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Abstract:The study was performed on the ski resort Krvavec, which is one of the most frequented ski resorts in Slovenia. The ski slopes serve as pastures for cattle during summer time and range from 1500 to 2000 m a.s.l., which is at or above the upper timberline. To offer a longer ski season and to profit snow better (either natural or artificial one) the slopes have been levelled and consequently the soil profile has been changed. Such altered soil profile characteristics strongly impact hydrological functions of soils. To study these impacts, five plots (20 × 20 m) have been chosen on the slopes with a different history: pasture without any amelioration work, a patch of forest in the ski resort without any ameliorations, and three plots with different intensity of amelioration. Dynamics of soil water content on each plot has been determined by measuring soil water content in-situ with portable TDR system during several days after long lasting heavy rains. Statistically significant differences were shown in soil water content between the plots after the rain, although some differences between plots have disappeared in the following days.

The purpose of this study was to expand an existing semi-mechanistic forest model, ANA-FORE (ANAlysing Forest Ecosystems), to allow for the prediction of log quality and the accompanying uncertainty as influenced by climate and management. The forest stand is described as consisting of trees of different cohorts, either of the same or of different species (deciduous or coniferous). In addition to photosynthesis, transpiration, total growth and yield, the model simulates the daily evolution in vessel biomass and radius, parenchyma and branch development. From these data early and latewood biomass, wood tissue composition, knot formation and density are calculated. The new version presented here, includes the description of log quality, including red heart formation of beeches.A Bayesian optimisation routine for the species parameters was added to the stand model. From a given range of input parameters (prior), the model calculates an optimised range for the parameters (posterior) based on given output data, as well as an uncertainty on the predicted values.A case study was performed for Slovenian beech forests to illustrate the main model functioning and more in particular the simulation of the wood quality. The results indicate that the ANAFORE model is a useful tool for analyzing wood quality development and forest ecosystem functioning in response to management, climate and stand characteristics. However, the Bayesian optimization showed that the remaining uncertainty on the input parameters for the chosen stand was very large, due to the large number of input parameters in comparison to the limited stand data.

With the advent of global warming, forests are becoming an increasingly important carbon sink that can mitigate the negative effects of climate change. An understanding of the carbon dynamics of forests is, therefore, crucial to implement appropriate forest management strategies and to meet the expectations of the Paris Agreement with respect to international reporting schemes. One of the most frequently used models for simulating the dynamics of carbon stocks in forests is the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3). We applied this model in our study to evaluate the effects of harvesting on the carbon sink dynamics in Slovenian forests. Five harvesting scenarios were defined: (1) business as usual (BAU), (2) harvesting in line with current forest management plans (PLAN), (3) more frequent natural hazards (HAZ), (4) high harvest (HH) and (5) low harvest (LH). The simulated forest carbon dynamics revealed important differences between the harvesting scenarios. Relative to the base year of 2014, by 2050 the carbon stock in above-ground biomass is projected to increase by 28.4% (LH), 19% (BAU), 10% (PLAN), 6.5% (HAZ) and 1.2% (HH). Slovenian forests can be expected to be a carbon sink until harvesting exceeds approximately 9 million m3 annually, which is close to the calculated total annual volume increase. Our results are also important in terms of Forest Reference Levels (FRL), which will take place in European Union (EU) member states in the period 2021–2025. For Slovenia, the FRL was set to −3270.2 Gg CO2 eq/year, meaning that the total timber harvested should not exceed 6 million m3 annually.

This article discusses single-tree growth models, which have become an important tool for decision-making, management and strategic decisions in the field of forest management. In Slovenia, we have only recently begun systematic development in the field of forest modelling, which includes the development of a matrix population model, testing selected models from abroad and the development of individual model components. The goal of our work is to introduce the field of empirical single-tree models for modelling forest development on a larger scale. We provide a detailed overview of established methods for modelling individual components of tree models, such as radial and height growth, crown recession, mortality, and recruitment and regeneration. We evaluated the suitability of the selected models from the perspective of their applicability in Slovenia. We conclude that the SILVA, WEHAM, MASSIMO and CALDIS models have the greatest potential for use in Slovenia, as they are all suitable for the different forest types and mixed forests with different structure that prevail in Slovenia. In addition to testing the existing models, we propose the development of new models adapted to the heterogeneous and mixed stands in Slovenia. We also propose expanding the set of indicators in forest inventories and measuring additional tree characteristics, such as canopy characteristics, which would expand forest modelling opportunities in Slovenia. In the conclusions, we also discuss the potential use of machine learning in forest development modelling, as this type of model could represent the next generation of forest models.