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Taller and slenderer trees in Swedish forests according to data from the National Forest Inventory / Alex Appiah Mensah in Forest ecology and management, vol 527 (January-1 2023)  

Public [article]  inForest ecology and management > vol 527 (January-1 2023) . - n° 120605 Titre : Taller and slenderer trees in Swedish forests according to data from the National Forest Inventory Type de document : Article/Communication Auteurs : Alex Appiah Mensah, Auteur ; Hans Petersson, Auteur ; Jonas Dahlgren, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 120605 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] azote [Termes IGN] changement climatique [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] forêt boréale [Termes IGN] gestion forestière [Termes IGN] hauteur des arbres [Termes IGN] inventaire forestier étranger (données) [Termes IGN] Picea abies [Termes IGN] Pinus sylvestris [Termes IGN] Suède [Termes IGN] surface terrière [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Changes over time in annual basal area growth and mean height for Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies (L.) Karst.) over the period, 1983–2020 were studied using sample tree data from temporary plots recorded in the Swedish National Forest Inventory. The annual basal area growth was derived from the last measured full ring on increment cores. Using 20 to 60-year-old dominant trees, the mean height and annual basal area growth were examined as functions of tree, stand and site conditions, and trends were assessed mainly using residual analyses over time. A significant increase in mean height at a given age was found for both species, but the annual basal area growth level remained stable over the 38-year period. Currently, at a given age of 50 annual rings at breast height, the mean heights of pines and spruces increased on average by 10.1% (i.e. ∼2 m), compared to 50 year-old pines and spruces in the 1980s, and the increase was similar in the different regions. The results suggest that trees have become taller and slenderer in Swedish forests. Increasing tree height over time at a given age in Northern Europe has been documented in several reports and many causes have been suggested, such as changed forest management, increasing temperatures and nitrogen deposition. We suggest that elevated CO2 in the air and improved water-use efficiency for the trees might also be strong drivers. Numéro de notice : A2023-005 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2022.120605 Date de publication en ligne : 05/11/2022 En ligne : https://doi.org/10.1016/j.foreco.2022.120605 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102008 [article]

A model-based scenario analysis of the impact of forest management and environmental change on the understorey of temperate forests in Europe / Bingbin Wen in Forest ecology and management, vol 522 (October-15 2022)  

Public [article]  inForest ecology and management > vol 522 (October-15 2022) . - n° 120465 Titre : A model-based scenario analysis of the impact of forest management and environmental change on the understorey of temperate forests in Europe Type de document : Article/Communication Auteurs : Bingbin Wen, Auteur ; Haben Blondeel, Auteur ; Dries Landuyt, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 120465 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse de sensibilité [Termes IGN] azote [Termes IGN] biodiversité [Termes IGN] changement climatique [Termes IGN] dynamique de la végétation [Termes IGN] Europe centrale [Termes IGN] forêt tempérée [Termes IGN] gestion forestière durable [Termes IGN] impact sur l'environnement [Termes IGN] modèle de simulation [Termes IGN] sous-étage [Termes IGN] système d'aide à la décision [Vedettes matières IGN] Ecologie forestière Résumé : (auteur) The temperate forest understorey is rich in terms of vascular plant diversity and plays a vital functional role. Given the sensitivity of this forest layer to forest management and global environmental change and the limited knowledge on its long-term dynamics, there is a need for decision support systems that can guide temperate forest managers to optimize their management in terms of understorey outcomes. In this study, using understorey resurvey data collected from across temperate Europe, we developed Generalized Additive Models (GAM) to predict four understorey properties based on forest management and environmental change data, and implemented this model in a web-based tool as a prototype understorey Decision Support System (DSS). Using seventy-two combined climate change, nitrogen(N) deposition and forest management scenarios, applied to two case study regions in Europe, we predicted temperate forest understorey biodiversity dynamics between 2020 and 2050. A sensitivity analysis subsequently allowed to quantify the relative importance of canopy opening, N deposition and climate change on understorey dynamics. Our study showed that, regardless of regions, understorey richness and the proportion of forest specialists generally decreased among most scenarios, but the proportion of woody species and the understorey vegetation total cover increased. Climate warming, N deposition, and increases in canopy openness all influenced understorey dynamics. Climate warming will shift composition towards a selection of forest generalists and woody species, but a less open canopy could mitigate this shift by increasing the proportion of forest specialists. The case studies also showed that these responses can be context-dependent, especially in terms of responses to N deposition. Numéro de notice : A2022-710 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2022.120465 Date de publication en ligne : 19/08/2022 En ligne : https://doi.org/10.1016/j.foreco.2022.120465 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101587 [article]

A comparative assessment of modeling groundwater vulnerability using DRASTIC method from GIS and a novel classification method using machine learning classifiers / Qasim Khan in Geocarto international, vol 37 n° 20 ([20/09/2022])  

Public [article]  inGeocarto international > vol 37 n° 20 [20/09/2022] . - pp 5832 - 5850 Titre : A comparative assessment of modeling groundwater vulnerability using DRASTIC method from GIS and a novel classification method using machine learning classifiers Type de document : Article/Communication Auteurs : Qasim Khan, Auteur ; Muhammad Usman Liaqat, Auteur ; Mohamed Mostafa Mohamed, Auteur Année de publication : 2022 Article en page(s) : pp 5832 - 5850 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] analyse en composantes principales [Termes IGN] apprentissage automatique [Termes IGN] aquifère [Termes IGN] ArcGIS [Termes IGN] classification bayesienne [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] eau souterraine [Termes IGN] Emirats Arabes Unis [Termes IGN] estimation par noyau [Termes IGN] nitrate [Termes IGN] vulnérabilité Résumé : (auteur) Groundwater is more prone to contamination due to its extensive usage. Different methods are applied to study vulnerability of groundwater including widely used DRASTIC method, SI and GOD. This study proposes a novel method of mapping groundwater vulnerability using machine learning algorithms. In this study, point extraction method was used to extract point values from a grid of 646 points of seven raster layer in the Al Khatim study area of United Arab Emirates. These extracted values were classified based on nitrate concentration threshold of 50 mg/L into two classes. Machine learning models were developed, using depth to water (D), recharge (R), aquifer media (A), soil media (S), topography (T), vadose zone (I) and hydraulic conductivity (C), on the basis of nitrate class. Classified ‘groundwater vulnerability class values’ were trained using 10-fold cross-validation, using four machine learning models which were Random Forest, Support Vector Machine, Naïve Bayes and C4. 5. Accuracy showed the model developed by Random Forest gained highest accuracy of 93%. Four groundwater vulnerability maps were developed from machine learning classifiers and was compared with base method of DRASTIC index. The efficiency, accuracy and validity of machine learning based models were evaluated based on Receiver Operating Characteristics (ROC) curve and Precision-Recall curve (PRC). The results proved that machine learning is an efficient tool to access, analyze and map groundwater vulnerability. Numéro de notice : A2022-716 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/10106049.2021.1923833 Date de publication en ligne : 01/06/2021 En ligne : https://doi.org/10.1080/10106049.2021.1923833 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101641 [article]

Experimental precipitation reduction slows down litter decomposition but exhibits weak to no effect on soil organic carbon and nitrogen stocks in three Mediterranean forests of Southern France / Mathieu Santonja in Forests, vol 13 n° 9 (september 2022)  

Public [article]  inForests > vol 13 n° 9 (september 2022) . - n° 1485 Titre : Experimental precipitation reduction slows down litter decomposition but exhibits weak to no effect on soil organic carbon and nitrogen stocks in three Mediterranean forests of Southern France Type de document : Article/Communication Auteurs : Mathieu Santonja, Auteur ; Susana Pereira, Auteur ; Thierry Gauquelin, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 1485 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] azote [Termes IGN] changement climatique [Termes IGN] déchet organique [Termes IGN] écosystème forestier [Termes IGN] forêt méditerranéenne [Termes IGN] France (administrative) [Termes IGN] litière [Termes IGN] Pinus halepensis [Termes IGN] précipitation [Termes IGN] puits de carbone [Termes IGN] Quercus ilex [Termes IGN] Quercus pubescens [Vedettes matières IGN] Ecologie forestière Résumé : (auteur) Forest ecosystems are some of the largest carbon (C) reservoirs on earth. Pinus halepensis Mill., Quercus ilex L. and Quercus pubescens Willd. represent the dominant tree cover in the Mediterranean forests of southern France. However, their contributions to the French and global forest C and nitrogen (N) stocks are frequently overlooked and inaccurately quantified and little is known about to what extent the ongoing climate change can alter these stocks. We quantified the soil organic C (SOC) and N (SN) stocks in Mediterranean forests dominated by these tree species and evaluated to what extent an experimental precipitation reduction (about −30% yearly) affects these stocks and the litter decomposition efficiency. Litter mass losses were 55.7, 49.8 and 45.7% after 24 months of decomposition in Q. ilex, Q. pubescens and P. halepensis forests, respectively, and were 19% lower under drier climatic conditions. The SOC stocks were 14.0, 16.7 and 18.5 Mg ha−1 and the SN stocks were 0.70, 0.93 and 0.88 Mg ha−1 in Q. ilex, Q. pubescens and P. halepensis forests, respectively. The shallowness and stoniness of these Mediterranean forests could explain these limited stocks. By distinguishing the organic from the organo–mineral layer, we showed 74% less SOC in the organic layer of the P. halepensis forest under drier conditions, while no difference was detected in the organo–mineral layer or in the two oak forests. This last finding deserves further investigation and points out the necessity to distinguish the organic from the organo–mineral layer to detect the first impacts of climate change on SOC stocks. Numéro de notice : A2022-753 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.3390/f13091485 Date de publication en ligne : 14/09/2022 En ligne : https://doi.org/10.3390/f13091485 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101756 [article]

Optimal resolution of soil properties maps varies according to their geographical extent and location / Christian Piedallu in Geoderma, vol 412 (15 April 2022)  

Public [article]  inGeoderma > vol 412 (15 April 2022) . - n° 115723 Titre : Optimal resolution of soil properties maps varies according to their geographical extent and location Type de document : Article/Communication Auteurs : Christian Piedallu, Auteur ; Eloïse Pedersoli, Auteur ; Emeline Chaste, Auteur ; François Morneau , Auteur ; Ingrid Seynave, Auteur ; Jean-Claude Gégout, Auteur Année de publication : 2022 Projets : 3-projet - voir note / Article en page(s) : n° 115723 Note générale : bibliographie This study was funded through the Rescale project by the Regional Council of Grand-Est (“Region Grand-Est”) and the “Direction de l’Agriculture et de la Forêt (DRAF) “Grand-Est. Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique [Termes IGN] azote [Termes IGN] carbone [Termes IGN] carte pédologique [Termes IGN] échelle cartographique [Termes IGN] Grand Est (région 2016) [Termes IGN] inventaire forestier national (données France) [Termes IGN] pédologie locale [Termes IGN] potentiel hydrogène [Termes IGN] précision cartographique Résumé : (auteur) The important development of digital soil mapping (DSM) these last decades has led to a large number of maps of soil properties with increasingly finer raster size. Map resolution is mostly determined by expert knowledge or by matching with the resolution of existing data, while scale is recognized as a major issue. Using the pH and the C/N ratio describing the surface horizon of forest soils and estimated by bioindication, we evaluated the effect of resolution changes on model and map performance for different geographical extents. Using 40,663 plots from the national forest inventory and 25 environmental variables calculated at eight different spatial resolution levels (50, 100, 250, 500, 1000, 8000, 16,000, and 50,000 m), we modeled and mapped pH and C/N over a vast and diversified area of 91,000 km2 in the north-east of France. The models highlighted the importance of geology in pH and C/N spatial variations, and to a lesser extent the importance of stand type, climate and topography, with a slight influence of data resolution on predictor selection. On the contrary, the accuracy of model or map performance decreased significantly above 1000 m resolution. Significant performance differences were observed according to the location and the size of the geographical extent. Globally, the more heterogeneous environmental characteristics and the smaller the geographical extent, the better fine spatial resolution performed. In addition, the aggregation of fine-resolution pH or C/N maps at a coarser cell size improved map performance as compared to the direct use of the coarse-resolution predictors. The impact of resolution changes on map accuracy varies according to the mapping procedure, the local environment, and the geographical extent, and should be evaluated in DSM studies to optimize map accuracy. Numéro de notice : A2022-141 Affiliation des auteurs : IGN+Ext (2020- ) Autre URL associée : vers HAL Thématique : FORET/GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.geoderma.2022.115723 Date de publication en ligne : 01/02/2022 En ligne : https://doi.org/10.1016/j.geoderma.2022.115723 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99953 [article]

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)  

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Multi-parameter risk mapping of Qazvin aquifer by classic and fuzzy clustering techniques / Saman Javadi in Geocarto international, vol 37 n° 4 ([15/02/2022])  

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Vegetation changes in the understory of nitrogen-sensitive temperate forests over the past 70 years / Marina Roth in Forest ecology and management, vol 503 (January-1 2022)  

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Apports de la télédétection au calcul d’indicateurs agri-environnementaux au service de la PAC, des agriculteurs et porteurs d’enjeu / Christian Bockstaller in Innovations Agronomiques, vol 83 (Mars 2021)  

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Analysis of chlorophyll concentration in potato crop by coupling continuous wavelet transform and spectral variable optimization / Ning Liu in Remote sensing, vol 12 n° 17 (September-1 2020)  

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Evaluating 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)  

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Influence of forest management activities on soil organic carbon stocks: A knowledge synthesis / Mathias Mayer in Forest ecology and management, Vol 466 (15 June 2020)  

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Forest gaps retard carbon and nutrient release from twig litter in alpine forest ecosystems / Bo Tan in European Journal of Forest Research, vol 139 n° 1 (February 2020)  

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Advances in forest management under global change / Ling Zhang (2020)  

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Spatial variability in environmental science / John P. Tiefenbacher (2020)  

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