Forest science issues最新文献

{"title":"CARBON AND NITROGEN CONTENT AND RESERVES IN TERRESTRIAL ECOSYSTEMS OF THE MURMANSK REGION","authors":"T. Sukhareva, E. Ivanova, V. Ershov, I.V. Zenkova, M. V. Korneykova, I. Shtabrovskaya, A. Soshina","doi":"10.31509/2658-607x-202362-125","DOIUrl":"https://doi.org/10.31509/2658-607x-202362-125","url":null,"abstract":"The article provides an overview of own and literature data on phytomass reserves, carbon and nitrogen content, diversity of soil fauna and mycobiota in terrestrial ecosystems of the Murmansk region under conditions of combined action of natural and anthropogenic factors. The environmental factors determining the functioning of ecosystems, including the regulation of carbon cycles, are considered. It is shown that in representative spruce and pine forests, the concentrations and precipitation of carbon compounds from the atmosphere and its removal from soil waters are higher in the subcron spaces than in the intercron spaces. In soil waters, there is a decrease in carbon removal with the depth of the soil profile. The podzols are characterized by a bimodal distribution of humus over the soil profile with maxima in the organogenic and illuvial horizons. The carbon content in the organogenic horizon of the soils of spruce and pine forests varies from 12 to 54%, nitrogen — from 4.7 to 18.7 g/kg. The main carbon reserves in the organogenic horizon of forest soils are concentrated in the sub-crown spaces and reach 27–34 t/ha. Carbon reserves in the meter layer of soil (mineral horizons) are 47–60 t/ha. The phytomass reserves of the North taiga forests are characterized by low values (12–188 t/ha). Significant reserves of plant organic matter of the North Taiga forests are concentrated in the ground cover. The carbon content in the assimilating organs (leaves/needles, shoots) of plants of the North Taiga forests varies from 35 to 73%, nitrogen — from 5.4 to 23.6 g/kg. The rate of decomposition of plant residues and carbon loss during the decomposition of the fall of evergreen plants in spruce forests is higher than in pine forests, as are the indicators of the number of soil macrofauna. The podzols of the North Taiga forests correspond to the predominance of secondary destroyers of plant litter — humifiers of earthworms and mixophages wireworms, litter mollusks) and the absence of calcifilic groups of mineralizers (woodlice, bipedal millipedes). 122 species of microscopic fungi have been isolated from the soils of the Murmansk region. Species of pp. Penicillium and Umbelopsis were dominant in terms of abundance in the background soil, in anthropogenically altered soils — species of pp. Aureobasidium, Penicillium, Trichocladium, Trichoderma and Umbelopsis.","PeriodicalId":237008,"journal":{"name":"Forest science issues","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139368588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"HISTORY OF RESEARCH ON FOREST PRODUTIVITY IN KARELIA","authors":"S.A. Moshnikov, A.M. Kryshen, I.V. Romashkin","doi":"10.31509/2658-607x-202362-126","DOIUrl":"https://doi.org/10.31509/2658-607x-202362-126","url":null,"abstract":"The article deals with the history of research on the biological productivity of forests in Republic of Karelia as a methodological basis for the modern field of research into the components of carbon balance in forests. Particular attention is paid to the review of the studies of the researchers of the Forest Institute of the Karelian Research Center of the Russian Academy of Sciences from the moment of its formation to the present. The studies of the structure and stocks of phytomass, organic matter and carbon in different components of forest ecosystems, as well as biological aspects of the productivity of the republic’s forests are considered. Some results and prospects of studying the carbon balance in the forests of Eastern Fennoscandia at the current stage of the Institute’s activities are discussed. The references list the main studies in this research field.","PeriodicalId":237008,"journal":{"name":"Forest science issues","volume":"246 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139368580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"METHODOLOGICAL APPROACHES TO MAPPING FOREST FUELS","authors":"D.V. Ershov, E. Sochilova, N. Koroleva","doi":"10.31509/2658-607x-202362-128","DOIUrl":"https://doi.org/10.31509/2658-607x-202362-128","url":null,"abstract":"Spatial data on the vertical structure and forest fuel loads are a very importance for reliable estimates of direct fire carbon emissions. Main purpose of our paper is to demonstrate methodological approaches to mapping pre-fire forest fuels, which sets of multidimensional regression models and thematic satellite products of forest stand characteristics are based on. The used models make it possible to calculate the parts of combustible biomass fractions (branches, foliage, undergrowth layer, ground vegetation cover, forest litter, detritus) of forest ecosystems for the main dominated species of different ages, relative density and site index for all the forested area of Russia in the different geographic zones. The article provides thematic input remote sensing data, which are used in models for calculating biomass fractions. The paper provides thematic input remote sensing data, which are used in models for calculating biomass fractions. The results of a preliminary comparison of estimates of biomass reserves of the upper canopy obtained based on satellite products and forest inventory data at the level of forest districts of the Kostroma region are presented.","PeriodicalId":237008,"journal":{"name":"Forest science issues","volume":"33 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139368630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A METHOD TO DEFINE A CELL SIZE OF REGULAR NETWORK FOR INFRASTRUCTURAL TERRITORY ZONING WITH PURPOSE OF FOREST FIRE PROTECTION","authors":"E. Podolskaia, D.V. Ershov, K. Kovganko","doi":"10.31509/2658-607x-202362-127","DOIUrl":"https://doi.org/10.31509/2658-607x-202362-127","url":null,"abstract":"Infrastructural projects at regional scale are ones of the important components of modern digital economy. In relation to the forestry, the main objects that determine infrastructural load of the territory in the forestry are the networks of fire stations and forest roads with settlements and public roads. A method to define a cell size of a regular uniform rectangular grid based on the pixel size of MODIS-based vegetation raster is described. It is based on the statistics of number of settlements, fire stations and road sections, as well as road sections lengths. Exploratory regression was used to choose a cell size with a number of forest fires as a dependent variable and number of settlements, road segments and fires stations as independent variables. It was found that the most optimal size of regular grid cell for Krasnoyark Region (Kray) is 24 km2. Paper’s findings could be used in climate and economic projects to estimate infrastructural load.","PeriodicalId":237008,"journal":{"name":"Forest science issues","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139368579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ASSESSMENT OF PROBABLE GAS CHEMICAL POLLUTION OF PROMISING FOREST PROTECTED AREAS BY APG BURNING EMISSIONS","authors":"V.A. Khamedov, N.V. Davydova","doi":"10.31509/2658-607x-202252-117","DOIUrl":"https://doi.org/10.31509/2658-607x-202252-117","url":null,"abstract":"The development and operation of oil fields in Western Siberia has a significant impact on various components of the environment. In particular, natural complexes of existing specially protected natural areas and promising areas that are significant for the conservation of biological diversity and landscapes are affected. In connection with the projected development of a system of specially protected natural areas in the Khanty-Mansiysk Autonomous Okrug, the aim of the work is to assess the likely pollution of municipalities in the region by emissions from the combustion of associated petroleum gas to provide decision support when choosing locations for promising protected areas. The paper presents a general description of chronic thermal and gas-chemical pollution of the atmosphere by products of associated petroleum gas combustion, zones of probable atmospheric pollution as a result of gas combustion are modeled, an assessment is made of the dynamics of the state of vegetation for the territories of municipalities, within the boundaries of which it is planned to create protected natural areas, and recommendations are given for designing such territories.","PeriodicalId":237008,"journal":{"name":"Forest science issues","volume":"192 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129107879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DYNAMICS OF FOREST VEGETATION DESTRUCTIOS IN THE AREA ADJAICENT TO THE COPPER MINE IN THE SVERDLOVSK REGION","authors":"A.E. Kvashnina, F.K. Vozmitel, V. Khamedov","doi":"10.31509/2658-607x-202361-123","DOIUrl":"https://doi.org/10.31509/2658-607x-202361-123","url":null,"abstract":"The study represents spatial and temporal analysis of the consequences of water pollution leading to vegetation destruction, caused by uncontrolled underspoil drain from a copper mine in the north of the Sverdlovsk region, based on GIS methods and satellite remote sensing data. Based on a 1:25 000 topography map DEM with filled sinks we built a flow accumulation model a watershed map. Examining the satellite imagery of the area dated from 2009 to 2023 we have noticed a distinct pattern of the vegetation destruction along the riverbeds located in the affected watersheds. Our ground observations and drone images have confirmed that the dead forest plots are located in the areas of flow accumulation, in the terrain depressions. The total area of forests affected by the uncontrolled underspoil drain from the copper mine gradually grows and has reaches 1140 ha.","PeriodicalId":237008,"journal":{"name":"Forest science issues","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124581205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Remote sensing data from Space for road image recognition in the forestry","authors":"E. Podolskaia","doi":"10.31509/2658-607x-202361-121","DOIUrl":"https://doi.org/10.31509/2658-607x-202361-121","url":null,"abstract":"Paper presents an overview of history and current research state on the use of remote sensing data from space to recognize roads for the regional projects in the forestry. We reviewed the principles of road detection on the optical satellite imagery. Group of direct recognition features used in combinations such as brightness and texture, geometry and brightness. Three research directions with examples were identified: visual roads recognition, use of special software and libraries for developers, and neural networks. For the road network detection we have described methods and software, type and spatial resolution of imagery. Road image recognition based on the optical survey from the open and commercial sources, machine learning methods and neural networks. Up-to-date tasks of road recognition are the following: evaluation of road surface condition, modeling of existing roads location, designing and building new roads, roads seasonality. A functional summary of MapFlow plugin for road recognition in Open Source QGIS is given. Paper is a part of regional forestry transport modeling project to access the forest fires and forest resources by ground means.","PeriodicalId":237008,"journal":{"name":"Forest science issues","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127590457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MAPPING OF SOIL ORGANIC CARBON CONTENT AND STOCK AT THE REGIONAL AND LOCAL LEVELS: THE ANALYSIS OF MODERN METHODOLOGICAL APPROACHES","authors":"N. V. Gopp, J. L. Meshalkina, A. Narykova, A.S. Plotnikova, O.V. Chernova","doi":"10.31509/2658-607x-202361-120","DOIUrl":"https://doi.org/10.31509/2658-607x-202361-120","url":null,"abstract":"This paper provides an overview of scientific publications in Russia and other countries devoted to the soil organic carbon (SOC) content and stocks mapping at regional and local levels. The analysis showed that the cartographic assessment of the SOC content and stocks was conducted using various approaches that the choice depends on the multiple factors: the size of the territory (continental, national, regional, local levels); the cartographic basis availability (maps of soil types, of landscapes, of vegetation formations, remote sensing data, etc.) and laboratory and field surveys data. Two main approaches were generally used for SOC content and stocks mapping: (1) based on available thematic maps; (2) digital soil mapping. The review also provides the analysis of all spatial predictors that were used in collected papers in concordance with the SCORPAN model widely used in digital soil mapping. Spatial terrain data was one of the most commonly used predictors, followed by the vegetation and climate variables. The accuracy of predictive maps significantly increased by using soil maps. The reviewed studies showed that climate variables had a significant impact on the spatial variation of the SOC content and stocks at the regional level, while at the local level the influence of climatic variables was less significant. The analysis showed that the most common methods used in digital mapping were machine learning algorithms. Random Forest method often showed the best results. Results were cross-validated almost in all studies. Tests of the map’s accuracy using an external independent validation dataset were rare, although this was the most important stage of digital soil mapping. R was the most popular software, that was used for modeling the SOC content and stocks. SAGA GIS, QGIS, ArcGIS, and cloud platform Google Earth Engine (GEE) were most commonly used to prepare predictors.","PeriodicalId":237008,"journal":{"name":"Forest science issues","volume":"22 6S 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115942745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"IMPACT OF SILVICULTURAL PRACTICES ON SOIL CARBON: A REVIEW","authors":"D. Tebenkova, D. V. Gichan, Y. Gagarin","doi":"10.31509/2658-607x-202252-116","DOIUrl":"https://doi.org/10.31509/2658-607x-202252-116","url":null,"abstract":"The paper provides a review of Russian and foreign articles regarding studying the impact of silvicultural practices on the soil carbon pool to assess the effectiveness of forest carbon projects. Analyzing the works allowed us to conclude that silvicultural practices affect the content of soil carbon through a change in the rate of influx and decomposition of organic matter and, as a result, affect the redistribution of carbon in the soil profile. High-intensity felling, including clear felling, removal of logging residues, damage to the ground cover when planting forest crops, and the development of monocultures can negatively affect the soil carbon pool. On the contrary, selective and low-intensity thinning, leaving logging residues, and planting mixed forest stands, especially on abandoned agricultural lands, proved to be promising forest management practices that contribute to the accumulation and conservation of soil carbon.","PeriodicalId":237008,"journal":{"name":"Forest science issues","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133686443","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"USE OF REMOTE SENSING DATA FROM SPACE FOR ROAD IMAGE RECOGNITION IN THE FORESTRY","authors":"E. Podolskaia","doi":"10.31509/2658-607x-202252-115","DOIUrl":"https://doi.org/10.31509/2658-607x-202252-115","url":null,"abstract":"Paper presents an overview of history and current research state on the use of remote sensing data from space to recognize roads for the regional projects. We have characterized principles of road detection on the imagery. A group of direct deciphering signs used in combinations such as brightness and texture, geometry and brightness. Three research directions with examples identified: visual roads recognition, use of special software and libraries for developers, and use of neural networks. For the road network detection we have described methods and software, type and spatial resolution of imagery. Road image recognition based on the optical survey from the open and commercial sources, machine learning methods and neural networks. Actual tasks of road recognition are the following: evaluation of road surface condition, modeling of existing roads location, designing and building new roads, seasonality of roads use. A functionality summary of MapFlow plugin for road recognition in Open Source QGIS is given. Paper is a part of regional forestry transport modeling project to access the forest fires and forest resources by ground means.","PeriodicalId":237008,"journal":{"name":"Forest science issues","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134107094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}