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An evaluation of multi-species empirical tree mortality algorithms for dynamic vegetation modelling / Timothy Thrippleton in Scientific reports, vol 11 (2021)  

Public [article]  inScientific reports > vol 11 (2021) . - n° 19845 Titre : An evaluation of multi-species empirical tree mortality algorithms for dynamic vegetation modelling Type de document : Article/Communication Auteurs : Timothy Thrippleton, Auteur ; Lisa Hülsmann, Auteur ; Maxime Cailleret, Auteur ; Harald Bugmann, Auteur Année de publication : 2021 Article en page(s) : n° 19845 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Abies alba [Termes IGN] Betula pendula [Termes IGN] dynamique de la végétation [Termes IGN] Europe (géographie politique) [Termes IGN] Fagus sylvatica [Termes IGN] forêt ancienne [Termes IGN] modélisation de la forêt [Termes IGN] mortalité [Termes IGN] Picea abies [Termes IGN] Pinus sylvestris [Termes IGN] Quercus sessiliflora [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Tree mortality is key for projecting forest dynamics, but difficult to portray in dynamic vegetation models (DVMs). Empirical mortality algorithms (MAs) are often considered promising, but little is known about DVM robustness when employing MAs of various structures and origins for multiple species. We analysed empirical MAs for a suite of European tree species within a consistent DVM framework under present and future climates in two climatically different study areas in Switzerland and evaluated their performance using empirical data from old-growth forests across Europe. DVM projections under present climate showed substantial variations when using alternative empirical MAs for the same species. Under climate change, DVM projections showed partly contrasting mortality responses for the same species. These opposing patterns were associated with MA structures (i.e. explanatory variables) and occurred independent of species ecological characteristics. When comparing simulated forest structure with data from old-growth forests, we found frequent overestimations of basal area, which can lead to flawed projections of carbon sequestration and other ecosystem services. While using empirical MAs in DVMs may appear promising, our results emphasize the importance of selecting them cautiously. We therefore synthesize our insights into a guideline for the appropriate use of empirical MAs in DVM applications. Numéro de notice : A2021-964 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1038/s41598-021-98880-2 Date de publication en ligne : 06/10/2021 En ligne : http://dx.doi.org/10.1038/s41598-021-98880-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100136 [article]

How do tree mortality models from combined tree-ring and inventory data affect projections of forest succession? / Marco Vanoni in Forest ecology and management, vol 433 (15 February 2019)  

Public [article]  inForest ecology and management > vol 433 (15 February 2019) . - pp 606 - 617 Titre : How do tree mortality models from combined tree-ring and inventory data affect projections of forest succession? Type de document : Article/Communication Auteurs : Marco Vanoni, Auteur ; Maxime Cailleret, Auteur ; Lisa Hülsmann, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 606 - 617 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Végétation [Termes IGN] Abies alba [Termes IGN] arbre (flore) [Termes IGN] arbre mort [Termes IGN] croissance des arbres [Termes IGN] diamètre des arbres [Termes IGN] données dendrométriques [Termes IGN] dynamique de la végétation [Termes IGN] Europe centrale [Termes IGN] Fagus sylvatica [Termes IGN] forêt [Termes IGN] inventaire forestier étranger (données) [Termes IGN] Larix decidua [Termes IGN] modèle de croissance végétale [Termes IGN] modèle de simulation [Termes IGN] mortalité [Termes IGN] Picea abies [Termes IGN] Pinus cembra [Termes IGN] prévision [Termes IGN] Quercus (genre) [Termes IGN] Suisse Résumé : (auteur) Tree mortality is caused by complex interactions between multiple biotic and abiotic factors. Processes of tree mortality that are not induced by natural disturbances are often reflected in distinct radial growth patterns of trees, which typically serve as reliable indicators of impending tree mortality. However, it remains unclear whether empirical mortality models that are based on tree size and growth result in more realistic projections of forest succession in dynamic vegetation models (DVMs). We used a combination of tree-ring and inventory data from unmanaged Swiss natural forest reserves to derive species-specific survival models for six Central European tree species (Abies alba, Fagus sylvatica, Larix decidua, Picea abies, Pinus cembra and Quercus spp.). We jointly used 528 tree-ring samples and inventory data from eight forest reserves. We implemented the estimated parameters of the survival models into the DVM ForClim and performed simulations of forest succession that were validated using the inventory data of the forest reserves. Size- and growth-dependent variables (i.e., diameter at breast height and mean ring width) over the last few years prior to tree death were reliable predictors to distinguish between dying and living trees. Very low mean ring widths over several preceding years as well as small and large trees, respectively, reflected low survival probabilities. However, the small sample sizes of small and large trees resulted in considerable uncertainty of the survival probabilities. The implementation of these survival models in ForClim yielded plausible projections in short-term simulations and for some sites improved the predictions compared to the current ForClim version. Stand basal area, however, tended to be overestimated. Long-term simulations of ForClim based on the empirical survival models resulted in realistic predictions only if the uncertainty of the predicted survival probabilities was considered. We conclude that the combination of different data sources in combination with the consideration of intra-specific trait variability yields robust predictions of tree survival probabilities, thus paving the way towards better tree mortality models and more reliable projections of future forest dynamics. Numéro de notice : A2019-009 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2018.11.042 Date de publication en ligne : 29/11/2018 En ligne : https://doi.org/10.1016/j.foreco.2018.11.042 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91603 [article]