Harvendusraietel toimunud metsaõigusnormide rikkumise juhtumite hindamine

Three cases of violation of forest management regulations in Estonia in 2004, 2005 and 2007 are presented in the study where the required lower limit of basal area after thinnings was not followed. These stands were revisited in 2017 to assess the impacts of such thinnings. The actual thinnings were well justified from the silvicultural and economic viewpoints. All three stands were ecologically in good condition in 2017. Also, all three stands had already reached the required age or dimensions allowing regeneration cutting in 2017. Forest management regulations on thinning did not work well in the studied cases and therefore some changes in the current regulations are necessary in Estonia.

Remote-sensing support for the Estonian National Forest Inventory, facilitating the construction of maps for forest height, standing-wood volume, and tree species composition

Since 1999, Estonia has conducted the National Forest Inventory (NFI) on the basis of sample plots. This paper presents a new module, incorporating remote-sensing feature variables from airborne laser scanning (ALS) and from multispectral satellite images, for the construction of maps of forest height, standing-wood volume, and tree species composition for the entire country. The models for sparse ALS point clouds yield coefficients of determination of 89.5–94.8% for stand height and 84.2–91.7% for wood volume. For the tree species prediction, the models yield Cohen's kappa values (taking 95% confidence intervals) of 0.69–0.72 upon comparing model results against a previous map, and values of 0.51–0.54 upon comparing model results against NFI sample plots. This paper additionally examines the influence of foliage phenology on the predictions and discusses options for further enhancement of the system.

Forest cover dynamics of the Bazoy Siberian pine (Pinus sibirica Du Tour) forest from 1915 to 2015

The article considers the long-term (100 years) dynamics of the forest cover of the southernmost unit of Siberian pine forests on the West Siberian plain. A key feature of forest management is that Siberian pine seeds are a valuable food product and, when cutting forests, this tree species, as a rule, is preserved. The basis of the experimental data was the material of the national forest inventories of 1915, 1974 and 2015 for a total area of 1,420.41 ha. During the period from 1915 to 2015, the forested area changed slightly (96.2 and 94.0%), while the share of Siberian pine stands increased significantly from 48.4 to 58.7%. Grassy Siberian pine forests (32.1%) of optimal age (120–140 years), which are characterised by the best seed productivity and the largest share of Siberian pine in the community (77%), predominate. Basically, human economic activity results in an increase in the area of Siberian pine stands, when deciduous stands with Siberian pine undergrowth are used for fuel and as building material. A decrease in the area of Siberian pine forests occurs mainly under the impact of fires. In the conflagrations of 1915–1920, 7 to 38% of silver birch forests have no Siberian pine undergrowth and are considered long-term secondary communities. In the remaining area, the proportion of Siberian pine undergrowth is 20–30% with a density of 800–1200 seedlings ha−1, which is sufficient for the natural formation of Siberian pine forests.

Decline of Fraxinus excelsior L. in parks of Saint Petersburg: Who is to blame – Hymenoscyphus fraxineus or Diplodia spp.?

The weakening and decline of European ash Fraxinus excelsior L. and other ash species have been recorded at different locations in the suburbs of Saint Petersburg, Russia. During the summer of 2019 and spring of 2020, samples from leaves, petioles, and shoots were collected from the weakened and declining ash trees in three parks in Pushkin and Gatchina and maintained in humid chambers to induce the fructification of fungi. In total, 30 taxa of micromycetes belonging to 23 genera were identified using methods of light microscopy. Hymenoscyphus fraxineus, a putative agent of ash dieback, was not recorded in the samples collected in the crowns of trees, but only on the petioles of the fallen leaves in spring. Out of all the micromycetes recorded, only coelomycetes from the genus Diplodia Fr. (in particular, D. mutila) can damage the branches of ash trees and, thus, be considered pathogenic. It is likely that H. fraxineus opens “the entry of infection” and Diplodia spp. cause the major weakening and decline of branches. The data obtained can significantly change our understanding of the causes of ash dieback and possible methods of ash stand preservation. The reason for the low pathogenicity and activity of H. fraxineus, as well as the possible role of ascomycetes Diplodia spp. in the dieback of ash stands requires further research.

Aerolaserskaneerimise kasutamine metsakorralduse alusena

In this summary, we give an overview of the application of airborne laser scanning (ALS) data for predicting the main forest inventory variables in Estonia. When Estonia being one of the few countries with wall-to-wall ALS availability, the need for applicable models for Estonian forests was imminent. Over the past decade, different studies have been carried out to develop models for standing wood volume, forest height, canopy cover, canopy base height, and methods for monitoring height growth and detect small-scale harvests. The main findings showed strong correlations for all the studied parameters and different methods utilizing low-density lidar data for practical forest inventory purposes. Options for using repea ted ALS measurements for continuous forest inventory are discussed.

Potential of ecological modelling and smart-drainage development for mitigating adverse effects of future global change-type droughts for the Estonian forest sector

Global change-type droughts will become more frequent in the future and threaten forest ecosystems around the globe. A large proportion of the Estonian forest sector is currently subject to artificial drainage, which could probably lead to negative feedbacks when water supply falls short because of high temperatures and low precipitation during future drought periods. In this short article, we propose a novel research perspective that could make use of already gathered data resources, such as remote sensing, climate data, tree-ring research, soil information and hydrological modelling. We conclude that, when applied in concert, such an assembled dataset has the potential to contribute to mitigation of negative climate change consequences for the Estonian forest sector. In particular, smart-drainage systems are currently a rare phenomenon in forestry, although their implementation into existing drainage systems could help maintain the critical soil water content during periods of drought, while properly fulfilling their main task of removing excess water during wet phases. We discuss this new research perspective in light of the current frame conditions of the Estonian forest sector and resolve some current lacks in knowledge and data resources which could help improve the concept in the future.

About the history of conflicts over urban forestry in Estonian towns

The article explores conflicts related to forests and parks of Estonian towns from the Middle Ages to the 1940s. A brief overview is first given of the development of urban forestry in Estonia. There are also cases where the loss of urban forests and the related problems that arose could have led to conflicts, but for certain reasons they did not emerge. The main focus of the research is on Tallinn and its nearby island of Naissaare and, to a lesser extent, on the town of Haapsalu. The cases with the probability of conflict are described on the example of Tallinn, Tartu and Pärnu. It is apparent that conflicts or preconditions for their emergence were caused by various reasons, both at the state and town level where local authorities and ownership relations played their role. But the causes of the conflicts can also be traced to the wider clash between military and political causes, economic development and the general public.

Microsatellite analysis of genetic diversity in Czech populations of European beech (Fagus sylvatica L.)

European beech (Fagus sylvatica L.) is one of the most important broadleaved tree species in Europe both ecologically and economically. Nowadays, in the Czech Republic, beech is underrepresented in forest tree species composition, and there are tendencies to increase its proportion. When reintroducing beech, genetic variability, along with other factors, play a key role. The main aim of this study was to evaluate the genetic diversity of ten selected indigenous beech populations across the Czech Republic. Two hundred and fifty individuals were genotyped on 21 polymorphic nuclear microsatellite markers, which were amplified using two newly assembled multiplexes. According to the results, observed heterozygosity (Ho ) among populations ranged from 0.595 to 0.654 and expected heterozygosity (He ) from 0.650 to 0.678. That is comparable with the findings in other European studies. The high discriminatory power of the assembled multiplexes was confirmed by calculating the Probability of Identity among both unrelated and related individuals. Principal Coordinate Analysis (PCoA) based on Nei's genetic distances revealed that there are genetic differences among populations resulting in three approximate clusters (geographically north, south-east, and south-west). Nevertheless, the results implicate that on a geographical scale of the Czech Republic, the distance is unlikely to be the primary driver of genetic differentiation.

An indirect approach to predict deadwood biomass in forests of Ukrainian Polissya using Landsat images and terrestrial data

Spatially explicit and consistent mapping of forest biomass is one of the key tasks towards full and appropriate accounting of carbon budgets and productivity potentials at different scales. Landsat imagery coupled with terrestrial-based data and processed using modern machine learning techniques is a suitable data source for mapping of forest components such as deadwood. Using relationships between deadwood biomass and growing stock volume, here we indirectly map this ecosystem compartment within the study area in northern Ukraine. Several machine learning techniques were applied: Random Forest (RF) for the land cover and tree species classification task, k-Nearest Neighbours (k-NN) and Gradient Boosting Machines (GBM) for the deadwood imputation purpose. Land cover (81.9%) and tree species classification (78.9%) were performed with a relatively high level of overall accuracy. Outputs of deadwood biomass mapping using k-NN and GBM matched quite well (8.4 ± 2.3 t·ha−1 (17% of the mean) vs. 8.1 ± 1.7 t·ha−1 (16% of the mean), respectively mean ± SD deadwood biomass stock), indicating a strong potential of ensemble boosters to predict forest biomass in a spatially explicit manner. The main challenges met in the study were related to the limitations of available ground-based data, thus showing the need for national statistical inventory implications in Ukraine.

Options for estimating horizontal visibility in hemiboreal forests using sparse airborne laser scanning data and forest inventory data

Horizontal visibility v in hemiboreal forest transects was measured in the field and then predicted, both from forest inventory (FI) data and from airborne laser scanning (ALS) data. Stand density N and mean diameter at breast height D were used as arguments in an FI predictive model assuming Poisson distribution of trees on a horizontal plane. It was found that a lack of FI data on forest regrowth and understorey trees caused v to be overestimated. Point cloud metrics of sparse ALS data from summer 2017 and spring 2019 were used as predictive variables for v in regression models. The best models were based on three variables: the 10th percentile of the point cloud height distribution, relative density of returns in a horizontal layer ranging 0.7–2.2 m above the ground, and canopy cover. The models had a coefficient of determination of up to 67% and a residual standard error of less than 25 m. In forests in which fertile soil produces rapid height growth of understorey woody vegetation after recent thinning, visibility was found to be substantially overestimated because the understorey was not detected by the lidar measurements.