Détail de l'autorité
ModForTrans / Bontemps, Jean-Daniel
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Nom :
ModForTrans
titre complet :
A new generation of forest MODels to predict FORest resources in a TRANSitional context
Auteurs :
Bontemps, Jean-Daniel
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Documents disponibles (2)
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Modeling and propagating inventory-based sampling uncertainty in the large-scale forest demographic model “MARGOT” / Timothée Audinot in Natural Resource Modelling, vol 35 n° 3 (August 2022)
[article]
Titre : Modeling and propagating inventory-based sampling uncertainty in the large-scale forest demographic model “MARGOT” Type de document : Article/Communication Auteurs : Timothée Audinot , Auteur ; Holger Wernsdörfer, Auteur ; Gilles Le Moguédec, Auteur ; Jean-Daniel Bontemps , Auteur Année de publication : 2022 Projets : ModForTrans / Bontemps, Jean-Daniel, ARBRE / AgroParisTech (2007 -) Article en page(s) : n° e12352 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] incertitude des données
[Termes IGN] inventaire forestier national (données France)
[Termes IGN] modélisation de la forêt
[Termes IGN] propagation d'incertitude
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Models based on national forest inventory (NFI) data intend to project forests under management and policy scenarios. This study aimed at quantifying the influence of NFI sampling uncertainty on parameters and simulations of the demographic model MARGOT. Parameter variance–covariance structure was estimated from bootstrap sampling of NFI field plots. Parameter variances and distributions were further modeled to serve as a plug-in option to any inventory-based initial condition. Forty-year time series of observed forest growing stock were compared with model simulations to balance model uncertainty and bias. Variance models showed high accuracies. The Gamma distribution best fitted the distributions of transition, mortality and felling rates, while the Gaussian distribution best fitted tree recruitment fluxes. Simulation uncertainty amounted to 12% of the model bias at the country scale. Parameter covariance structure increased simulation uncertainty by 5.5% in this 12%. This uncertainty appraisal allows targeting model bias as a modeling priority. Numéro de notice : A2022-576 Affiliation des auteurs : LIF+Ext (2020- ) Autre URL associée : vers HAL Thématique : FORET/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/nrm.12352 Date de publication en ligne : 08/08/2022 En ligne : https://doi.org/10.1111/nrm.12352 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101333
in Natural Resource Modelling > vol 35 n° 3 (August 2022) . - n° e12352[article]A large-scale forest dynamic model to estimate wood resources in the French forests based on NFI information / Timothée Audinot (2019)
Titre : A large-scale forest dynamic model to estimate wood resources in the French forests based on NFI information Type de document : Article/Communication Auteurs : Timothée Audinot , Auteur ; Holger Wernsdörfer, Auteur ; Jean-Daniel Bontemps , Auteur Editeur : Saint-Mandé : Institut national de l'information géographique et forestière - IGN (2012-) Année de publication : 2019 Projets : MOPROF-CC / AgroParisTech (2007 -) Conférence : Conference 2019, A century of national forest inventories – informing past, present and future decisions 19/05/2019 21/05/2019 Oslo Norvège programme sans actes Projets : ModForTrans / Bontemps, Jean-Daniel Langues : Anglais (eng) Descripteur : [Termes IGN] forêt
[Termes IGN] France métropolitaine
[Termes IGN] inventaire forestier national (données France)
[Termes IGN] modèle dynamique
[Termes IGN] ressources forestières
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Introduction : Non-stationary forest dynamics of secular arising from the forest transition, and current agenda on climate change mitigation and valuation of wood resources (Bioeconomy), make the development of large-scale models crucial to support forest management strategies on these issues. French forests further exhibit significant contrasts in climatic context and diversity in tree species, challenging these developments. Based on the MARGOT model (Pignard, 1993; Wernsdörfer et al., 2012), we intend to model all the diversity of the French forest in a non-stationary context.Materials and methods: Using NFI data to both build reference historical chronologies of growing stock and estimate model parameters, we compared past retrospective projections of model MARGOT, constructed at different hierarchical scales representative of diversity of the French forests, with historical and modern database from the French NFI over a period of 40 years (1971-2011), to conduct model evaluation. We also performed a sensitivity analysis on the felling rates. Second step is to represent density-dependent processes in the model in order to better simulate forest management. Results: MARGOT was found to overestimate the growing stock trajectories, both on a regional and national scale. A sensitivity analysis on felling rates suggested their underestimation from the NFI protocol by a factor of 2, as a consequence of the temporary nature of sampling plots. Modelling of density-dependence was introduced and tested against former simulations.Conclusion: In spite of overestimations in the growing stock, MARGOT was found able to describe the French forest expansion, indicating that forest maturation is a key current process in these increases. Density-dependence was found to lower overestimations in the growing stock. A next step will consist in hybridizing Margot with a process-based model in order to account for climatic forcings. Numéro de notice : C2019-063 Affiliation des auteurs : LIF+Ext (2012-2019) Thématique : FORET Nature : Communication nature-HAL : ComSansActesPubliés-Unpublished DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96976