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scientifique

Tree species growth response to climate in mixtures of Quercus robur/Quercus petraea and Pinus sylvestris across Europe - a dynamic, sensitive equilibrium / Sonja Vospernik in Forest ecology and management, vol 530 (February-15 2023)  

Public [article]  inForest ecology and management > vol 530 (February-15 2023) . - n° 120753 Titre : Tree species growth response to climate in mixtures of Quercus robur/Quercus petraea and Pinus sylvestris across Europe - a dynamic, sensitive equilibrium Type de document : Article/Communication Auteurs : Sonja Vospernik, Auteur ; Michael Heym, Auteur ; Hans Pretzsch, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 120753 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] climat [Termes IGN] croissance des arbres [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] Europe (géographie politique) [Termes IGN] évapotranspiration [Termes IGN] forêt inéquienne [Termes IGN] modèle dynamique [Termes IGN] peuplement mélangé [Termes IGN] Pinus sylvestris [Termes IGN] Quercus pedunculata [Termes IGN] Quercus sessiliflora [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Quercus robur/Quercus petraea and Pinus sylvestris are widely distributed and economically important tree species in Europe co-occurring on mesotrophic, xeric and mesic sites. Increasing dry conditions may reduce their growth, but growth reductions may be modified by mixture, competition and site conditions. The annual diameter growth in monospecific and mixed stands along an ecological gradient with mean annual temperatures ranging from 5.5 °C to 11.5 °C was investigated in this study. On 36 triplets (108 plots), trees were cored and the year-ring series were cross-dated, resulting in year-ring series of 785 and 804 trees for Q. spp. and P. sylvestris, respectively. A generalized additive model with a logarithmic link was fit to the data with random effects for the intercept at the triplet, year and tree level and a random slope for the covariate age for each tree; the Tweedie-distribution was used. The final model explained 87 % of the total variation in diameter increment for both tree species. Significant covariates were age, climate variables (long-term mean, monthly), local competition variables, relative dbh, mixture, stand structure and interactions thereof. Tree growth declined with age and local density and increased with social position. It was positively influenced by mixture and structural diversity (Gini coefficient); mixture effects were significant for P. sylvestris only. The influence of potential evapotranspiration (PET) in spring and autumn on tree growth was positive and non-linear, whereas tree growth sharply decreased with increasing PET in June, which proved to be the most influential month on tree growth along the whole ecological gradient. Interactions of PET with tree social position (relative dbh) were significant in July and September for Q. spp. and in April for P. sylvestris. Interactions of climate with density or mixture were not significant. Climatic effects found agree well with previous results from intra-annual growth studies and indicate that the model captures the causal factors for tree growth well. Furthermore, the interaction between climate and relative dbh might indicate a longer growth duration for trees of higher social classes. Analysis of random effects across time and space showed highly dynamic patterns, with competitive advantages changing annually between species and spatial patterns showing no large-scale trends but pointing to the prevalence of local site factors. In mixed-species stands, the tree species have the same competitivity in the long-term, which is modified by climate each year. Climate warming will shift the competitive advantages, but the direction will be highly site-specific. Numéro de notice : A2023-108 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2022.120753 Date de publication en ligne : 29/12/2022 En ligne : https://doi.org/10.1016/j.foreco.2022.120753 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102443 [article]

Evaluation of growth models for mixed forests used in Swedish and Finnish decision support systems / Jorge Aldea in Forest ecology and management, vol 529 (February-1 2023)  

Public [article]  inForest ecology and management > vol 529 (February-1 2023) . - n° 120721 Titre : Evaluation of growth models for mixed forests used in Swedish and Finnish decision support systems Type de document : Article/Communication Auteurs : Jorge Aldea, Auteur ; Simone Bianchi, Auteur ; Urban Nilsson, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 120721 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Betula (genre) [Termes IGN] Finlande [Termes IGN] forêt boréale [Termes IGN] inventaire forestier étranger (données) [Termes IGN] modèle de croissance végétale [Termes IGN] modèle de simulation [Termes IGN] peuplement mélangé [Termes IGN] Picea abies [Termes IGN] Pinus sylvestris [Termes IGN] Suède [Termes IGN] système d'aide à la décision [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Interest in mixed forests is increasing since they could provide higher benefits and positive externalities compared to monocultures, although their management is more complex and silvicultural prescriptions for them are still scarce. Growth simulations are a powerful tool for developing useful guidelines for mixed stands. Heureka and Motti are two decision support systems commonly used for forest management in Sweden and Finland respectively. They were developed mostly with data from pure stands, so how they would perform in mixed stands is currently uncertain. We compiled a large and updated common database of well-replicated experimental research sites and monitoring networks composed by 218 and 1,160 plot-level observations of mixed stands from Sweden and Finland, respectively. We aimed to evaluated the accuracy of Heureka and Motti basal area growth models in those mixed-species stands and to detect any bias in their short-term predictions. Basal area growth simulations (excluding mortality models) were compared to observed stand-level values in a period-wise process with update of the start values in each period. The residual plots were visually examined for different stand mixtures: Norway spruce (Picea abies Karst.)-birch (Betula spp), Scots pine (Pinus sylvestris L.)-birch and Scots pine-Norway spruce. We observed that the basal area growth models in both decision support systems performed quite well for all mixtures regardless of the proportion of species. Motti simulations overestimated growth in Scots pine-Norway spruce mixtures by 0.063 m2·ha−1·year−1 which may be acceptable for practical use. Therefore, we corroborated that both decision support systems can be currently utilized for short-term forest growth simulation of mixed boreal forests. Numéro de notice : A2023-107 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2022.120721 Date de publication en ligne : 28/12/2022 En ligne : https://doi.org/10.1016/j.foreco.2022.120721 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102441 [article]

Stochastic multicriteria acceptability analysis as a forest management priority mapping approach based on airborne laser scanning and field inventory data / Parvez Rana in Landscape and Urban Planning, vol 230 (February 2023)  

Public [article]  inLandscape and Urban Planning > vol 230 (February 2023) . - n° 104637 Titre : Stochastic multicriteria acceptability analysis as a forest management priority mapping approach based on airborne laser scanning and field inventory data Type de document : Article/Communication Auteurs : Parvez Rana, Auteur ; Jari Vauhkonen, Auteur Année de publication : 2023 Article en page(s) : n° 104637 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] aide à la décision [Termes IGN] analyse multicritère [Termes IGN] classification barycentrique [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] Finlande [Termes IGN] forêt boréale [Termes IGN] gestion forestière [Termes IGN] inventaire forestier étranger (données) [Termes IGN] Picea abies [Termes IGN] Pinus sylvestris [Termes IGN] processus stochastique [Termes IGN] semis de points [Termes IGN] service écosystémique [Termes IGN] structure d'un peuplement forestier Résumé : (auteur) The mapping of ecosystem service (ES) provisioning often lacks decision-makers’ preferences on the ESs provided. Analyzing the related uncertainties can be computationally demanding for a landscape tessellated to a large number of spatial units such as pixels. We propose stochastic multicriteria acceptability analyses to incorporate (unknown or only partially known) decision-makers’ preferences into the spatial forest management prioritization in a Scandinavian boreal forest landscape. The potential of the landscape for the management alternatives was quantified by airborne laser scanning based proxies. A nearest-neighbor imputation method was applied to provide each pixel with stochastic acceptabilities on the alternatives based on decision-makers’ preferences sampled from a probability distribution. We showed that this workflow could be used to derive two types of maps for forest use prioritization: one showing the alternative that a decision-maker with given preferences should choose and another showing areas where the suitability of the forest structure suggested different alternative than the preferences. We discuss the potential of the latter approach for mapping management hotspots. The stochastic approach allows estimating the strength of the decision with respect to the uncertainty in both the proxy values and preferences. The nearest neighbor imputation of stochastic acceptabilities is a computationally feasible way to improve decisions based on ES proxy maps by accounting for uncertainties, although the need for such detailed information at the pixel level should be separately assessed. Numéro de notice : A2023-024 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article DOI : 10.1016/j.landurbplan.2022.104637 Date de publication en ligne : 16/11/2022 En ligne : https://doi.org/10.1016/j.landurbplan.2022.104637 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102247 [article]

Testing the application of process-based forest growth model PREBAS to uneven-aged forests in Finland / Man Hu in Forest ecology and management, vol 529 (February-1 2023)  

Public [article]  inForest ecology and management > vol 529 (February-1 2023) . - n° 120702 Titre : Testing the application of process-based forest growth model PREBAS to uneven-aged forests in Finland Type de document : Article/Communication Auteurs : Man Hu, Auteur ; Francesco Minunno, Auteur ; Mikko Peltoniemi, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 120702 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] biomasse forestière [Termes IGN] croissance des arbres [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] Finlande [Termes IGN] forêt boréale [Termes IGN] forêt inéquienne [Termes IGN] hauteur des arbres [Termes IGN] modèle de croissance végétale [Termes IGN] modèle de simulation [Termes IGN] modélisation de la forêt [Termes IGN] mortalité [Termes IGN] peuplement mélangé [Termes IGN] photosynthèse [Termes IGN] Picea abies [Termes IGN] structure d'un peuplement forestier [Vedettes matières IGN] Foresterie Résumé : (auteur) The challenges of applying process-based models to uneven-aged forests are the difficulties in simulating the interactions between trees and resource allocation between size classes. In this study, we focused on a process-based forest growth model PREBAS which is a mean tree model with Reineke self-thinning mortality and was originally developed for even-aged forests. The primary aim was to test the application of PREBAS model to uneven-aged forests by introducing different diameter at breast height (DBH) size classes to better represent the forest structure. Additionally, we introduced a new mortality model to PREBAS which is developed for uneven-aged stands and compared with the current PREBAS version in which a modification Reineke rule is used. The tests were conducted in 26 old Norway spruce dominated stands in southern and central Finland with three consecutive measurements (on average a 25-year study period). To evaluate the model performance, we compared the estimations of stand averaged diameter at breast height (D), stand averaged tree height (H), stand averaged crown base height (), stand basal area (B) and density (N) with measurements. Moreover, biomass estimations of each tree component (foliage, branch and stem) were compared to estimations from empirical models. Results showed that introducing size distributions can represent better stand structure and improve the model predictions compared with data. Moreover, the new mortality model showed promise with qualitatively more realistic results especially among the largest tree size classes. However, model bias still existed in the simulation although the predictions were improved. It revealed that further calibration of the PREBAS model with size classes should be done to better extend the model applicability to uneven-aged forests. Numéro de notice : A2023-022 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2022.120702 Date de publication en ligne : 05/12/2022 En ligne : https://doi.org/10.1016/j.foreco.2022.120702 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102228 [article]

Topology-based individual tree segmentation for automated processing of terrestrial laser scanning point clouds / Xin Xu in International journal of applied Earth observation and geoinformation, vol 116 (February 2023)  

Public [article]  inInternational journal of applied Earth observation and geoinformation > vol 116 (February 2023) . - n° 103145 Titre : Topology-based individual tree segmentation for automated processing of terrestrial laser scanning point clouds Type de document : Article/Communication Auteurs : Xin Xu, Auteur ; Federico Iuricich, Auteur ; Kim Calders, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 103145 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] analyse de groupement [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] extraction d'arbres [Termes IGN] houppier [Termes IGN] segmentation d'image [Termes IGN] semis de points [Termes IGN] topologie Résumé : (auteur) Terrestrial laser scanning (TLS) is a ground-based approach to rapidly acquire 3D point clouds via Light Detection and Ranging (LiDAR) technologies. Quantifying tree-scale structure from TLS point clouds requires segmentation, yet there is a lack of automated methods available to the forest ecology community. In this work, we consider the problem of segmenting a forest TLS point cloud into individual tree point clouds. Different approaches have been investigated to identify and segment individual trees in a forest point cloud. Typically these methods require intensive parameter tuning and time-consuming user interactions, which has inhibited the application of TLS to large area research. Our goal is to define a new automated segmentation method that lifts these limitations. Our Topology-based Tree Segmentation (TTS) algorithm uses a new topological technique rooted in discrete Morse theory to segment input point clouds into single trees. TTS algorithm identifies distinctive tree structures (i.e., tree bottoms and tops) without user interactions. Tree tops and bottoms are then used to reconstruct single trees using the notion of relevant topological features. This mathematically well-established notion helps distinguish between noise and relevant tree features. To demonstrate the generality of our approach, we present an evaluation using multiple datasets, including different forest types and point densities. We also compare our TTS approach with open-source tree segmentation methods. The experiments show that we achieve a higher segmentation accuracy when performing point-by-point validation. Without expensive user interactions, TTS algorithm is promising for greater usage of TLS point clouds in the forest ecology community, such as fire risk and behavior modeling, estimating tree-level biodiversity structural traits, and above-ground biomass monitoring. Numéro de notice : A2023-129 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.jag.2022.103145 Date de publication en ligne : 12/12/2022 En ligne : https://doi.org/10.1016/j.jag.2022.103145 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102517 [article]

Tree growth, wood anatomy and carbon and oxygen isotopes responses to drought in Mediterranean riparian forests / J. Julio Camarero in Forest ecology and management, vol 529 (February-1 2023)  

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GIS-based planning of buffer zones for protection of boreal streams and their riparian forests / Heikki Mykrä in Forest ecology and management, vol 528 (January-15 2023)  

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Modelling the dynamics of Pinus sylvestris forests after a die-off event under climate change scenarios / Jordi Margalef- Marrase in Science of the total environment, vol 856 n° 2 (January 2023)  

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Perspectives: Critical zone perspectives for managing changing forests / Marissa Kopp in Forest ecology and management, vol 528 (January-15 2023)  

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Decision tree-based machine learning models for above-ground biomass estimation using multi-source remote sensing data and object-based image analysis / Haifa Tamiminia in Geocarto international, vol 38 n° inconnu ([01/01/2023])  

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Detection of growth change of young forest based on UAV RGB images at single-tree level / Xiaocheng Zhou in Forests, vol 14 n° 1 (January 2023)  

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Estimating mangrove above-ground biomass at Maowei Sea, Beibu Gulf of China using machine learning algorithm with Sentinel-1 and Sentinel-2 data / Zhuomei Huang in Geocarto international, vol 38 n° inconnu ([01/01/2023])  

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Improving generalized models of forest structure in complex forest types using area- and voxel-based approaches from lidar / Andrew W. Whelan in Remote sensing of environment, vol 284 (January 2023)  

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Improving methods to predict aboveground biomass of Pinus sylvestris in urban forest using UFB model, LiDAR and digital hemispherical photography / Ihor Kozak in Urban Forestry & Urban Greening, vol 79 (January 2023)  

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Management of birch spruce mixed stands with consideration of carbon stock in biomass and harvested wood products / Jānis Vuguls in Forests, vol 14 n° 1 (January 2023)  

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