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Mixed mountain forests with an uneven-aged structure are characterized by a high tree-growth variability making traditional age-dependent growth models inapplicable. Estimating site productivity is yet another impediment for modelling tree growth in such forests. Uneven-aged mixed-stand forests are known for their high resilience, resistance and productivity, and are being promoted as a suitable alternative to even-aged, pure plantations for climate change adaptation and mitigation. However, their growth must be accurately measured and predicted, but diameter at the breast height (dbh) increment models specifically designed for uneven-aged mixed mountain forests are still rare. Using permanent sampling network data and 465 increment cores, we built two age-independent dbh increment ($${i}_{d}$$ i d ) models for the main species of the study area, namely Norway spruce (Picea abies (L.) Karst.), silver fir (Abies alba Mill.) and European beech (Fagus sylvatica L.). Mixed effects models and the algebraic difference approach were employed to develop $${i}_{d}$$ i d models based on empirical and commonly used theoretical growth functions. A past growth index was further developed and introduced in the model in order to explain the $${i}_{d}$$ i d variability. Several mixed effects calibration strategies were assessed in order to obtain the most accurate localized curve for new plots. Tree size, competition and biogeoclimatic variables were found to explain the $${i}_{d}$$ i d through the empirical growth function, while the growth index significantly improved the theoretical growth function for Norway spruce. The optimization of the calibration strategy for the mixed effects modelling framework enables the growth index implementation in forest practice as an accurate method for estimating site productivity. The accuracy of the two $${i}_{d}$$ i d models was similar: the root mean squared error of the empirical growth function varied between 0.940 and 1.042 cm for spruce, beech and fir, while the root mean squared error obtained through the theoretical growth function for spruce only was 1.105 cm. The basal area increment prediction at the plot level based on the theoretical growth function reached a root mean squared error of 0.043 m2 while using the empirical growth function the root mean squared error is 0.047 m2. The high accuracy obtained using age-independent models underlines their suitability for predicting growth in mixed uneven-aged forests. The developed models can be easily integrated into forest practice to accurately obtain $${i}_{d}$$ i d estimates.

18 Päg. Departamento de Medio Ambiente y Agronomía​, The structure and functioning of temperate forests are shifting due to changes in climate. Foreseeing the trajectory of such changes is critical to implementing adequate management practices and defining long-term strategies. This study investigated future shifts in temperate forest species composition and abundance expected to occur due to climate change. It also identified the ecological mechanisms underpinning such changes. Using an altitudinal gradient in the Romanian Carpathian temperate forests encompassing several vegetation types, we explored forest change using the Landis-II landscape model coupled with the PnET ecophysiological process model. We specifically assessed the change in biomass, forest production, species composition and natural disturbance impacts under three climate change scenarios, namely, RCP 2.6, 4.5 and 8.5. The results show that, over the short term (15 years), biomass across all forest types in the altitudinal gradient will increase, and species composition will remain unaltered. In contrast, over the medium and long terms (after 2040), changes in species composition will accelerate, with some species spreading (e.g., Abies alba Mill.) and others declining (e.g., Fagus sylvatica L.), particularly under the most extreme climate change scenario. Some forest types (e.g., Picea abies (L.) karst forests) in the Southern Carpathians will notably increase their standing biomass due to climate change, compared to other types, such as Quercus forests. Our findings suggest that climate change will alter the forest composition and species abundance, with some forests being particularly vulnerable to climate change, e.g., F. sylvatica forests. As far as productivity and forest composition changes are concerned, management practices should accommodate the new conditions in order to mitigate climate change impacts., This work was supported financially by EO-ROFORMON project, ID P_37_651/SMIS 105058 and PN 19070101

Height-diameter (H-D) models are important tools for forest management practice. Sandy Mongolian pine plantations (Pinus sylvestris var. mongolica) are a major component of the Three-North Afforestation Shelterbelt in Northern China. However, few H-D models are available for Mongolian pine plantations. In this paper we compared different equations found in the literature for predicting tree height, using diameter at breast height and additional stand-level predictor variables. We tested if the additional stand-level predictor variable is necessary to produce more accurate results. The dominant height was used as a stand-level predictor variable to describe the variation of the H-D relationship among plots. We found that the basic mixed-effects H-D model provided a similar predictive accuracy as the generalized mixed-effects H-D model. Moreover, it had the advantage of reducing the sampling effort. The basic mixed-effects H-D model calibration, in which the heights of the two thickest trees in the plot were included to calibrate the random effects, resulted in accurate and reliable individual tree height estimations. Thus, the basic mixed-effects H-D model with the above-described calibration design can be an accurate and cost-effective solution for estimating the heights of Mongolian pine trees in northern China.

Tree diameter measurements are repetitive, time-consuming, and laborious but necessary to obtain the diameter distribution of the stands. Tree diameter distribution provides much of the information necessary for sustainable management and can be predicted with high accuracy, thus saving time and financial resources. Permanent sample plots that belong to a permanent sampling network located in a protected area in the South Western Carpathians in Romania were used in this study. We compared two theoretical distribution functions and predicted or recovered their parameters using parameter prediction and parameter recovery methods. Five modeling approaches based on maximum likelihood and the method of moments were used to predict the diameter distribution of unmanaged mixed uneven-aged stands. Parameter recovery methods outperformed parameter prediction methods while the left-truncated Weibull distribution outperformed the complete Weibull distribution. The accuracy obtained by the best modeling approach measured by the relative root mean squared error (%RMSE) reaches up to 12.6% when the sums of the diameters are raised to the third power and only 0.02% and 4.8% for the sums of the second powers and the sum of the diameters respectively. This research is the first of this kind in Romania and can serve as an example of alternative solutions to the yield tables in estimating the volume of mixed uneven-aged stands and can be easily implemented into forest growth models to predict the diameter distribution in the absence of tree lists.

This study presents the biometric relationships among various increments that is useful in both scientific and practical terms for the silvicultural of silver fir. The increments recorded in the biometric characteristics of trees are a faithful indicator of the effect of silvicultural work measures and of environmental conditions. Knowing these increments, and the relationships among them, can contribute to adaptations in silvicultural work on these stands with the purpose of reducing risks generated by environmental factors. We carried an inventory based on tree increment cores. The sample size was determined based on both radial increment and height increment variability of the trees. The sample trees were selected in proportion to their basal area on diameter categories. Current annual height increment (CAIh) was measured on felled trees from mean tree category. For CAIh we generated models based on the mean tree height. Percentages of the basal area increment and of form-height increment were used to compute the current annual volume increment percentage (PCAIv). For the mean tree, the CAIh estimated through the used models had a root-mean-square error (RMSE) of 0.8749 and for the current annual volume increment (CAIv) the RMSE value was 0.1295. In even-aged stands, the mean current volume increment tree is a hypothetical tree that may have the mean basal area of all the trees and the form-height of the stand. Conclusions: The diameter, height, and volume increments of trees are influenced by structural conditions and natural factors. The structures comprising several generations of fir mixed with beech and other deciduous trees, which have been obtained by the natural regeneration of local provenances, are stable and must become management targets. Stable structures are a condition for the sustainable management of stands.

This study aims to present a comparison analysis of two data collection methods that can be used in order to obtain reference ground truth data for forestry – a conventional method that uses specific equipment such as Field Map system, caliper and vertex inclinometer and a modern method based on terrestrial laser scanning (TLS) technology. The research was conducted in six circular Permanent Plots (PPs) with an area of 500 squaremeters each, within thinning and selected cuttings stands of sessile oak (Quercus petraea (Matt.) Liebl.), common beech (Fagus sylvatica L.) and Norway spruce (Picea abies L. Karst.), all situated in the Southern Carpathians (Mihăești, Mușeteși and Vidraru Forest Districts). Using the conventional method, the dendrometric tree characteristics such as height, diameter at breast height (dbh) and tree position were directly recorded in thefield. As a modern method for data collection, a Faro Focus3D X 130 HDR terrestrial laser scanning device was used to scan each plot and to extract the dbh and height of the trees. In this regard, two scanning approaches were used - single scan (SS) and multiple scan (MS). In order to compare the two data acquisitions methods, we applied a Strengths, Weaknesses, Opportunities, Threats (SWOT) analysis on the basis of which we could establish the pros and cons of using the two methods. Therefore, one can choose the most advantageous method for obtaining the reference data for forestry, in terms of equipment acquisition cost, personnel skills and qualifications, data collection working time, accuracy of the data recorded, post processing time, labor costs. Although the use of TLS in forest inventory is a technology with high potential, further investigations need to be done, especially in the case of automatic extraction of the tree height. For accurate reference ground data for forest inventory purposes, we still recommend using the conventional methods although they are time consuming.

This study aimed to simulate oak and beech forest growth under various scenarios of climate change and to evaluate how the forest response depends on site properties and particularly on stand characteristics using the individual process-based model HETEROFOR. First, this model was evaluated on a wide range of site conditions. We used data from 36 long-term forest monitoring plots to initialize, calibrate, and evaluate HETEROFOR. This evaluation showed that HETEROFOR predicts individual tree radial growth and height increment reasonably well under different growing conditions when evaluated on independent sites. In our simulations under constant CO2 concentration ([CO2]cst) for the 2071-2100 period, climate change induced a moderate net primary production (NPP) gain in continental and mountainous zones and no change in the oceanic zone. The NPP changes were negatively affected by air temperature during the vegetation period and by the annual rainfall decrease. To a lower extent, they were influenced by soil extractable water reserve and stand characteristics. These NPP changes were positively affected by longer vegetation periods and negatively by drought for beech and larger autotrophic respiration costs for oak. For both species, the NPP gain was much larger with rising CO2 concentration ([CO2]var) mainly due to the CO2 fertilisation effect. Even if the species composition and structure had a limited influence on the forest response to climate change, they explained a large part of the NPP variability (44% and 34% for [CO2]cst and [CO2]var, respectively) compared to the climate change scenario (5% and 29%) and the inter-annual climate variability (20% and 16%). This gives the forester the possibility to act on the productivity of broadleaved forests and prepare them for possible adverse effects of climate change by reinforcing their resilience.

This study aims to investigate the combined use of two types of remote sensing data — ALS derived and digital aerial photogrammetry data (based on imagery collected by airborne UAV sensors) — along with intensive field measurements for extracting and predicting tree and stand parameters in even-aged mixed forests. The study is located in South West Romania and analyzes data collected from mixed-species plots. The main tree species within each plot are Norway spruce (Picea abies L. Karst.) and Beech (Fagus sylvatica L.). The ALS data were used to extract the digital terrain model (DTM), digital surface model (DSM) and normalized canopy height model (CHM). Object-Based Image Analysis (OBIA) classification was performed to automatically detect and separate the main tree species. A local filtering algorithm with a canopy-height based variable window size was applied to identify the position, height and crown diameter of the main tree species within each plot. The filter was separately applied for each of the plots and for the areas covered with Norway spruce and beech trees, respectively (i.e. as resulted from OBIA classification). The dbh was predicted based on ALS data by statistical Monte Carlo simulations and a linear regression model that relates field dbh for each tree species with their corresponding ALS-derived tree height and crown diameter. The overall RMSE for each of the tree species within all the plots was 5.8 cm for the Norway spruce trees, respectively 5.9 cm for the beech trees. The results indicate a higher individual tree detection rate and subsequently a more precise estimation of dendrometric parameters for Norway spruce compared to beech trees located in spruce-beech even-aged mixed stands. Further investigations are required, particularly in the case of choosing the best method for individual tree detection of beech trees located in temperate even-aged mixed stands.

Natural and anthropogenic disturbances pose a significant threat to forest condition. Continuous, reliable and accurate forest monitoring systems are needed to provide early warning of potential declines in forest condition. To address that need, state-of-the-art simulations models were used to evaluate the utility of C-, L- and P-band synthetic aperture radar (SAR) sensors within an integrated Earth-Observation monitoring system for beech, oak and coniferous forests in Romania. The electromagnetic simulations showed differentiated sensitivity to vegetation water content, leaf area index, and forest disturbance depending on SAR wavelength and forest structure. C-band data was largely influenced by foliage volume and therefore may be useful for monitoring defoliation. Changes in water content modulated the C-band signal by

Tree height measurements are laborious and require more time and effort compared to tree diameter measurements. That being the case, height-diameter (H-D) models are usually used to predict individual tree heights, which are necessary for estimating the tree volume and the site index, as well as for projecting the stand development over time. Using a permanent sampling network (400x400m) from Retezat National Park in Romania, twenty-one (H-D) functions were evaluated for their fit performance, sensitivity to outliers and prediction ability for Norway spruce in mixed uneven aged stands. A set of twenty-three stand variables, both spatial and non-spatial, were used to describe the stand structure, species inter-mingling and competition, in order to be used as stand predictors in a generalized H-D model. Nonlinear mixed effects model was used in modelling the H-D relationship of Norway spruce. We developed the first generalized height-diameter model in Romania using three stand predictors as measures of the stand vertical structure, density and competition. Random and fixed effects calibration techniques were compared, testing various sampling designs in order to improve the height prediction accuracy of the model on a new dataset. Measuring six trees around the median and the thickest tree gave the best result in calibrating both fixed and random effects. On average, the best calibration design increased the accuracy of the prediction by 50 cm compared to the fixed effects prediction. The use of the estimated coefficients and the calibration design will significantly decrease the amount of work done by forest management planners, while ensuring high accuracy and reducing costs.

Background and Purpose: Romania’s forests are of globally significant value due to their natural characteristics, as similar forests in some other parts of the world have been lost forever. These types of forests, so-called "virgin" and "quasi-virgin (old growth)" forests, are also identified in the Buzau Mountains, which are part of the Eastern Carpathians in Romania (Curvature Region). Materials and Methods: To study and understand the structure and dynamics of primeval forest, four permanent one-hectare research plots were installed in the Penteleu Mountains, part of the Buzau Mountains. All trees with a diameter at breast height (DBH) greater than 80 mm were measured and their main dendrometric characteristics (DBH, height and social position) registered. The forest structure was analysed by fitting different theoretical distribution functions (beta, gamma, gamma 3P, gamma 3P mixt, loglogistic 3p, lognormal 3P and Weibull 3p). The structural homogeneity of the permanent research plots was tested using the Camino index (H) and Gini index (G). Results: For the smaller DBH categories, Norway spruce was relatively shorter in height, but with increasing DBH, the heights of Norway spruce exceeded those of European beech. Stand volume varied between 615 and 1133 m3 per hectare. The area of maximum stability where we encountered the lowest tree height variability was recorded between the 60 cm and 100 cm diameter categories. The Lorenz curve and the Gini index indicated that the studied stands have high structural biodiversity. Conclusions: The results showed that the studied forests have an optimal structural diversity, assuring them a higher stability and multifunctionality. Thus, these forests are models for managed forests.