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Models for integrating and identifying the effect of senescence on individual tree survival probability for Norway spruce / Jouni Siipilehto in Silva fennica, vol 55 n° 2 (April 2021)  

Public [article]  inSilva fennica > vol 55 n° 2 (April 2021) . - n° 10496 Titre : Models for integrating and identifying the effect of senescence on individual tree survival probability for Norway spruce Type de document : Article/Communication Auteurs : Jouni Siipilehto, Auteur ; Harri Mäkinen, Auteur ; Kjell Andreassen, Auteur ; Mikko Peltoniemi, Auteur Année de publication : 2021 Article en page(s) : n° 10496 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] âge du peuplement forestier [Termes IGN] analyse comparative [Termes IGN] dynamique de la végétation [Termes IGN] Finlande [Termes IGN] modèle de croissance végétale [Termes IGN] modélisation de la forêt [Termes IGN] mortalité [Termes IGN] Norvège [Termes IGN] Picea abies [Vedettes matières IGN] Foresterie Résumé : (auteur) Ageing and competition reduce trees’ ability to capture resources, which predisposes them to death. In this study, the effect of senescence on the survival probability of Norway spruce (Picea abies (L.) Karst.) was analysed by fitting alternative survival probability models. Different model formulations were compared in the dataset, which comprised managed and unmanaged plots in long-term forest experiments in Finland and Norway, as well as old-growth stands in Finland. Stand total age ranged from 19 to 290 years. Two models were formulated without an age variable, such that the negative coefficient for the squared stem diameter described a decreasing survival probability for the largest trees. One of the models included stand age as a separate independent variable, and three models included an interaction term between stem diameter and stand age. According to the model including stand age and its interaction with stem diameter, the survival probability curves could intersect each other in stands with a similar structure but a different mean age. Models that did not include stand age underestimated the survival rate of the largest trees in the managed stands and overestimated their survival rate in the old-growth stands. Models that included stand age produced more plausible predictions, especially for the largest trees. The results supported the hypothesis that the stand age and senescence of trees decreases the survival probability of trees, and that the ageing effect improves survival probability models for Norway spruce. Numéro de notice : A2021-737 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.14214/sf.10496 Date de publication en ligne : 10/06/2021 En ligne : https://doi.org/10.14214/sf.10496 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98696 [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]

Stand-level mortality models for Nordic boreal forests / Jouni Siipilehto in Silva fennica, vol 54 n° 5 (December 2020)  

Public [article]  inSilva fennica > vol 54 n° 5 (December 2020) . - n° 10414 Titre : Stand-level mortality models for Nordic boreal forests Type de document : Article/Communication Auteurs : Jouni Siipilehto, Auteur ; Micky Allen, Auteur ; Urban Nilsson, Auteur ; Andreas Brunner, Auteur ; et al., Auteur ; Urban Nilsson Année de publication : 2020 Article en page(s) : n° 10414 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] âge du peuplement forestier [Termes IGN] Finlande [Termes IGN] forêt boréale [Termes IGN] inventaire forestier étranger (données) [Termes IGN] modèle de simulation [Termes IGN] modélisation de la forêt [Termes IGN] mortalité [Termes IGN] Norvège [Termes IGN] régression logistique [Termes IGN] Suède [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) New mortality models were developed for the purpose of improving long-term growth and yield simulations in Finland, Norway, and Sweden and were based on permanent national forest inventory plots from Sweden and Norway. Mortality was modelled in two steps. The first model predicts the probability of survival, while the second model predicts the proportion of basal area in surviving trees for plots where mortality has occurred. In both models, the logistic function was used. The models incorporate the variation in prediction period length and in plot size. Validation of both models indicated unbiased mortality rates with respect to various stand characteristics such as stand density, average tree diameter, stand age, and the proportion of different tree species, Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) Karst.), and broadleaves. When testing against an independent dataset of unmanaged spruce-dominated stands in Finland, the models provided unbiased prediction with respect to stand age. Numéro de notice : A2020-854 Affiliation des auteurs : non IGN Thématique : FORET/MATHEMATIQUE Nature : Article DOI : 10.14214/sf.10414 Date de publication en ligne : 01/12/2020 En ligne : https://doi.org/10.14214/sf.10414 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98710 [article]