Afforestation and reforestation in Romania: History, current practice and future perspectives

Preserving forest legacy was an important objective throughout Romanian history and so is today. Artificial forest regeneration (including both reforestation and afforestation) was widely used to ensure the forest continuity, following forest harvesting, or to create new forests on non-forest lands. As Romania has undergone various political changes that affected the socio-economic environment, these changes also left significant marks on forest cover dynamics. In this paper, we chronologically present the historical initiatives to preserve and increase forest cover in Romania, the current practices, available funding and future perspectives on artificial forest regeneration. Increasing forest cover from the current level of 27% to, and beyond European average of 33% seems an ambitious target for Romania. However, that may be achievable if the sources of funding for afforestation would diversify and increase, the available funds would be more effectively accessed, national forestry regulations would be less bureaucratic and the guidelines on artificial forest regeneration would be up to date and less restrictive. The whole framework of forestation should be revised to comply with recent social, economic and environmental realities, and modern criteria and indicators for sustainable forest management should be explicitly included. The new goals should also be tailored to the changes regarding the property type, climate related trends and new requirements of the forest certification systems

The Variation Driven by Differences between Species and between Sites in Allometric Biomass Models

Background and Objectives: It is commonly assumed that allometric biomass models are species-specific and site-specific. However, the magnitude of species and site dependency in these models is not well-known. This study aims to investigate the variation in allometric models (i.e., aboveground biomass predicted by diameter at breast height and tree height) that has originated from the differences between tree species and between sites, thereby contributing to a better understanding of species and site-specificity issue in these models. Materials and Methods: The study is based on two large biomass datasets of 4921 and 5199 trees, from Eurasia and Canada. Using a nested ANOVA model on relative aboveground biomass residuals (with species and site as random effects), the proportion of variance explained by species or site was assessed by means of Variance Partition Coefficient (VPC). Results: The proportion of variance explained by species (VPCspecies = 42.56%, SE = 6.10% for Dataset 1 and VPCspecies = 47.54%, SE = 6.07% for Dataset 2) was larger than that explained by site (VPCsite = 20.08%, SE = 3.35% for Dataset 1 and VPCsite = 8.27%, SE = 1.38% for Dataset 2). The proportion of variance explained by site decreased by 24%–44% and the proportion of variance explained by species changed only slightly, when height is included in the allometric biomass models (i.e., models based on diameter at breast height alone, compared to models based on diameter at breast height and tree height). Conclusions: Allometric biomass models were more species-specific than they were site-specific. Therefore, the species (i.e., differences between species) seems to be a more important driver of variability in allometric models compared to site (i.e., differences between sites). Including height in allometric biomass models helped reduce the dependency of these models, on sites only

Tree biomass allometry during the early growth of Norway spruce (Picea abies (L.) Karst) varies between pure stands and mixtures with European beech (Fagus sylvatica L.)

In this paper we report an investigation of how forest stand mixture may affect biomass allometric relationships in Norway spruce (Picea abies (L.) Karst). Analysis of aboveground biomass data was conducted for 50 trees. Twenty-five sample trees were from a pure Norway spruce stand and the remainder were taken from a mixed stand of Norway spruce with European beech (Fagus sylvatica L.). ANCOVA results demonstrated that individual tree biomass allometry of the pure stand significantly differed from that of the mixed stand. Allometric characteristics depended on the biomass component recorded and the type of biomass predictor used. When predicted by DBH and/or height, the total aboveground biomass of mixed stand trees was significantly less than that for pure stand ones. This ‘apparent’ lower aboveground biomass was attributed to the lower branch and needle biomass proportions of trees growing in mixed stands. The findings indicate that caution should be exercised when applying biomass allometric models developed from pure stands to predict tree biomass in mixed stands (and vice versa), as such data treatment may introduce significant bias

Afforestation and reforestation in Romania: History, current practice and future perspectives

Preserving forest legacy was an important objective throughout Romanian history and so is today. Artificial forest regeneration (including both reforestation and afforestation) was widely used to ensure the forest continuity, following forest harvesting, or to create new forests on non-forest lands. As Romania has undergone various political changes that affected the socio-economic environment, these changes also left significant marks on forest cover dynamics. In this paper, we chronologically present the historical initiatives to preserve and increase forest cover in Romania, the current practices, available funding and future perspectives on artificial forest regeneration. Increasing forest cover from the current level of 27% to, and beyond European average of 33% seems an ambitious target for Romania. However, that may be achievable if the sources of funding for afforestation would diversify and increase, the available funds would be more effectively accessed, national forestry regulations would be less bureaucratic and the guidelines on artificial forest regeneration would be up to date and less restrictive. The whole framework of forestation should be revised to comply with recent social, economic and environmental realities, and modern criteria and indicators for sustainable forest management should be explicitly included. The new goals should also be tailored to the changes regarding the property type, climate related trends and new requirements of the forest certification systems

Site-effects on biomass allometric models for early growth plantations of Norway spruce ( Picea abies (L.) Karst.)

Although it is commonly assumed that biomass allometric models are site specific, evaluations of site-effects are rarely undertaken. In this paper we develop biomass-allometric models to determine site influences. This study is based on data from 240 Norway spruce trees (Picea abies (L.) Karst.), growing in 24 early-growth plantations. A multilevel modelling approach was adopted and intraclass correlation was used to evaluate site effects. Results indicated that biomass allometric models were highly specific to sites and that, depending on the biomass component and the type of predictor adopted, some 33% and 86% of overall model variance could be attributed to forest stand effects. The remaining variance was attributable within stand variability. Stem biomass was the most site-specific biomass component whereas branch biomass was the least influenced by site effects. Diameter at collar height (D) was less site-specific than height (H) in predicting biomass. Using D and H within the same model as distinct predictors, although improving the model fit, increased the model site-specificity. However, when D and H were combined in one predictor expression (i.e. D2H), this reduced model site specificity, despite requiring fewer parameters than other models. This also compensated for undesirable collinearity effects amongst predictor variables. Furthermore, for the sampled diameter range, the site-specificity was mainly driven by biomass allocation pattern (to branches, needles and roots). The considerable between site variability of allometric relationships suggests that consideration of stand effects is essential for the robust prediction of biomass

A practical measure for determining if diameter (D) and height (H) should be combined into D2H in allometric biomass models

Tree diameter at breast height (D) and tree height (H) are often used as predictors of individual tree biomass. Because D and H are correlated, the combined variable D2H is frequently used in regression models instead of two separate independent variables, to avoid collinearity related issues. The justification for D2H is that aboveground biomass is proportional to the volume of a cylinder of diameter, D, and height, H. However, the D2H predictor constrains the model to produce parameter estimates for D and H that have a fixed ratio, in this case, 2.0. In this paper we investigate the degree to which the D2H predictor reduces prediction accuracy relative to D and H separately and propose a practical measure, Q-ratio, to guide the decision as to whether D and H should or should not be combined into D2H. Using five training biomass datasets and two fitting approaches, weighted nonlinear regression and linear regression following logarithmic transformations, we showed that the D2H predictor becomes less efficient in predicting aboveground biomass as the Q-ratio deviates from 2.0. Because of the model constraint, the D2H-based model performed less well than the separate variable model by as much as 12 per cent with regard to mean absolute percentage residual and as much as 18 per cent with regard to sum of squares of log accuracy ratios. For the analysed datasets, we observed a wide variation in Q-ratios, ranging from 2.5 to 5.1, and a large decrease in efficiency for the combined variable model. Therefore, we recommend using the Q-ratio as a measure to guide the decision as to whether D and H may be combined further into D2H without the adverse effects of loss in biomass prediction accuracy

Does Slope Aspect Affect the Aboveground Tree Shape and Volume Allometry of European Beech (Fagus sylvatica L.) Trees?

In mountainous or hilly areas, the slope aspect affects the amount of solar radiation, with direct consequences on species distribution and tree growth. However, little is known on how the tree shape and volume allometry may be affected by contrasting environmental conditions driven by the slope aspect. This study aims to investigate whether the slope aspect affects the aboveground tree shape and volume allometry of European beech (Fagus sylvatica L.) trees. We used the data of scanned trees from two plots located on south- and respectively north-facing slopes and, additionally, an inventory dataset containing measurements of diameter at breast height (D) and tree height (H). To investigate the differences in tree shape, we used analysis of covariance. However, to assess the differences in volume allometry, we first predicted the volume of each individual tree within the inventory dataset using either the south- or the north-facing slope volume model, and then performed a paired t-test on the plot estimates based on the two volume models. Since the uncertainty originating from allometric volume model predictions was likely to affect the results of the paired t-test, we performed a Monte-Carlo simulation to assess the rate of null hypothesis acceptance with the paired t-test. The results showed that trees growing on the north-facing slope were significantly thinner (p < 0.001), with a significantly longer branching system (p < 0.001) compared to those on the southfacing slope. Correspondingly, the volume estimates per unit of forest area based on the south- vs. north-facing slope allometric volume models were significantly different (p < 0.001). The estimates of total aboveground volume per unit of forest area based on the north-facing slope allometric models were significantly larger compared to those based on the south-facing slope volume models, a difference driven by the significantly larger branch and stem volume for the north-facing slope. These differences in estimates per unit of forest area were larger when based on allometric models that only used D as a predictor of aboveground tree volume. The rates of null hypothesis acceptance within the paired t-test were generally low. For total aboveground volume estimated by D and H, the acceptance rate was 1.79%. Nevertheless, only using D to predict tree volume, the rates of null hypothesis acceptance were lower (i.e., 0.1%), suggesting that addition of H as a predictor of tree volume partly explains the differences caused by the slope aspect on volume allometry, but not enough to offset the differences entirely. In conclusion, slope aspect has significantly affected the tree shape and volume allometry of European beech trees

Silvicultural Interventions Drive the Changes in Soil Organic Carbon in Romanian Forests According to Two Model Simulations

We investigated the effects of forest management on the carbon (C) dynamics in Romanian forest soils, using two model simulations: CBM-CFS3 and Yasso15. Default parametrization of the models and harmonized litterfall simulated by CBM provided satisfactory results when compared to observed data from National Forest Inventory (NFI). We explored a stratification approach to investigate the improvement of soil C prediction. For stratification on forest types only, the NRMSE (i.e., normalized RMSE of simulated vs. NFI) was approximately 26%, for both models; the NRMSE values reduced to 13% when stratification was done based on climate only. Assuming the continuation of the current forest management practices for a period of 50 years, both models simulated a very small C sink during simulation period (0.05 MgC ha(-1) yr(-1)). Yet, a change towards extensive forest management practices would yield a constant, minor accumulation of soil C, while more intensive practices would yield a constant, minor loss of soil C. For the maximum wood supply scenario (entire volume increment is removed by silvicultural interventions during the simulated period) Yasso15 resulted in larger emissions (-0.3 MgC ha(-1) yr(-1)) than CBM (-0.1 MgC ha(-1) yr(-1)). Under 'no interventions' scenario, both models simulated a stable accumulation of C which was, nevertheless, larger in Yasso15 (0.35 MgC ha(-1) yr(-1)) compared to CBM-CSF (0.18 MgC ha(-1) yr(-1)). The simulation of C stock change showed a strong "start-up" effect during the first decade of the simulation, for both models, explained by the difference in litterfall applied to each scenario compared to the spinoff scenario. Stratification at regional scale based on climate and forest types, represented a reasonable spatial stratification, that improved the prediction of soil C stock and stock change.Peer reviewe

The Influence of Age, Location and Soil Conditions on the Allometry of Young Norway Spruce (Picea abies L. Karst.) Trees

In this study the influence of tree’s age, location (i.e. latitude and altitude) and soil conditions (i.e. pH, humus content, carbon to nitrogen ratio, cation exchange capacity and percent base saturation) on tree allometry was investigated. The data was collected from 22 Norway spruce (Picea abies L. Karst) plantations located in Eastern Carpathians of Romania, aged between 4 and 15. From each plantation a soil sample and 10 trees were collected for soil chemical properties and biomass measurements, respectively. Root collar diameter (RCD) and height (H) based allometric equations were developed for total tree and vegetative organs of the tree (i.e. stem, branches, needles and roots). Furthermore, the interaction between the standardised residuals of these models and the tested factors was analysed. In order to account for the random effect of the clustered data, the mixed-effect modelling procedure was used. The results have shown no influence of these factors (age, location and soil conditions) on RCD based models, except for branches biomass model which was linked to soil carbon/nitrogen ratio. The H based models, however, were significantly influenced by latitude and soil cation exchange capacity as a consequence of H/RCD ratio change with these factors. The trees were more likely to allocate more to height growth when growing in higher latitudes or on soils with higher values of cation exchange capacity

Allometric Biomass Models for European Beech and Silver Fir: Testing Approaches to Minimize the Demand for Site-Specific Biomass Observations

In this paper, site-specific allometric biomass models were developed for European beech (Fagus sylvatica L.) and silver fir (Abies alba Mill.) to estimate the aboveground biomass in Șinca virgin forest, Romania. Several approaches to minimize the demand for site-specific observations in allometric biomass model development were also investigated. Developing site-specific allometric biomass models requires new measurements of biomass for a sample of trees from that specific site. Yet, measuring biomass is laborious, time consuming, and requires extensive logistics, especially for very large trees. The allometric biomass models were developed for a wide range of diameters at breast height, D (6−86 cm for European beech and 6−93 cm for silver fir) using a logarithmic transformation approach. Two alternative approaches were applied, i.e., random intercept model (RIM) and a Bayesian model with strong informative priors, to enhance the information of the site-specific sample (of biomass observations) by supplementing with a generic biomass sample. The appropriateness of each model was evaluated based on the aboveground biomass prediction of a 1 ha sample plot in Șinca forest. The results showed that models based on both D and tree height (H) to predict tree aboveground biomass (AGB) were more accurate predictors of AGB and produced plot-level estimates with better precision, than models based on D only. Furthermore, both RIM and Bayesian approach performed similarly well when a small local sample (of seven smallest trees) was used to calibrate the allometric model. Therefore, the generic biomass observations may effectively be combined with a small local sample (of just a few small trees) to calibrate an allometric model to a certain site and to minimize the demand for site-specific biomass measurements. However, special attention should be given to the H-D ratio, since it can affect the allometry and the performance of the reduced local sample approach