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The concept of ecosystem services and their valuation has gained significant attention in recent years due to the profound interdependence and interconnectedness between humans and ecosystems. As several studies on valuation of forest ecosystem services have stressed the human-nature interactions lately, in the research study area, the environmental conditions shows rapid changes while human pressures on forests intensify. Thus, the research questions are as follows: (i) what are the the monetary and non-monetary value of ecosystem services provided by forests in Piatra Craiului National Park and (ii) their relationship with other variables, focusing on identifying differences and resemblances between each approach. The R PASTECS package was utilized to analyze primary statistical indicators for both monetary and non-monetary values, revealing significant variability in the results (s% monetary 141% and s% non-monetary 62%). Both monetary and non-monetary assessments were computed at the management unit level and the data used was provided by the Forest Management plans and photograph analysis which have significant value as indicators of ecosystem services. The correlation between nature and culture was assessed through social-media based method, highly known to stimulate participant engagement while the quantitative data was assessed through forest data computation and PCA method for visualization. The research highlighted that, in monetary terms, the minimum value of identified ecosystem services was €34 and the maximum value exceeded €570,000 at management unit level and in non-monetary terms, the values ranged from 1 to 5 (kernel score). The research reveals a substantial variability in both types of valuations. Strong associations between certain variables (monetary value with carbon stock and stand volume), moderate connections (slope with stand productivity), and weaker relationships (non-monetary value with altitude, age with slope, type of flora with altitude, and altitude with stand productivity) were revealed. The findings provided valuable insights for policymakers, land managers, and stakeholders involved in natural resource management and conservation, emphasizing the importance of considering both economic and non-economic benefits in decision-making processes. The integrated approach of this study shows how we can better assess the mixed value of ecosystem services, contributing to the ongoing actions of raising awareness and social responsibility.

An excess of ozone (O3) is currently stressing plant ecosystems and may negatively affect the nutrient use of plants. Plants may modify leaf turnover rates and nutrient allocation at the organ level to counteract O3 damage. We investigated leaf turnover rate and allocation of primary (C, N, P, K) and secondary macronutrients (Ca, S, Mg) under various O3 treatments (ambient concentration, AA, with a daily hourly average of 35 ppb; 1.5 × AA; 2.0 × AA) and fertilization levels (N: 0 and 80 kg N ha−1 y−1; P: 0 and 80 kg N ha−1 y−1) in an O3-sensitive poplar clone (Oxford: Populus maximowiczii Henry × P. berolinensis Dippel) in a Free-Air Controlled Exposure (FACE) experiment. The results indicated that both fertilization and O3 had a significant impact on the nutrient content. Specifically, fertilization and O3 increased foliar C and N contents (+5.8% and +34.2%, respectively) and root Ca and Mg contents (+46.3% and +70.2%, respectively). Plants are known to increase the content of certain elements to mitigate the damage caused by high levels of O3. The leaf turnover rate was accelerated as a result of increased O3 exposure, indicating that O3 plays a main role in influencing this physiological parameter. A PCA result showed that O3 fumigation affected the overall allocation of primary and secondary elements depending on the organ (leaves, stems, roots). As a conclusion, such different patterns of element allocation in plant leaves in response to elevated O3 levels can have significant ecological implications.

With the intensification of the effects of climate change, the urgent need to address their drivers, especially greenhouse gas emissions, has become essential. In this context, forests offer a robust solution, with their potential to store and mitigate carbon emissions. However, striking a balance is critical given the significant economic contribution of the forestry and wood-based industries, which account for about 5% of Romania’s GDP and employ 6% (around 300 thousand) of its active workforce. This study, conducted in the Piatra Craiului National Park located in Romania’s Southern Carpathians, we utilize the EFISCEN application to generate three distinct 50-year forest evolution scenarios based on harvest intensity, namely Business As Usual (BAU), Maximum Intensity (MAX), and No Harvest (MIN), on two historical different managed forests, i.e., conservation and production. The study aims to guide forest owners in decision making with scenario modeling tools, with the objectives of assessing the forest carbon sequestration potential and evaluating the economic feasibility. In the most probable scenario, the BAU scenario, the growing stock increases from 2.6 million m3 to 3.8 million m3 over 50 years, with a more than 40% increase. Comparing the carbon stock change for all tree harvest scenario types indicates that the MIN scenario has the highest carbon sink capacity in the next 50 years; the BAU scenario is a well-balanced option between carbon sink and wood provision and has an optimal EUR 3.7 million in annual revenue. The MAX scenario can boost the growth and increase the annual revenue from wood by 35% but is effective only for a short time and thus has the smallest calculated revenue in time. Achieving a win–win relationship between carbon sequestration and wood supply is imperative, as well as good planning and scenarios to contribute to climate mitigation and also as provisions for local communities and to sustain the local economy.

Tropospheric ozone (O3) is a phytotoxic air pollutant and the O3-induced visible foliar injury (O3 VFI) is a biomarker. A recently developed Free-air O3 eXposure (FO3X) is a promising facility to verify field-observed “O3-like” VFIs and to establish a flux-based threshold for the O3 VFI onset. The present study compared O3-like VFI registered in the southern European forest sites with actual O3 VFI observed in a FO3X experiment. The O3-like VFIs were evaluated by eye in forests and thus it was subjective. According to the imaging analysis, we firstly demonstrated that major parts of the colors were similar in the field and the FO3X. The color pallets for O3 VFI was species-specific and considered a advanced tool for the O3 VFI diagnosis. In addition, we calculated a flux-based threshold for the O3 VFI onset at the FO3X based on a Phytotoxic Ozone Dose (POD1), which ranged from 4.9 to 18.1 mmol m−2 POD1. This FO3X-derived threshold partly explained but did not necessarily match with the observation for several tree species in actual forests. The multivariate analysis showed that O3 VFI was decreased by the presence of various species and suggested the importance of continuous monitoring activities in the field for the further analysis.

Climate change’s negative effects, such as rising global temperatures and the disruption of global ecological ecosystems as a direct effect of rising carbon emissions in the atmosphere, are a significant concern for human health, communities, and ecosystems. The condition and presence of forest ecosystems, especially those in peri-urban areas, play an essential role in mitigating the negative effects of climate change on society. They provide direct benefits to the residents of large cities and their surrounding areas, and they must be managed sustainably to protect all their component ecosystems. This research was carried out in the forests of Lunca Muresului Natural Park and Bazos Arboretum, located in the Romanian sector of the Pannonian Plain, near urban agglomerations. The results showed high variability in the stands. Using the height-to-diameter ratio indicator concerning dbh and species, a strong Pearson correlation was registered (between 0.45 and 0.82). These values indicate the high stability of these stands, providing positive human–nature interactions such as recreational or outdoor activities (and a complementary yet indirect use value through attractive landscape views). Protecting these ecosystems offers a so-called insurance policy for the next generations from a climate change standpoint.

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.

Understanding soil moisture and its relationship with different climatic and soil characteristics is essential for better analysing the interactions between forest and soil water dynamics, allowing us to more precisely predict climatic changes. The present paper investigates the temporal variability of soil moisture in three different forest ecosystems (LTER – long term ecological research site) with the same soil type (Eutric Cambisol). Soil moisture was measured daily from 2011 to 2016 by using three sensors at three different depths (20, 40, 70 cm). We identified the interactions between soil properties, vegetation type, local climatic conditions and soil moisture. In order to establish the temporal variability of the soil moisture content, we have applied two procedures, namely the Fourier series and the neural network fitting. A high variability in time and depth for soil volumetric water content was identified. The highest soil moisture levels were recorded at higher depths (70 cm) for almost all surfaces, with the exception of the Fundata surface because of the occurrence of limestone. In the mountainous areas, with higher precipitation (Fundata and Predeal sites), volumetric soil water content was mainly influenced by soil physical characteristics. Soil moisture levels below the drought level were only recorded for the Stalpeni site from September to October 2012. There was a delay between the precipitation event and soil humidification of 0.4-0.8 time units (days). We also found a significant correlation between soil moisture and soil texture and a weak correlation with vegetation type. Temperature influenced soil moisture levels at almost all depths, while precipitation only had an impact when there was a delay of 1 or 2 days. Our results can serve as a scientific base in the monitoring and analysing of soil moisture against the background of a changing climate.

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.

To verify the responses of visible foliar injury (VFI), we exposed seedlings of three oak species for 4.5 months in an open air facility, using differing ozone (O3) and drought treatments: O3 (three levels from ambient to ×1.4 ambient), and drought (three levels of irrigation from 40% to 100% field capacity). We related the accumulated phytotoxic O3 dose (POD1) and cumulative drought index (CDI) to the O3 and drought VFI and assessed growth increment (height, diameter, leaf number), biomass (of all organs), and physiological parameters: net photosynthesis per plant (Pn), photosynthetic nitrogen (PNUE) and phosphorus use efficiency (PPUE)). The results indicated that an increase in POD1 promoted O3 VFI in Quercus robur and Quercus pubescens, while Quercus ilex was asymptomatic. The POD1-based critical level at the onset of O3 VFI was lower for Q. robur than for Q. pubescens (12.2 vs. 15.6 mmol m−2 POD1). Interestingly, drought reduced O3 VFI in Q. robur but increased it in Q. pubescens. Both O3 and drought were detrimental to the plant biomass. However, Q. robur and Q. pubescens invested more in shoots than in roots, while Q. ilex invested more in roots, which might be related to a hormetic mechanism. Pn, PNUE and PPUE decreased in all species under drought, and only in the sensitive Q. robur (PPUE) and Q. pubescens (PNUE) under O3. This study confirms that POD1 is a good indicator to explain the development of O3 VFI and helps a differential diagnosis of co-occurring drought and O3 VFI in oak forests.

Atmospheric pollutants over the last century have led to increased negative impacts on the environment, especially on forest ecosystems. In the Baia Mare region of Romania, the influence of pollution on the neighboring forests of the municipality has been reported since 1970, and its negative effects have been reported mainly in the form of reduced tree growth, which implies significant losses of wood biomass. The objective of this study is to analyze the temporal and spatial effect of industrial pollution on the auxological processes of beech trees in this region. Quantification of auxological changes was performed by analyzing the resilience, recovery and resistance indices. The most intense negative effect of local pollution with heavy metal dusts, sulfur and nitrogen oxides, and sulfuric acid vapors, on the auxological processes of beech trees was found in the period 1960–1990, with a maximum in the period 1970–1980, when the mining activity was at its highest intensity. Beech trees responded to the negative effect of pollution by significantly reducing their growth during the period affected by local pollution, and after 1990 they resumed their auxological activity close to normal. In addition, it was noted that the index that best captures the effect of pollution over time is the resilience index. Tree growth resilience, recovery, and resistance assessment and analysis significantly contributes to our understanding of trees response to environment pollution more broadly creating also the base for strategic planning initiatives with valuable insight into the efforts of making the forests more resilient and resistant.

Dead wood (DW) is an important component of sustainable forest management and climate change mitigation. Three research plots (each with an area of 1 ha), located in virgin forests in the Southern Carpathians (Semenic P20, Retezat–Zănoaga, and Făgăraș–Șinca), were installed in order to study the synergies between DW and climate change mitigation effects. Data on the dendrometric characteristics of standing and lying DW, the species, and the degree of decay were recorded. The aboveground biomass (AGB) and carbon stock (CS) of the DW were also determined. The DW volume was between 48 m3·ha−1 and 148 m3·ha−1, with the total volume (dead and alive) ranging between 725 m3·ha−1 and 966 m3·ha−1. The DW volume distribution shows a decreasing trend, with the most suitable theoretical distributions for describing this being the lognormal, the 2P Weibull, and the 2P-Gamma. The AGB ranged between 17 t·ha−1 and 30 t·ha−1 and showed a decreasing trend according to altitude. The CS was between 8 t·ha−1 and 14.33 t·ha−1. A slow decomposition rate for the hardwood was identified by analyzing the relationship between the surface and volume of the DW. This highlighted the capacity of DW to store carbon for a long period of time.

Climate change, air pollution, urbanization, globalization, demographic changes and changing consumption patterns affect forests and their social, cultural, ecological and economic functions, resulting in consequences for the social value of forests and for people’s livelihoods, health and quality of life [...]

This study tested the ability of Sentinel-1 C-band to separate forest from other common land use classes (i.e., urban, low vegetation and water) at two different sites. The first site is characterized by temperate forests and rough terrain while the second by tropical forest and near-flat terrain. We trained a support vector machine classifier using increasing feature sets starting from annual backscatter statistics (average, standard deviation) and adding long-term coherence (i.e., coherence estimate for two acquisitions with a large time difference), as well as short-term (six to twelve days) coherence statistics from annual time series. Classification accuracies using all feature sets was high (>92% overall accuracy). For temperate forests the overall accuracy improved by up to 5% when coherence features were added: long-term coherence reduced misclassification of forest as urban, whereas short-term coherence statistics reduced the misclassification of low vegetation as forest. Classification accuracy for tropical forests showed little differences across feature sets, as the annual backscatter statistics sufficed to separate forest from low vegetation, the other dominant land cover. Our results show the importance of coherence for forest classification over rough terrain, where forest omission error was reduced up to 11%.

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.

At forest sites, phytotoxic tropospheric ozone (O3) can be monitored with continuously operating, active monitors (AM) or passive, cumulative samplers (PM). For the first time, we present evidence that the sustainability of active monitoring is better than that of passive sensors, as the environmental, economic, and social costs are usually lower in the former than in the latter. By using data collected in the field, environmental, social, and economic costs were analyzed. The study considered monitoring sites at three distances from a control station in Italy (30, 400, and 750 km), two forest types (deciduous and Mediterranean evergreen), and three time windows (5, 10, and 20 years of monitoring). AM resulted in more convenience than PM, even after 5 years, in terms of O3 depletion, global warming, and photochemical O3 creation potential, suggesting that passive monitoring of ozone is not environmentally sustainable, especially for long time periods. AM led to savings ranging from a minimum of EUR 9650 in 5 years up to EUR 94,796 in 20 years in evergreen forests. The resulting social cost of PM was always higher than that of AM. The present evaluation will help in the decision process for the set-up of long-term forest monitoring sites dedicated to the protection of forests from O3.

Forests play an important role in biodiversity conservation, being one of the main providers of ecosystem services, according to the Economics of Ecosystems and Biodiversity. The functions and ecosystem services provided by forests are various concerning the natural capital and the socio-economic systems. Past decades of remote-sensing advances make it possible to address a large set of variables, including both biophysical parameters and ecological indicators, that characterize forest ecosystems and their capacity to supply services. This research aims to identify and implement existing methods that can be used for evaluating ecosystem services by employing airborne and terrestrial stationary laser scanning on plots from the Southern Carpathian mountains. Moreover, this paper discusses the adaptation of field-based approaches for evaluating ecological indicators to automated processing techniques based on airborne and terrestrial stationary laser scanning (ALS and TLS). Forest ecosystem functions, such as provisioning, regulation, and support, and the overall forest condition were assessed through the measurement and analysis of stand-based biomass characteristics (e.g., trees’ heights, wood volume), horizontal structure indices (e.g., canopy cover), and recruitment-mortality processes as well as overall health status assessment (e.g., dead trees identification, deadwood volume). The paper, through the implementation of the above-mentioned analyses, facilitates the development of a complex multi-source monitoring approach as a potential solution for assessing ecosystem services provided by the forest, as well as a basis for further monetization approaches.

Research Highlights: Carpathian forests hold high ecological and economic value while generating conservation concerns, with some of these forests being among the few remaining temperate virgin forests in Europe. Carpathian forests partially lost their original integrity due to their management. Climate change has also gradually contributed to forest changes due to its modification of the environmental conditions. Background and Objectives: Understanding trees’ responses to past climates and forms of management is critical in foreseeing the responses of forests to future conditions. This study aims (1) to determine the sensitivity of Carpathian forests to past climates using dendrochronological records and (2) to describe the effects that climate change and management will have on the attributes of Carpathian forests, with a particular focus on the different response of pure and mixed forests. Materials and Methods: To this end, we first analysed the past climate-induced growth change in a dendrochronological reference series generated for virgin forests in the Romanian Curvature Carpathians and then used the obtained information to calibrate spatially explicit forest Landis-II models for the same region. The model was used to project forest change under four climate change scenarios, from mild to extreme. Results: The dendrochronological analysis revealed a climate-driven increase in forest growth over time. Landis-II model simulations also indicate that the amount of aboveground forest biomass will tend to increase with climate change. Conclusions: There are differences in the response of pure and mixed forests. Therefore, suitable forest management is required when forests change with the climate.

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.

While products generated at global levels provide easy access to information on forest growing stock volume (GSV), their use at regional to national levels is limited by temporal frequency, spatial resolution, or unknown local errors that may be overcome through locally calibrated products. This study assessed the need, and utility, of developing locally calibrated GSV products for the Romanian forests. To this end, we used national forest inventory (NFI) permanent sampling plots with largely concurrent SAR datasets acquired at C- and L-bands to train and validate a machine learning algorithm. Different configurations of independent variables were evaluated to assess potential synergies between C- and L-band. The results show that GSV estimation errors at C- and L-band were rather similar, relative root mean squared errors (RelRMSE) around 55% for forests averaging over 450 m3 ha−1, while synergies between the two wavelengths were limited. Locally calibrated models improved GSV estimation by 14% when compared to values obtained from global datasets. However, even the locally calibrated models showed particularly large errors over low GSV intervals. Aggregating the results over larger areas considerably reduced (down to 25%) the relative estimation errors.

The research aims to evaluate the impact of local industrial pollution on radial growth in affected Norway spruce (Picea abies (L.) Karst.) and silver fir (Abies alba Mill.) stands in the Tarnița study area in Suceava. For northeastern Romania, the Tarnița mining operation constituted a hotspot of industrial pollution. The primary processing of non-ferrous ores containing heavy metals in the form of complex sulfides was the main cause of pollution in the Tarnița region from 1968 to 1990. Air pollution of Tarnița induced substantial tree growth reduction from 1978 to 1990, causing a decline in tree health and vitality. Growth decline in stands located over 6 km from the pollution source was weaker or absent. Spruce trees were much less affected by the phenomenon of local pollution than fir trees. We analyzed the dynamics of resilience indices and average radial growth indices and found that the period in which the trees suffered the most from local pollution was between 1978 and 1984. Growth recovery of the intensively polluted stand was observed after the 1990s when the environmental condition improved because of a significant reduction in air pollution.

The objective of this study was to analyze the efficiency of individual tree identification and stand volume estimation from LiDAR data. The study was located in Norway spruce [Picea abies (L.) Karst.] stands in southwestern Romania and linked airborne laser scanning (ALS) with terrestrial measurements through empirical modelling. The proposed method uses the Canopy Maxima algorithm for individual tree detection together with biometric field measurements and individual trees positioning. Field data was collected using Field-Map real-time GIS-laser equipment, a high-accuracy GNSS receiver and a Vertex IV ultrasound inclinometer. ALS data were collected using a Riegl LMS-Q560 instrument and processed using LP360 and Fusion software to extract digital terrain, surface and canopy height models. For the estimation of tree heights, number of trees and tree crown widths from the ALS data, the Canopy Maxima algorithm was used together with local regression equations relating field-measured tree heights and crown widths at each plot. When compared to LiDAR detected trees, about 40-61% of the field-measured trees were correctly identified. Such trees represented, in general, predominant, dominant and co-dominant trees from the upper canopy. However, it should be noted that the volume of the correctly identified trees represented 60-78% of the total plot volume. The estimation of stand volume using the LiDAR data was achieved by empirical modelling, taking into account the individual tree heights (as identified from the ALS data) and the corresponding ground reference stem volume. The root mean square error (RMSE) between the individual tree heights measured in the field and the corresponding heights identified in the ALS data was 1.7-2.2 meters. Comparing the ground reference estimated stem volume (at trees level) with the corresponding ALS estimated tree stem volume, an RMSE of 0.5-0.7 m3 was achieved. The RMSE was slightly lower when comparing the ground reference stem volume at plot level with the ALS-estimated one, taking into account both the identified and unidentified trees in the LiDAR data (0.4-0.6 m3).

Spaceborne remote sensing can track ecosystems changes thanks to continuous and systematic coverage at short revisit intervals. Active remote sensing from synthetic aperture radar (SAR) sensors allows day and night imaging as they are not affected by cloud cover and solar illumination and can capture unique information about its targets. However, SAR observations are affected by the coupled effect of viewing geometry and terrain topography. The study aims to assess the impact of global digital elevation models (DEMs) on the normalization of Sentinel-1 backscattered intensity and interferometric coherence. For each DEM, we analyzed the difference between orbit tracks, the difference with results obtained with a high-resolution local DEM, and the impact on land cover classification. Tests were carried out at two sites located in mountainous regions in Romania and Spain using the SRTM (Shuttle Radar Topography Mission, 30 m), AW3D (ALOS (Advanced Land Observation Satellite) World 3D, 30 m), TanDEM-X (12.5, 30, 90 m), and Spain national ALS (aerial laser scanning) based DEM (5 m resolution). The TanDEM-X DEM was the global DEM most suitable for topographic normalization, since it provided the smallest differences between orbital tracks, up to 3.5 dB smaller than with other DEMs for peak landform, and 1.4–1.9 dB for pit and valley landforms.

Research Highlights: The present study case investigates the differences occurring when tree’s biophysical parameters are extracted through single and multiple scans. Scan sessions covered mountainous and hill regions of the Carpathian forests. Background and Objectives: We focused on analyzing stems, as a function of diameter at breast height (DBH) and the total height (H), at sample plot level for natural forests, with the purpose of assessing the potential for transitioning available methodology to field work in Romania. Materials and Methods: We performed single and multiple scans using a FARO Focus 3D X130 phase shift terrestrial laser scanner at 122 kpts and 0.3:0.15 mm noise compression ratio, resulting in an average point density of 6pts at 10m. The point cloud we obtained underpinned the DBH and heights analysis. In order to reach values similar to those measured in the field, we used both the original and the segmented point clouds, postprocessed in subsamples of different radii. Results: Pearson’s correlation coefficient above 0.8 for diameters showed high correlation with the field measurements. Diameter averages displayed differences within tolerances (0.02 m) for 10 out of 12 plots. Height analysis led to poorer results. For both acquisition methods, the values of the correlation coefficient peaked at 0.6. The initial hypothesis that trees positioned at a distance equivalent to their height can be measured more precise, was not valid; no increase in correlation strength was visible for either heights or diameters as the distance from scanner varied (r = 0.52). Conclusions: With regard to tree biophysical parameters extraction, the acquisition method has no major influence upon visible trees. We emphasize the term “visible”, as an increase in the number of acquisitions led to an increased number of detected trees (16% in old stands and 29% in young stands).

The paper presents information on the Conference.

Forests provide essential benefits and services as an important component of terrestrial ecosystems. Their functionality and health result from multiple and cumulative interactions of biotic and abiotic stress factors such as air pollution, climate change, changes in land use, and poor management practices. A forest monitoring system was established to identify, analyse and assess the degradation of European forests. Two levels of forest monitoring were developed: I) large-scale forest condition surveys, based on an European grid system starting in 1986 and II) an intensive non-systematic survey network placed in representative forest ecosystems starting in 1994. Romania implemented both level I (1990-1991) and level II (1991-1992) forest monitoring surveys with the results showing the effects of increased air temperatures and a drastic decrease of precipitation since the decade of 1971-1980. Thus, the highest values of damaged trees (crown defoliation >25%) percent were recorded in 1993, 1994, 2000 and 2003 both in the national and European networks. Also, in southern and South-Eastern Romania the forests are more frequently damaged as a response to worsening of climatic factors in this region in recent decades, with temperatures rising 0.7-0.8°C. In general, in Romania, ozone concentrations remained below the critical threshold (40-50 ppb) for affecting growth or health of trees. The levels of S-SO4 and N-NO3 declined in the atmosphere but the accumulation continued to increase in the soil, leading to soil acidification, mainly at depths of 10-40 cm). In general, during the last decade, Romanian forests were affected at low to medium intensities with damage rate up to 11% of the trees and the status of general forest health improved slightly.

Oaks are among the most important broad-leaved species in Romanian forests from both an economic and socio-ecological point of view. A significant decline of these species has been observed, which was first evident in various studies and investigations followed by the more results of interdisciplinary research performed in intensive monitoring plots (level II) showing that the decline is climate induced. Thus, it is important to understand the climate change conditions and factors that influence Quercus spp. Typical dendroclimatological investigations were conducted on an intensive forest monitoring network based on four oak species (Q. robur, Q. petraea, Q.cerris, and Q. frainetto) in 7 permanent plots placed in southern Romania. Three patterns of climate-growth relationships were identified and discerned in accordance with the Quercus species. All oak species were found to have a positive correlation with the level of precipitation. In addition, the intensity and level of significance of correlation coefficients differ from one species to another and from one region to another.