Abstract not found

Empirical observations suggest that in pure even-aged forests, the mean diameter of forest trees (D, diameter at breast height, 1.3 m above ground) tends to remain a constant proportion of stand height (H, average height of the largest trees in a stand) divided by the logarithm of stand density (N, number of trees per hectare): D = β(H − 1.3) / ln(N). Thinning causes a relatively small and temporary change in the slope β, the magnitude and duration of which depends on the nature of the thinning. This relationship may provide a robust predictor of growth in situations where scarce data and resources preclude more sophisticated modelling approaches.

Idealisation is the process of finding simple representations of the real-world whilst conceptualising a model. There are three ways to limit complication in a model of a complex real-world: by focussing the scope of the modelling process onto a clearly defined issue; by idealising elements of the real-world during model conceptualisation; and by simplifying the implemented simulation program. Careful idealisation has the greatest potential for increasing model tractability whilst generating insights during the model design process. The Forest Land Oriented Resource Envisioning System (FLORES) project deals with social forest landscapes which are highly complex. Benefits of idealisation are demonstrated using six examples from this modelling work. These examples encompass issues dealing with land tenure, forest management, economic values, social diversity, communication and collaboration. Each example illustrates a different method to achieve an idealisation which yields insights relevant for policy players. A number of lessons about idealisation are also identified: (1) sometimes it is only possible

a b s t r a c t A model is presented to predict sanitary felling of Norway spruce (Picea abies) due to spruce bark beetles (Ips typographus, Pityogenes chalcographus) in Slovenia according to different climate change scenarios. The model incorporates 21 variables that are directly or indirectly related to the dependent variable, and that can be arranged into five groups: climate, forest, landscape, topography, and soil. The soil properties are represented by 8 variables, 4 variables define the topography, 4 describe the climate, 4 define the landscape, and one additional variable provides the quantity of Norway spruce present in the model cell. The model was developed using the M5 model tree. The basic spatial unit of the model is 1 km 2 , and the time resolution is 1 year. The model evaluation was performed by three different measures: (1) the correlation coefficient (51.9%), (2) the Theil's inequality coefficient (0.49) and (3) the modelling efficiency (0.32). Validation of the model was carried out by 10-fold cross-validation. The model tree consists of 28 linear models, and model was calculated for three different climate change scenarios extending over a period until 2100, in 10-year intervals. The model is valid for the entire area of Slovenia; however, climate change projections were made only for the Maribor region (596 km 2 ). The model assumes that relationships among the incorporated factors will remain unchanged under climate change, and the influence of humans was not taken into account. The structure of the model reveals the great importance of landscape variables, which proved to be positively correlated with the dependent variable. Variables that describe the water regime in the model cell were also highly correlated with the dependent variable, with evapotranspiration and parent material being of particular importance. The results of the model support the hypothesis that bark beetles do greater damage to Norway spruce artificially planted out of its native range in Slovenia, i.e., lowlands and soils rich in N, P, and K. The model calculation for climate change scenarios in the Maribor region shows an increase in sanitary felling of Norway spruce due to spruce bark beetles, for all scenarios. The model provides a path towards better understanding of the complex ecological interactions involved in bark beetle outbreaks. Potential application of the results in forest management and planning is discussed.

H. Wagle1 and R. P. Sharma2 Quantifi cation of height-diameter relationship helps in better understanding of stand dynamics. Height-diameter models can be used as necessary inputs to growth and yield models and growth simulation systems. The researchers developed height-diameter models with 364 Blue pine (Pinus wallichiana) tree data from Lete and Kunjo Village Development Committees (VDCs) of Mustang district. Eighteen non-linear models were calibrated, among which, Weibull model described the largest proportion of height variation (R2adj = 0. 9362). Gunary and Chapman-Richards ’ models also appeared almost identical to Weibull model in terms of fi t statistics and graphical appearance. The researchers recommend Weibull model for predicting total heights of Blue pine trees for the VDCs covered by the study. Key words: Blue pine, height-diameter models, modelling, Mustang district The measurements of individual tree height and diameter are essential component of forest inventories. Tree heights are used for estimating volume, site index, growth and yield, succession and carbon budget models (Peng, 2001). Although, theoretically, height can be measured on standing trees, practically, it is expensive, tedious and time consuming due to stand conditions and land confi gurations. Therefore, with many permanent or temporary sample plot systems, diameters for all trees, but height of only a few sample trees are measured. Alternatively, indirect estimation of tree heights can be made from diameter at breast height (dbh) which can be easily and accurately measured in relatively low cost. But for this, a site-and species-specific model describing a height-diameter relationship is necessary. Height-diameter model can be developed using accurately measured heights and diameters from individual trees sampled from every stand within a forest. Height-diameter models are used to predict missing heights on the stands or permanent sample

To obtain relevant information for prudent decision-making in forest management and forest policy, it is necessary to understand the growth patterns of a species and to assess site quality

Boreal mixedwoods are some of the most diverse forest ecosystems in North America, with the stands typically consisting of mixtures of aspen ( Populus tremuloides Michx.) and white spruce

Abstract. Many slopes in the Alps are prone to rockfall and forests play a vital role in protecting objects such as (rail) roads and infrastructure against rockfall. Decision support tools are required to assess rockfall processes and to quan-tify the rockfall protection effect of forest stands. This paper presents results of an iterative sequence of tests and improve-ments of a coupled rockfall and forest dynamics model with focus on the rockfall module. As evaluation data a real-size rockfall experiment in the French Alps and two 2-D rockfall trajectories from Austria and Switzerland were used. Mod-ification of the rebound algorithm and the inclusion of an algorithm accounting for the sudden halt of falling rocks due to surface roughness greatly improved the correspondence between simulated and observed key rockfall variables like run-out distances, rebound heights and jump lengths for the real-size rockfall experiment. Moreover, the observed jump lengths and run-out distances of the 2-D trajectories were well within the stochastic range of variation yielded by the simulations. Based on evaluation results it is concluded that the rockfall model can be employed to assess the protective effect of forest vegetation. Correspondence to: W. Rammer

The relationship between tree height and diameter is an important element in growth and yield models, in carbon budget and timber volume models, and in the description of stand dynamics. Six non-linear growth functions (i.e. Chapman-Richards, Schnute, Lundqvist/Korf, Weibull, Modified Logistic and Exponential) were fitted to tree height-diameter data of oriental beech in the Hyrcanian mixed hardwood forests of Iran. The predictive performance of these models was in the first place assessed by means of different model evaluation criteria such as adjusted R squared (adj R 2 ), root mean square error (RMSE), Akaike information criterion (AIC), mean difference (MD), mean absolute difference (MAD) and mean square (MS) error criteria. Although each of the six models accounted for approximately 75% of total variation in height, a large difference in asymptotic estimates was observed. Apart from this, the predictive performance of the models was also evaluated by means of cross-validation and by splitting the data into 5-cm diameter classes. Plotting the MD in relation to these diameter at breast height (DBH) classes showed for all growth functions, except for the Modified Logistic function, similar mean prediction errors for small-and medium-sized trees. Large-sized trees, however, showed a higher mean prediction error. The Modified Logistic function showed the worst performance due to a large model bias. The Exponential and Lundqvist/Korf models were discarded due to their showing biologically illogical behavior and unreasonable estimates for the asymptotic coefficient, respectively. Considering all the above-mentioned criteria, the Chapman-Richards, Weibull, and Schnute functions provided the most satisfactory height predictions. However, we would recommend the Chapman-Richards function for further analysis because of its higher predictive performance. Keywords. Forest trees, Fagus orientalis, simulation models, growth, Iran. Modèles non linéaires de diamètre de hauteur pour le hêtre oriental (Fagus orientalis Lipsky) dans les forêts Hyrcaniennes en Iran. La relation entre la hauteur des arbres et le diamètre est un élément important pour les modèles de croissance, de rendement, du budget de carbone et de volume du bois, et pour la description de la dynamique des peuplements. Six fonctions de croissance non linéaires (Chapman-Richards, Schnute, Lundqvist/Korf, Weibull, fonctions logistiques et exponentielles modifiées) ont été ajustées aux données de diamètre de hauteur des arbres de hêtre oriental dans les forêts mélangées hyrcaniennes d'Iran. La performance prévue des modèles a été évaluée à l'aide du R² ajusté (adj R²), de l'erreur quadratique moyenne (RMSE), du critère d'information d'Akaike (AIC), de la différence moyenne (MD), de la différence absolue moyenne (MAD) et de l'erreur quadratique moyenne (MS). Les résultats ont montré que chacun de ces six modèles représente environ 75 % de la variation totale de hauteur, mais produit différentes estimations asymptotiques. La performance prévue a également été évaluée à l'aide des validations croisées et par séparation des données en classes de 5 cm de diamètre à hauteur de poitrine (DBH) afin de calculer le MD pour chaque classe. Les visualisations de MD pour toutes les classes DBH ont montré que les six fonctions de croissance, sauf la logistique modifiée, produisent des erreurs de prédiction moyennes similaires pour les arbres de tailles petites et moyennes. Cependant, pour les arbres de grande taille, l'erreur de prédiction moyenne est plus élevée. La fonction de logistique modifiée est la moins performante, en raison d'un large biais. Les modèles exponentiels et de Lundqvist/Korf ont été rejetés en raison, respectivement, de leur comportement biologique illogique et des estimations déraisonnables pour les coefficients asymptotiques. En envisageant tous les critères mentionnés ci-dessus, les fonctions Chapman-Richards, Weibull et Schnute fournissent les prédictions de hauteur les plus satisfaisantes, mais la fonction de Chapman-Richards pourrait être recommandée pour une analyse plus approfondie en raison de sa meilleure performance.

This study tested the effects of inserting climatic variables in Eucalyptus grandis as covariables of a dominant height model, which for site index classification is usually related to age alone. Dominant height values ranging from 1 to 12 years of age located in the Southeast region of Brazil were used, as well as data from 19 automatic meteorological stations from the area. The ChapmanRichards model was chosen to represent dominant height as a function of age. To include the environmental variables a modifier was included in the asymptote of the model. The asymptote was chosen since this parameter is responsible for the maximum value which the dominant height can reach. Of the four environmental variables most responsible for database variation, the two with the highest correlation to the mean annual increment in dominant height (mean monthly precipitation and temperature) were selected to compose the asymptote modifier. Model validation showed a gain in precision of 33% (reduction of the standard error of estimate) when climatic variables were inserted in the model. Possible applications of the method include the estimation of site capacity in regions lacking any planting history, as well as updating forest inventory data based on past climate regimes.