1. Developing National Forest Inventory-based indicators for monitoring minority ravine forestsAnže Martin Pintar, Janez Kermavnar, Luka Krajnc, Gal Kušar, Lado Kutnar, 2026, original scientific article Abstract: Ravine forests represent a priority habitat type of the European Natura 2000 network for which empirical data are limited, particularly regarding the influence of stand structure on biodiversity. Assessment of forest habitats can largely be supported by National Forest Inventory (NFI) data, which enable frequent and spatially dense monitoring of the stand conditions and potential vulnerability of forest habitat types. In this study, we established an independent, nationwide classification system of close-to-nature managed ravine forests dominated by different characteristic broadleaf trees, based on stratifying NFI data into homogeneous subtypes. On the basis of tree species composition, which is a basic component in forest habitat types, we identified three subtypes of ravine forests, dominated by Acer pseudoplatanus, Fraxinus excelsior, and Tilia spp. We examined these subtypes using structural, compositional, deadwood, and diversity-related indicators. The Tilia-dominated subtype was more common in the lower altitudinal belt (≤ 502 m), while the Acer-dominated subtype was more prominent in the higher belt (> 502 m). The Acer-dominated subtype predominated in stands with SDI lower than 432, while the Tilia-dominated subtype was relatively more common in stands with higher SDI. In stands with Evenness values lower than 0.3, the Acer-dominated subtype predominated, while in stands with higher Evenness index values, the Fraxinus-dominated subtype was more common. In the Fraxinus-dominated subtype, the volume of standing dead trees was statistically significantly higher than in the other two subtypes (14 m3 /ha compared to 8 m3 /ha) due to the high mortality rate of trees caused by ash dieback. In all three subtypes of ravine forests, we observed a lack of natural regeneration of key tree species, which is crucial for maintaining the favorable conservation status of the habitat type. The observed ranges of structural and compositional attributes, deadwood components, and diversity indices provide empirical reference conditions that reflect the current nationwide variability of ravine forests.
Keywords: National Forest Inventory, Tilio-Acerion, characteristic broadleaf trees, forest composition, forest structure, deadwood biomass
Published in DiRROS: 08.04.2026; Views: 207; Downloads: 137
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2. Identification of even- and uneven-aged forest stand structures using freely available national airborne laser scanning data on National Forest Inventory plots in spruce-beech-fir dominated regionsAnže Martin Pintar, 2026, original scientific article Abstract: Even-aged forests are still predominant across Europe. However, due to the higher resilience and resistance of uneven-aged forests to disturbances and climate change, their proportion is expected to increase both in Europe and globally. The primary objective of this study is to demonstrate the feasibility of distinguishing between uneven- and even-aged forest stand structures on National Forest Inventory (NFI) permanent sample plots solely based on freely available, national airborne low-resolution laser scanning data, without the use of field-based estimates or measurements. Forest structure was described and classified based on canopy closure, dominant height, and canopy height diversity derived from the canopy height model (CHM) and voxel-based metrics calculated from the point cloud. Comparable results were obtained using both approaches for assessing forest structural diversity: canopy height diversity derived from the canopy height model (CHDCHM) and from voxel-based metrics (CHDV). However, differences in vertical diversity between uneven- and even-aged stands were more pronounced when using CHM-based metrics. Therefore, we conclude that in areas with low-density laser scanning data, CHM analysis represents a more suitable method for evaluating the vertical heterogeneity of forest stand structures. The CHDCHM values were estimated at 1.71 for uneven-aged forests, with values of 1.24 and 1.54 observed in mature even-aged forests. In comparison, CHDV values were 2.50 for uneven-aged forests, while mature even-aged forests showed values of 2.18 and 2.24.
Keywords: vertical heterogeneity, national forest inventory, canopy height model, voxels, uneven- aged forests, even-aged forests
Published in DiRROS: 26.02.2026; Views: 293; Downloads: 212
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4. Experiences with the National Forest Inventory (NFI) in Slovenia : presented at 3rd Meeting of the Regional Expert Advisory Working Group on Forest from the Western Balkans, 31 January–1 February 2023, in Durrës, AlbaniaMitja Skudnik, Primož Simončič, 2023, unpublished conference contribution Keywords: national forest inventory, monitoring, developement of forests, national level, Slovenia
Published in DiRROS: 24.07.2023; Views: 1661; Downloads: 777
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6. What could be 3DForEcoTech COST Action contribution to National Forest Inventories : presented at the 3DForEcoTech workshop, 15.06.2022, PragueGal Kušar, Mitja Skudnik, Luka Krajnc, Anže Martin Pintar, 2022, unpublished conference contribution Keywords: National Forest Inventory, dendrometry, improvement, field mensuration, Slovenia
Published in DiRROS: 28.06.2022; Views: 2077; Downloads: 0 |
7. Artificial neural networks as an alternative method to nonlinear mixed-effects models for tree height predictionsMitja Skudnik, Jernej Jevšenak, 2022, original scientific article Abstract: 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.
Keywords: height-diameter models, national forest inventory, permanent sample plot, mixed forests, model comparison, principal component analysis
Published in DiRROS: 08.06.2022; Views: 1700; Downloads: 681
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