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Climate change-induced background tree mortality is exacerbated towards the warm limits of the species ranges / Adrien Taccoen in Annals of Forest Science [en ligne], vol 79 n° 1 (2022)  

Public [article]  inAnnals of Forest Science [en ligne] > vol 79 n° 1 (2022) . - n° 23 Titre : Climate change-induced background tree mortality is exacerbated towards the warm limits of the species ranges Type de document : Article/Communication Auteurs : Adrien Taccoen, Auteur ; Christian Piedallu, Auteur ; Ingrid Seynave, Auteur ; Anne Gégout-Petit, Auteur ; Jean-Claude Gégout, Auteur Année de publication : 2022 Article en page(s) : n° 23 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] arbre mort [Termes IGN] changement climatique [Termes IGN] espèce végétale [Termes IGN] inventaire forestier national (données France) [Termes IGN] mortalité [Termes IGN] stress hydrique [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Key message : An influence of the recent changes in temperature or rainfall was demonstrated, increasing background tree mortality rates for 2/3 of the 12 studied tree species. Climate change-induced tree mortality was exacerbated towards the warm or dry limits of the species ranges, suggesting in these areas a progressive replacement by more xeric species. Context : Despite the identification of climate change effects on tree mortality in various biomes, the characterization of species-specific areas of vulnerability remains poorly understood. Aims : We sought to assess if the effects of temperature and rainfall changes on background tree mortality rates, which did not result from abrupt disturbances, were linked to climate change intensity only, or if they also depended on the tree’s location along climatic gradients. Methods : We modelled background mortality for 12 of the most common European tree species using 265,056 trees including 4384 dead trees from the French national forest inventory. To explain mortality, we considered variables linked to tree characteristics, stand attributes, logging intensity and site environmental characteristics, and climate change effects. Results : We found an influence of temperature and rainfall changes on 9 species out of 12. For 8 of them, climate change-induced tree mortality was exacerbated towards the warm or dry limits of the species ranges. Conclusion : These results highlight that tree mortality varies according to the climate change intensity and the tree location along temperature and rainfall gradients. They strengthen the poleward and upward shifts of trees forecasted from climate envelope models for a large number of European tree species. Numéro de notice : A2022-440 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1186/s13595-022-01142-y Date de publication en ligne : 30/05/2022 En ligne : http://dx.doi.org/10.1186/s13595-022-01142-y Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100773 [article]

Transfer learning from citizen science photographs enables plant species identification in UAV imagery / Salim Soltani in ISPRS Open Journal of Photogrammetry and Remote Sensing, vol 5 (August 2022)  

Public [article]  inISPRS Open Journal of Photogrammetry and Remote Sensing > vol 5 (August 2022) . - n° 100016 Titre : Transfer learning from citizen science photographs enables plant species identification in UAV imagery Type de document : Article/Communication Auteurs : Salim Soltani, Auteur ; Hannes Feilhauer, Auteur ; Robbert Duker, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 100016 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] apprentissage profond [Termes IGN] base de données naturalistes [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] distribution spatiale [Termes IGN] données localisées des bénévoles [Termes IGN] espèce végétale [Termes IGN] filtrage de la végétation [Termes IGN] identification de plantes [Termes IGN] image captée par drone [Termes IGN] orthoimage couleur [Termes IGN] science citoyenne [Termes IGN] segmentation sémantique Résumé : (auteur) Accurate information on the spatial distribution of plant species and communities is in high demand for various fields of application, such as nature conservation, forestry, and agriculture. A series of studies has shown that Convolutional Neural Networks (CNNs) accurately predict plant species and communities in high-resolution remote sensing data, in particular with data at the centimeter scale acquired with Unoccupied Aerial Vehicles (UAV). However, such tasks often require ample training data, which is commonly generated in the field via geocoded in-situ observations or labeling remote sensing data through visual interpretation. Both approaches are laborious and can present a critical bottleneck for CNN applications. An alternative source of training data is given by using knowledge on the appearance of plants in the form of plant photographs from citizen science projects such as the iNaturalist database. Such crowd-sourced plant photographs typically exhibit very different perspectives and great heterogeneity in various aspects, yet the sheer volume of data could reveal great potential for application to bird’s eye views from remote sensing platforms. Here, we explore the potential of transfer learning from such a crowd-sourced data treasure to the remote sensing context. Therefore, we investigate firstly, if we can use crowd-sourced plant photographs for CNN training and subsequent mapping of plant species in high-resolution remote sensing imagery. Secondly, we test if the predictive performance can be increased by a priori selecting photographs that share a more similar perspective to the remote sensing data. We used two case studies to test our proposed approach with multiple RGB orthoimages acquired from UAV with the target plant species Fallopia japonica and Portulacaria afra respectively. Our results demonstrate that CNN models trained with heterogeneous, crowd-sourced plant photographs can indeed predict the target species in UAV orthoimages with surprising accuracy. Filtering the crowd-sourced photographs used for training by acquisition properties increased the predictive performance. This study demonstrates that citizen science data can effectively anticipate a common bottleneck for vegetation assessments and provides an example on how we can effectively harness the ever-increasing availability of crowd-sourced and big data for remote sensing applications. Numéro de notice : A2022-488 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.ophoto.2022.100016 Date de publication en ligne : 23/05/2022 En ligne : https://doi.org/10.1016/j.ophoto.2022.100016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100956 [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]

Pourquoi la forêt française a besoin d’un traitement de fond / Guillaume Decocq in The Conversation France, vol 2022 ([10/02/2022])  

Public [article]  inThe Conversation France > vol 2022 [10/02/2022] 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 climatique Résumé : (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 [article]

Use of remotely sensed data to estimate tree species diversity as an indicator of biodiversity in Blouberg Nature Reserve, South Africa / Mangana Rampheri in Geocarto international, vol 37 n° 2 ([15/01/2022])  

Public [article]  inGeocarto international > vol 37 n° 2 [15/01/2022] . - pp 526 - 542 Titre : Use of remotely sensed data to estimate tree species diversity as an indicator of biodiversity in Blouberg Nature Reserve, South Africa Type de document : Article/Communication Auteurs : Mangana Rampheri, Auteur ; Timothy Dube, Auteur ; Inos Dhau, Auteur Année de publication : 2022 Article en page(s) : pp 526 - 542 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Afrique du sud (état) [Termes IGN] arbre (flore) [Termes IGN] bande spectrale [Termes IGN] biodiversité végétale [Termes IGN] conservation de la flore [Termes IGN] détection de changement [Termes IGN] espèce végétale [Termes IGN] image Landsat-OLI [Termes IGN] image Landsat-TM [Termes IGN] indice de végétation [Termes IGN] régression [Termes IGN] réserve naturelle Résumé : (auteur) We use remotely sensed data to estimate species diversity in Blouberg Nature Reserve (BNR) in the Limpopo province, South Africa to understand the state of biodiversity since communities’ involvement in conservation initiatives. To achieve this objective, Landsat series data collected before and after community involvement in biodiversity conservation were used in conjunction with selected diversity indices i.e., Shannon-Wiener Index (H’) and Simpson Index (D). Thirty 15 m × 15 m field plots were selected and all trees within each plot were identified, with the help of Botanists. Further, we applied regression analysis to determine the relationship between satellite derived tree species diversity and field observations. The results of the study demonstrated a significant (p  Numéro de notice : A2022-052 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET/IMAGERIE Nature : Article DOI : 10.1080/10106049.2020.1723717 Date de publication en ligne : 16/04/2020 En ligne : https://doi.org/10.1080/10106049.2020.1723717 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99443 [article]

Application of deep learning with stratified K-fold for vegetation species discrimation in a protected mountainous region using Sentinel-2 image / Efosa Gbenga Adagbasa in Geocarto international, vol 37 n° 1 ([01/01/2022])  

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Mapping temperate forest tree species using dense Sentinel-2 time series / Jan Hemmerling in Remote sensing of environment, vol 267 (December-15 2021)  

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Production potential, biodiversity and soil properties of forest reclamations: Opportunities or risk of introduced coniferous tree species under climate change? / Zdeněk Vacek in European Journal of Forest Research, vol 140 n° 5 (October 2021)  

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Classification of tree species in a heterogeneous urban environment using object-based ensemble analysis and World View-2 satellite imagery / Simbarashe Jombo in Applied geomatics, vol 13 n° 3 (September 2021)  

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Multi-task fully convolutional network for tree species mapping in dense forests using small training hyperspectral data / Laura Elena Cué La Rosa in ISPRS Journal of photogrammetry and remote sensing, vol 179 (September 2021)  

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Picea abies and Pseudotsuga menziesii radial growth in relation to climate: case study from South Bohemia / Jan Mondek in Austrian journal of forest science, vol 2021 n° 3 (2021)  

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Direct analysis in real-time (DART) time-of-flight mass spectrometry (TOFMS) of wood reveals distinct chemical signatures of two species of Afzelia / Peter Kitin in Annals of Forest Science [en ligne], vol 78 n° 2 (June 2021)  

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Provisioning forest and conservation science with high-resolution maps of potential distribution of major European tree species under climate change / Debojyoti Chakraborty in Annals of Forest Science [en ligne], vol 78 n° 2 (June 2021)  

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Shedding light on typical species: implications for habitat monitoring / Gianmaria Bonari in Plant sociology, vol 58 n° 1 ([01/02/2021])  

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Analyse de la dynamique d’embroussaillement des pelouses calcaires par traitement d’images / Théo Mesure (2021) 

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