steur in Scientific reports, vol 12 (2022)PermalinkSurvival time and mortality rate of regeneration in the deep shade of a primeval beech forest / R. Petrovska in European Journal of Forest Research, vol 141 n° 1 (February 2022)PermalinkConservation zones increase habitat heterogeneity of certified Mediterranean oak woodlands / Teresa Mexia in Forest ecology and management, vol 504 (January-15 2022)PermalinkForest floor alteration by canopy trees and soil wetness drive regeneration of a spruce-beech forest / Pavel Daněk in Forest ecology and management, vol 504 (January-15 2022)Permalink3D stem modelling in tropical forest: towards improved biomass and biomass change estimates / Sébastien Bauwens (2022)PermalinkAn assessment of forest loss and its drivers in protected areas on the Copperbelt province of Zambia: 1972–2016 / Darius Phiri in Geomatics, Natural Hazards and Risk, vol 13 (2022)PermalinkBeech and hornbeam dominate oak 20 years after the creation of storm-induced gaps / Lucie Dietz in Forest ecology and management, vol 503 (January-1 2022)PermalinkCharacteristics of taiga and tundra snowpack in development and validation of remote sensing of snow / Henna-Reetta Hannula (2022)Permalink