Forest Compartments Research Articles

Above‐ and below‐ground complementarity rather than selection drive tree diversity–productivity relationships in European forests

AbstractBiodiversity experiments have identified both complementarity and selection as important drivers of the relationship between biodiversity and ecosystem functioning. However, their relative importance in above‐ and below‐ground ecosystem compartments of mature forests remains yet to be explored.We adopted a trait‐based approach to partition biodiversity effects in above‐ and below‐ground complementarity and selection. This approach was based on canopy and root traits measured in single‐ and mixed‐species plots in mature forests across a European latitudinal gradient.We assessed the relative importance of above‐ and below‐ground selection and complementarity in driving the relationship between tree species diversity and above‐ground wood production. We used the expected values (based on the values measured in monocultures) of leaf area index (LAI) and fine root biomass as proxies for above‐ and below‐ground selection, whereas canopy packing and rooting depth variability were used as proxies for above‐ and below‐ground complementarity.Our results showed that tree species richness–wood production relationships were driven by above‐ and below‐ground complementarity (i.e. canopy packing and rooting depth variability), rather than selection. The proxies for selection were found to have a positive effect on wood production but were not affected by tree species richness.We concluded that above‐ground‐ but also the largely neglected below‐ground complementarity drives biodiversity–productivity relationships in mature forests. Our findings suggest that choosing tree species with complementary above‐ and below‐ground traits should be considered in afforestation and forest management to promote tree diversity and productivity in European forests.

Recovery of fruit-feeding butterfly communities in Budongo Forest Reserve after anthropogenic disturbance

Understanding of how biodiversity can recover after anthropogenic disturbances, such as selective logging, is important for planning conservation strategies for tropical forests and for more sustainable timber harvest regimes. However, the knowledge of insect community compositions in regenerating logged forests is still limited, especially in the Afrotropics. Here, we evaluated the recovery patterns of fruit-feeding butterfly communities in four different-aged secondary forest compartments and one primary forest compartment in the Budongo Central Forest Reserve, Uganda. In each compartment, butterflies were sampled monthly for five consecutive months in 2017 using traps baited with fermented bananas. A total of 3,778 individuals, representing 82 species (78 identified at the species level and four morphogroups) were recorded. The fruit-feeding butterfly community composition differed among forest compartments and study months. Fruit-feeding butterfly communities of the oldest 72-year-old secondary forest compartment were similar to the primary forest compartment. In the younger secondary forest compartments the seasonal variation was large; especially the communities of the “core” rainy season months were distinct from the communities in primary and oldest secondary forest. The majority of individuals captured from both primary and secondary forests represented forest-dependent species. Primary forests are irreplaceable for preserving the diversity of tropical forests in the long-term. Nevertheless, our study demonstrates that selective logging can allow fruit-feeding butterfly community composition to recover if enough time (>70 years) is allowed for recovery.

Spatial and compositional structure of European oak urban forests in Kyiv city, Ukraine

Forest dimensional structure and tree species composition strictly define ecosystem resilience, success of its functioning and development. Spatial structure of forest compartments provides an additional information on the forest stand heterogeneity. The aim of this study is to examine structural patterns (both spatial and nonspatial ones) in European oak (Quercus robur L.) urban forests located in Kyiv city, Ukraine. We compared two middle-aged (~ 80 years) and two mature (~ 180 years) oak stands in terms of structural metrics collecting a data from geo-referenced trees on the established permanent sample plots. Younger stands reached similar tree diameter diversity (9.07 and 10.45 vs. 11.42 and 14.05 of Shannon indices), while the compositional diversity was driven by the dominance of either oak or European hornbeam (Carpinus betulus L.). We have not found any differences in the species mingling and deadwood distribution indices except a clear occurrence pattern for the stand located near roads. Herewith, the largest distance between the plot and park pathways was an indicator of changed spatial variation and tree dimensional differentiation within one middle-aged stand. We hypothesize that human impacts can alter structural development in urban deciduous forests providing both positive (gap formation, deadwood occurrence and ecosystem complexity) and negative (shifts in compositional and successional trajectories) effects on such forest stands.

Evaluating five forest models using multi-decadal inventory data from mountain forests

Forest ecosystem models, being widespread science tools and used for forest management decision support are usually evaluated individually against field data sets, while model intercomparison and joint evaluation studies are rare. We tested five forest models according to a harmonized protocol against data from nine forest compartments in the Snĕžnik region, in Slovenia. The suite of models included stand- and landscape-scale, empirical- and process-based models used across Europe. The test dataset originated from inventory data covering 50 years (tree measurements 1963, 1983 and 2013) and included annual harvesting records at tree level. Uncertainties in data and forest conditions were considered by defining 12 scenarios varying initial regeneration, browsing pressure and harvest modalities. We evaluated the models` ability to initialize forest conditions accurately, whether management interventions could be implemented based on harvest records, and how well basal area and diameter structure could be predicted. Simulation results for basal area development showed good to satisfactory performance for all models, at which SAMSARA2, SIBYLA and PICUS showed the best agreement. Comparison of simulated and observed diameter distributions showed good performance of ForClim, PICUS, SAMSARA2 and SIBYLA. Model output variability was between 6% and 24%, indicating the relevance to consider uncertainties that can be attributed to specific sources. There was no clear hierarchy between more empirical or more process-based models regarding accuracy of stand development projections. The cohort-based landscape model LandClim showed the lowest stand-level accuracy and scenario sensitivity, but results nevertheless qualified it for complementary application at landscape scale. Within individual-based models, spatially explicit models seemed to be more suitable for heterogeneous mixed mountain forests. The findings demonstrated the usefulness of inventory datasets for model testing and intercomparison.

Asymbiotic nitrogen fixation in the phyllosphere of the Amazon forest: Changing nitrogen cycle paradigms

Biological nitrogen fixation is a key process for the maintenance of natural ecosystems productivity. In tropical forests, the contribution of asymbiotic nitrogen fixation (ANF) to the nitrogen (N) input has been underestimated, even though few studies have shown that ANF may be as important as symbiotic nitrogen fixation in such environments. The inputs and abiotic modulators of ANF in the Amazon forest are not completely understood. Here, we determined ANF rates and estimated the N inputs from ANF in the phyllosphere, litter and rhizospheric soil of nine tree species in the Amazon forest over time, including an extreme drought period induced by the El Niño–Southern Oscillation. Our data showed that ANF rates in the phyllosphere were 2.8- and 17.6-fold higher than in the litter and rhizospheric soil, respectively, and was highly dependent on tree taxon. Sampling time was the major factor modulating ANF in all forest compartments. At the driest period, ANF rates were approximately 1.8-fold and 13.1-fold higher than at periods with higher rainfall, before and after the extreme drought period, respectively. Tree species was a key modulator of ANF in the phyllosphere, as well as N and Vanadium concentrations. Carbon, molybdenum and vanadium concentrations were significant modulators of ANF in the litter. Based on ANF rates at the three sampling times, we estimated that the N input in the Amazon forest through ANF in the phyllosphere, litter and rhizospheric soil, was between 0.459 and 0.714 kg N ha−1 yr−1. Our results highlight the importance of ANF in the phyllosphere for the N input in the Amazon forest, and suggest that changes in the patterns of ANF driven by large scale climatic events may impact total N inputs and likely alter forest productivity.

Temporal Changes in Tree Species Composition in Karsog Area of Northwest Himalaya

ABSTRACT The forests of Karsog Forest Division in Himachal Pradesh were temporally analyzed for change in tree species composition. These are based on the species composition in different communities and variations along the different altitudinal gradients. The enumeration records were procured from the forest department. Total 143 forest compartments were analyzed to study the change in tree species in thirteen delineated communities, out of which six were pure forest communities and seven were mixed forest communities. The change in density (Ind/ ha) in tree species was calculated between two enumeration years, that is 1986and 2013. Results showed that out of thirteen communities, only three pure communities viz., Pinus roxburghii, Abies pindrow and Quercus leucotrichophora showed increased density while other pure communities showed decreased density in two enumeration years. Altitudinal based study revealed that the lowest altitudinal gradient (1000-2000 m) showed increase in tree density while in 2000-3000 m zone a gradual fall in tree density was observed temporally.

Risk assessment and prediction of forest health for effective geo-environmental planning and monitoring of mining affected forest area in hilltop region

This paper focuses on forest health risk (FHR) assessment and prediction in the mining-affected forest region using AHP model based on multi-criteria analysis in a GIS platform. We considered a total twenty-eight (twenty two present and six predicted) causative parameters including climate, natural or geomorphological, forestry, topographical, environmental, and anthropogenic. The assessment results of FHR show that of the total existing forest area, 2.85% area under very high, 13.63% high, 31.98% moderate, 32.68% low, and 18.87% are under very low categories. According to the assessment and prediction FHR results, the very high-risk classes were found at mines surrounding forest compartments. The sensitivity analysis showed that some factors were more sensitive to FHR. The correlation results showed a negative relationship between FHR and distance from mines and foliar dust concentration. This work will provide a basic guideline for effective planning and management in forestry studies for the mining-affected region.

Standard trees versus underwood: Historical patterns of tree taxon occurrence in coppice forests

AbstractQuestionsCoppice woods were once widespread in Europe. It is usually assumed that underwood tree taxon composition was not directly influenced by people, whereas especially Quercus was promoted among standard trees. However, no work has quantitatively tested these assumptions. Our main question was whether there were any patterns in our data to suggest that certain trees occurred more frequently as standards than as underwood, possibly as a result of management decisions.LocationCzech Republic.MethodsWe constructed a database covering 12,000 hectares of forests around AD 1900. We recorded the occurrence of tree taxa for standards and underwood in 1,507 compartments in 21 forest units. We visualised patterns in these data by bar graphs and chord diagrams. We analysed correlation patterns through association analysis and co‐correspondence analysis.ResultsThere was a statistically significant association between the occurrences of standards and underwood in individual compartments for Quercus, Alnus, Carpinus, Fagus, Larix, Populus tremula and Tilia. Only Quercus standards and underwood showed a positive association. The taxon composition of standards and underwood in forest compartments was statistically significantly correlated.ConclusionsNo simple answer can be given to the question whether or not the taxon composition of standards and underwood in coppice woods differed as a result of management. At the level of individual tree taxa, some trees were more common as standards while others, as underwood. However, the prevalence of Quercus among standards was not confirmed because in our study area Quercus was a common underwood tree as well. At the same time, no significant differences were apparent in the taxon composition of standards and underwood in individual forest compartments. It seems difficult to differentiate between the effects of human selection and indirect selection through natural properties and environmental factors. Our results also highlight the need to carefully consider the properties of written historical sources.

Sensitivity of PolSAR decomposition to forest disturbance and regrowth dynamics in a managed forest

Managed forests, dynamic with activities of harvest and afforestation, have become an area of imminent research opportunity to understand the effects of these disturbances and regrowth dynamics. As low frequency polarized radar signals have the ability to penetrate forest canopies, the fully polarized Synthetic Aperture Radar (SAR) data gives an ideal representation of conditions in the forest. However, this valuable information has not been optimally utilized in understanding the forest disturbances and regrowth dynamics. Several forest change monitoring studies have been performed using single or dual polarization SAR data, whereas limited studies utilized full polarimetric information. In this study, L-band ALOS/PALSAR and ALOS-2/PALSAR-2 fully polarimetric data is used to study and understand the behavioural dynamics of homogeneous and heterogeneous forest compartments having single and multiple species composition, respectively. Radar scattering pattern of different species, and its variation with respect to phenology, disturbances, harvesting and plantation regrowth are analysed to understand the trend in scattering components with respect to above said forest changes. Based on the scattering properties and their analyses, a two stage rule based classifier has been developed to categorize the forest based on its disturbance and regrowth status into disturbed, re-growth, stable/no change and non forest classes. The classifier performed with, considerably, high accuracy having an overall accuracy of 85.39% and a kappa coefficient of 0.8. The classifier developed in this work presents the potential of fully polarimetric data in understanding the level and extent of disturbances and regrowth dynamics of a forest.

Current status of asian elephant population <i> Elephas maximus </i> in Pumat National Park Region, Nghe An Province

Asian elephants are under high threats of extinction in Vietnam and worldwide. Population assessment of Asian elephants in Pumat National Park (NP) region, carried out in 2018−2019, showed that the wild Asian elephants population this region consisted of 3 groups with a total of 13−14 individuals. In Tuong Duong District, a group of 4-5 individuals lived in an area near Canh Ta stream (Tam Dinh commune, Vietnam) and Nam Xi stream (Muong Long commune, Laos), across the border between Vietnam and Laos. The group in Con Cuong district, with only one adult female, lived in forest compartments 780, 781,789 and 786 of Con Cuong Forestry Company, within the buffer zone of Pumat NP. The group in Anh Son district consisted of 8 individuals (5 adult females, 1 adult male, 1 sub-adult male and an juvenile born in 2016). They live in Cao Veu sector of Pumat NP core zone and buffer zone areas consisting of protected forests, rubber plantation forests and agricultural lands of households in Phuc Son Commune (Anh Son District) and Thanh Duc Commune (Thanh Chuong District).Wild Asian elephants in Pumat NP region are facing dangers of extinction due to their small number as well as direct and indirect threats from human. The elephant group in Anh Son district, with the largest number of individuals consisting of breeding males, breeding females and a calf, is the most important for the maintainance and future development of elephant population within Puman NP. However, they are facing a number of serious threats such as: un-controlled wildlife hunting and trade; rapid decrease and degradation of natural forest outside of Pumat National Park; and increasingly serious human-elephant conflicts.

The Accessibility of Post-Fire Areas for Mechanized Thinning Operations

In 1992, in Southern Poland, large areas of Silesian forests were affected by the country’s largest forest fire. Stands introduced in the 9000-ha post-fire region are currently undergoing early thinning. Due to the scope of these treatments, the chance for their timely implementation is ensured only by the application of cut-to-length (CTL) technologies, i.e., with the use of harvesters and forwarders. The use of CTL technologies may, however, be difficult due to the fire history of these stands, which could affect the bearing capacity of their soils. The objective of this study is to determine the accessibility of stands for forest machines in relation to the bearing capacity of the soils and changes in soil compaction in the post-fire sites. Soil compaction was measured in terms of penetrometer resistance in the stands introduced in the post-fire area in question, as well as in control stands growing on five different soil types. It was shown that in the topsoil layer—from 8 to 18 cm thick depending on the soil type—differences in soil compaction in the post-fire and control areas were relatively small. The impacts of the forest fire—manifested as a significant increase in the compaction of the forest soils—were still visible, but only in the deeper layers of the soil profile. In all of the compared pairs of forest compartments located in the stands regenerated after the fire, significantly higher values of cone indexes (CI) were found. The average value of this index in the post-fire stands was 2.15 MPa, while in the control stands it was 1.60 MPa, which indicates that in both groups of stands the bearing capacity of the soils should not limit the accessibility for vehicles used for timber harvesting and extraction.

Estimating soil organic carbon stocks under commercial forestry using topo-climate variables in KwaZulu-Natal, South Africa

Commercial forests are expanding globally, with great potential to absorb carbon and mitigate climate change. However, whereas the role of natural forests in carbon sequestration has been widely investigated, there is a paucity in the literature on the role of commercial forests in carbon assimilation. Hence, understanding the role of commercial forests in carbon storage is essential for quantifying local, regional or global carbon balances, which is valuable for climate change mitigation. Soil carbon is known to be the largest pool within any forest landscape, and is controlled by a wide range of physical and climatic factors. However, the relationship between soil organic carbon (SOC) and topo-climatic variables controlling its distribution within commercial forests is still poorly understood. Due to the limitations encountered in traditional systems of SOC determination, particularly at large spatial extents, geospatial techniques have recently emerged as a viable alternative for mapping soil properties. Therefore, this study sought to map SOC stocks variability within the commercial forest landscape, using landscape topo-climatic variables. A total of 81 soil samples was analysed for SOC concentrations and 31 topographic and climatic variables were used as predictors to SOC variability. To reduce multicollinearity, these variables were reduced to 11 using stepwise backward elimination and the maximum entropy (Maxent) algorithm was used for regression analysis to determine the relationship between SOC and the selected topo-climatic variables. Good accuracies were obtained for both training (area under the curve = 0.906) and test (area under the curve = 0.885) data sets, and demonstrate the effectiveness of selected topo-climatic variables and the Maxent algorithm in predicting SOC stocks. This study provides a framework for monitoring the status of soil carbon in commercial forest compartments and provides a viable approach for local, national or regional carbon accounting – valuable for climate change mitigation.
 Significance:
 
 Rainfall and temperature, as well as topographic variables (such as slope, elevation and topographic wetness index) are effective in mapping SOC distribution.
 The model developed is useful in predicting SOC occurrence and yielded an effective framework for continuous monitoring and assessment of SOC.
 The method developed in this study is cost-effective and suggests the use of other readily available climatic and topographic information for the prediction of SOC under commercial forestry in South Africa and indeed globally.
 Results from this study are important to achieve the national carbon accounting objective and are also valuable to forest managers, ecologists and relevant stakeholders in understanding the spatial distribution of SOC.

Trade-Offs Among Aboveground, Belowground, and Soil Organic Carbon Stocks Along Altitudinal Gradients in Andean Tropical Montane Forests.

Tropical montane forests (TMFs) play an important role as a carbon reservoir at a global scale. However, there is a lack of a comprehensive understanding on the variation in carbon storage across TMF compartments [namely aboveground biomass (AGB), belowground biomass (BGB), and soil organic matter] along altitudinal and environmental gradients and their potential trade-offs. This study aims to: 1) understand how carbon stocks vary along altitudinal gradients in Andean TMFs, and; 2) determine the influence of climate, particularly precipitation seasonality, on the distribution of carbon stocks across different forest compartments. The study was conducted in sixty 0.1 ha plots along two altitudinal gradients at the Podocarpus National Park (Ecuador) and Río Abiseo National Park (Peru). At each plot, we calculated the amount of carbon in AGB (i.e. aboveground carbon stock, AGC), BGB (i.e. belowground carbon stock, BGC), and soil organic matter (i.e. soil organic carbon stock, SOC). The mean total carbon stock was 244.76 ± 80.38 Mg ha–1 and 211.51 ± 46.95 Mg ha–1 in the Ecuadorian and Peruvian plots, respectively. Although AGC, BGC, and SOC showed different partitioning patterns along the altitudinal gradient both in Ecuador and Peru, total carbon stock did not change with altitude in either site. The combination of annual mean temperature and precipitation seasonality explained differences in the observed patterns of carbon stocks across forest compartments between the two sites. This study suggests that the greater precipitation seasonality of colder, higher altitudes may promote faster turnover rates of organic matter and nutrients and, consequently, less accumulation of SOC but greater AGC and BGC, compared to those sites with lesser precipitation seasonality. Our results demonstrate the capacity of TMFs to store substantial amounts of carbon and suggest the existence of a trade-off in carbon stocks among forest compartments, which could be partly driven by differences in precipitation seasonality, especially under the colder temperatures of high altitudes.

Predicting soil organic carbon stocks under commercial forest plantations in KwaZulu-Natal province, South Africa using remotely sensed data

ABSTRACT Commercial forest plantations are increasing globally, absorbing a large amount of carbon valuable for climate change mitigation. Whereas most carbon assimilation studies have mainly focused on natural forests, understanding the spatial distribution of carbon in commercial forests is central to determining their role in the global carbon cycle. Forest soils are the largest carbon reservoir; hence soils under commercial forests could store a significant amount of carbon. However, the variability of soil organic carbon (SOC) within forest landscapes is still poorly understood. Due to limitations encountered in traditional systems of SOC determination, especially at large spatial extents, remote sensing approaches have recently emerged as a suitable option in mapping soil characteristics. Therefore, this study aimed at predicting soil organic carbon (SOC) stocks in commercial forests using Landsat 8 data. Eighty-one soil samples were processed for SOC concentration and fifteen Landsat 8 derived variables, including vegetation indices and bands were used as predictors to SOC variability. The random forest (RF) was adopted for variable selection and regression method for SOC prediction. Variable selection was done using RF backward elimination to derive three best subset predictors and improve prediction accuracy. These variables were then used to build the RF final model for SOC prediction. The RF model yielded good accuracies with root mean square error of prediction (RMSE) of 0.704 t/ha (16.50% of measured mean SOC) and 10-fold cross-validation of 0.729 t/ha (17.09% of measured mean SOC). The results demonstrate the effectiveness of Landsat 8 bands and derived vegetation indices and RF algorithm in predicting SOC stocks in commercial forests. This study provides an effective framework for local, national or global carbon accounting as well as helps forest managers constantly evaluate the status of SOC in commercial forest compartments.

Fuel and lubricants consumption during timber felling and processing in the area of p.j. Forest office „Zavidovići“

Chainsaw is the main tool for work in a phase of wood felling and processing of forest harvesting in BiH. The aim of the research was to determine fuel and lubricant consumption of the chainsaws Husqvarna 365 and Dolmar PS – 7310 in the phase of felling and processing of wood assortments at the area of P.J. Forest Office „Zavidovići“, forest compartment 203. The volumetric method was applied for the measurement of fuel and lubricants consumption, with precise determination of fuel and lubricant quantity in chainsaw tanks. In total 140 trees of the sessile oak were felled (70 trees with chainsaw Husqvarna 365 and 70 trees with chainsaw Dolmar PS – 7310) during the research. The diameter at the breast height of felled trees ranged from 15 to 84 cm, while tree height ranged from 10,3 to 37,2 m. The total volume of processed assortments was 180,11 m<sup>3</sup>. The average fuel consumption per m<sup>3</sup> processed assortments was 0,306 L/m<sup>3</sup> for trees felled by chainsaw Husqvarna 365 which is for 0,042 L/m<sup>3 </sup>larger in comparison to chainsaw Dolmar PS – 7310 with average fuel consumption of 0,264 L/m<sup>3</sup>. The average lubricant consumption per m<sup>3</sup> processed assortments was 0,102 L/m<sup>3 </sup>for trees felled by chainsaw Husqvarna 365 which is for 0,012 L/m<sup>3</sup> larger in comparison to chainsaw Dolmar PS – 7310 with average lubricant consumption of 0,09 L/m<sup>3</sup>. Considering conducted research it can be assumed that there are differences in fuel and lubricant consumption between this two type of chainsaws for considered working conditions, but differences are not statistically significant.

Potential of UAV photogrammetry for characterization of forest canopy structure in uneven-aged mixed conifer–broadleaf forests

ABSTRACT Forest canopy structure is an important parameter in multipurpose forest management. An understanding of forest structure plays a particularly important role in the management of uneven-aged forests. The identification of vertical and horizontal variations in forest canopy structure using a ground-based survey is resource intensive, hence often demands for alternative data sources. In this study, one of the advanced remote sensing (RS) techniques, i.e. digital aerial photogrammetry was used to characterize forest canopy structure in a mixed conifer–broadleaf forest. We used aerial imagery acquired with a fixed-wing unmanned aerial vehicle (UAV) platform to produce RS metrics that could be used to classify and map forest structure types at landscape scale. Our results demonstrated that few structural and spectral metrics derived from UAV photogrammetric data, e.g. mean height, standard deviation of height, canopy cover, and percentage broadleaf vegetation cover, could characterize the forest structure across landscapes, particularly at the forest management compartment level, in a limited amount of time. We used cluster analysis for classification of forest structure types and identified five forest structure classes with varying levels of forest canopy structural complexity: (1) short, open-canopy, conifer-dominated structure; (2) short, dense-canopy, broadleaf-dominated structure; (3) tall, closed-canopy, broadleaf-dominated structure; (4) very tall, closed-canopy, conifer-dominated structure with a relatively high degree of variation in canopy height; and (5) very tall, closed-canopy, conifer-dominated structure with a relatively low degree of variation in canopy height. These classes showed relationships with forest management activities (e.g. selection harvesting) and natural disturbances (e.g. typhoon damage). Spatial distribution of forest canopy structural complexity that was revealed in this study is capable of providing important information for forest management planning and habitat modelling. Further, the simple, and flexible data-driven method used in this study to characterize forest structure has the potential to be applied with necessary changes over larger landscapes and different forest types for characterizing and mapping forest structural complexity.

Метод определения характеристик лесов на основе материалов дистанционного зондирования Земли, данных лесоустройства и алгоритма k-NN (на примере Лодейнопольского лесничества Ленинградской области)

The Russian system of National (State) Forest Inventory (NFI) valid from 2007 is methodologically imperfect and serves as a target of criticism and discussion. Insufficient attention paid to remote sensing should be attributed to the system’s weaknesses. A possible way of improving the NFI system is the use of automatic classification of forests’ characteristics based on materials of Earth remote sensing. One of the advanced automatic methods for forest remote sensing materials classification is k-NN or k-nearest neighbors algorithm, which have been successively used in the NFIs in other countries. It is based on regression between the spectral response characteristics of pixels with known forest characteristics and remaining pixels of the image. Questions of practical application of this method for the purposes of NFI were first raised and studied by Finnish researchers in the 1990s. Over the past two decades, a considerable amount of research in this area has been carried out in different countries. The purpose of our research is to assess the feasibility of using the k-NN method for determining the generalized characteristics of forests on the example of the Lodeynopol’skoe forest district in Leningrad region. The forest district area is 401,866 ha. It consists of 16 forest sub-districts. A regular network was created at a pitch of 1×1 km in order to form a set of trial plots for the classification by the means of GIS-technologies within the forest district. Round-shaped plots with a radius of 10 m or forest inventory compartments were used as trial plots located in the network nodes. Forest description for both types of plots was taken from the forest management data. Landsat-8 images were used for the classification (spectral channels: GREEN, RED, NIR, SWIR 2). The Landsat-8 images were automatically classified according to a number of forest inventory characteristics: average growing stock per 1 ha; middle class of bonitet; average relative density; share of coniferous and deciduous plantations area. The results of the k-NN classification were compared with the forest management materials. Systematic errors in the assessment of growing stocks, completeness and bonitet for the territory of Lodeynopol’skoe forest district made up less than 5 %. The obtained results confirm the potential of further study of conceptual and practical issues of the k-NN method application for determining forest characteristics. The development of this direction can contribute to the improvement of the Russian State Forest Inventory methodology.For citation: Chernikhovskii D.M., Alekseev A.S. The Method for Determining Forest Characteristics Based on Earth Remote Sensing Materials, Forest Management Data and the k-NN Algorithm (Case Study of Lodeynopol’skoe Forest District of Leningrad Region). Lesnoy Zhurnal [Forestry Journal], 2019, no. 4, pp. 45–65. DOI: 10.17238/issn0536-1036.2019.4.45

Changes in soil parameters of forests after windstorms and timber extraction

One of the main problems in close-to-nature management of high forests is linked to the ecological and economic aspects of salvage logging. This research involved analysing soil disturbance from salvage logging in four mountain forests, managed with close-to-nature silviculture: the Hyrcanian forest (three forest compartments in Iran), using extraction by skidder, and the Camaldoli forest (one parcel in Italy), using extraction by tractor. The point transect method was used for assessing soil disturbance and also included further measurements of ruts’ size and selected physical soil parameters on skid trails after operation. After a windstorm, more than 94% and 17% of the area were undisturbed in the Hyrcanian and Camaldoli forests, respectively. Bulk density, penetration resistance, and pH did not show any significant differences with their average values specifically between disturbed and undisturbed soil after a windstorm. Related only to the effect of salvage logging, more than 80% of the area was undisturbed. The results were significantly lower in terms of the average values of soil variables such as bulk density, penetration resistance, and total porosity in disturbed soil than in undisturbed soil. For all the sites that were studied, bulk density and penetration resistance increased with the increasing number of machines that passes, while total porosity decreased. The results showed significant positive correlations between bulk density and penetration resistance, bulk density and pH value, and total porosity and pH value and significant negative correlations between bulk density and total porosity and penetration resistance and total porosity. The results indicated that the point transect method of assessing soil disturbance provides a rapid assessment of soil conditions for monitoring soil disturbance after salvage logging. Our results also indicated that to reduce impacts to soil during salvage logging, if the volume of windthrow timber is low, salvage logging is not always necessary because of the broad ecological importance as well as the economic aspects of dead wood in forest ecosystems.

Numerical study of transport pathways of 137Cs from forests to freshwater fish living in mountain streams in Fukushima, Japan

The accident at the Fukushima Dai-ichi Nuclear Power Plant in 2011 released a large quantity of radiocesium into the surrounding environment. Radiocesium concentrations in some freshwater fish caught in rivers in Fukushima Prefecture in October 2018 were still higher than the Japanese limit of 100 Bq kg−1 for general foodstuffs. To assess the uptake of 137Cs by freshwater fish living in mountain streams in Fukushima Prefecture, we developed a compartment model for the migration of 137Cs on the catchment scale from forests to river water. We modelled a generic forest catchment with Fukushima-like parameters to ascertain the importance of three export pathways of 137Cs from forests to river water for the uptake of 137Cs by freshwater fish. The pathways were direct litter fall into rivers, lateral inflow from the forest litter layer, and lateral transfer from the underlying forest soil. Simulation cases modelling only a single export pathway did not reproduce the actual trend of 137Cs concentrations in river water and freshwater fish in Fukushima Prefecture. Simulations allowing a combined effect of the three pathways reproduced the trends well. In the latter simulations, the decreasing trend of 137Cs in river water and freshwater fish was due to a combination of the decreasing trend in the forest leaves/needles and litter compartments, and the increasing trend in soil. The modelled 137Cs concentrations within the forest compartments were predicted to reach an equilibrium state at around ten years after the fallout due to the equilibration of 137Cs cycling in forests. The model suggests that long term 137Cs concentrations in freshwater fish in mountain streams will be controlled by the transfer of 137Cs to river water from forest organic soils.

Methods for Processing Information of Radar Topographic Survey for Solving the Tasks for Determining Heights and Wood Stocks For Forest Stands

The paper studies the possibilities of using global elevation models SRTM (Shuttle radar topographic mission) to assess the characteristics of forest stands – average heights and wood stocks. It is known that in process of radar shooting vegetation is considered as a barrier to correctly determining the height of the earth’s surface. The surface, fixed by the sensors above the forest covered territory (scattering phase center height), is located in the upper part of the forest canopy. The review of publications confirms the relevance of this area of investigation in the world. , A brief theoretical basis of the SRTM survey, factors determining the values of the heights and the errors associated with them are presented based on literature reviews. The possibility of determining the height of forest canopy based on evaluation models is shown.
 The part of Uchebno-Opytnoe Forest District of the Leningrad region was chosen as the model territory. The geographic information databases, data of radar survey SRTM and topographic maps were the origin data for the study. The model territory is divided by a regular network into cells with 1 km step. Most of the territory is covered with forest vegetation. Relief modeling was performed on the basis of digitized topographic maps of 1:25000 scale by interpolation using TIN method. A visual and statistical comparison of both evaluation models – a surface model (based on SRTM radar survey data) and a relief model (based on topographic maps) was done. With help of the profiles construction an assessment of the nature of changes in the heights of the relief and surface models was performed. It is noted that for most of the model territory, the differences in height between the surface and relief models are 15-20 m. The convergence of graphs for heights is observed in areas, which are not covered with forest vegetation.
 The set of linear regression dependencies between the scattering phase center heights (independent variable) and average heights or wood stocks (dependent variable) within the borders of forest compartments, grouped by the predominated tree species, was obtained. The influence on the closeness of the relationship and the value of the regression coefficient of such factors as the value of basal area and the share of predominant tree species in composition was found.
 The established regularities can be used to improve the theory and practice of forest inventory, as well as to solve other problems related to the assessment of natural resources at the regional and global level (national forest inventory, carbon stock determination, assessment of biomass).