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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, vol 79 n° 1 (2022)  

Public [article]  inAnnals of Forest Science > 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]

Combination of Sentinel-1 and Sentinel-2 data for tree species classification in a Central European biosphere reserve / Michael Lechner in Remote sensing, vol 14 n° 11 (June-1 2022)  

Public [article]  inRemote sensing > vol 14 n° 11 (June-1 2022) . - n° 2687 Titre : Combination of Sentinel-1 and Sentinel-2 data for tree species classification in a Central European biosphere reserve Type de document : Article/Communication Auteurs : Michael Lechner, Auteur ; Alena Dostalova, Auteur ; Markus Hollaus, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 2687 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte [Termes IGN] analyse comparative [Termes IGN] analyse harmonique [Termes IGN] Autriche [Termes IGN] biosphère [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] espèce végétale [Termes IGN] feuillu [Termes IGN] image Sentinel-MSI [Termes IGN] image Sentinel-SAR [Termes IGN] nébulosité [Termes IGN] phénologie [Termes IGN] Pinophyta [Termes IGN] rapport signal sur bruit [Termes IGN] réserve forestière Résumé : (auteur) Microwave and optical imaging methods react differently to different land surface parameters and, thus, provide highly complementary information. However, the contribution of individual features from these two domains of the electromagnetic spectrum for tree species classification is still unclear. For large-scale forest assessments, it is moreover important to better understand the domain-specific limitations of the two sensor families, such as the impact of cloudiness and low signal-to-noise-ratio, respectively. In this study, seven deciduous and five coniferous tree species of the Austrian Biosphere Reserve Wienerwald (105,000 ha) were classified using Breiman’s random forest classifier, labeled with help of forest enterprise data. In nine test cases, variations of Sentinel-1 and Sentinel-2 imagery were passed to the classifier to evaluate their respective contributions. By solely using a high number of Sentinel-2 scenes well spread over the growing season, an overall accuracy of 83.2% was achieved. With ample Sentinel-2 scenes available, the additional use of Sentinel-1 data improved the results by 0.5 percentage points. This changed when only a single Sentinel-2 scene was supposedly available. In this case, the full set of Sentinel-1-derived features increased the overall accuracy on average by 4.7 percentage points. The same level of accuracy could be obtained using three Sentinel-2 scenes spread over the vegetation period. On the other hand, the sole use of Sentinel-1 including phenological indicators and additional features derived from the time series did not yield satisfactory overall classification accuracies (55.7%), as only coniferous species were well separated. Numéro de notice : A2022-540 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/rs14112687 Date de publication en ligne : 03/06/2022 En ligne : https://doi.org/10.3390/rs14112687 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101103 [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]

Cartographie et caractérisation des lieux d'intérêt de cervidés en milieu forestier / Laurence Jolivet in Cartes & Géomatique, n° 247-248 (mars-juin 2022)

Public [article]  inCartes & Géomatique > n° 247-248 (mars-juin 2022) . - pp 47 - 59 Titre : Cartographie et caractérisation des lieux d'intérêt de cervidés en milieu forestier Type de document : Article/Communication Auteurs : Laurence Jolivet , Auteur ; Florian Masson, Auteur ; Sonia Saïd, Auteur Année de publication : 2022 Conférence : ICC 2021, 30th ICA international cartographic conference 14/12/2021 18/12/2021 Florence Italie Article en page(s) : pp 47 - 59 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] analyse comparative [Termes IGN] Cervidae [Termes IGN] données spatiotemporelles [Termes IGN] espèce végétale [Termes IGN] faune locale [Termes IGN] forêt tempérée [Termes IGN] gestion forestière [Termes IGN] jeu de données localisées [Termes IGN] migration animale [Termes IGN] parcelle forestière [Termes IGN] positionnement par GPS [Termes IGN] Vosges (88) Résumé : (Auteur) La faune influence son environnement spatial et cet environnement influence en retour l'utilisation de l'espace par la faune. En gestion forestière, il est nécessaire de protéger les parcelles sensibles à la pression des animaux. Notre objectif est de proposer des cartes pertinentes pour la gestion, contenant les déplacements individuels et les espaces utilisés selon les espèces animales, ainsi que leur contexte spatio-temporel. Le cas d'étude concerne deux espèces, le chevreuil et le cerf, dans un site en milieu forestier au nord-est de la France. Les déplacements de plusieurs individus ont été analysés à partir de localisations GPS. Les lieux d'intérêt pour la recherche de nourriture supposés correspondre à des comportements de recherche intensive ont été calculés par la Méthode du temps de Premier Passage. Ces lieux ont ensuite été caractérisés avec les éléments du paysage et des indications de temporalité. Des cartes ont été réalisées afin de visualiser les informations disponibles sur ces lieux d'intérêt, en définissant des symbolisations adaptées. Des cartes ont aussi été réalisées par rapport à l'espace fonctionnel comprenant des parcelles favorables ou évitées issues de la comparaison entre espace parcouru et espace disponible. Ces parcelles sont qualifiées selon un gradient d'intérêt potentiel par espèce animale. Le processus cartographique a été effectué afin d'obtenir des cartes adaptées à l'affichage dans un portail géographique numérique et à la lecture par des utilisateurs impliqués en gestion forestière et en aménagement. Numéro de notice : A2022-675 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : FORET/GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101889 [article]

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