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Are pine-oak mixed stands in Mediterranean mountains more resilient to drought than their monospecific counterparts? / Francisco J. Muñoz-Gálvez in Forest ecology and management, vol 484 ([15/03/2021])  

Public [article]  inForest ecology and management > vol 484 [15/03/2021] . - n° 118955 Titre : Are pine-oak mixed stands in Mediterranean mountains more resilient to drought than their monospecific counterparts? Type de document : Article/Communication Auteurs : Francisco J. Muñoz-Gálvez, Auteur ; Asier Herrero, Auteur ; Maria Esther Pérez-Corona, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 118955 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse comparative [Termes IGN] changement climatique [Termes IGN] croissance des arbres [Termes IGN] Espagne [Termes IGN] forêt méditerranéenne [Termes IGN] gestion forestière [Termes IGN] module linéaire [Termes IGN] peuplement mélangé [Termes IGN] Pinus sylvestris [Termes IGN] Quercus pyrenaica [Termes IGN] sécheresse [Termes IGN] service écosystémique [Termes IGN] vulnérabilité [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Climate change projections point to an increase in the intensity and frequency of extreme drought events with important negative impacts on forest functioning. Predicting these impacts constitutes a crucial challenge for forest managers and for the maintenance of ecosystem services supply. Promoting mixed stands seems a promising strategy for adapting forest ecosystems to ongoing climate change. However, some uncertainty exists regarding whether admixture can improve growth resilience to extreme drought events. Here, we aim to assess tree growth response to drought in mixed and monospecific stands of Pinus sylvestris L. and Quercus pyrenaica Willd. in central Spain. We built tree-ring chronologies and evaluated tree growth sensitivity to water availability and growth resilience components to extreme droughts using linear mixed models. We found contrasting species- and climate-specific responses to admixture. Q. pyrenaica growth was significantly higher in mixed than in monospecific stands, especially in years without water limitations, while P. sylvestris showed higher growth in mixed stands under dry conditions. However, our results showed a species-specific trade-off between resistance and recovery. While P. sylvestris showed higher resistance but lower recovery to drought events in mixed than monospecific stands, Q. pyrenaica showed higher recovery but lower resistance. This trade-off might explain the absence of admixture effects on species resilience. Our results highlight the importance of considering species-specific responses to water availability and associated trade-offs when evaluating admixture effects on drought vulnerability. Overall, we show a positive effect of admixture on the long-term growth stability in response to average climate conditions, but no effects in short-term resilience capacity to increasingly common extreme dry conditions. Consequently, admixture can promote forest productivity stability but should be carefully considered as a management solution for promoting the resilience of Mediterranean mountain forests to increasing aridity. Numéro de notice : A2021-264 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2021.118955 Date de publication en ligne : 25/01/2021 En ligne : https://doi.org/10.1016/j.foreco.2021.118955 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97316 [article]

Early detection of forest stress from European spruce bark beetle attack, and a new vegetation index: Normalized distance red & SWIR (NDRS) / Langning Huo in Remote sensing of environment, Vol 255 (March 2021)  

Public [article]  inRemote sensing of environment > Vol 255 (March 2021) . - n° 112240 Titre : Early detection of forest stress from European spruce bark beetle attack, and a new vegetation index: Normalized distance red & SWIR (NDRS) Type de document : Article/Communication Auteurs : Langning Huo, Auteur ; Henrik J. Persson, Auteur ; Eva Lindberg, Auteur Année de publication : 2021 Article en page(s) : n° 112240 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] bande infrarouge [Termes IGN] écho radar [Termes IGN] houppier [Termes IGN] image Sentinel-MSI [Termes IGN] image Sentinel-SAR [Termes IGN] indice de stress [Termes IGN] indice de végétation [Termes IGN] insecte nuisible [Termes IGN] maladie parasitaire [Termes IGN] Picea mariana [Termes IGN] Scolytinae [Termes IGN] signature spectrale [Termes IGN] Suède [Termes IGN] vulnérabilité Résumé : (auteur) The European spruce bark beetle (Ips typographus [L.]) is one of the most damaging pest insects of European spruce forests. A crucial measure in pest control is the removal of infested trees before the beetles leave the bark, which generally happens before the end of June. However, stressed tree crowns do not show any significant color changes in the visible spectrum at this early-stage of infestation, making early detection difficult. In order to detect the related forest stress at an early stage, we investigated the differences in radar and spectral signals of healthy and stressed trees. How the characteristics of stressed trees changed over time was analyzed for the whole vegetation season, which covered the period before attacks (April), early-stage infestation (‘green-attacks’, May to July), and middle to late-stage infestation (August to October). The results show that spectral differences already existed at the beginning of the vegetation season, before the attacks. The spectral separability between the healthy and infested samples did not change significantly during the ‘green-attack’ stage. The results indicate that the trees were stressed before the attacks and had spectral signatures that differed from healthy ones. These stress-induced spectral changes could be more efficient indicators of early infestations than the ‘green-attack’ symptoms. In this study we used Sentinel-1 and 2 images of a test site in southern Sweden from April to October in 2018 and 2019. The red and SWIR bands from Sentinel-2 showed the highest separability of healthy and stressed samples. The backscatter from Sentinel-1 and additional bands from Sentinel-2 contributed only slightly in the Random Forest classification models. We therefore propose the Normalized Distance Red & SWIR (NDRS) index as a new index based on our observations and the linear relationship between the red and SWIR bands. This index identified stressed forest with accuracies from 0.80 to 0.88 before the attacks, from 0.80 to 0.82 in the early-stage infestation, and from 0.81 to 0.91 in middle- and late-stage infestations. These accuracies are higher than those attained by established vegetation indices aimed at ‘green-attack’ detection, such as the Normalized Difference Water Index, Ratio Drought Index, and Disease Stress Water Index. By using the proposed method, we highlight the potential of using NDRS with Sentinel-2 images to estimate forest vulnerability to European spruce bark beetle attacks early in the vegetation season. Numéro de notice : A2021-190 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2020.112240 Date de publication en ligne : 20/01/2021 En ligne : https://doi.org/10.1016/j.rse.2020.112240 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97111 [article]

Terrestrial laser scanning intensity captures diurnal variation in leaf water potential / S. Junttila in Remote sensing of environment, Vol 255 (March 2021)  

Public [article]  inRemote sensing of environment > Vol 255 (March 2021) . - n° 112274 Titre : Terrestrial laser scanning intensity captures diurnal variation in leaf water potential Type de document : Article/Communication Auteurs : S. Junttila, Auteur ; T. Hölttä, Auteur ; Eetu Puttonen, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 112274 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] Betula (genre) [Termes IGN] diagnostic foliaire [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] dynamique de la végétation [Termes IGN] Pinus sylvestris [Termes IGN] sécheresse [Termes IGN] semis de points [Termes IGN] stress hydrique [Termes IGN] teneur en eau de la végétation [Termes IGN] variation diurne Résumé : (auteur) During the past decades, extreme events have become more prevalent and last longer, and as a result drought-induced plant mortality has increased globally. Timely information on plant water dynamics is essential for understanding and anticipating drought-induced plant mortality. Leaf water potential (ΨL), which is usually measured destructively, is the most common metric that has been used for decades for measuring water stress. Remote sensing methods have been developed to obtain information on water dynamics from trees and forested landscapes. However, the spatial and temporal resolutions of the existing methods have limited our understanding of the water dynamics and diurnal variation of ΨL within single trees. Thus, we investigated the capability of terrestrial laser scanning (TLS) intensity in observing diurnal variation in ΨL during a 50-h monitoring period. We aimed to improve the understanding on how large a part of the diurnal variation in ΨL can be captured using TLS intensity observations. We found that TLS intensity at the 905 nm wavelength measured from a static position was able to explain 77% of the variation in ΨL for three trees of two tree species with a root mean square error of 0.141 MPa. Based on our experiment with three trees, a time series of TLS intensity measurements can be used in detecting changes in ΨL, and thus it is worthwhile to expand the investigations to cover a wider range of tree species and forests and further increase our understanding of plant water dynamics at wider spatial and temporal scales. Numéro de notice : A2021-192 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2020.112274 Date de publication en ligne : 14/01/2021 En ligne : https://doi.org/10.1016/j.rse.2020.112274 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97113 [article]

Analysis of plot-level volume increment models developed from machine learning methods applied to an uneven-aged mixed forest / Seyedeh Kosar Hamidi in Annals of Forest Science, vol 78 n° 1 (March 2021)  

Public [article]  inAnnals of Forest Science > vol 78 n° 1 (March 2021) . - n° 4 Titre : Analysis of plot-level volume increment models developed from machine learning methods applied to an uneven-aged mixed forest Type de document : Article/Communication Auteurs : Seyedeh Kosar Hamidi, Auteur ; Eric K. Zenner, Auteur ; Mahmoud Bayat, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 4 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Acer velutinum [Termes IGN] Alnus cordata [Termes IGN] analyse comparative [Termes IGN] apprentissage automatique [Termes IGN] Carpinus betulus [Termes IGN] classification barycentrique [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] classification par réseau neuronal [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] dynamique de la végétation [Termes IGN] écosystème forestier [Termes IGN] Fagus orientalis [Termes IGN] forêt inéquienne [Termes IGN] inventaire forestier étranger (données) [Termes IGN] Iran [Termes IGN] modèle de croissance végétale [Termes IGN] modèle de simulation [Termes IGN] peuplement mélangé [Termes IGN] régression linéaire [Termes IGN] volume en bois [Vedettes matières IGN] Sylviculture Résumé : (auteur) Key message: We modeled 10-year net stand volume growth with four machine learning (ML) methods, i.e., artificial neural networks (ANN), support vector machines (SVM), random forests (RF), and nearest neighbor analysis (NN), and with linear regression analysis. Incorporating interactions of multiple variables, the ML methods ANN and SVM predicted nonlinear system behavior and unraveled complex relations with greater accuracy than regression analysis. Context: Investigating the quantitative and qualitative characteristics of short-term forest dynamics is essential for testing whether the desired goals in forest-ecosystem conservation and restoration are achieved. Inventory data from the Jojadeh section of the Farim Forest located in the uneven-aged, mixed Hyrcanian Forest were used to model and predict 10-year net annual stand volume increment with new machine learning technologies. Aims: The main objective of this study was to predict net annual stand volume increment as the preeminent factor of forest growth and yield models. Methods: In the current study, volume increment was modeled from two consecutive inventories in 2003 and 2013 using four machine learning techniques that used physiographic data of the forest as input for model development: (i) artificial neural networks (ANN), (ii) support vector machines (SVM), (iii) random forests (RF), and (iv) nearest neighbor analysis (NN). Results from the various machine learning technologies were compared against results produced with regression analysis. Results: ANNs and SVMs with a linear kernel function that incorporated field-measurements of terrain slope and aspect as input variables were able to predict plot-level volume increment with a greater accuracy (94%) than regression analysis (87%). Conclusion: These results provide compelling evidence for the added utility of machine learning technologies for modeling plot-level volume increment in the context of forest dynamics and management. Numéro de notice : A2021-071 Affiliation des auteurs : non IGN Thématique : FORET/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-020-01011-6 Date de publication en ligne : 12/01/2021 En ligne : https://doi.org/10.1007/s13595-020-01011-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96794 [article]

Comparison of two parameter recovery methods for the transformation of Pinus sylvestris yield tables into a diameter distribution model / Francisco Mauro in Annals of Forest Science, vol 78 n° 1 (March 2021)  

Public [article]  inAnnals of Forest Science > vol 78 n° 1 (March 2021) . - n° 12 Titre : Comparison of two parameter recovery methods for the transformation of Pinus sylvestris yield tables into a diameter distribution model Type de document : Article/Communication Auteurs : Francisco Mauro, Auteur ; Antonio Garcia-Abril, Auteur ; Esperanza Ayuga-Téllez, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 12 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse comparative [Termes IGN] croissance des arbres [Termes IGN] densité de la végétation [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] diamètre des arbres [Termes IGN] distribution spatiale [Termes IGN] Espagne [Termes IGN] Pinus sylvestris [Termes IGN] structure d'un peuplement forestier [Vedettes matières IGN] Sylviculture Résumé : (auteur) Key message: We successfully transformed Pinus sylvestris yield tables into diameter distribution models. The best results were obtained with the parameter recovery method based on both mean and quadratic mean diameter, which explained 70% of the variability of frequencies by diameter classes and provided better results in the analysis of errors. On the other hand, the method based on stand density, dominant diameter and quadratic mean diameter explained less variability of frequencies by diameter classes (64.4%). Context: Old datasets used to develop yield table models can be recovered to transform those yield tables into diameter distribution models that provide a more detailed description of size variability and forest structure. Methods: We compared two different parameter recovery methods, one based on both mean and quadratic mean diameter and another one based on dominant diameter, stand density and quadratic mean diameter and used a set of 104 even aged plots to analyze the performance of the said methods for the transformation of Pinus sylvestris L yield tables in central Spain into a diameter distribution model. Results: The parameter recovery method based on both mean and quadratic mean diameter explained 70% of the variability of frequencies by diameter classes and provided better results than the method based on stand density, dominant diameter and quadratic mean diameter that explained 64.4% of the variability of frequencies by diameter classes. However, more important than the method itself were the errors that propagated from the models predicting the different variables used in the parameter recovery. Conclusion: Based on the results from the analysis of errors by diameter classes, the method using both mean and quadratic mean diameter outperformed the method using dominant diameter, stand density and quadratic mean diameter and is the best option to transform P. sylvestris yield tables into diameter distribution models. Numéro de notice : A2021-164 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-021-01028-5 Date de publication en ligne : 28/01/2021 En ligne : https://doi.org/10.1007/s13595-021-01028-5 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97094 [article]

European beech leads to more bioactive humus forms but stronger mineral soil acidification as Norway spruce and Scots pine – Results of a repeated site assessment after 63 and 82 years of forest conversion in Central Germany / Florian Achilles in Forest ecology and management, vol 483 ([01/03/2021])  

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How to accelerate the germination of Scots pine and Norway spruce seeds? / Kateřina Houšková in Journal of forest science, vol 67 n° 3 (March 2021)  

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Is the seasonal variation in frost resistance and plant performance in four oak species affected by changing temperatures? / Maggie Preißer in Forests, vol 12 n° 3 (March 2021)  

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Keeping mixtures of Norway spruce and birch in production forests: insights from survey data / Emma Hölmstrom in Scandinavian journal of forest research, vol 36 n° 2-3 ([01/03/2021])  

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Modeling size-density trajectories of even-aged ash (Fraxinus excelsior L.) stands in France. A baseline to assess the impact of Chalara ash dieback / Noël Le Goff in Annals of Forest Science, vol 78 n° 1 (March 2021)  

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Search for top‐down and bottom‐up drivers of latitudinal trends in insect herbivory in oak trees in Europe / Elena Valdés-Correcher in Global ecology and biogeography, vol 30 n° 3 (March 2021)  

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Secondary metabolites in leaves of hybrid aspen are affected by the competitive status and early thinning in dense coppices / Linda Rusalepp in Annals of Forest Science, vol 78 n° 1 (March 2021)  

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Variations in temperate forest biomass ratio along three environmental gradients are dominated by interspecific differences in wood density / Baptiste Kerfriden in Plant ecology, vol 222 n° 3 (March 2021)  

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Contrasting responses of habitat conditions and insect biodiversity to pest- or climate-induced dieback in coniferous mountain forests / Jérémy Cours in Forest ecology and management, vol 482 ([15/02/2021])  

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Modelling potential density of natural regeneration of European oak species (Quercus robur L., Quercus petraea (Matt.) Liebl.) depending on the distance to the potential seed source: Methodological approach for modelling dispersal from inventory data at forest enterprise level / Maximilian Axer in Forest ecology and management, vol 482 ([15/02/2021])  

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An evaluation of multi-species empirical tree mortality algorithms for dynamic vegetation modelling / Timothy Thrippleton in Scientific reports, vol 11 (2021)  

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Developing a site index model for P. Pinaster stands in NW Spain by combining bi-temporal ALS data and environmental data / Juan Guerra-Hernández in Forest ecology and management, vol 481 (February 2021)  

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Effects of thinning practice, high pruning and slash management on crop tree and stand growth in young even-aged stands of planted silver birch (Betula pendula Roth) / Jens Peter Skovsgaard in Forests, vol 12 n° 2 (February 2021)  

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Long-term tree species population dynamics in Swiss forest reserves influenced by forest structure and climate / Amanda S. Mathys in Forest ecology and management, vol 481 (February 2021)  

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Pure and even-aged forestry of fast growing conifers under climate change: on the need of a silvicultural paradigm shift / Clémentine Ols in Environmental Research Letters, vol 16 n° 2 (February 2021)    

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Spruce budworm tree host species distribution and abundance mapping using multi-temporal Sentinel-1 and Sentinel-2 satellite imagery / Rajeev Bhattarai in ISPRS Journal of photogrammetry and remote sensing, vol 172 (February 2021)  

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Individual tree diameter growth modeling system for Dalat pine (Pinus dalatensis Ferré) of the upland mixed tropical forests / Bao Huy in Forest ecology and management, vol 480 (15 January 2021)  

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Applications of remote sensing data in mapping of forest growing stock and biomass / Jose Aranha (2021)  

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Apports des méthodes d'apprentissage profond pour la reconnaissance automatique des modes d'occupation des sols et d'objets par télédétection en milieu tropical / Guillaume Rousset (2021)  

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Automated detection of individual Juniper tree location and forest cover changes using Google Earth Engine / Sudeera Wickramarathna in Annals of forest research, vol 64 n° 1 (2021)  

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Diagnostics of Plant Diseases / Dmitry Kurouski (2021)  

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Diurnal cycles of C-band temporal coherence and backscattering coefficient over an olive orchard in a semi-arid area: Comparison of in situ and Sentinel-1 radar observations / Adnane Chakir (2021)  

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Effects of different site preparation methods on the root development of planted Quercus petraea and Pinus nigra / Mathieu Dassot in New forests, vol 52 n° 1 (January 2021)  

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Ensemble learning methods on the space of covariance matrices : application to remote sensing scene and multivariate time series classification / Sara Akodad (2021)  

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Examining the effectiveness of Sentinel-1 and 2 imagery for commercial forest species mapping / Mthembeni Mngadi in Geocarto international, vol 36 n° 1 ([01/01/2021])  

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Forest biomass / Ana Cristina Goncalves (2021)  

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From local to global: A transfer learning-based approach for mapping poplar plantations at national scale using Sentinel-2 / Yousra Hamrouni in ISPRS Journal of photogrammetry and remote sensing, vol 171 (January 2021)  

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Genome-wide evolutionary response of European oaks since the Little Ice Age / Dounia Saleh (2021)  

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Interactions between oak and cervids during the process of forest regeneration / Julien Barrere (2021)  

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Investigation of Sentinel-1 time series for sensitivity to fern vegetation in an European temperate forest / Marlin Mueller (2021)  

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Is Xylella fastidiosa a serious threat to European forests? / Marie-Laure Desprez-Loustau in Forestry, an international journal of forest research, vol 94 n° 1 (January 2021)  

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Norway spruce seedlings from an Eastern Baltic provenance show tolerance to simulated drought / Roberts Matisons in Forests, vol 12 n° 1 (January 2021)  

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Range-wide demographic patterns in European forests along climatic marginality gradients : An approach using national forest inventories / Alexandre Changenet (2021)  

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Soil biodiversity as affected by different thinning intensities in a pinus laricio stand of Calabrian Apennine, South Italy / Adele Muscolo in Forests, vol 12 n° 1 (January 2021)  

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Spatial characterization and distribution modelling of Ensete ventricosum (wild and cultivated) in Ethiopia / Meron Awoke Eshetae in Geocarto international, vol 36 n° 1 ([01/01/2021])  

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Sylviculture / Ana Cristina Goncalves (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 ([01/01/2021])  

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The strong and the stronger: The effects of increasing ozone and nitrogen dioxide concentrations in pollen of different forest species / Sónia Pereira in Forests, vol 12 n° 1 (January 2021)  

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Threat degree classification according to habitat quality: A case study from the Czech Republic / Pavel Lustyk in Forests, vol 12 n° 1 (January 2021)  

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Topographic, edaphic and climate influences on aspen (Populus tremuloides) drought stress on an intermountain bunchgrass prairie / Andrew Neary in Forest ecology and management, vol 479 ([01/01/2021])  

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Turgor – a limiting factor for radial growth in mature conifers along an elevational gradient / Richard L. Peters in New phytologist, vol 229 n° 1 (January 2021)  

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Climate sensitive single tree growth modeling using a hierarchical Bayes approach and integrated nested Laplace approximations (INLA) for a distributed lag model / Arne Nothdurft in Forest ecology and management, vol 478 ([15/12/2020])  

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Comparison of spatially and nonspatially explicit nonlinear mixed effects models for Norway spruce individual tree growth under single-tree selection / Simone Bianchi in Forests, vol 11 n° 12 (December 2020)  

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Competition overrides climate as trigger of growth decline in a mixed Fagaceae Mediterranean rear-edge forest / Alvaro Rubio-Cuadrado in Annals of Forest Science, vol 77 n° 4 (December 2020)  

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Does recent fire activity impact fire-related traits of Pinus halepensis Mill. and Pinus sylvestris L. in the French Mediterranean area? / Bastien Romero in Annals of Forest Science, vol 77 n° 4 (December 2020)  

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