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Evaluation of the mixed-effects model and quantile regression approaches for predicting tree height in larch (Larix olgensis) plantations in northeastern China / Longfei Xie in Canadian Journal of Forest Research, Vol 52 n° 3 (March 2022)  

Public [article]  inCanadian Journal of Forest Research > Vol 52 n° 3 (March 2022) . - pp 309 - 319 Titre : Evaluation of the mixed-effects model and quantile regression approaches for predicting tree height in larch (Larix olgensis) plantations in northeastern China Type de document : Article/Communication Auteurs : Longfei Xie, Auteur ; Faris Rafi Almay Widagdo, Auteur ; Zheng Miao, Auteur ; Lihu Dong, Auteur ; Fengri Li, Auteur Année de publication : 2022 Article en page(s) : pp 309 - 319 Note générale : bibliographie Langues : Français (fre) Anglais (eng) Descripteur : [Vedettes matières IGN] Statistiques [Termes IGN] biométrie [Termes IGN] Chine [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] hauteur des arbres [Termes IGN] Larix olgensis [Termes IGN] modèle de croissance végétale [Termes IGN] modèle de simulation [Termes IGN] régression non linéaire [Termes IGN] régression par quantile Résumé : (auteur) Tree height (H) is one of the most important tree variables and is widely used in growth and yield models, and its measurement is often time-consuming and costly. Hence, height–diameter (H–D) models have become a great alternative, providing easy-to-use and accurate tools for H prediction. In this study, H–D models were developed for Larix olgensis A. Henry in northeastern China. The Chapman–Richards function with three predictors (diameter at breast height, dominant tree height, and relative size of individual trees) performed best. Nonlinear mixed-effects (NLME) models and nonlinear quantile regressions (NQR9, nine quantiles; NQR5, five quantiles; and NQR3, three quantiles) were further used and improved the generalized H–D model, successfully providing accurate H predictions. In addition, the H predictions were calibrated using several measurements from subsamples, which were obtained from different sampling designs and sizes. The results indicated that the predictive accuracy was higher when calibrated by using any number of height measurements for the NLME model and more than three height measurements for the NQR3, NQR5, and NQR9 models. The best sampling strategy for the NLME and NQR models involved sampling medium-sized trees. Overall, the newly developed H–D models can provide highly accurate height predictions for L. olgensis. Numéro de notice : A2022-313 Affiliation des auteurs : non IGN Autre URL associée : Draft Thématique : FORET/MATHEMATIQUE Nature : Article DOI : 10.1139/cjfr-2021-0184 En ligne : https://doi.org/10.1139/cjfr-2021-0184 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100412 [article]

Evolution de la ressource et de la production des chênes pubescent, pédonculé et sessile / Ingrid Bonhême in Forêt entreprise, n° 261 (novembre-décembre 2021)

Public [article]  inForêt entreprise > n° 261 (novembre-décembre 2021) . - pp 22 - 26 Titre : Evolution de la ressource et de la production des chênes pubescent, pédonculé et sessile Type de document : Article/Communication Auteurs : Ingrid Bonhême , Auteur ; Clémentine Ols , Auteur Année de publication : 2022 Article en page(s) : pp 22 - 26 Langues : Français (fre) Descripteur : [Termes IGN] analyse diachronique [Termes IGN] changement climatique [Termes IGN] croissance végétale [Termes IGN] inventaire forestier national (données France) [Termes IGN] Loire (bassin) [Termes IGN] Quercus pedunculata [Termes IGN] Quercus pubescens [Termes IGN] Quercus sessiliflora [Termes IGN] ressources forestières [Termes IGN] surface terrière [Termes IGN] volume en bois [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Les données de l’Inventaire forestier national de l’IGN montrent une augmentation en surface terrière et en volume des trois chênes entre 1987 et 2014 : la part relative du pubescent est à la hausse, celle du sessile est à la baisse et celle du pédonculé est stable. Le nombre de tiges du sessile et du pédonculé est en baisse, en particulier dans les petites classes de diamètre ; leur augmentation en volume est liée à un grossissement des bois. Le chêne pubescent présente une dynamique différente, avec une augmentation du nombre de tiges dans toutes les classes de diamètre, en particulier dans les petites classes. L’étude de leur accroissement radial montre un ralentissement de la production pour les chênes sessile et pédonculé et un maintien de production pour le pubescent, qui reste néanmoins le moins productif des trois. Numéro de notice : A2021-976 Affiliation des auteurs : IGN (2020- ) Thématique : FORET Nature : Article nature-HAL : ArtSansCL DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100620 [article]

Exemplaires (1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
IFN-001-P002294	PER	Revue	Nogent-sur-Vernisson	Salle périodiques	Exclu du prêt

Unexpected negative effect of available water capacity detected on recent conifer forest growth trends across wide environmental gradients / Clémentine Ols in Ecosystems, vol 25 n° 2 (March 2022)  

Public [article]  inEcosystems > vol 25 n° 2 (March 2022) . - pp 404 - 421 Titre : Unexpected negative effect of available water capacity detected on recent conifer forest growth trends across wide environmental gradients Type de document : Article/Communication Auteurs : Clémentine Ols , Auteur ; Thomas Gschwantner, Auteur ; Klemens Schadauer, Auteur ; Jean-Daniel Bontemps , Auteur Année de publication : 2022 Projets : ARBRE / AgroParisTech, LUE / Université de Lorraine Article en page(s) : pp 404 - 421 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Abies alba [Termes IGN] analyse diachronique [Termes IGN] Autriche [Termes IGN] cerne [Termes IGN] changement climatique [Termes IGN] croissance des arbres [Termes IGN] gradient d'altitude [Termes IGN] hétérogénéité environnementale [Termes IGN] inventaire forestier étranger (données) [Termes IGN] inventaire forestier national (données France) [Termes IGN] Larix decidua [Termes IGN] modèle de croissance végétale [Termes IGN] Picea abies [Termes IGN] Pinus sylvestris [Termes IGN] ressources en eau [Termes IGN] structure d'un peuplement forestier [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) National Forest Inventories (NFIs) perform systematic forest surveys across space and time. They are hence powerful tools to understand climate controls on forest growth at wide geographical scales and account for the effects of local abiotic and biotic interactions. To investigate the effects of climate change upon growth dynamics of four major European conifer species along elevation and continentality gradients, we herein provide an original harmonization of the French and Austrian NFI datasets. The growth of Norway spruce, Scots pine, silver fir and European larch over the 1996–2016 period was studied in pure and even-aged plots across different ecological regions. We derived climate-driven growth trends from > 65, 000 radial increment series filtered out from major biotic and abiotic influences using statistical modeling. We further identified primary environmental drivers of conifer growth by regressing growth trends against regionally aggregated biotic and abiotic forest attributes. Negative growth trends were observed in continental regions undergoing the most rapid warming and thermal amplitude contraction over the study period. Negative trends were also associated with lower forest structural heterogeneity and, surprisingly, with greater available water capacity. Remarkably, we observed these associations both at the inter- and intra-species levels, suggesting the universality of these primary growth determinants. Our study shows that harmonized NFI data at the transnational level provide reliable information on climate–growth interactions. Here, greater forest structural complexity and greater water resource limitation were highlighted as drivers of greater forest resilience to climate change at large-scale. This result forms crucial bases to implementing climate-smart forest management. Numéro de notice : A2022-023 Affiliation des auteurs : LIF+Ext (2020- ) Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10021-021-00663-3 En ligne : https://doi.org/10.1007/s10021-021-00663-3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98116 [article]

Multi-species individual tree segmentation and identification based on improved mask R-CNN and UAV imagery in mixed forests / Chong Zhang in Remote sensing, vol 14 n° 4 (February-2 2022)  

Public [article]  inRemote sensing > vol 14 n° 4 (February-2 2022) . - n° 874 Titre : Multi-species individual tree segmentation and identification based on improved mask R-CNN and UAV imagery in mixed forests Type de document : Article/Communication Auteurs : Chong Zhang, Auteur ; Jiawei Zhou, Auteur ; Huiwen Wang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 874 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] Chine [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] détection de contours [Termes IGN] échantillonnage de données [Termes IGN] entropie [Termes IGN] estimation quantitative [Termes IGN] feuillu [Termes IGN] hauteur des arbres [Termes IGN] image captée par drone [Termes IGN] peuplement mélangé [Termes IGN] Pinophyta [Termes IGN] segmentation d'image Résumé : (auteur) High-resolution UAV imagery paired with a convolutional neural network approach offers significant advantages in accurately measuring forestry ecosystems. Despite numerous studies existing for individual tree crown delineation, species classification, and quantity detection, the comprehensive situation in performing the above tasks simultaneously has rarely been explored, especially in mixed forests. In this study, we propose a new method for individual tree segmentation and identification based on the improved Mask R-CNN. For the optimized network, the fusion type in the feature pyramid network is modified from down-top to top-down to shorten the feature acquisition path among the different levels. Meanwhile, a boundary-weighted loss module is introduced to the cross-entropy loss function Lmask to refine the target loss. All geometric parameters (contour, the center of gravity and area) associated with canopies ultimately are extracted from the mask by a boundary segmentation algorithm. The results showed that F1-score and mAP for coniferous species were higher than 90%, and that of broadleaf species were located between 75%–85.44%. The producer’s accuracy of coniferous forests was distributed between 0.8–0.95 and that of broadleaf ranged in 0.87–0.93; user’s accuracy of coniferous was distributed between 0.81–0.84 and that of broadleaf ranged in 0.71–0.76. The total number of trees predicted was 50,041 for the entire study area, with an overall error of 5.11%. The method under study is compared with other networks including U-net and YOLOv3. Results in this study show that the improved Mask R-CNN has more advantages in broadleaf canopy segmentation and number detection. Numéro de notice : A2022-168 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/rs14040874 Date de publication en ligne : 11/02/2022 En ligne : https://doi.org/10.3390/rs14040874 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99793 [article]

Scorch height and volume modeling in prescribed fires: Effects of canopy gaps in Pinus pinaster stands in Southern Europe / J.R. Molina in Forest ecology and management, vol 506 (February-15 2022)  

Public [article]  inForest ecology and management > vol 506 (February-15 2022) . - n° 119979 Titre : Scorch height and volume modeling in prescribed fires: Effects of canopy gaps in Pinus pinaster stands in Southern Europe Type de document : Article/Communication Auteurs : J.R. Molina, Auteur ; M. Ortega, Auteur ; F. Rodríguez y Silva, Auteur Année de publication : 2022 Article en page(s) : n° 119979 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] brûlis [Termes IGN] canopée [Termes IGN] échantillonnage de données [Termes IGN] Espagne [Termes IGN] gestion des risques [Termes IGN] gestion forestière [Termes IGN] incendie de forêt [Termes IGN] Pinus pinaster [Vedettes matières IGN] Foresterie Résumé : (auteur) The use of prescribed fire has been on the rise in recent years owing to its effectiveness in surface fuel reduction, its implementation cost, and the possibility of firefighter training. However, greater knowledge regarding the effects of fire on woodlands is required by forest managers. Scorch height and scorch volume are the most widely used variables for evaluating the effects of burning on trees. This study proposes a scorch height model for the prescribed fires of pine stands in Southern Europe. Although the two main variables of the existing models (fire-line intensity and air temperature) were considered, our model achieved a coefficient of determination of 89% with the incorporation of the canopy base height. A decision tree for scorch volume was also developed using the three independent variables. The presence of canopy gaps in the lower, mid-, and upper slopes resulted in significant differences in the scorch height. The scorch height increased between 0.33 m and 2.08 m because of the canopy gaps in the upper slope. These findings can play an important role in the implementation and improvement of prescribed burn windows. Numéro de notice : A2022-058 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2021.119979 Date de publication en ligne : 24/12/2021 En ligne : https://doi.org/10.1016/j.foreco.2021.119979 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99469 [article]

A stand-level growth and yield model for thinned and unthinned even-aged Scots pine forests in Norway / Christian Kuehne in Silva fennica, vol 56 n° 1 (January 2022)  

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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)  

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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)  

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Deriving a tree growth model from any existing stand growth model / Quang V. Cao in Canadian Journal of Forest Research, Vol 52 n° 2 (February 2022)  

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European-wide forest monitoring substantiate the neccessity for a joint conservation strategy to rescue European ash species (Fraxinus spp.) / Jan-Peter George in Scientific reports, vol 12 (2022)  

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Five decades of ground flora changes in a temperate forest: The good, the bad and the ambiguous in biodiversity terms / K.J. Kirby in Forest ecology and management, vol 505 (February-1 2022)  

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Genome-wide evolutionary response of European oaks during the Anthropocene / Dounia Saleh in Evolution letters, vol 6 n° 1 (February 2022)  

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Integrating terrestrial laser scanning and unmanned aerial vehicle photogrammetry to estimate individual tree attributes in managed coniferous forests in Japan / Katsuto Shimizu in International journal of applied Earth observation and geoinformation, vol 106 (February 2022)  

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Mapping abundance distributions of allergenic tree species in urbanized landscapes: A nation-wide study for Belgium using forest inventory and citizen science data / Sébastien Dujardin in Landscape and Urban Planning, vol 218 (February 2022)  

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Survival 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)  

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