Centre de documentation
scientifique

Chilling and forcing temperatures interact to predict the onset of wood formation in Northern Hemisphere conifers / Nicolas Delpierre in Global change biology, vol 25 n° 3 (March 2019)    

Public [article]  inGlobal change biology > vol 25 n° 3 (March 2019) . - pp 1089 - 1105 Titre : Chilling and forcing temperatures interact to predict the onset of wood formation in Northern Hemisphere conifers Type de document : Article/Communication Auteurs : Nicolas Delpierre, Auteur ; Ségolène Lireux, Auteur ; Florian Hartig, Auteur ; J. Julio Camarero, Auteur ; Alissar Cheaib, Auteur ; Katarina Čufar, Auteur ; Henri E. Cuny , Auteur ; Annie Deslauriers, Auteur ; Patrick Fonti, Auteur ; et al., Auteur Année de publication : 2019 Projets : ARBRE / AgroParisTech (2007 -) Article en page(s) : pp 1089 - 1105 Note générale : bibliographie Funding information : notamment Agence Nationale de la Recherche. Grant Number: ANR‐11‐LABX‐0002‐01, Lab of Excellence ARBRE GIP‐ECOFOR. Grant Number: SACROBOQUE 2016.013 Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung. Grant Number: INTEGRAL‐121859, LOTFOR‐150205 French National Research Agency. Grant Numbers: ANR‐11‐LABX‐0002‐01, LOTFOR‐150205 Langues : Anglais (eng) Descripteur : [Termes IGN] analyse comparative [Termes IGN] Canada [Termes IGN] Europe (géographie politique) [Termes IGN] forêt boréale [Termes IGN] forêt tempérée [Termes IGN] formation du bois [Termes IGN] hémisphère Nord [Termes IGN] inférence statistique [Termes IGN] Larix decidua [Termes IGN] phénologie [Termes IGN] Picea abies [Termes IGN] Picea mariana [Termes IGN] Pinophyta [Termes IGN] Pinus sylvestris [Termes IGN] température au sol [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) The phenology of wood formation is a critical process to consider for predicting how trees from the temperate and boreal zones may react to climate change. Compared to leaf phenology, however, the determinism of wood phenology is still poorly known. Here, we compared for the first time three alternative ecophysiological model classes (threshold models, heat‐sum models and chilling‐influenced heat‐sum models) and an empirical model in their ability to predict the starting date of xylem cell enlargement in spring, for four major Northern Hemisphere conifers (Larix decidua, Pinus sylvestris, Picea abies and Picea mariana). We fitted models with Bayesian inference to wood phenological data collected for 220 site‐years over Europe and Canada. The chilling‐influenced heat‐sum model received most support for all the four studied species, predicting validation data with a 7.7‐day error, which is within one day of the observed data resolution. We conclude that both chilling and forcing temperatures determine the onset of wood formation in Northern Hemisphere conifers. Importantly, the chilling‐influenced heat‐sum model showed virtually no spatial bias whichever the species, despite the large environmental gradients considered. This suggests that the spring onset of wood formation is far less affected by local adaptation than by environmentally driven plasticity. In a context of climate change, we therefore expect rising winter–spring temperature to exert ambivalent effects on the spring onset of wood formation, tending to hasten it through the accumulation of forcing temperature, but imposing a higher forcing temperature requirement through the lower accumulation of chilling. Numéro de notice : A2019-646 Affiliation des auteurs : IGN+Ext (2012-2019) Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/gcb.14539 Date de publication en ligne : 09/12/2018 En ligne : https://doi.org/10.1111/gcb.14539 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96894 [article]

Documents numériques

peut être téléchargé Chilling and forcing temperatures interact - préprint Adobe Acrobat PDF

Estimating over- and understorey canopy density of temperate mixed stands by airborne LiDAR data / Hooman Latifi in Forestry, an international journal of forest research, vol 89 n° 1 (January 2016)  

Public [article]  inForestry, an international journal of forest research > vol 89 n° 1 (January 2016) . - pp 61 - 81 Titre : Estimating over- and understorey canopy density of temperate mixed stands by airborne LiDAR data Type de document : Article/Communication Auteurs : Hooman Latifi, Auteur ; Marco Heurich, Auteur ; Florian Hartig, Auteur ; Jorg Müller, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 61 - 81 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] Abies alba [Termes IGN] Acer pseudoplatanus [Termes IGN] Betula pendula [Termes IGN] betula pubescens [Termes IGN] canopée [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] Fagus sylvatica [Termes IGN] habitat forestier [Termes IGN] Picea abies [Termes IGN] régression [Termes IGN] sorbus aucuparia [Termes IGN] sous-bois Résumé : (auteur) Estimating forest structural attributes is one of the essential forestry-related remote sensing applications. The methods applied so far typically concentrate on the structure of the overstorey. For various conservation and management applications, however, information on lower layers is also of great interest. Detecting understorey cover by remote sensing is challenging, as passive sensors do not penetrate to the forest ground layer. An alternative to these is 3D metrics from active light detection and ranging (LiDAR). Here, we evaluate this technique for describing the vegetation density of multiple stand layers within the temperate stands of a large protected area in south-eastern Germany. We combined LiDAR metrics and information on forest habitat types with regression models to investigate LiDAR metrics that are significantly correlated with vegetation density. The top canopy and the herbal layer showed strong correlations with the applied LiDAR metrics, whereas the predictive power was lower for the intermediate stand layers. Moreover, our results suggest that the relationship between LiDAR predictors and vegetation density depends on the forest type. A comparison of the regression models with random forest predictions showed no major improvement in predictive error. In conclusion, this study highlights the value of the LiDAR metrics for characterizing the structural properties of lower forest layers, which has implications for wildlife and forest management applications, especially in protected areas. Numéro de notice : A2016--102 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1093/forestry/cpv032 En ligne : https://doi.org/10.1093/forestry/cpv032 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84668 [article]