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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]

Comparison of spatially and nonspatially explicit nonlinear mixed effects models for Norway spruce individual tree growth under single-tree selection / Simone Bianchi in Forests, vol 11 n° 12 (December 2020)  

Public [article]  inForests > vol 11 n° 12 (December 2020) . - n° 1338 Titre : Comparison of spatially and nonspatially explicit nonlinear mixed effects models for Norway spruce individual tree growth under single-tree selection Type de document : Article/Communication Auteurs : Simone Bianchi, Auteur ; Mari Myllymäki, Auteur ; Jouni Siipilehto, Auteur ; Hannu Salminen, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : n° 1338 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] arbre (flore) [Termes IGN] croissance des arbres [Termes IGN] forêt boréale [Termes IGN] modèle de croissance végétale [Termes IGN] modèle non linéaire [Termes IGN] Picea abies [Vedettes matières IGN] Sylviculture Résumé : (auteur) Background and Objectives: Continuous cover forestry is of increasing importance, but operational forest growth models are still lacking. The debate is especially open if more complex spatial approaches would provide a worthwhile increase in accuracy. Our objective was to compare a nonspatial versus a spatial approach for individual Norway spruce tree growth models under single-tree selection cutting. Materials and Methods: We calibrated nonlinear mixed models using data from a long-term experiment in Finland (20 stands with 3538 individual trees for 10,238 growth measurements). We compared the use of nonspatial versus spatial predictors to describe the competitive pressure and its release after cutting. The models were compared in terms of Akaike Information Criteria (AIC), root mean square error (RMSE), and mean absolute bias (MAB), both with the training data and after cross-validation with a leave-one-out method at stand level. Results: Even though the spatial model had a lower AIC than the nonspatial model, RMSE and MAB of the two models were similar. Both models tended to underpredict growth for the highest observed values when the tree-level random effects were not used. After cross-validation, the aggregated predictions at stand level well represented the observations in both models. For most of the predictors, the use of values based on trees’ height rather than trees’ diameter improved the fit. After single-tree selection cutting, trees had a growth boost both in the first and second five-year period after cutting, however, with different predicted intensity in the two models. Conclusions: Under the research framework here considered, the spatial modeling approach was not more accurate than the nonspatial one. Regarding the single-tree selection cutting, an intervention regime spaced no more than 15 years apart seems necessary to sustain the individual tree growth. However, the model’s fixed effect parts were not able to capture the high growth of the few fastest-growing trees, and a proper estimation of site potential is needed for uneven-aged stands. Numéro de notice : A2020-578 Affiliation des auteurs : non IGN Thématique : FORET/MATHEMATIQUE Nature : Article DOI : 10.3390/f11121338 Date de publication en ligne : 16/12/2020 En ligne : https://doi.org/10.3390/f11121338 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97034 [article]