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.
COBISS.SI-ID: 32930819
Forest development models predict development of trees and forest stands according to tree, stand, site, and forest management factors. Due to complex nature of forest ecosystems and long production cycles, forest development modeling is an important feature of forest management. Stand models have been identified as suitable for decision support in forest management, an example of such a model is the Swiss model SiWaWa (Rosset et al., 2013), which was tested in Slovenian forests in the present study. Forest development simulations for 10-y periods were performed on four samples of 50 permanent sample plots in unmanaged and managed pure beech and pure spruce stands. Afterwards, we compared the actual and modelled values of stand basal area G, number of trees N, and mean squared diameter Dg. Predicting the development of pure beech forests was fairly accurate, the root mean square error RMSE for G was 2,35 m2/ha for unmanaged, and 3,42 m2/ha and 4,35 m2/ha for managed stands considering only harvesting or entire mortality, respectively. We cannot claim the same for the development of pure spruce stands. Measures of accuracy were significantly worse, the RMSE was 8,94 m2/ha for unmanaged stands, and 6,13 m2/ha and 6,11 m2/ha for managed stands considering only harvesting or entire mortality, respectively. The SiWaWa model, parameterized for Swiss forests, seems to be applicable for simulating the development of pure beech forests without or with simulated fellings, but the model does not yet provide reliable simulations for pure spruce stands.
COBISS.SI-ID: 54039299
Here, we present one of the first attempts to use a machine learning model for the prediction and interpretation of tree basal area increment (BAI) based on data from the National Forest Inventory (NFI). The developed model is based on the random forest (RF) algorithm, trained with 18 independent variables and 15,580 data points (trees from the Slovenian NFI). The RF model was trained for four individual species and two groups of species and evaluated using 10-fold blocked cross-validation. Squared correlation coefficients calculated for independent data ranged from 0.289 for Scots pine (Pinus Sylvestris) to 0.342 for maple and ash species (Acer sp. and Fraxinus sp.), 0.429 for oak species (Quercus sp.), 0.475 for Norway spruce (Picea abies), 0.486 for common beech (Fagus sylvatica), and 0.565 for silver fir (Abies alba). The most important predictor variables were the basal areas of individual trees and their competition status, expressed as the basal area in larger trees and tree social position. Simulations of selected key variables revealed different ecological traits of the studied species: silver fir and Norway spruce have the highest growth characteristics, while common beech has the strongest competition potential. For valuable broadleaves and silver fir, site specific conditions play an important role in tree growth, while oaks and Scots pine have less site-specific demands and wider ecological amplitudes. Finally, in comparison to BAI models from similar studies, the presented RF model showed similar accuracy and could potentially be used as a tool in forest management practices and for making professionally informed decisions.
COBISS.SI-ID: 29906947
Forest growth models are important for forest managers to understand the dynamics of forest stands and simulate stand development under different silvicultural strategies. We present the parameterization and development of matrix population models coupled with cutting optimization to schedule optimal management regimes for certain management objectives. To parameterize the models, we studied diameter and height growth of trees, survival rate and ingrowth of trees in uneven- aged forests in Slovenia. Data from permanent sample plots (n=3183) with measurements of trees were used to estimate the matrix model equation parameters. Diameter of trees, stand basal area, basal area of larger trees, tree species, forest type and selected topographic variables were tested as possible predictors for the models of diameter and height growth, mortality and ingrowth. We present two parametric log-logistic distribution of ingrowth which accounts for the general rule that the number of recruits decreases with increasing stand density, but it also considers that recruitment is possible only at a minimum stand density representing continuous cover of mature stands with seed trees. Such a function may be more realistic for shade tolerant species than commonly used functions for recruitment which assume a monotonous decrease of recruitment with increasing basal area, while, in an extreme case, it can also be parameterized to show monotonously decreasing ingrowth with increasing basal area by setting scale parameter 1. We compare our regression models to other models of plant life stages dynamics. Finally, the application for uneven-aged management is discussed.
COBISS.SI-ID: 5265318
Growth of individual trees – in diameter, basal area or volume – is often highly diverse. Silver fir was recognized as a tree species with highly variable basal area growth. Its growth in the 1970s and 1980s was relatively low due to fir dieback. However, in the past 20-30 years a recovery of silver fir has been observed and its growth has increased noticeably. In the SE Europe studies of basal area growth of dominant silver fir trees after their recovery on different sites across larger area are missing. Thus we aimed to analyze it in relation to elevation and exposition (warmer / colder sites), parent material and soil acidity (silicate / carbonate), stand structure (evenaged / unevenaged), and stand density (stand basal area), but also in relation to individual tree dbh. We applied some basic statistics to test the differences in silver fir growth between categories of each factors, while the mutual influence of these factors was analyzed by the mixed effects modelling. We conducted our study in Slovenia, including ) 62.000 dominant silver fir trees registered and measured on permanent forest inventory sampling plots (500 m2 each). Mean basal area increment of dominant silver fir trees was 28.2 cm2/y. Diameter increments were very similar up to tree dbh of 65 cm (0.43-0.44 cm/y), but increased with thicker trees (up to 0.56 cm/y). Basal area increments increased constantly with dbh, but more sharply with trees of 65 cm in dbh and more. Basal area increments differed significantly along the elevation gradient, while exposition did not affect it significantly. Silver fir was found to grow better on silicate bedrock (acidic soils) and colder sites. Silver fir (diameter and) basal area growth is high even at its late age and large thickness. We could not determine the culmination of increment in relation to their dbh with trees up to 100 cm in dbh (over 200 y old). Findings, thus, suggest that silver fir is reasonable to be managed up to large dimensions, especially if compared to some species admixed with silver fir (e.g. Norway spruce, European beech, sycamore maple), but differences between sites must be highly considered.
COBISS.SI-ID: 5417638