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Povzetek: Changing environmental conditions, disturbances, and escalating demands for forest ecosystem services require foresters to restore present forestlands with new forest generations that will exhibit ecological integrity, diversity, high adaptive capacity, and the ability to provide essential ecosystem services. Establishing such forests requires careful consideration of the forest landscape and site dynamics. In pursuit of these requirements, we developed a novel framework that enables the restoration of forest sites and promotes the desired features of the forest complex at the same time. This framework was designed with the methods of system engineering and was organized in the same way as the forest planning process. It was tested in the habitat type of Illyrian Fagus sylvatica forests belonging to the Natura 2000 network. The environmental, vegetation, and site conditions were investigated via field inspections, available forest management plans, and simple GIS analyses. Additionally, we established a seminatural stand composed of European beech, sessile oak, sycamore maple, silver fir, and some wild fruit tree species. The survival of planted species was assessed using census and simple random sampling, the performance of provenances by the Student’s test, while microhabitat factors were explored by a one-way ANOVA. The survival rate of key species was estimated to be 55.6%, while that of fruit species was estimated to be 94.5%. Our framework demonstrated satisfactory performance and contained sufficient benchmarks to facilitate consistent decision-making. In the discussion, we elucidate the framework’s primary features and attributes of the mixed stand, where we also expose some open issues to be addressed in the future.
Ključne besede: restoration, forest habitat type, indigenous species, planting, mixed stand, key species, fruit species
Objavljeno v DiRROS: 13.06.2024; Ogledov: 27; Prenosov: 18
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Povzetek: Tree heights are one of the most important aspects of forest mensuration, but data are often unavailable due to costly and time-consuming field measurements. Therefore, various types of models have been developed for the imputation of tree heights for unmeasured trees, with mixed-effects models being one of the most commonly applied approaches. The disadvantage here is the need of sufficient sample size per tree species for each plot, which is often not met, especially in mixed forests. To avoid this limitation, we used principal component analysis (PCA) for the grouping of similar plots based on the most relevant site descriptors. Next, we compared mixed-effects models with height-diameter models based on artificial neural networks (ANN). In terms of root mean square error (RMSE), mixed-effects models provided the most accurate tree height predictions at the plot level, especially for tree species with a smaller number of tree height measurements. When plots were grouped using the PCA and the number of observations per category increased, ANN predictions improved and became more accurate than those provided by mixed-effects models. The performance of ANN also increased when the competition index was included as an additional explanatory variable. Our results show that in the pursuit of the most accurate modelling approach for tree height predictions, ANN should be seriously considered, especially when the number of tree measurements and their distribution is sufficient.
Ključne besede: height-diameter models, national forest inventory, permanent sample plot, mixed forests, model comparison, principal component analysis
Objavljeno v DiRROS: 08.06.2022; Ogledov: 576; Prenosov: 248
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