Phytoremediation capacity of hybrid aspen at sites affected by industry and agriculture.

Fast-growing Populus spp. are well-acknowledged to restore contaminated soils from heavy metals in industrial areas. Thus far, there is no knowledge about the phytoremediation capacity of Populus spp. plantations in hemiboreal Estonia conditions to restore industrially polluted areas. The objective of this study was to assess the soil contamination rate of heavy metals (As, Cd, Co, Cr, Cu, Fe, Mn, Mo, Ni, Pb and Zn) and their uptake by mature hybrid aspen (Populus tremula × Populus tremuloides Michx.) in plantations in different industrial pollution areas (e.g. cement factory, oil shale mining). For the reference, industrially polluted plantations were compared with the low pollution area hybrid aspen plantation on former agricultural soil, which was influenced by fertilization and liming before afforestation. Twenty-one years after afforestation, soil samples were collected from the 0-10 cm topsoil layer. Aboveground biomass sampling was performed for bark and stem wood by ingrowth cores to separate wood formed during early (1-10 years) and late (11-21 years) stand development. Two decades after the afforestation of industrially polluted areas, the heavy metal concentrations in the soil were higher than the reference plantation and the standard reference for unpolluted soils in most cases. The highest concentrations of heavy metals in woody biomass were in the oil shale quarry spoil; because of poor growth, the accumulated pools in aboveground biomass were low. Cd differed from other metals and accumulated less in wood and more in bark. The concentration of heavy metals (Cd, Cr, Cu, Fe, Mn, Ni and Zn) was higher in the first decade of stand formation (1-10 years) than in the last 10 years (11-21 years). High pools of heavy metals were accumulated in aboveground biomass in the reference plantation, indicating the considerable removal of heavy metal residues from the previous fertilization and liming source with harvest. Two decades of afforestation with hybrid aspen is too short for complete ecosystem restoration from heavy metals in industrially polluted areas.

Incorporating high-resolution climate, remote sensing and topographic data to map annual forest growth in central and eastern Europe.

To enhance our understanding of forest carbon sequestration, climate change mitigation and drought impact on forest ecosystems, the availability of high-resolution annual forest growth maps based on tree-ring width (TRW) would provide a significant advancement to the field. Site-specific characteristics, which can be approximated by high-resolution Earth observation by satellites (EOS), emerge as crucial drivers of forest growth, influencing how climate translates into tree growth. EOS provides information on surface reflectance related to forest characteristics and thus can potentially improve the accuracy of forest growth models based on TRW. Through the modelling of TRW using EOS, climate and topography data, we showed that species-specific models can explain up to 52 % of model variance (Quercus petraea), while combining different species results in relatively poor model performance (R2 = 13 %). The integration of EOS into models based solely on climate and elevation data improved the explained variance by 6 % on average. Leveraging these insights, we successfully generated a map of annual TRW for the year 2021. We employed the area of applicability (AOA) approach to delineate the range in which our models are deemed valid. The calculated AOA for the established forest-type models was 73 % of the study region, indicating robust spatial applicability. Notably, unreliable predictions predominantly occurred in the climate margins of our dataset. In conclusion, our large-scale assessment underscores the efficacy of combining climate, EOS and topographic data to develop robust models for mapping annual TRW. This research not only fills a critical void in the current understanding of forest growth dynamics but also highlights the potential of integrated data sources for comprehensive ecosystem assessments.

Growth responses of Scots pine to climatic factors on reclaimed oil shale mined land.

Afforestation on reclaimed mining areas has high ecological and economic importance. However, ecosystems established on post-mining substrate can become vulnerable due to climate variability. We used tree-ring data and dendrochronological techniques to study the relationship between climate variables and annual growth of Scots pine (Pinus sylvestris L.) growing on reclaimed open cast oil shale mining areas in Northeast Estonia. Chronologies for trees of different age classes (50, 40, 30) were developed. Pearson's correlation analysis between radial growth indices and monthly climate variables revealed that precipitation in June-July and higher mean temperatures in spring season enhanced radial growth of pine plantations, while higher than average temperatures in summer months inhibited wood production. Sensitivity of radial increment to climatic factors on post-mining soils was not homogenous among the studied populations. Older trees growing on more developed soils were more sensitive to precipitation deficit in summer, while growth indices of two other stand groups (young and middle-aged) were highly correlated to temperature. High mean temperatures in August were negatively related to annual wood production in all trees, while trees in the youngest stands benefited from warmer temperatures in January. As a response to thinning, mean annual basal area increment increased up to 50 %. By managing tree competition in the closed-canopy stands, through the thinning activities, tree sensitivity and response to climate could be manipulated.