Significant increase in natural disturbance impacts on European forests since 1950.

Over the last decades, the natural disturbance is increasingly putting pressure on European forests. Shifts in disturbance regimes may compromise forest functioning and the continuous provisioning of ecosystem services to society, including their climate change mitigation potential. Although forests are central to many European policies, we lack the long-term empirical data needed for thoroughly understanding disturbance dynamics, modeling them, and developing adaptive management strategies. Here, we present a unique database of >170,000 records of ground-based natural disturbance observations in European forests from 1950 to 2019. Reported data confirm a significant increase in forest disturbance in 34 European countries, causing on an average of 43.8 million m3 of disturbed timber volume per year over the 70-year study period. This value is likely a conservative estimate due to under-reporting, especially of small-scale disturbances. We used machine learning techniques for assessing the magnitude of unreported disturbances, which are estimated to be between 8.6 and 18.3 million m3 /year. In the last 20 years, disturbances on average accounted for 16% of the mean annual harvest in Europe. Wind was the most important disturbance agent over the study period (46% of total damage), followed by fire (24%) and bark beetles (17%). Bark beetle disturbance doubled its share of the total damage in the last 20 years. Forest disturbances can profoundly impact ecosystem services (e.g., climate change mitigation), affect regional forest resource provisioning and consequently disrupt long-term management planning objectives and timber markets. We conclude that adaptation to changing disturbance regimes must be placed at the core of the European forest management and policy debate. Furthermore, a coherent and homogeneous monitoring system of natural disturbances is urgently needed in Europe, to better observe and respond to the ongoing changes in forest disturbance regimes.

Diameter, height and species of 42 million trees in three European landscapes generated from field data and airborne laser scanning data.

Ecology and forestry sciences are using an increasing amount of data to address a wide variety of technical and research questions at the local, continental and global scales. However, one type of data remains rare: fine-grain descriptions of large landscapes. Yet, this type of data could help address the scaling issues in ecology and could prove useful for testing forest management strategies and accurately predicting the dynamics of ecosystem services. Here we present three datasets describing three large European landscapes in France, Poland and Slovenia down to the tree level. Tree diameter, height and species data were generated combining field data, vegetation maps and airborne laser scanning (ALS) data following an area-based approach. Together, these landscapes cover more than 100 000 ha and consist of more than 42 million trees of 51 different species. Alongside the data, we provide here a simple method to produce high-resolution descriptions of large landscapes using increasingly available data: inventory and ALS data. We carried out an in-depth evaluation of our workflow including, among other analyses, a leave-one-out cross validation. Overall, the landscapes we generated are in good agreement with the landscapes they aim to reproduce. In the most favourable conditions, the root mean square error (RMSE) of stand basal area (BA) and mean quadratic diameter (Dg) predictions were respectively 5.4 m 2.ha -1 and 3.9 cm, and the generated main species corresponded to the observed main species in 76.2% of cases.

Modelling bark thickness for Scots pine (Pinus sylvestris L.) and common oak (Quercus robur L.) with recurrent neural networks.

Variation of the bark depends on tree age, origin, geographic location, or site conditions like temperature and water availability. Most of these variables are characterized by very high variability but above of all are also affected by climate changes. This requires the construction of improved bark thickness models that take this complexity into account. We propose a new approach based on time series. We used a recurrent neural network (ANN) to build the bark thickness model and compare it with stem taper curves adjusted to predict double bark thickness. The data includes 750 felled trees from common oak and 144 Scots pine-trees representing dominant forest-forming tree species in Europe. The trees were selected across stands varied in terms of age and site conditions. Based on the data, we built recurrent ANN and calculated bark thickness along the stem. We tested different network structures with one- and two-time window delay and three learning algorithms-Bayesian Regularization, Levenberg-Marquardt, and Scaled Conjugate Gradient. The evaluation criteria of the models were: coefficient of determination, root mean square error, mean absolute error as well as graphical analysis of observed and estimated values. The results show that recurrent ANN is a universal approach that offers the most precise estimation of bark thickness at a particular stem height. The ANN recursive model had an advantage in estimating trees that were atypical for height, as well as upper and lower parts on the stem.

Biomonitoring of Mercury Contamination in Poland Based on Its Concentration in Scots Pine (Pinus sylvestris L.) Foliage.

This work evaluates current mercury (Hg) contamination in Poland, represented by the Hg concentrations in Scots pine foliage. Samples were collected over 295 investigation plots in monitoring grids throughout Poland, from pines aged between 12 and 147 years. Analyses were conducted with consideration of bioclimatic factors and soil properties. Concentrations in the pine foliage did not exceed the values characteristic of an ecosystem unaffected by industrial pollution, ranging from 0.0032 to 0.0252 mg kg-1 dry mass. However, pine stands located in western and central Poland, and in the northwest near the Baltic Sea, exhibited higher Hg concentrations in foliage than in eastern regions. Hg content in foliage depends on the mean temperature of the driest quarter, as well as on Hg content in soils. This indicates that the periods of drought observed in recent years in Poland may affect Hg concentrations in pine foliage.

Regional height growth models for Scots pine in Poland.

Site productivity remains a fundamental concern in forestry as a significant driver of resource availability for tree growth. The site index (SI) reflects the overall impact of all environmental factors that determine tree height growth and is the most commonly used indirect proxy for forest site productivity estimated using stand age and height. The SI concept challenges are local variations in climate, soil, and genotype-environmental interactions that lead to variable height growth patterns among ecoregions and cause inappropriate estimation of site productivity. Developing regional models allow us to determine forest growth and SI more appropriately. This study aimed to develop height growth models for the Scots pine in Poland, considering the natural forest region effect. For height growth modelling, we used the growth trajectory data of 855 sample trees, representing the Scots pine entire range of geographic locations and site conditions in Poland. We compared the development of regional height growth models using nonlinear-fixed-effects (NFE) and nonlinear-mixed-effects (NME) modelling approaches. Our results indicate a slightly better fit to the data of the model built using NFE approach. The results showed significant differences between Scots pine growth in natural forest regions I, II, and III located in northern Poland and natural forest regions IV, V, and VI in southern Poland. We compared the development of regional height growth models using NFE and NME modelling approaches. Our results indicate a slightly better fit to the data of the model built using the NFE approach. The developed models show differences in height growth patterns of Scots pines in Poland and revealed that acknowledgement of region as the independent variable could improve the growth prediction and quality of the SI estimation. Differences in climate and soil conditions that distinguish natural forest regions affect Scots pine height growth patterns. Therefore, extending this research to models that directly describe height growth interactions with site variables, such as climate, soil properties, and topography, can provide valuable forest management information.

Evaluating the effect of stand properties and site conditions on the forest reflectance from Sentinel-2 time series.

Forest stand reflectance at the canopy level results from various factors, such as vegetation chemical properties, leaf morphology, canopy structure, and tree sizes. These factors are dependent on the species, age, and health statuses of trees, as well as the site conditions. Sentinel-2 imagery with the high spatial, spectral, and temporal resolution, has enabled analysis of the relationships between vegetation properties and their spectral responses at large spatial scales. A comprehensive study of these relationships is needed to understand the drivers of vegetation spectral patterns and is essential from the point of view of remote sensing data interpretation. Our study aimed to quantify the site and forest parameters affecting forest stands reflectance. The analysis was conducted for common beech-, silver fir- and Scots pine-dominated stands in a mountainous area of the Polish Carpathians. The effect of stands and site properties on reflectance in different parts of the growing season was captured using the dense time series provided by Sentinel-2 from 2018-2019. The results indicate that the reflectance of common beech stands is mainly influenced by elevation, particularly during spring and autumn. Other factors influencing beech stand reflectance include the share of the broadleaved understory, aspect, and, during summer, the age of stands. The reflectance of coniferous species, i.e., Scots pine and silver fir, is mainly influenced by the age and stand properties, namely the crown closure and stand density. The age is a primary driver for silver fir stands reflectance changes, while the stand properties have a large impact on Scots pine stands reflectance. Also, the understory influences Scots pine stands reflectance, while there appears to be no impact on silver fir stands. The influence of the abovementioned factors is highly diverse, depending on the used band and time of the season.

The current state of environmental pollution with sulfur dioxide (SO2) in Poland based on sulfur concentration in Scots pine needles.

The current air pollution by SO2 due to anthropogenic pressure in Poland was assessed based on sulfur concentrations in pine needles (Pinus sylvestris L.). On 308 monitoring sample plots located in pine stands distributed across Poland, measurements were conducted in mineral soil layers (0-10 cm, 10-40 cm, 40-100 cm) and in the soil organic layer (+5-0 cm). Samples of Scots pine foliage (current-year needles) were then collected, and the sulfur concentration in these needles was determined. Based on these data, a map of the spatial variability of sulfur concentrations in pine needles was drawn. The mean sulfur concentration in the pine needles was 854.8 mg kg-1 in dry mass. Higher SO2 emissions were noted in regions influenced by industry, such as the Upper Silesia and regions under strong urban pressure. Sulfur concentrations in Scots pine needles were related to the stands' degrees of defoliation. A comparison of the current sulfur concentrations in pine needles from biomonitoring in 2015-2016 with those from previous biomonitoring (in 1983-1985, by Dmuchowski and Bytnerowicz (1995) showed that air quality has improved and SO2 emissions have decreased.

Tree species affects the concentration of total mercury (Hg) in forest soils: Evidence from a forest soil inventory in Poland.

This study was performed to test the hypothesis that tree species significantly affects mercury (Hg) sequestration in forest soils. We analyzed the effect of seven dominant tree species (Scots pine, black alder, Norway spruce, silver birch, deciduous oak, silver fir, and European beech on the concentrations and pools of Hg in a range of forest soils in Poland. We set up 277 sample plots representing dominant tree species in Poland. Soil samples were taken and analyzed for total Hg content, soil texture, and soil C and nitrogen (N) content. Concentrations of total Hg in forest soil (organic and mineral horizons) varied by several orders of magnitude as a result of natural variations in organic matter, sand content, and altitude. Spatial analysis revealed that maximum concentrations (mg kg-1) and stocks (mg m-2) of Hg were related to mountain stands at higher elevations with loamy soils and greater accumulation of soil organic matter. The stocks of Hg in the investigated soil profiles increased in the order of: pine (12 mg m-2) ≈ birch (15 mg m-2) < oak (21 mg m-2) ≈ alder (24 mg m-2) < beech (45 mg m-2) ≈ spruce (50 mg m-2) < fir (66 mg m-2). Simple analysis of variance suggested an important effect of dominant tree species on Hg concentrations and stocks in entire soil profiles, but multiple regression analysis showed that dominant tree species had a significant effect on accumulation of Hg in soil, but only in the organic horizon; in mineral soil the Hg was content was related to C content, soil texture and altitude. The organic horizon had greater accumulation of Hg under coniferous tree species (Scots pine, silver fir and Norway spruce) and European beech when compared with deciduous oak, black alder, and silver birch.

Effect of variable soil texture, metal saturation of soil organic matter (SOM) and tree species composition on spatial distribution of SOM in forest soils in Poland.

In this study we investigated the effect of fine (ϕ<0.05mm) fraction, i.e., silt+clay (FF) content in soils, site moisture, metal (Al and Fe) of soil organic matter (SOM) and forest species composition on the spatial distribution of carbon (C) pools in forest soils at the landscape scale. We established 275 plots in regular 200×200m grid in a forested area of 14.4km(2). Fieldwork included soil sampling of the organic horizon, mineral topsoil and subsoil down to 40cm deep. We analysed the vertical and horizontal distribution of soil organic carbon (SOC) stocks, as well as the quantity of physically separated fractions including the free light (fLF), occluded light (oLF) and mineral associated fractions (MAF) in the mineral topsoil (A, AE) horizons. Distribution of C in soils was predominantly affected by the variation in the FF content. In soils richer in the FF more SOC was accumulated in mineral horizons and less in the organic horizons. Accumulation of SOC in mineral soil was also positively affected by the degree of saturation of SOM with Al and Fe. The increasing share of beech influenced the distribution of C stock in soil profiles by reducing the depth of O horizon and increasing C stored in mineral soil. The content of FF was positively correlated with the content of C in MAF and fLF fractions. The content of oLF and MAF fractions was also positively influenced by a higher degree of metal saturation, particularly Al. Our results confirmed that Al plays an important role in the stabilization of SOM inside aggregates (CoLF) and as in CMAF fractions. We also found a significant, positive effect of beech on the CfLF and fir on the CoLF content.

Linking heavy metal bioavailability (Cd, Cu, Zn and Pb) in Scots pine needles to soil properties in reclaimed mine areas.

This work deals with bioaccumulation of Zn, Pb, Cu and Cd in foliage of Scots pine, grown on mine soils. Regression models were used to describe relationships between pine elements bioavailability and biological (dehydrogenase activity) and physico-chemical properties of mine soils developed at different parental rocks. Concentration of trace elements in post-mine ecosystems did not differ from data for Scots pine on natural sites. We conclude that, in this part of Europe in afforested areas affected by hard coal, sand, lignite and sulphur mining, there is no risk of trace element concentrations in mine soils. An exception was in the case of Cd in soils on sand quarry and hard coal spoil heap located in the Upper Silesia region, which was more due to industrial pressure and pollutant deposition than the original Cd concentration in parental rocks.