Original Russian Text © 2019 O. I. Evstigneev, V. N. Korotkov published in Forest Science Issues Vol. 2, No. 4, pp. 1–36.

© 2022                                             O. I. Evstigneev ^{1, 3 *}, V. N. Korotkov²                

¹State Nature Biosphere Reserve “Bryanskii Les”,
Nerussa Station, Bryansk Oblast 242180, Russia

²Yu. A. Israel Institute of Global Climate and Ecology, 20B
Glebovskaya st., Moscow 107258, Russia

³Center for Forest Ecology and Productivity of the RAS,
Profsoyuznaya st. 84/32 bldg. 14, Moscow, 117997, Russia

*E-mail: quercus_eo@mail.ru

Received: 16.09.2019

Revised: 07.10.2019

Accepted: 07.10.2019

Professor Olga V. Smirnova, Doctor of Biological Sciences, is a prominent scientist in the field of plant demography, population biology, and forest ecosystem ecology. Professor Olga V. Smirnova’s edifice is based on ideas about the leading role of plant and animal populations in the organization of the biogeocenotic cover. In this case, it is implied that a continuous generational turnover in edificator (keystone species) populations is necessary to maintain the species and structural diversity in communities and ensure their sustainability. This system of views was influenced by Professor Alexey A. Uranov. The development of these ideas was consistent and gradual. First, Professor Olga V. Smirnova studied the biology of different plant species life forms. Examining their individual development, with identification of ontogenetic stages, is necessary for demographic research. She then developed the theory of coenopopulations as supraorganismal systems, which can self-sustain under different conditions. Finally, she developed the doctrine of biogeocenosis as a system of interacting populations and created the concept of anthropogenic transformation of the forest cover in the Holocene. Her contributions helped researchers to understand the mechanisms of the formation of modern zonality that are due to human activity.

Key words: plant biological age, plant population strategy, coenopopulation, edificator, forest ecosystem ecology, modern zonality, historical ecology

October 9, 2019 marks the anniversary of Professor Olga Vsevolodovna Smirnova, Doctor of Biological Sciences, a prominent scientist in the field of plant demography, population biology and forest ecosystem ecology (Fig. 1).

Professor Olga V. Smirnova was born to the family of intellectual workers in 1939. Her mother, Nina Nikolaevna, was a French to Russian translator, and her father, Vsevolod Mikhailovich, was an engineer. Her maternal grandfather, Nikolai A. Zhukov, graduated from the Moscow Higher Vocational School of Commerce (now Financial Academy) and worked as an economist with the People’s Commissariat for Foreign Affairs. Her paternal grandfather, Mikhail I. Smirnov, graduated from the Moscow Archaeological Institute in Nizhny Novgorod. He was an outstanding professional who specialized in local history and founded the Pereslavl-Zalessky Historical, Architectural and Art Museum-Reserve in 1919. Olga V. Smirnova spent her childhood in Gagarinsky Lane in the very heart of Moscow (Zhukova, 2006).

She showed interest in biology in her high school years, attending a young naturalists hobby group at the All-Russian Society for the Protection of Nature (VOOP) headed by a renowned biologist Pyotr P. Smolin. In 1963, Olga V. Smirnova graduated from the Chair in Geobotany at M. V. Lomonosov Moscow State University. In 1968, she defended her Candidate of Sciences thesis under supervision of Professor Alexey A. Uranov that was devoted to the topic “Life cycles, number and age composition of populations of the main components of oak grass cover”. In 1983, she defended her Doctor of Sciences thesis devoted to the topic “Behavior of species and functional organization of grass cover of deciduous forests (a case study of plain broad-leaved forests in the European part of the USSR and linden forests of Siberia)”. From 1966 to 1992, Olga V. Smirnova had been employed with the Problem-Centered Biology Laboratory (PBL) at the V. I. Lenin Moscow State Pedagogical Institute (MGPI) (Fig. 2, 3). In 1987, she published the book Grass Cover Structure of Broad-Leaved Forests that resulted from her Candidate’s thesis and Doctor’s thesis. Since September 1, 1992, Professor Olga V. Smirnova has been employed as Principal Researcher at the Center of Forest Ecology and Productivity of the Russian Academy of Sciences (CEPF RAS). From 1993 to 2008, she taught at Pushchino State University (PuschGENI) at the Department of System Ecology, founded and headed by Professor Alexander S. Komarov (Fig. 4, 5). In 1994, a collective monograph Eastern European Broadleaf Forests, and in 2004, a two-volume book Eastern European Forests: History in Holocene and Contemporaneity were published under her editorship. In 2017, Springer published a revised version of this book, European Russian Forests: Their Current State and Features of Their History as requested by the Plant and Vegetation editorial board. The fundamentals of Professor Olga V. Smirnova’s research, starting with the young naturalists hobby group and to the present day, are her expeditionary studies she conducts every year (Fig. 6–8).

In 2015, Professor Olga V. Smirnova founded an international research journal, Russian Journal of Ecosystem Ecology. The journal covers the functioning and dynamics of ecosystems, the organization of biogeocenotic cover, and other issues of ecology. Professor Olga V. Smirnova supervised 25 successfully defended Candidate’s theses (Sugorkina, 1989; Evstigneev, 1990; Argunova, 1993; Istomina, 1993; Korotkov, 1993; Nedoseko, 1993; Chumachenko, 1993; Kiseleva, 1994; Shanijazova, 1994; Barinova, 1997; Ripa, 1997; Samohina, 1997; Sarycheva, 2000; Bobrovskaja, 2001; Braslavskaja, 2001; Turubanova, 2002; Bobrovskij, 2004; Shestakova, 2005; Bogdanova, 2006; Romanovskij, 2006; Lugovaja, 2008; Popov, 2008; Aleinikov, 2010; Zaprudina, 2012; Kharitonenkov, 2012); five of her students were awarded the degree of Doctors of Sciences (Chumachenko, 2006; Argunova, 2010; Evstigneev, 2010; Bobrovskij, 2013; Nedoseko, 2018). On December 2, 1994, she was awarded the title of Full Professor in Botany. To date, Professor Olga V. Smirnova has published over 300 works. All her publications, including an extensive reference list, are available online at http://istina.msu.ru/profile/sov1933/.

Professor Olga V. Smirnova’s views in forest biogeocenology / forest ecosystem ecology are based on ideas about interacting populations of living beings, which were shaped under the influence of her mentor, Professor Alexey A. Uranov (Shorina et al., 2014). Within the framework of said system of views, Professor Olga V. Smirnova made a significant contribution to enhancing the concepts of plant biological age and plant population strategy by developing the doctrine of coenopopopulations and biogeocenosis as a system of interacting populations, as well as to ideas about modern zonality as an anthropogenic phenomenon.

Figure 1. Olga V. Smirnova. Top left: An expedition in Sabar, August 1979, the Middle Urals, Artinsky District, Sverdlovsk Oblast. Photo by O. G. Barinov. Top right: Before the trip to Sabar in 1991. Photo by M. A. Barinova. Bottom left: Defense of Natalia E. Bogdanova’s Candidate’s thesis at the Moscow State Pedagogical University, November 20, 2006. Bottom right: Defense of Ekaterina L. Zheleznaya’s Candidate’s thesis at Moscow State Pedagogical University, March 2, 2009. Photo by O. M. Zhelezny

Figure 2. Professor Olga V. Smirnova’s colleagues (start). Top: Olga V. Smirnova with Alexey A. Uranov’s students — Inna M. Ermakova (Researcher at the Problem-Centered Biology Laboratory, Moscow State Pedagogical Institute) and Nina M. Grigorieva (Professor of the Chair in Botany of the Moscow State Pedagogical Institute, right), 1974. Bottom left: Among the tall forest herbs with Tatiana I. Serebryakova (Head of Chair in Botany at the Moscow State Pedagogical Institute from 1974 to 1986) during a trip to Salair (Guryevsky District, Kemerovo Oblast), 1982. Photo by M. A. Barinova. Bottom right: Aleksandra A. Chistyakova (Candidate of Biological Sciences, Full Professor at the Chair in Botany, Physiology and Plant Biochemistry, Penza State University), a co-author of Olga V. Smirnova’s principal works devoted to the interacting populations in forest communities

Figure 3. Professor Olga V. Smirnova’s colleagues (cont’d). Top: With Roman V. Popadjuk (Researcher at the Problem-Centered Biology Laboratory, Moscow State Pedagogical Institute) during an expedition to Prioksko-Terrasny Nature Reserve in 1990. Photo by M. A. Barinova. Bottom left: Natalia A. Toropova (Candidate of Biological Sciences, Associate Professor at the Chair in Botany, Tambov State Pedagogical Institute) in the Kanevsky Nature Reserve (Cherkasy Oblast, Ukraine), 1983. Bottom right: Professor Olga V. Smirnova’s colleagues discussing research plans in the Laboratory of Ecosystem Modeling, Institute of Physicochemical and Biological Problems of Soil Science, RAS (Pushchino). Left: Lyudmila B. Zaugol’nova (Doctor of Biological Sciences, Principal Researcher at the Center of Forest Ecology and Productivity, RAS, Moscow), right: Larisa G. Khanina (Candidate of Biological Sciences, Associate Professor, Head of Laboratory of Computational Ecology, Institute of Mathematical Problems of Biology, RAS, Pushchino), 1999

The Concept of Plant Biological Age

Classifying plant populations into ontogenetic (age) groups constitutes the basis of population demographics studies. The works of Tikhon A. Rabotnov (1950) and his followers, including Professor Olga V. Smirnova, substantiated and developed an approach to age differentiation in individual plants based on studying the ontogeny of living organisms from birth to death. The method provides for the allocation of stages in individual plant development, or ontogenetic states that reflect the biological age of an individual plant. Professor Olga V. Smirnova studied the ontogeny of over 30 plant species growing in Eastern European forests and linden trees of Western Siberia (Table 1). She presented early descriptions of the ontogeny in three collective monographs edited by Professor Alexey A. Uranov, Ontogenesis and Age Composition of Flowering Plant Populations (1967), Morphogenesis of Flowering Plants and The Structure of Their Populations (1968) and Age Composition of Flowering Plant Populations Due to Their Ontogenesis (1974).

These works show that defining the ontogenetic (age) state is incomparably more important for demographic research than the analysis of numerical age. This is due to two reasons: 1) different individual plants of the same species often reach the same ontogenetic state in different numerical terms; yet, since they are at the same development stage, they play the same part in the population and in the community; 2) the time individual plants of different species and life forms take to go through the same ontogenetic states may vary. All this means that it may be more logical to associate comparative assessment of significance of plants in coenosis with not numerical age but development stage, that is, the ontogenetic state.

Table 1. Ontogeny of plants studied by Professor Olga V. Smirnova

Figure 4. Field trips. Top left: Summer field trip with 2nd-year undergraduate students of the Moscow State Pedagogical Institute in 1977 with Olga V. Smirnova (Candidate of Sciences, left) and Marina P. Solovyova (Associate Professor, Candidate of Sciences, second right) in Tellermanovskoe Forestry (Voronezh Oblast). Top right: Winter field trip with Master’s students of the Pushchino State University in Central Forest Nature Reserve, 1994: Konstantin V. Belyakov (Master’s student, left), Olga V. Smirnova, Mikhail S. Romanov (Master’s student, right). Photo by M. A. Barinova. Bottom left: Fall field trip with 1st-year Master’s students of the Pushchino State University in Kaluzhskiye Zaseki Nature Reserve, 1996. Left to right: Vladimir N. Korotkov (Candidate of Sciences, Senior Researcher at the All-Russian Research Center for Forest Resources), Oksana Sinotova (Master’s student), Marina Mishchenko (Master’s student), Larisa Tarasova (Master’s student), Maxim V. Bobrovskij (Senior Lecturer). Sitting, left to right: Aleksandr Kuritsyn (Master’s student), Vladimir Timofeev (Master’s student), Aleksandra Agafonova (postgraduate student), Olga V. Smirnova, Alexey Egorov (Master’s student). Bottom right: Fall field trip with 1st-year Master’s students of the Pushchino State University in Russky Sever National Park, 2005. Left to right: Alexey Aleinikov, Maxim Kharitonenkov, Olga V. Smirnova, Ekaterina Kobozeva, Vladimir Shanin, Alexey Gornov. Photo by M. V. Bobrovskij

The Concept of Plant Population Strategy

Based on the system of ideas about plant coenotypes proposed by Leonty G. Ramensky (1935) and the concept of plant strategies developed by J. Grime (1979), Professor Olga V. Smirnova substantiated a new approach to studying plant population strategies (population behavior) (Smirnova, 1980, 1987; Smirnova, Chistyakova, 1980). The essential provisions of this approach are as follows.

1. The following properties are considered as integral, phytocoenotically significant plant population strategies: competitive, phytocoenotically tolerant, and reactive. Competitive strategy (violent, competitive power) means the ability of species to create and control the environment in a community, as well as suppress other living organisms due to the great vitality and highly intensive environment use. Phytocoenotically tolerant strategy (patient, resistance, endurance in an extremely unfavorable phytocoenotic environment) means the ability of species to survive for a long time in the area occupied by other living organisms, due to the maximum lowered vitality. Reactive strategy (explerent, dynamism, pioneering, ruderality) means the tendency of a species to the fastest possible development of released resources in the community due to vigorous vegetative growth and significant reproductive effort.

According to said definitions, a plant population strategy means the ability of species to dominate or occupy a subordinate position in a community, which resulted from a long evolution in preagricultural climax coenoses undisturbed by humans. The described population strategies reflect the phytocoenotic potencies of a species. The real-life ranking of a species in a particular coenosis makes up its phytocoenotic position. Phytocoenotic potencies and phytocoenotic positions may be expected to overlap completely in climax communities in the preagricultural age. Real-life position of a species in modern communities differ significantly from its role in climax coenoses, since the communities structure has been fundamentally transformed by humans.

2. Integral properties (competitive, phytocoenotically tolerant, reactive) are inherent in every species but expressed to various degrees. Species that are predominantly competitive are violent, species that are predominantly tolerant are patient, and species that are predominantly ruderal are explerent. Aside from groups of species characterized by these three strategy types (behavior), following J. Grime (1979), Professor Olga V. Smirnova identified the groups of species that occupy an intermediate position.
3. Investigation of a plant strategy is based on investigation of biological properties of a species. This assumes a differentiated approach to studying biological (behavior) and ecosystem properties of a species. Knowing the ecosystem properties, one could reveal the requirements of a species to environment resources, whereas studying biological properties could help to define the method and nature of how to use said resources. In other words, plant ecosystem properties determine the species composition in a community, whereas biological properties determine the predominant or subordinate role of the species in the community. This approach to identifying types of plant behavior differs significantly from the methods of studying the coenotypes proposed by Leonty G. Ramensky (1935) and plant strategies developed by J. Grime (1979). Thus, Ramensky’s patient plants (or Grime’s stress-tolerant plants) are allocated based on ecosystem properties of species, while violent (competitive) plants and explerent (reactive) plants are allocated based on biological properties.
4. The history of studying phytocoenotic potencies in plants shows that it is not possible to single out any standalone, independent feature that would determine the type of plant behavior in its entirety. At the same time, each type of plant behavior is characterized by a set of particular (differential) properties, which are specific manifestations of competitive, tolerant and reactive strategy.
5. It may be advisable to analyze the types of behavior in plants of relative life forms occupying the same space-time niche and belonging to the same trophic level, i. e. the same synusia (Smirnova, 1987). This is determined by the fact that the types of a single synusia are characterized by similar impact on the environment and play a similar role in the community. Moreover, the biological originality of a given species is most fully manifested if we investigate the entire historically formed set of species at the same time. In temperate forests, synusias of trees, shrubs, summer broadleaf herbs, and early spring ephemeroids are usually considered as such (Eastern European …, 1994).

Based on these provisions and a detailed study of the biological plant properties, Professor Olga V. Smirnova developed a classification of plant species by strategy (behavior) type in the synusias of spring ephemeroids and summer broadleaf herbs (Smirnova, 1987). This approach was successfully implemented when studying the types of strategy of trees and shrubs in Eastern European forests (Smirnova, Chistyakova, 1980; Evstigneev, 2004, 2010; Evstigneev, Didenko, 2004). Below is an example of a plant classification by type of behavior in the synusia of summer broadleaf herbs (Smirnova, 1987).

Type I. Competitive species (violent).

Group 1 — vegetatively mobile: Aegopodium podagraria L., Convallaria majalis L., Carex pilosa Scop., Mercurialis perennis L.

Type II. Tolerant species (patient).

Group 1 — vegetatively slightly mobile: Asarum europaeum L., Carex digitata L., C. rhizina Blytt ex Lindbl., Paris quadrifolia L., Polygonatum multiflorum (L.) All., Pulmonaria obscura Dumort., Viola mirabilis L.

Group 2 — vegetatively immobile: Brachypodium sylvaticum (Huds.) Beauv., Bromopsis benekenii (Lange) Holub, Carex sylvatica Huds., Campanula latifolia L., C. rapunculoides L., C. trachelium L., Dactylis glomerata L., Festuca gigantea (L.) Vill., F. sylvatica L., Geum urbanum L., Melica nutans L., Lathyrus vernus (L.) Bernh., Poa nemoralis L., Ranunculus cassubicus L., Scrophularia nodosa L., Scutellaria altissima L.

Type III. Reactive species (explerent).

Subtype 1: competitive reactive species. Group 1 — vegetatively mobile: Ajuga genevensis L., A. reptans L., Galeobdolon luteum Huds., Milium effusum L., Viola odorata L. Group 2 — vegetatively immobile: Lamium maculatum (L.) L.

Subtype 2: Actually reactive. Group 1. Vegetatively mobile: Galium odoratum (L.) Scop., Glechoma hederacea L., Stachys sylvatica L., Stellaria holostea L., Urtica dioica L. Group 2: vegetatively immobile: Alliaria petiolata (Bieb.) Cavara & Grande, Chaerophyllum temulum L., Geranium robertianum L., Torilis japonica (Houtt.) DC.

Professor Olga V. Smirnova showed that defining phytocoenotic potencies in plants makes it possible to understand some features in the organization of climax coenoses which differed in maximum species diversity (Smirnova, Chistyakova, 1980; Smirnova, 1983, 1987). Competitive plant species constituted a stable basis for every synusia, for they were predominant in number and biomass, involved the largest portion of matter and energy in the community, significantly changed the coenotic environment, and executed the function of edificators. Tolerant plant species, having an extremely low vitality level, used resources that could not be occupied by competitively powerful plants. Reactive plant species “roamed around” from one disturbance to another and “patched the holes” that occasionally occurred in the community in areas where individuals died in populations of edificators. Species with different strategy (behavior) types act as complementary formations, thanks to which the community resources are used most efficiently.

The Theory of Coenopopulations

The team at the Problem-Centered Biology Laboratory at the Moscow State Pedagogical Institute where Professor Olga V. Smirnova was employed at the time, published four outstanding books on plant demography, Plant Coenopopulations (Basic Concepts and Structure) (1976), Plant Coenopopulations (Development and Relationships) (1977), Dynamics of Plant Coenopopulations (1985), and Plant Coenopopulations (Essays on Population Biology) (1988). The books are based on ideas of plant biological age. These monographs present the concept apparatus and propose a system of methods in plant population biology. Having summarized her long-term studies at the Problem-Centered Biology Laboratory and Chair in Botany at the Moscow State Pedagogical Institute, Professor Olga V. Smirnova, in collaboration with Lyudmila B. Zaugol’nova, developed the ideas of characteristic ontogenetic spectrum (COS) and elementary demographic unit (EDU).

COS is a full-membered ontogenetic spectrum with a certain ratio of ontogenetic group number, which allows for a continuous generational turnover. This spectrum is due to the plant biological properties: 1) total duration of ontogeny and individual age states; 2) rate of development in individuals having various ontogenetic states; 3) methods of population self-sustainment; 4) intensity and frequency of inspermation and elimination; 5) ability to create a soil reserve of seeds or other vegetative rudiments; 6) area of resource consumption by individuals at different stages of ontogeny (Zaugol’nova, 1994; Zaugol’nova, Smirnova, 1978; Smirnova, 1987; Zaugol’nova et al., 1992; Eastern European …, 1994, 2004). At first, in the framework of studies conducted by said researchers, COS was considered synonymous with “basic ontogenetic spectrum”. However, the authors later limited the concept of the basic ontogenetic spectrum with the modal one, obtained by averaging data on several coenopopulations belonging to one community variant (Smirnova et al., 1993; Zaugol’nova, 1994).

Figure 5. Chair in System Ecology at the Training Center for Mathematical Biology of the Pushchino State University. Top: After Master’s thesis defense, July 1998. Sitting, left to right: Vitaly E. Reif (Master), Elena P. Sarycheva (postgraduate student), Andrey M. Tsyplyanovsky (postgraduate student), Sergey S. Bykhovets (Senior Lecturer). Standing (first row, left to right): Oksana A. Sinotova (Master), Galina E. Rubashko (Master), Elena S. Esipova (Master), Elena G. Didenko (Master), Irina F. Medvedeva (Head of Education Department), Valentina S. (Laboratory Assistant), Svetlana A. Turubanova (Master), Larisa G. Khanina (Candidate of Sciences, Associate Professor). Standing (second row, left to right): Vadim N. Pavlov (Doctor of Biology, Professor, Chairman of the State Examination Board), Maria M. Palenova (Candidate of Biological Sciences, Associate Professor), Alexander S. Komarov (Candidate of Biological Sciences, Associate Professor, Head of Chair), Olga V. Smirnova (Doctor of Biology, Full Professor), Anna V. Manukyants (Master), Vladimir V. Timofeev (Master), Maxim V. Bobrovskij (Senior Lecturer). Bottom left: Professor Olga V. Smirnova’s speech at the defense of Master’s theses on June 18, 2007. Bottom right: Olga V. Smirnova and Natalia A. Leonova (Candidate of Biological Sciences, Associate Professor at the Chair in Botany, Physiology and Plant Biochemistry of the Penza State University) after a research seminar on October 11, 1996 at the Chair in System Ecology

Figure 6. Expeditions (start). Left: Olga V. Smirnova in the test area next to a wych elm, 1979. Sabar, Middle Urals, Artinsky District, Sverdlovsk Oblast. Photo by O. G. Barinov. Top: Before the trip to Sabar in 1991. Left to right: Svetlana I. Ripa (postgraduate student, Chair in Botany of the Moscow State Pedagogical Institute), Tatyana O. Yanitskaya (employee at the Chair in Higher Plants of the Moscow State University), Oleg G. Barinov (postgraduate student in Chemistry of the Moscow State Pedagogical Institute), Vladimir N. Korotkov (Researcher at the Laboratory of Nature Conservation Research Institute), Olga V. Smirnova (Doctor of Biological Sciences, Senior Researcher at the Moscow State Pedagogical Institute). Photo by M. A. Barinova. Bottom: Olga V. Smirnova on an all-terrain vehicle in Gorno-Khadytinsky Nature Reserve (Yamalo-Nenets Autonomous Okrug), 1999. Photo by M. V. Bobrovskij

Figure 7. Expeditions (cont’d 1). Top left: Olga V. Smirnova in Voronezh Nature Reserve, 1974, studying the structure of the grass cover in broad-leaved forests. Top right: Olga V. Smirnova next to a Korean pine in Ussurisky Nature Reserve (Far East), 2008. Photo by V. N. Korotkov. Bottom: Exploring the river bottom of the Podkamennaya Tunguska, July 2006. Evenkiysky District, Krasnoyarsk Krai, central area of Central Siberian Plateau. Olga V. Smirnova and Maxim V. Bobrovskij (Candidate of Biological Sciences, Associate Professor at the Chair in System Ecology, Pushchino State University)

Figure 8. Expeditions (cont’d 2). Left: Olga V. Smirnova next to a rowan tree in Visimsky State Nature Biosphere Reserve, May 2019. Photo by A. P. Geraskina. Top: In the Pechora-Ilych Nature Reserve, August 2003. Left to right: Olga V. Smirnova, Elena Chernenkova, Sergey Pautov (Omsk State Technical University employee), Maxim Bobrovskij (Senior Lecturer at the Pushchino State University). Photo by V. N. Korotkov. Bottom: In the protected area of the Visimsky Nature Reserve during the study of a unique coniferous/broad-leaved forest populated with small-leaved linden and wych elm, May 2019. Left to right: Anna P. Geraskina (Candidate of Biological Sciences, Zoologist at the Center of Forest Ecology and Productivity, RAS), Rustam Z. Sibgatullin (Geobotanist at the nature reserve), Natalia V. Belyaeva (Phenologist at the nature reserve), Denis S. Shilov (Florist at the nature reserve), Olga V. Smirnova. Photo by V. N. Korotkov

COS reflects the dynamically stable (definitive) coenopopulation state to which it returns from deviations caused by external influences. The real ontogenetic spectrum is most consistent with the COS in undisturbed (climax) communities. In human-transformed coenoses, the ontogenetic spectrum of a population generally deviates from COS to varying degrees (Coenopopopulations…, 1976; Smirnova et al., 1987, 1989, 1990, 1991, 1992; Eastern European …, 1994).

Professor Olga V. Smirnova showed that plants have three types of characteristic ontogenetic spectra (Smirnova, 1987; Eastern European …, 1994). The first type is left-sided spectrum, with the maximum falling on pregenerative individuals. It is found in trees, monocarpic and oligocarpic tap-root herbs, bulbous, tuber-bulbous, and tuberous geophytes. These plants actively propagate by seed and/or deep rejuvenated vegetative rudiments. The second type is a centered spectrum: the largest number of individuals are located on middle-aged generative plants. It is characteristic of tap-rooted, long- and short-rhizomed herbs, sod grasses, and semi-shrubs. They have a weakly expressed aging period, propagate by seed or have a mixed propagation type, their vegetative reproduction is not accompanied by deep rejuvenation. The third type is a bimodal spectrum with two maxima: one in young individuals, and the other in mature or old generative individuals. This type is described in dense and loose sod grasses, tap-rooted and short-rhizomed herbs, in semi-shrubs. These plants have a significant life expectancy with a well-defined period of aging, their active propagation by seed is combined with vegetative reproduction with no deep rejuvenation.

EDU is a population unit, which is a set of individuals of different ages of the same species, necessary and sufficient to ensure sustainable generational turnover in the minimum allowable area. Important EDU characteristics include: 1) minimum number of individuals which allows for a continuous generational turnover; 2) minimum space necessary for a steady flow of generations; 3) lifetime of one generation (Smirnova et al., 1989; Zaugol’nova et al., 1993). EDU of different types are arranged in continuous series by values of each of the listed features (Table 2).

Table 2. Some parameters of elementary demographic units (EDU) in plants growing in broad-leaved forests (Smirnova et al., 1992)

The idea of EDU allowed Professor Olga V. Smirnova to propose a deeper definition of an important concept in forest ecology, namely the edificator (Smirnova, 1998; Smirnova, Toropova, 2008). This category includes species with the largest EDU and population mosaics existing for a long time. They include the largest portion of matter and energy in the cycles of generational turnover. Edificators belong to powerful environment converters. Populations of edificators with spontaneous development may transform a habitat to the greatest extent: they can change the hydrology, temperature, and lighting regime of a community, create micro- and mesorelief, and transform the soil cover. The intrinsic heterogeneity of the edificator EDU habitat allows for the coexistence of ecologically and biologically diverse species with smaller EDUs, and also maintains a high biodiversity level. The concept of edificator is synonymous with those of keystone species and ecosystem engineer. In the forest zone, edificators include species of various trophic groups and systematic positions: for example, large trees, needle- and leaf-eating insects, and tree-destroying fungi; river beavers join them in floodplain communities.

The Concept of Biogeocenosis as a System of Interacting Populations

Professor Olga V. Smirnova has been actively developing an idea of the structure and dynamics of undisturbed (climax) forest biogeocoenoses that existed in the preagricultural age with no human intervention (East European …, 1994, 2004; Smirnova et al., 1988, 1989, 1990; Smirnova, 1998, 2000; Smirnova, Toropova, 2008). This understanding is based on a population view of the community and biogeocenotic cover. According to the concept of biogeocenosis as a system of interacting populations, the forest cover should be considered a hierarchy of population units in species of different trophic groups. The population life of edificators unites this multiscale mosaic into communities. Population mosaics of keystone species create an environment suitable for sustainable life of populations of many subordinate species and determine the maximum species diversity in communities.

Phytogenic mosaicism in undisturbed forests results from the population life of edificator trees. In forests, the population life of trees creates a mosaic of lighting, water and soil regimes. This mosaic results from gaps in tree canopy that occur due to aging and death of one or several trees growing nearby. The death of a tree and associated soil perturbation determine the development of wind-soil complexes. At the same time, it builds a specific dumping microrelief, including hills, depressions, and coarse woody debris (Bobrovskij, 2004, 2013). Heterogeneous gap-like environment and wind-soil complexes, created as a result of generation flows in edificator tree populations, determines the presence of the maximum possible set of subordinate species of plants, animals, fungi, and representatives of other kingdoms in undisturbed forests. Having studied said mosaicism, Professor Olga V. Smirnova and her students created a new system of understanding forest ecology, the gap paradigm (Korotkov, 1991, 1993; Smirnova, 1998; Assessment …, 2000).

Professor Olga V. Smirnova convincingly shows that mosaicism caused by vitality of animal phytophages is as characteristic a feature of forest landscapes as phytogenic one (Smirnova et al., 1993; Eastern European …, 1994, 2004). Zoogenic mosaicism in preagricultural forests resulted from population life of animal edificators. In undisturbed European forests, these animals included: 1) large herd ungulates (bison, auroch, tarpan, etc.); 2) leaf- and needle-eating insects; 3) beavers. Large herd ungulates that destroyed young trees, shrubs, and grasses, as well as compacted and cherished the soil, created zoogenic glades with meadow, forest margin, and meadow-steppe flora. By destroying leaves and needles, insects increase the illumination on the grass cover surface and the temperature of the air and soil, enrich the soil with nitrogen and other minerals, and also contribute to an increase in number of light-loving and nitrophilic types of herbs. Beavers, by building dams on streams and small rivers, create ponds and lowland swamps, increase species diversity and the number of related plant and animal species. By destroying trees and shrubs in the coastal strip, beavers form glades with light-loving flora and fauna.

Professor Olga V. Smirnova shows that strong anthropogenic impact, destroying the population mosaic, breaks the cycles of generational turnover in keystone species. As a result, the development of communities becomes unidirectional, or succession, before the natural mosaic is restored. Understanding biogeocenosis as a system of interacting populations and a quantitative assessment of population parameters of principal coenosis builders make it possible to reconstruct the potential structure of biogeocenotic cover in an area, quantify the degree of disturbance in communities and their complexes, as well as to streamline existing succession systems.

The Concept of Anthropogenic Transformation of the Forest Cover in the Holocene

Despite the large number of works devoted to anthropogenic transformation of the forest cover in the Holocene, the paradigm of climate migration still prevails in domestic science. Summarizing historical and paleontological data, Professor Olga V. Smirnova proposed a new, “anthropic” system of views that defines human impact as the essential factor in biogeocoenotic cover transformation in the Holocene (Smirnova, Bobrovskij, 2000; Smirnova et al., 2001a, 2001b, 2006, 2013; Turubanova, 2002; Smirnova, Turubanova, 2003; Haritonenkov, 2012; Smirnova, Toropova, 2016; Kalyakin et al., 2016; Smirnova, Toropova, 2016; Smirnova et al., 2018). This new paradigm can be described as follows.

Written sources indicate that, over the recent 1–2 millennia, the diversity of life on Earth has been rapidly decreasing due to anthropogenic transformation. However, paleontological studies show that significant transformations on the Russian Plain and throughout Northern Eurasia date back much earlier. The first man-made environmental crisis in said area occurred 22–18 thousand years ago. It was caused by extermination of crucial edificators of late Pleistocene — that is, mammoths, woolly rhinoceros, giant deer, and other animals. They used to edify the composition and structure of plants and animals at that time. Herbs, primarily grasses, growing on meadow-steppe glades and forest margins were their primary source of nutrition. Meadow-steppe communities alternated with small clusters of trees. At the same time, palynology studies show that coniferous and broad-leaved tree species used to inhabit the entire Russian Plain in the Pleistocene. The soils of cryogenic savannah with a layer of permafrost underneath are chemically similar to modern chernozem soils. Their productivity throughout Northern Eurasia was so great that it allowed for sustainable existence of huge herds of giant phytophages and their retinue. Paleozoologists call this feature “the paradox of prehistoric pastures”. It was in cryogenic savannahs of the late Pleistocene (Upper or Final Paleolithic) that the sites of mammoth hunters with highly-developed farming and culture were found.

Over the recent 10.000–7.000 years, there has been a general climate warming, which coincided with gradual destruction of keystone species of giant and large animals of the mammoth complex as a result of hunting. The degradation of the mammoth complex, which began in the late Pleistocene, led to woody plants strengthening their role. The pastures the mammoths and their companions used to graze were then inhabited by trees. The first trees appeared by volatile seeds and a rapid generational turnover: that were birch, willow, aspen, and pine trees. They were followed by dark coniferous (spruce, fir) and broad-leaved (oak, linden, maple, ash, beech, hornbeam, etc.) trees. The near extinction of the giants and largest phytophages in the mammoth complex, combined with warming, marked the beginning of development of a forest belt in the early Holocene at the site of former Pleistocene cryogenic savannahs.

At the beginning of the Middle Holocene (7.000–2.500 years ago), the forest belt was almost completely developed on the Russian plain with broad-leaved and dark coniferous trees being predominant species; it occupied the space from the northern to southern seas. Within the forest belt, due to transforming activity of bisons, aurochs, tarpans, the saiga and other animals, zoogenic glades with meadow and steppe plants occurred constantly. Beavers built settlements with wetlands along small watercourses. As a result, the biogeocenotic cover of the Middle Holocene was a set of forest-meadow-bog complexes, created and regulated by keystone species, that is, large herd ungulates, beavers, and trees.

Since the mid-Middle Holocene occurred the production economy as the most powerful factor of biogeocenotic cover impact (agriculture, cattle breeding, smelting). The osteological material of this time includes a greatly reduced ratio of bones of wild ungulates (bison, auroch, tarpan, etc.) and increased ratio of livestock bones, whereas pollen of cultivated grasses appeared in the spore-pollen spectra. The production economy changed the biogeocenotic cover structure fundamentally. First of all, large herd ungulates and beavers disappeared not only due to hunting, but also due to the radical transformation of their habitats under the influence of slash-and-burn agriculture, logging and other harvesting trades. With the destruction of keystone animal species, the ratio of natural meadow-steppe ecosystems decreased, and that of forest ecosystems increased. As a result, the life of light-loving tree species (primarily oak and pine), as well as all light-loving plant species of other life forms, and many animal species that had previously inhabited zoogenic glades, became possible only in anthropogenic habitats. For example, pioneer tree species regenerated mainly on abandoned arable land.

Relatively “independent” from humans remained the ecosystems of “shadow” coniferous/broad-leaved forests; their spontaneous development is possible even now under a natural reserve regime. However, only part of the region’s natural flora and fauna can sustainably exist in these communities.  Ecosystems representing the “fragments” of mid-Holocene forest-meadow-bog complexes have been preserved in the modern forest cover of the Russian Plain only as a small number of refugiums, untouched by strong anthropogenic transformation of recent centuries.

It is from the late mid-Holocene that it becomes fundamentally impossible to restore the potential (former) biogeocenotic cover in a spontaneous mode, since, on the one hand, the populations of keystone animal species (large herd ungulates and beavers) have greatly decreased in number, and, on the other hand, humans have become the most powerful environment transforming force. Human activity began to determine the existence of certain subordinate plant and animal species.

By the late mid-Holocene, forest burning for the slash-and-burn agriculture cycle pushed the southern border of the forest belt to the north. The spread of nomadic cattle breeding in the south of the Russian Plain resulted in the formation of steppe and semi-desert-steppe zones. These events were a major step towards modern zonality and probably had a significant impact on changes in the macroclimate of Eurasia in its entirety. They maybe were a reason for the growing climate instability in the second half of the Holocene.

From Iron Age to early Middle Ages (2.500–500 years ago), the northern borders of the ranges of broad-leaved tree species significantly retreated to the south, mainly due to slash-and-burn agriculture, which marked the beginning of the modern taiga — a forest strip where said tree species do not exist. At the same time, specific pyrogenic forests with predominance of Pinus sylvestris developed on the sandy soils of the forest belt. Slash-and-burn, and then cross-bed and arable agriculture, forest grazing, gathering litter and coarse woody debris as well as other kinds of forest use resulted in soil cover degradation in large areas. Forest burning on the northern border was the reason why the tundra zone developed from the forest tundra and northern taiga in the late Holocene.

In general, the production economy of the mid- and late Holocene divided the unified forest-meadow-bog complex into two groups: 1) ecosystems capable of supporting themselves with spontaneous development (“shadow” forests), which formed the forest belt itself; 2) ecosystems that require constant anthropogenic impact for life (floodplain and land meadows, meadow steppes, forests of pioneer tree species). At the same time, there was a final step in formation of anthropogenic zonality — under human impact, the unified forest belt on the Russian Plain divided into coniferous, coniferous/broad-leaved and broad-leaved forests.

 CONCLUSION

Professor Olga V. Smirnova’s edifice is based on ideas about the leading role of plant and animal populations in the organization of the biogeocenotic cover. In this case, it is implied that a continuous generational turnover in edificator (keystone species) populations is necessary to maintain the species and structural diversity in communities and ensure their sustainability. This system of views was influenced by Professor Alexey A. Uranov. The development of these ideas was consistent and gradual. First, Professor Olga V. Smirnova studied the biology of different plant species life forms. Examining their individual development, with identification of ontogenetic stages, is necessary for demographic research. She then developed the theory of coenopopulations as supraorganismal systems, which can self-sustain under different conditions. Finally, she developed the doctrine of biogeocenosis as a system of interacting populations and created the concept of anthropogenic transformation of the forest cover in the Holocene. Her contributions helped researchers to understand the mechanisms of the formation of modern zonality that are due to human activity.

We would like to congratulate Professor Olga V. Smirnova on her anniversary! We wish her a long life full of success in her new creative endeavors, vigor, energy, and good health! Her colleagues and students, as well as Forest Science Issues editorial board, join the congratulation.

 ACKNOWLEDGMENTS

The authors thank Oleg G. Barinov, Maria A. Barinova, Maxim V. Bobrovskij, Natalia N. Bogomolova, Alexey V. Gornov, Elena S. Esipova, Ekaterina L. Zheleznaya, Ekaterina A. Kobozeva, Svetlana I. Ripa, Mikhail S. Romanov, Andrey M. Romanovskij, Elena P. Sarycheva, Nikolay S. Smirnov and Larisa G. Khanina for their help in preparing this article.

REFERENCES

Aleinikov A. A., Sostojanie populjacii i sredopreobrazujushhaja dejatel’nost’ bobra evropejskogo na territorii zapovednika “Brjanskij les” i ego ohrannoj zony: avtoref. dis. … kand. biol. nauk (Population status and environmental activity of the European beaver on the territory of the reserve “Bryansk forest” and its protection zone. Extended abstract of Candidate’s thesis), Tol’jatti: In-t jekologii Volzhskogo bassejna RAN, 2010, 22 p.

Argunova M. V., Ekologicheskoe obrazovanie v interesah ustojchivogo razvitija kak nadpredmetnoe napravlenie modernizacii shkol’nogo obrazovanija: avtoref. dis. … d-ra. ped. nauk (Environmental education for sustainable development as a non-objective direction of modernization of school education. Extended abstract of Doctor’s thesis), Moscow: Mosk. gos. obl. un-t, 2010, 47 p.

Argunova M. V., Populjacionnaja organizacija dubovo-grabovyh lesov Zapadnoj Ukrainy i optimizacija ih struktury: avtoref. dis. … kand. biol. nauk (Population organization of oak-hornbeam forests of Western Ukraine and optimization of their structure, Extended abstract of Candidate’s thesis), Moscow: MGPU im. V. I. Lenina, 1993, 16 p.

Barinova M. A., Vlijanie vodohranilishha na sinuzii zelenyh mhov doliny Giljuja: avtoref. dis. … kand. biol. nauk (The reservoir effect on sinusoi green mosses of the valley Gilya. Extended abstract of Candidate’s thesis), Moscow: MGPU im. V. I. Lenina, 1997, 16 p.

Bobrovskaja N. E., Formirovanie struktury kron listvennyh i hvojnyh derev’ev v ontogeneze: avtoref. dis. … kand. biol. nauk (Formation of crown structure of deciduous and coniferous trees in ontogenesis, Extended abstract of Candidate’s thesis), Moscow: MGPU, 2001, 19 p.

Bobrovskij M. V., Bioticheskie i antropogennye faktory dolgovremennoj dinamiki lesnyh pochv Evropejskoj Rossii: avtoref. dis. … d-ra biol. nauk (Biotic and anthropogenic factors of long-term dynamics of forest soils in European Russia. Extended abstract of Doctor’s thesis), Vladimir: im. A. G. i N. G. Stoletovyh, 2013, 48 p.

Bobrovskij M. V., Raznoobrazie rastitel’nosti i pochv zapovednika “Kaluzhskie zaseki” i ego svjaz’ s tradicionnym prirodopol’zovaniem: avtoref. dis. … kand. biol. nauk (Diversity of vegetation and soils of the reserve “Kaluga Zaseki” and its connection with traditional nature management. Extended abstract of Candidate’s thesis), Moscow: MGPU, 2004, 23 p.

Bogdanova N. G., Formirovanie travjanogo pokrova hvojno-shirokolistvennyh i shirokolistvennyh lesov v hode vosstanovitel’nyh sukcessij v Nerusso-Desnjanskom poles’e: avtoref. dis. … kand. biol. nauk (The formation of grass cover coniferous and deciduous forests during the restoration successions in Nerussa-Desna Polesye), Moscow: MGPU, 2006, 21 p.

Braslavskaja T. Ju., Biologicheskoe raznoobrazie i dinamika rastitel’nosti v pojme maloj reki Juzhnogo Nechernozem’ja (na primere r. Nerussa, Brjanskaja obl.): avtoref. dis. … kand. biol. nauk (Biological diversity and vegetation dynamics in the floodplain of the small river of the southern non-Chernozem region (by the example of the Neruss river, Bryansk region), Extended abstract of Candidate’s thesis), Moscow: MGPU, 2001, 21 p.

Cenopopuljacii rastenij (ocherki populjacionnoj biologii) (Plant coenopopulations (essays on population biology)), Moscow: Nauka, 1988, 184 p.

Cenopopuljacii rastenij (osnovnye ponjatija i struktura) (Plant coenopopulations (basic concepts and structure)), Moscow: Nauka, 1976, 217 p.

Cenopopuljacii rastenij (razvitie i vzaimootnoshenija) (Plant coenopopulations (development and relationships)), Moscow: Nauka, 1977, 135 p.

Chumachenko S. I., Biojekologicheskaja model’ raznovozrastnogo lesnogo cenoza: avtoref. dis. … kand. biol. nauk (Bioecological model of uneven-aged forest cenosis. Extended abstract of Candidate’s thesis), Moscow: MGPU im. V. I. Lenina, 1993, 16 p.

Chumachenko S. I., Imitacionnoe modelirovanie mnogovidovyh raznovozrastnyh lesnyh nasazhdenij: avtoref. dis. … d-ra biol. nauk (Simulation modeling of multi-species multi-age forest stands. Extended abstract of Doctor’s thesis), Moscow: Mosk. gos. u-t lesa, 2006, 32 p.

Dinamika cenopopuljacij rastenij (Dynamics of plant coenopopulations), Moscow: Nauka, 1985, 208 p.

European Russian Forests. Their Current State and Features of Their History, Smirnova O., Bobrovskij M., Khanina L. (eds.). Dordrecht: Springer Nature, 2017, 566 p.

Evstigneev O. I., Didenko E. G., Populjacionnye strategii vidov kustarnikov (Population strategies of shrub species), Vostochnoevropejskie lesa: istorija v golocene i sovremennost’ (Eastern European forests: history in Holocene and contemporaneity), Vol. 2, Moscow: Nauka, 2004, pp. 205–224.

Evstigneev O. I., Fitocenotipy i otnoshenie listvennyh derev’ev k svetu: avtoref. dis. … kand. biol. nauk (Fitocenotype and the relation of deciduous trees to light. Extended abstract of Candidate’s thesis), Moscow: MGPI, 1990, 17 p.

Evstigneev O. I., Mehanizmy podderzhanija biologicheskogo raznoobrazija lesnyh biogeocenozov: avtoref. dis. … d-ra biol. nauk (Mechanisms of maintenance of biological diversity of forest biogeocenoses. Extended abstract of Doctor’s thesis), Nizhnij Novgorod: NNGU, 2010, 48 p.

Evstigneev O. I., Populjacionnye strategii vidov derev’ev (Population strategies of tree species), Vostochnoevropejskie lesa: istorija v golocene i sovremennost’, Moscow: Nauka, 2004, Vol. 1, pp. 176–205.

Grime J. P., Plant strategies and vegetation processes, N. Y., 1979, 222 p.

Istomina I. I., Kvazisenil’nost’ i ee rol’ v zhizni drevesnyh rastenij: avtoref. dis. … kand. biol. nauk (Quasi-senility and its role in the life of woody plants. Extended abstract of Candidate’s thesis), Moscow: MGPU im. V. I. Lenina, 1993, 16 p.

Kharitonenkov M. A., Rol’ antropogennogo faktora v formirovanii rastitel’nogo pokrova juga Zapadno-Sibirskoj ravniny v jepohu tradicionnogo prirodopol’zovanija (s pozdnego paleolita do konca XIX v.): avtoref. dis. … kand. biol. nauk (The role of anthropogenic factor in the formation of vegetation cover of the South of the West Siberian plain in the era of traditional nature management (from the late Paleolithic to the end of the XIX century), Extended abstract of Candidate’s thesis), Moscow: Mosk. gos. obl. un-t, 2012, 25 p.

Kalyakin V. N., Turubanova S. A., Smirnova O. V., The origin and development of the East European taiga in late Cenozoic, Russian Journal of Ecosystem Ecology, 2016, Vol. 1, No 1, pp. 1–26, DOI: 10.21685/2500-0578-2016-1-2.

Kiseleva L. L., Jekologo-floristicheskij analiz jekotonnyh soobshhestv central’noj lesostepi: avtoref. dis. … kand. biol. nauk (Ecological and floristic analysis of ecotonic communities of the Central forest-steppe. Extended abstract of Candidate’s thesis), Moscow: MGPU im. V. I. Lenina, 1994, 16 p.

Korotkov V. N., Demutacionnye processy v ostrovnyh lesnyh massivah (na primere GIZL “Gorki Leninskie” i Kanevskogo zapovednika): avtoref. dis. … kand. biol. nauk (Demutation processes in island forests (on the example GISL Gorki Leninskie and Kanev nature reserve). Extended abstract of Candidate’s thesis), Moscow: MGPU im. V. I. Lenina, 1993, 16 p.

Korotkov V. N., Novaja paradigma v lesnoj jekologii (New paradigm in forest ecology), Biologicheskie nauki, 1991, No 8, pp. 7–20.

Lugovaja D. L., Rol’ jekotopicheskih i antropogennyh faktorov v formirovanii vidovogo i strukturnogo raznoobrazija juzhnotaezhnyh lesov (vostok Kostromskoj oblasti): avtoref. dis. … kand. biol. nauk (The role of ecotopic and anthropogenic factors in the formation of species and structural diversity of South taiga forests (East of Kostroma region), Extended abstract of Candidate’s thesis), Moscow: MGPU, 2008, 28 p.

Nedoseko O. I., Ontomorfogenez Salix pentandra L., Salix caprea L., Salix cinerea L.: avtoref. dis. … kand. biol. nauk (The ontomorphogenesis Salix pentandra L., Salix caprea L., Salix cinerea L. Extended abstract of Candidate’s thesis), Moscow: MGPU im. V. I. Lenina, 1993, 16 p.

Nedoseko O. I., Stanovlenie zhiznennyh form i arhitektoniki kron boreal’nyh vidov iv podrodov Salix i Vetrix Dumort. v ontogeneze: avtoref. dis. … d-ra biol. nauk (Formation of life forms and architectonics of crowns of boreal species of willows of subgenera Salix and Vetrix Dumort. in ontogenesis. Extended abstract of Doctor’s thesis), Moscow: MSHA im. K. A. Timirjazeva, 2018, 43 p.

Ocenka i sohranenija bioraznoobrazija lesnogo pokrova v zapovednikah Evropejskoj Rossii (Assessment and conservation of forest cover biodiversity in reserves of European Russia), Moscow: Nauchnyj mir, 2000, 196 p.

Ontogenez i vozrastnoj sostav populjacij cvetkovyh rastenij (Ontogenesis and age composition of flowering plant populations), Moscow: Nauka, 1967, 156 p.

Popov S. Ju., Struktura i dinamika rastitel’nosti Kerzhenskogo zapovednika: avtoref. dis. … kand. biol. nauk (Structure and dynamics of vegetation of Kerzhensky reserve. Extended abstract of Candidate’s thesis), Moscow: MGPU, 2008, 20 p.

Rabotnov T. A., Zhiznennyj cikl mnogoletnih travjanistyh rastenij v lugovyh cenozah (Life cycle of perennial herbaceous plants in meadow cenoses), Trudy BIN ANSSSR, Ser. 3, Geobotanika, 1950, Vol. 6, pp. 7–204.

Ramenskij L. G., O principial’nyh ustanovkah, osnovnyh ponjatijah i terminah proizvodstvennoj tipologii zemel’, geobotaniki i jekologii (On fundamental principles, basic concepts and terms of production typology of land, geobotany and ecology), Sovetskaja botanika, 1935, No 4, pp. 25–41.

Ripa S. I., Populjacionno-cenoticheskij analiz gornyh bukovyh i smeshannyh lesov Ukrainskih Karpat: avtoref. dis. … kand. biol. nauk (Population-cenotic analysis of mountain beech and mixed forests of the Ukrainian Carpathians. Extended abstract of Candidate’s thesis), Moscow: MGPU im. V. I. Lenina, 1997, 16 p.

Romanovskij A. M., Osobennosti ontogeneza i fitocenoticheekaja rol’ eli evropejskoj v lesah Nerusso-Desnjanskogo poles’ja: avtoref. dis. … kand. biol. nauk (Features of ontogenesis and phytocenotic role of spruce in the forests Nerussa-Desna Polesye. Extended abstract of Candidate’s thesis), Moscow: MGPU, 2006, 18 p.

Samohina T. Ju., Struktura i spontannaja dinamika hvojno-shirokolistvennyh lesov Srednego Urala: avtoref. dis. … kand. biol. nauk (Structure and spontaneous dynamics of coniferous broad-leaved forests of the Middle Urals. Extended abstract of Candidate’s thesis), M.: MGPU im. V. I. Lenina, 1997, 16 p.

Sarycheva E. P., Strukturnoe i vidovoe raznoobrazie chernool’hovyh lesov centra evropejskoj Rossii (na primere zapovednikov “Brjanskij les” i “Voroninskij”): avtoref. dis. … kand. biol. nauk (Structural and species diversity of black alder forests in the center of European Russia (on the example of reserves “Bryansk forest” and “Voroninsky”) Extended abstract of Candidate’s thesis), M.: MGPU, 2000, 16 p.

Shanijazova Z. P., Populjacionnaja biologija jefemerov Karakalpakii: avtoref. dis. … kand. biol. nauk (Population biology of the ephemera of Karakalpakstan. Extended abstract of Candidate’s thesis), Moscow: MGPU, 1994, 16 p.

Shestakova A. A., Jekologo-cenoticheskie i floristicheskie osobennosti organizacii briobioty na territorii Nizhegorodskoj oblasti: avtoref. dis. … kand. biol. nauk (Ecological-cenotic and floristic features of the organization of mosses in the Nizhny Novgorod region. Extended abstract of Candidate’s thesis), Nizhnij Novgorod: NNGU im. N. I. Lobachevskogo, 2005, 28 p.

Shorina N. I., Kurchenko E. I., Grigor’eva N. M., Aleksej Aleksandrovich Uranov (1901–1974) (Alexei Alexandrovich Uranov, 1901–1974), Samarskaja Luka: problemy regional’noj i global’noj jekologii, 2014, Vol. 23, No 1, pp. 93–129.

Smirnova O. V., Bakun E. Ju., Turubanova S. A., Predstavlenie o potencial’nom i vosstanovlennom rastitel’nom pokrove lesnogo pojasa Vostochnoj Evropy (Understanding of the potential and restored vegetation cover of the forest belt of Eastern Europe), Lesovedenie, 2006, No 1, pp. 22–33.

Smirnova O. V., Bobrovskij M. V., Vozdejstvie proizvodjashhego hozjajstva na sostav i strukturu lesnogo pokrova (The impact of the producing economy on the composition and structure of forest cover), Ocenka i sohranenija bioraznoobrazija lesnogo pokrova v zapovednikah Evropejskoj Rossii (Assessment and conservation of forest cover biodiversity in reserves of European Russia), Moscow: Nauchnyj mir, 2000, pp. 22–26.

Smirnova O. V., Chistjakova A. A., Analiz fitocenoticheskih potencij nekotoryh drevesnyh vidov shirokolistvennyh lesov Evropejskoj chasti SSSR (Analysis of phytocenotic potencies of some woody species of broad-leaved forests of the European part of the USSR), Zhurn. obshh. biol., 1980, Vol. 41, No 3, pp. 350–362.

Smirnova O. V., Chistjakova A. A., Drobysheva T. I., Cenopopuljacionnyj analiz i prognozy razvitija dubovo-grabovyh lesov Ukrainy (Cenopopulation analysis and forecasts of development of oak-hornbeam forests in Ukraine), Zhurn. obshh. biol., 1987, Vol. 48, No 2, pp. 200–212.

Smirnova O. V., Chistjakova A. A., Popadjuk R. V., Evstigneev O. I., Korotkov V. N., Mitrofanova M. V., Ponomarenko E. V., Populjacionnaja organizacija rastitel’nogo pokrova lesnyh territorij (na primere shirokolistvennyh lesov evropejskoj chasti SSSR) (Population organization of vegetation cover of forest areas (on the example of broad-leaved forests of the European part of the USSR)), Pushhino: ONTI Nauchnyj centr biol. issledovanij AN SSSR, 1990, 92 p.

Smirnova O. V., Chistjakova A. A., Popadjuk R. V., Populjacionnye mehanizmy dinamiki lesnyh cenozov (Population mechanisms of the dynamics of forest cenoses), Biologicheskie nauki, 1989, No 11, pp. 48–58.

Smirnova O. V., Chistjakova A. A., Ripa S. I., Lysyh N. I., Populjacionnaja organizacija bukovyh lesov Zakarpat’ja (Population organization of beech forests in Transcarpathia), Bjul. MOIP. Otd. biol., 1989, Vol. 94, No 5, pp. 78–91.

Smirnova O. V., Geraskina A. P., Aleinikov A. A., The concept “complementarity” as the basis for model and nature reconstruction of potential biota in the current climate, Russian Journal of Ecosystem Ecology, 2018, Vol. 3, No 3, pp. 1–21, DOI: 10.21685/2500-0578-2018-3-1.

Smirnova O. V., Kaljakin V. N., Turubanova S. A., Bobrovskij M. V., Sovremennaja zonal’nost’ Vostochnoj Evropy kak rezul’tat preobrazovanija pozdneplejstocenovogo kompleksa kljuchevyh vidov (Modern zoning of Eastern Europe as a result of transformation of the late Pleistocene complex of key species), Mamont i ego okruzhenie: 200 let izuchenija (Mammoth and its environment: 200 years of study), Moscow: Geos, 2001a, pp. 200–208.

Smirnova O. V., Lugovaja D. L., Prokazina T. S., Model’naja rekonstrukcija vosstanovlennogo lesnogo pokrova taezhnyh lesov (Model reconstruction of the restored forest cover of taiga forests), Uspehi sovrem. biol., 2013, Vol. 133, No 2, pp. 164–177.

Smirnova O. V., Popadjuk R. V., Chistjakova A. A., Populjacionnye metody opredelenija minimal’noj ploshhadi lesnogo cenoza (Population methods for determining the minimum area of forest cenosis), Bot. zhurn., 1988, Vol. 73, No 10, pp. 1423–1433.

Smirnova O. V., Popadjuk R. V., Janickaja T. O., Korotkov V. N., Puti vosstanovlenija populjacionnoj struktury i vidovogo raznoobrazija v lesnyh demutacionnyh kompleksah (Ways of restoration of population structure and species diversity in forest demutation complexes), Biologicheskie nauki, 1992, No 5, pp. 7–25.

Smirnova O. V., Populjacionnaja organizacija biocenoticheskogo pokrova lesnyh landshaftov (Population organization of biocenotic cover of forest landscapes), Uspehi sovrem. biol., 1998, Vol. 118, No 2, pp. 148–165.

Smirnova O. V., Populjacionnaja organizacija biogeocenoticheskogo pokrova lesnyh territorij (Population organization of biogeocenosis cover of forest territories), Ocenka i sohranenija bioraznoobrazija lesnogo pokrova v zapovednikah Evropejskoj Rossii (Assessment and conservation of forest cover biodiversity in reserves of European Russia), Moscow: Nauchnyj mir, 2000, pp. 14–22.

Smirnova O. V., Povedenie vidov i funkcional’naja organizacija travjanogo pokrova shirokolistvennyh lesov (na primere ravninnyh shirokolistvennyh lesov Evropejskoj chasti SSSR i lipnjakov Sibiri): dis. … d-ra biol. nauk (Behavior of species and functional organization of grass cover of broad-leaved forests (on the example of flat broad-leaved forests of the European part of the USSR and Linden forests of Siberia). Doctor’s thesis), Leningrad: LGU im. A. A. Zhdanova, 1983, 685 p.

Smirnova O. V., Povedenie vidov i funkcional’naja organizacija travjanogo pokrova shirokolistvennyh lesov Evropejskoj chasti SSSR (Behavior of species and functional organization of grass cover of deciduous forests of the European part of the USSR), Bjul. MOIP. Otd. biol., 1980, Vol. 85, No 5, pp. 53–67.

Smirnova O. V., Struktura travjanogo pokrova shirokolistvennyh lesov (Grass cover structure of broad-leaved forests), Moscow: Nauka, 1987, 208 p.

Smirnova O. V., Toropova N. A., Potencial’naja rastitel’nost’ i potencial’nyj jekosistemnyj pokrov (Potential vegetation and potential ecosystem cover), Uspehi sovrem. biol., 2016, Vol. 136. No 2, pp. 199–211.

Smirnova O. V., Toropova N. A., Potential ecosystem cover — a new approach to conservation biology, Russian Journal of Ecosystem Ecology, 2016, Vol. 1, No 1, pp. 1–16, DOI: 10.21685/2500-0578-2016-1-1.

Smirnova O. V., Toropova N. A., Sukcessija i klimaks kak jekosistemnyj process (Potential vegetation and potential ecosystem cover), Uspehi sovrem. biol., 2008, Vol. 128, No 2, pp. 129–144.

Smirnova O. V., Turubanova S. A., Bobrovskij M. V., Korotkov V. N., Hanina L. G., Rekonstrukcija istorii biocenoticheskogo pokrova Vostochnoj Evropy i problema podderzhanija biologicheskogo raznoobrazija (Reconstruction of the history of the biocenotic cover of Eastern Europe and the problem of maintaining biological diversity), Uspehi sovrem. biol., 2001b, No 2, pp. 144–159.

Smirnova O. V., Turubanova S. A., Formirovanie i razvitie Vostochnoevropejskih shirokolistvennyh lesov v golocene (Formation and development of Eastern European broadleaf forests in the Holocene), Bjul. MOIP. Otd. biol., 2003, Vol. 108, No 2, pp. 32–40.

Smirnova O. V., Voznjak R. R., Evstigneev O. I., Korotkov V. N., Nosach N. Ja., Popadjuk R. V., Samojlenko V. K., Toropova N. A., Populjacionnaja diagnostika i prognozy razvitija zapovednyh lesnyh massivov (na primere Kanevskogo zapovednika) (Population diagnostics and forecasts of development of protected forests (on the example of Kanev reserve)), Bot. zhurn., 1991, Vol. 76, No 6, pp. 860–871.

Smirnova O. V., Zaugol’nova L. A., Popadjuk R. V., Populjacionnaja koncepcija v biocenologii (Population concept in biotsenology), Zhurn. obshh. biol. 1993, Vol. 54, No 4, pp. 438–448.

Smirnova O. V., Zhiznennye cikly, chislennost’ i vozrastnoj sostav populjacij osnovnyh komponentov travjanogo pokrova dubrav: dis. … kand. biol. nauk (Life cycles, number and age composition of populations of the main components of oak grass cover. Candidate’s thesis), Moscow: MGPI im. V. I. Lenina, 1968, 285 p.

Smirnova Ol’ga Vsevolodovna, Intellektual’naya Sistema Tematicheskogo Issledovaniya Naukometricheskih dannyh (Intelligent System case Studies Scientometric data), available at: http://istina.msu.ru/profile/sov1933/ (September 14, 2019).

Sugorkina N. S., Ontogenez i osobennosti populjacionnoj biologii vidov roda geran’: avtoref. dis. … kand. biol. nauk (Ontogenesis and peculiarities of population biology of geranium species. Extended abstract of Candidate’s thesis), Moscow: MGPI, 1989, 17 p.

Turubanova S. A., Jekologicheskij scenarij istorii formirovanija zhivogo pokrova Evropejskoj Rossii i sopredel’nyh territorij na osnove rekonstrukcii arealov kljuchevyh vidov zhivotnyh i rastenij: avtoref. dis. … kand. biol. nauk (Ecological scenario of the history of the formation of the living cover of European Russia and adjacent territories on the basis of the reconstruction of the habitats of key species of animals and plants. Extended abstract of Candidate’s thesis), Moscow: In-t biol. Komi nauchn. centra Ural’skogo otd. RAN, 2002, 23 p.

Voprosy morfogeneza cvetkovyh rastenij i stroenija ih populjacij (Morphogenesis of flowering plants and the structure of their populations), Moscow: Nauka, 1968, 234 p.

Vostochnoevropejskie lesa: istorija v golocene i sovremennost’ (Eastern European forests: history in Holocene and contemporaneity), Moscow: Nauka, 2004a, Vol. 1, 479 p.

Vostochnoevropejskie lesa: istorija v golocene i sovremennost’ (Eastern European forests: history in Holocene and contemporaneity), Moscow: Nauka, 2004b, Vol. 2, 575 p.

Vostochnoevropejskie shirokolistvennye lesa (Eastern European broadleaf forests). Moscow: Nauka, 1994, 364 p.

Vozrastnoj sostav populjacij cvetkovyh rastenij v svjazi s ih ontogenezom (Age composition of flowering plant populations due to their ontogenesis), Moscow: MGPI im. V. I. Lenina, 1974, 216 p.

Zaprudina M. V., Mikromozaichnaja organizacija travjano-kustarnichkovogo i mohovogo pokrova srednetaezhnyh temnohvojnyh lesov Urala: avtoref. dis. … kand. biol. nauk (Micromosaic organization of grass-shrub and moss cover of middle taiga dark coniferous forests of the Urals. Extended abstract of Candidate’s thesis), Moscow: MGPU, M., 2012, 23 p.

Zaugol’nova L. A., Zhukova L. A., Popadjuk R. V., Smirnova O. V., Kriticheskoe sostojanie cenopopuljacij rastenij (The critical state of plant coenopopulations), Problemy ustojchivosti biologicheskih system, Moscow: Nauka, 1992, pp. 51–59.

Zaugol’nova L. B., Smirnova O. V., Komarov A. S., Hanina L. G., Monitoring fitopopuljacij (Monitoring of phytopopulation), Uspehi sovrem. biol. 1993, Vol. 113, No 4, pp. 402–414.

Zaugol’nova L. B., Smirnova O. V., Vozrastnaja struktura cenopopuljacij mnogoletnih rastenij i ee dinamika (Age structure of perennial plant coenopopulations and its dynamics), Zhurn. obshh. biol., 1978, Vol. 39, No 6, pp. 849–858.

Zaugol’nova L. B., Struktura cenopopuljacij semennyh rastenij i problemy ih monitoringa: dis. … d-ra biol. nauk (Structure of seed plant coenopopulations and problems of their monitoring. Doctor’s thesis), SPb: SPb gos. un-t, 1994, 70 p.

Zaugol’nova L. B., Svjaz’ vozrastnogo spektra cenopopuljacij s biologicheskimi svojstvami vida (Relation of age spectrum of coenopopulations with biological properties of a species), In: Vozrastnoj sostav populjacij cvetkovyh rastenij v svjazi s ih ontogenezom (Age composition of flowering plant populations due to their ontogenesis), Moscow: MGPI im. V. I. Lenina, 1974, pp. 38–55.

Zhukova L. A., Mir prinadlezhit optimistam (The world belongs to the optimists), Polivariantnost’ razvitija organizmov, populjacij i soobshhestv, Joshkar-Ola: Mar. gos. un-t, 2006, pp. 229–278.

Reviewer: Candidate of Biological Sciences A. V. Gornov

]]> https://jfsi.ru/en/5-2-2022-ershov_sochilova/ Fri, 09 Jun 2023 16:31:59 +0000 https://jfsi.ru/?p=5696

 D.V. Ershov^*, E. N. Sochilova

Center for Forest Ecology and Productivity of the Russian Academy of Sciences

Profsoyuznaya st. 84/32 bldg. 14, Moscow, 117997, Russian Federation

 ^*E-mail: dvershov67@gmail.com

Received: 28.11.2022

Revised: 15.12.2022

Accepted: 18.12.2022

The paper presents statistic of the amount of direct Carbon emissions during wildfires of 2021 in the forested lands of Russia using long-term satellite data. In 2021, the area of ​​forest fire damages was 9.3 million hectares, and the amount of Carbon emissions was 66.4 MtC. These values are almost two points higher than the long-term average values. A comparison of similar indicators for twenty years allowed us to conclude that that year is anomalous with respect to the entire time series, similarly to the fire seasons of 2003 and 2012. The period or interval of recurrence of three anomalous fire seasons is nine years. We do not know the reason for the recurrence of anomalous fire seasons. At the same time, the forested areas damaged of the wildfires and the amount of direst Carbon and other greenhouse gases emissions in anomalous fire season years decreases from 127.2 MtC (3.7 p.) in 2003, 83.8 MtC (2.4 p.) in 2012 to 66.4 MtC (1.9 p.) in 2021.

Keywords: Wildfires, Pyrogenic Emissions, Carbon, Remote Sensing Monitoring, Forest Fire Fuels

REFERENCES

Bartalev S. A., Egorov V. A., Zharko V. O., Lupjan E. A., Plotnikov D. E., Hvostikov S. A., Shabanov N. V., Sputnikovoe kartografirovanie rastitel’nogo pokrova Rossii (Land cover mapping over Russia using Earth observation data), Moscow: IKI RAN, 2016, 208 p.

Cvetkov P. A., Zapasy gorjuchih materialov v lesah severo-vostoka Jevenkii (Stocks of fire fuels in the forests of the north-east of Evenkia), Lesnoe hozjajstvo, 2001, No 4, pp. 93–96.

Ershov D. V., Bartalev S. A., Isaev A. S., Sochilova E. N., Stycenko F. V., Metod ocenki pozharnyh jemissij parnikovyh gazov s ispol’zovaniem sputnikovyh dannyh: rezul’taty primenenija dlja lesov Rossii v 21 veke (Fire assessment method of greenhouse gas emission with satellite data: results of forest for Russia in the 21st century), Ajerokosmicheskie metody i geoinformacionnye tehnologii v lesovedenii, lesnom hozjajstve i jekologii (Aerospace Methods and GIS-Technologies in Forestry, Forest Management and Ecology), Proc. VI All-Russian Conference, Moscow, Russia, April 20-22, 2016, pp. 12–17.

Ershov D. V., Kovganko K. A., Sochilova E. N., GIS-tehnologija ocenki pirogennyh jemissij ugleroda po dannym Terra-MODIS i gosudarstvennogo ucheta lesov (GIS-technology of fire carbon emission assessment using Terra-Modis products and state forest account data), Sovremennye problemy distancionnogo zondirovanija Zemli iz kosmosa, 2009, Issue 6, Vol. 2, pp. 365–372.

Ershov D. V., Sochilova E. N., Dvadcatiletnjaja dinamika prjamyh pirogennyh jemissij ugleroda v lesah Rossii v 21 veke po dannym distancionnogo monitoringa (Twenty-year dynamics of direct pyrogenic carbon emissions in the forests of Russia in the 21st century according to remote monitoring data), Nauchnye osnovy ustojchivogo upravlenija lesami (Scientific Basis for Sustainable Forest Management), Proc. IV All-Russian Conference, Moscow, Russia, April 21–25, 2022, pp. 267–269.

Ershov D. V., Sochilova E. N., Ocenka prjamyh pirogennyh jemissij ugleroda v lesah Rossii za 2020 god po dannym distancionnogo monitoringa (Assessment of direct pyrogenic carbon emissions in russian forests for 2020 using remote monitoring data), Voprosy lesnoj nauki, 2020, Vol. 3, No 4, pp. 1–8.

Fedorov E. H., Cykalov A. G., Nazemnye gorjuchie materialy v zelenomoshnyh listvennichnikah Srednej Sibiri (Land fire fuels in green-moss larch forest of Central Siberia), Lesovedenie, 2002, No 6, pp. 63–67.

Furjaev I. V., Dement’eva Ju. S., Furjaev V. V., Struktura kompleksov napochvennyh gorjuchih materialov v nasazhdenijah Verhne-Obskogo massiva Altajskogo kraja (Structure of complexes of ground fire fuels in the stands of the Verkhne-Ob massif of the Altai Region), In: Problemy lesovedenija i lesovodstva (Problems of forest science and forestry), Issue 69, 2009, pp. 737–742.

Furjaev V. V., Zablockij V. I., Zlobina L. P., Chernyh V. A., Samsonenko S. D., Kompleksy napochvennyh gorjuchih materialov i vozmozhnost’ ih regulirovanija v profilaktike lesnyh pozharov (Complexes of ground fire fuels and the possibility of their regulation in the prevention of forest fires), Lesnoe hozjajstvo, 2007, No 1, pp. 43–44.

Kharuk V. I., Ponomarev E. I., Ivanova G. A., Dvinskaya M. L., Coogan S. C. P., Flannigan M. D., Wildfires in the Siberian taiga, Ambio, 2021, Vol. 50, pp. 1953–1974, DOI: 10.1007/s13280-020-01490-x.

Kovaleva N. M., Sobachkin R. S., Sobachkin D. S., Petrenko A. E., Struktura gorjuchih materialov v sosnjakah raznogo vozrasta Krasnojarskoj stepi (The structure of forest fuels in variously aged pine woodlands of forest steppe domain in Krasnoyarsk), Lesovedenie, 2017, No 5, pp. 431–436, DOI: 10.7868/S0024114817060055.

Kurbatskij N. P., Issledovanie kolichestva i sostava lesnyh gorjuchih materialov (Investigation of quantity and composition of the forest fire fuels), In: Voprosy lesnoj pirologii (Questions of forest pyrology), Krasnojarsk, 1970, pp. 5−58.

Lupjan E. A., Proshin A. A., Burcev M. A., Kashnickij A. V., Balashov I. V., Bartalev S. A., Konstantinova A. M., Kobec D. A., Mazurov A. A., Marchenkov V. V., Matveev A. M., Radchenko M. V., Sychugov I. G., Tolpin V. A., Uvarov I. A., Opyt jekspluatacii i razvitija centra kollektivnogo pol’zovanija sistemami arhivacii, obrabotki i analiza sputnikovyh dannyh (CKP “IKI-Monitoring”) (Experience of development and operation of the IKI-Monitoring center for collective use of systems for archiving, processing and analyzing satellite data), Sovremennye problemy distancionnogo zondirovanija Zemli iz kosmosa, 2019, Vol. 16, No 3, pp. 151–170. DOI: 10.2104

Matveeva T. A., Zapasy lesnyh gorjuchih materialov v gornyh lesah Juzhnoj Sibiri (Wood combustibles resources in mountain forests of south Siberia), Vestnik Altajskogo gosudarstvennogo agrarnogo universiteta, 2008, No 12 (50), pp. 30–33.

Ponomarev E., Yakimov N., Ponomareva T., Yakubailik O., Conard S. G., Current trend of carbon emissions from wildfires in Siberia, Atmosphere, 2021, Vol. 12 (5), Article 559. DOI: 10.3390/atmos12050559.

Rasporyazhenie Pravitel’stva Rossijskoj Federacii ot 29 oktyabrya 2022 goda № 3240-r (Government Decree of the Russian Federation No 3240-r, October 29, 2022) “Ob utverzhdenii innovacionnogo proekta po sozdaniyu nacional’noj sistemy monitoringa klimaticheski aktivnyh veshchestv”, 2022, 30 p., available at: URL: http://government.ru/docs/46939/ (November 14, 2023).

Schepaschenko D. G., Muhortova L. V., Shvidenko A. Z., Vedrova Je. F., Zapasy organicheskogo ugleroda v pochvah Rossii (The pool of organic carbon in the soils of Russia), Pochvovedenie, 2013, No 2, pp. 123–132.

Schepaschenko D., Moltchanova E., Shvidenko A., Blyshchyk V., Dmitriev E., Martynenko O., See L., Kraxner F., Improved estimates of biomass expansion factors for Russian forests, Forests, 2018, Vol. 9 (6), Article 312, DOI: 10.3390/f9060312

Sheshukov M. A., Vlijanie nekotoryh faktorov sredy na polnotu sgoranija gorjuchih materialov i ih kriticheskij zapas pri lesnyh pozharah (Impact of some environmental factors on complete combustion of fire fuels and their critical volume in case of forest fires), Lesovedenie, 1970, No 4, pp. 40–43.

Shvidenko A. Z., Schepaschenko D. G., Climate change and wildfires in Russia, Contemporary Problems of Ecology, 2013, Vol. 6, No 7, pp. 683–692, DOI: 10.1134/S199542551307010X.

Shvidenko A. Z., Schepaschenko D. G., Nil’sson S., Buluj Ju. I., Tablicy i modeli hoda rosta i produktivnosti nasazhdenij osnovnyh lesoobrazujushhih porod Severnoj Evrazii (normativno-spravochnye materialy) (Tables and models of growth and productivity of forests of major forest forming species of Northern Eurasia (standard and reference materials)), Moscow: Federal’noe agentstvo lesnogo hozjajstva, 2008, 803 p.

Shvidenko A., Schepaschenko D., Nil’sson S., Ocenka zapasov drevesnogo detrita v lesah Rossii (Assessment of wood detritus storage in forests of Russia), Lesnaja taksacija i lesoustrojstvo, 2009, No 1 (41), pp. 133–147.

Sochilova E. N., Ershov D. V., Korovin G. N., Metody sozdanija kart zapasov lesnyh gorjuchih materialov nizkogo prostranstvennogo razreshenija (Methods of course resolution forest fuel load mapping), Sovremennye problemy distancionnogo zondirovanija Zemli iz kosmosa, 2009, Vol. 2, Issue 6, pp. 441–449.

Stycenko F. V., Bartalev S. A., Egorov V. A., Lupjan E. A., Metod ocenki stepeni povrezhdenija lesov pozharami na osnove sputnikovyh dannyh MODIS (Post-fire forest tree mortality assessment method using MODIS satellite data), Sovremennye problemy distancionnogo zondirovanija Zemli iz kosmosa, 2013, Vol. 10, No 1, pp. 254–266.

Utkin A. I., Gul’be Ja. I., Gul’be T. A., Ermolova L. S., Biologicheskaja produktivnost’ lesnyh jekosistem (Biological productivity of forest ecosystems), Database, Moscow: IL RAN, CEPL RAN, 1994.

VEGA-RRO, available at: http://pro-vega.ru (November 29, 2022)

Vonskij S. M., Intensivnost’ ognja nizovyh lesnyh pozharov i ee prakticheskoe znachenie (The intensity of ground forest fires and their practical significance), Leningrad: LenNIILH, 1957, 52 p.

Zamolodchikov D. G., Korovin G. N., Utkin A. I., Chestnyh O. V., Sangen B., Uglerod v lesnom fonde i sel’skohozjajstvennyh ugod’jah Rossii (Carbon in forest and agricultural lands of Russia), Moscow: KMK, 2005, 200 p.

Zamolodchikov D. G., Utkin A. I., Chestnyh O. V., Kojefficienty konversii zapasov nasazhdenij v fitomassu dlja osnovnyh lesoobrazujushhih porod Rossii (Conversion factors of forest stocks volumes in biomass for the main dominated forest species of Russia), Lesnaja taksacija i lesoustrojstvo, 2003, Issue 1 (32), pp. 119–127.

]]> https://jfsi.ru/en/5-4-2022-tebenkova_et_al/ Fri, 02 Jun 2023 16:18:19 +0000 https://jfsi.ru/?p=5688

D.N. Tebenkova, D. V. Gichan, Yu. N. Gagarin

Center for Forest Ecology and Productivity of the Russian Academy of Sciences

Profsoyuznaya st. 84/32 bldg. 14, Moscow, 117997, Russian Federation

E-mail: tebenkova.dn@gmail.com

Received: 20.11.2022

Revised: 18.12.2022

Accepted: 20.12.2022

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.

 Keywords: carbon, soil, forest carbon projects, silvicultural practices

REFERENCES

Achat D. L., Fortin M., Landmann G., Ringeval B., Augusto L., Forest soil carbon is threatened by intensive biomass harvesting, Scientific reports, 2015, Vol. 5, No 1, pp. 1–10.

Akkumuljacija ugleroda v lesnyh pochvah i sukcessionnyj status lesov (Carbon accumulation in forest soils and the successional status of forests) / Pod red. Lukinoj N. V. Moscow: KMK, 2018, 232 p.

Atmadja S., Verchot L., A review of the state of research, policies and strategies in addressing leakage from reducing emissions from deforestation and forest degradation (REDD+), Mitigation and Adaptation Strategies for Global Change, 2012, No 17(3), pp. 311–336.

Aukland L., Costa P. M., Brown S. A., Conceptual framework and its application for addressing leakage: the case of avoided deforestation, Climate Policy, 2003, No 3(2), pp. 123–136.

Behrendt H., Dannowski R., Nutrients and heavy metals in the Odra River System, Germany: Weissensee Verlag Publ, 2007, 337 p.

Boča A., Van Miegroet H., Gruselle M. C., Forest overstory effect on soil organic carbon storage: a meta-analysis, Soil Science Society of America Journal, 2014, Vol. 78, No S1, pp. 35–47.

Bravo–Oviedo A., Ruiz–Peinado R., Modrego P., Alonso R., Montero G., Forest thinning impact on carbon stock and soil condition in Southern European populations of P. sylvestris L, Forest Ecology and Management, 2015, Vol. 357, pp. 259–267.

Byhovec S. S., Komarov A. S., Prostoj statisticheskij imitator klimata pochvy s mesjachnym shagom (Simple statistical Soil Climate Simulator with monthly increments), Pochvovedenie, 2002, No 4, pp. 443–452.

Cardenas E., Kranabetter J. M., Hope G., Maas K. R., Hallam S., Mohn W. W., Forest harvesting reduces the soil metagenomic potential for biomass decomposition, The ISME Journal, 2015, Vol. 9, No 11, pp. 2465–2476.

Carlyle J. C., Organic carbon in forested sandy soils: properties, processes, and the impact of forest management, New Zealand Journal of Forestry Science, 1993, Vol. 23, No 3, pp. 390–402.

Chertov O., Komarov A., Shaw C., Bykhovets S., Frolov P., Shanin V., Grabarnik P., Priputina I., Zubkova E., Shashkov M., Romul_Hum—A model of soil organic matter formation coupling with soil biota activity. II. Parameterisation of the soil food web biota activity, Ecological Modelling, 2017, Vol. 345, pp. 125–139.

Chertov O., Shaw C., Shashkov M., Komarov A., Bykhovets S., Shanin, V., Grabarnik P., Frolov, P., Priputina I., Kalinina O., Zubkova E., Romul_Hum model of soil organic matter formation coupled with soil biota activity. III. Parameterisation of earthworm activity, Ecological Modelling, 2017, Vol. 345, pp. 140–149.

Chestnyh O. V., Grabovskij V. I., Zamolodchikov D. G., Ocenka zapasov pochvennogo ugleroda lesnyh rajonov Rossii s ispol’zovaniem baz dannyh pochvennyh harakteristik (Assessment of soil carbon reserves in Russian forest areas using soil characteristics databases), Lesovedenie, 2022, No 3, pp. 227–238.

Christophel D., Höllerl S., Prietzel J., Steffens M., Long-term development of soil organic carbon and nitrogen stocks after shelterwood- and clear-cutting in a mountain forest in the Bavarian Limestone Alps, European Journal of Forest Research, 2015, Vol. 134, No 4, pp. 623–640.

Chumachenko S. I., Shanin V. N., Mitrofanov E. M., Lebedev S. V., Frolov P. V., Kondrat’ev S. A., Shmakova M. V., Lukina N. V., Teben’kova D. N., Hanina L. G., Grabarnik P. Ja., Chertov O. G. Bobrovskij M. V., RUFOSS — programmnyj modul’ integracii imitacionnyh modelej dlja ocenki vzaimodejstvij mezhdu lesnymi jekosistemnymi uslugami (RUFOSS is a software module for integrating simulation models to assess interactions between forest ecosystem services) Svidetel’stvo No 2020666245.

Chumachenko S. I., Korotkov V. N., Palenova M. M., Politov D., Simulation modeling of long-term stand dynamics at different scenarios of forest management for coniferous–broad-leaved forests, Ecological Modelling, 2003, Vol. 170, pp. 345–362.

Chumachenko S. I., Bazovaja model’ dinamiki mnogovidovogo raznovozrastnogo lesnogo cenoza (The basic model of the dynamics of a multi-species multi-age forest cenosis), Voprosy jekologii i modelirovanija lesnyh jekosistem (Issues of ecology and modeling of forest ecosystems), Proc. Conf., Vol. 248, Moscow, 1993, pp. 147–180.

Clarke N., Gundersen P., Jönsson-Belyazid U., Kjønaas O. J., Persson T., Sigurdsson B. D., Vesterdal L., Influence of different tree-harvesting intensities on forest soil carbon stocks in boreal and northern temperate forest ecosystems, Forest Ecology and Management, 2015, Vol. 351, pp. 9–19.

Córdova S. C., Olk D. C., Dietzel R. N., Mueller K. E., Archontouilis S. V., Castella M. J., Plant litter quality affects the accumulation rate, composition, and stability of mineral-associated soil organic matter, Soil Biology and Biochemistry, 2018, Vol. 125, pp. 115–124.

Cotrufo M. F., Wallenstein M. D., Boot C. M., Denef K., Paul E., The Microbial Efficiency Matrix Stabilization (MEMS) framework integrates plant litter decomposition with soil organic matter stabilization: do labile plant inputs form stable soil organic matter? Global change biology, 2013, Vol. 19, No 4, pp. 988–995.

Craig M. E., Turner B. L., Liang C., Clay K., Johnson D. J., Phillips R. P., Tree mycorrhizal type predicts within site variability in the storage and distribution of soil organic matter, Global change biology, 2018, Vol. 24, No 8, pp. 3317–3330.

De Coninck H., Revi A., Babiker M., Bertoldi P., Buckeridge M., Cartwright A., Sugiyama T., Strengthening and implementing the global response, Global warming of 1.5 C: Summary for policy makers. — IPCC–The Intergovernmental Panel on Climate Change, 2018, pp. 313–443.

Devine W. D., Harrington C. A., Influence of harvest residues and vegetation on microsite soil and air temperatures in a young conifer plantation, Agricultural and Forest Meteorology, 2007, Vol. 145, No 1–2, pp. 125–138.

Donofrio S., Maguire P., Daley Ch., Calderon C., Lin K., Forest Trends’ Ecosystem Marketplace The Art of Integrity: State of Voluntary Carbon Markets, Q3 Insights Briefing. Washington DC, Forest Trends Association, 2022, p. 21.

Dymov A. A., Vlijanie sploshnyh rubok v boreal’nyh lesah Rossii na pochvy (obzor) (The effect of continuous logging in boreal forests of Russia on soils (review)), Pochvovedenie, 2017, No 7, pp. 787–798.

Dymov A. A., Starcev V. V., Izmenenie temperaturnogo rezhima podzolistyh pochv v processe estestvennogo lesovozobnovlenija posle sploshnyh rubok (Changes in the temperature regime of podzolic soils in the process of natural reforestation after continuous logging, Pochvovedenie, 2016, No 5, pp. 599–608.

Fedorov B. G., Rossijskij uglerodnyj balans: monografija (Russian carbon balance: monograph), Moscow: Nauchnyj konsul’tant, 2017, 82 p.

FIA. Forest Inventory Analysis National Program, USFS, USDA Forest Service, 2020, available at: https://www.fia.fs.fed.us./ (June 24, 2022).

Finér L., Domisch T., Dawud S. M., Raulund–Rasmussen K., Vesterdal L., Bouriaud O., Valladares F., Conifer proportion explains fine root biomass more than tree species diversity and site factors in major European forest types, Forest Ecology and Management, 2017, Vol. 406, pp. 330–350.

Fischer H., Bens O., Hüttl R., Veränderung von Humusform,–vorrat und–verteilung im Zuge von Waldumbau–Maßnahmen im Nordostdeutschen Tiefland, Forstwissenschaftliches Centralblatt vereinigt mit Tharandter forstliches Jahrbuch, 2002, Vol. 121, No 6, pp. 322–334.

Fröberg M., Hansson K., Kleja D. B., Alavi Gh., Dissolved organic carbon and nitrogen leaching from Scots pine, Norway spruce and silver birch stands in southern Sweden, Forest ecology and management, 2011, Vol. 262, No 9, pp. 1742–1747.

Gamfeldt L., Snäll T., Bagchi R., Jonsson M., Gustafsson L., Kjellander P., Bengtsson J., Higher levels of multiple ecosystem services are found in forests with more tree species, Nature communications, 2013, Vol. 4, No 1, pp. 1–8.

Georgiadis P., Vesterdal L., Stupak I., Raulund‐Rasmussen K., Accumulation of soil organic carbon after cropland conversion to short rotation willow and poplar, GCB Bioenergy, 2017, Vol. 9, No 8, pp. 1390–1401.

Gillingham K., Stock J. H., The Cost of Reducing Greenhouse Gas Emissions, Journal of Economic Perspectives, 2018, No 32 (4), pp. 53–72.

Gross C. D., James J. N., Turnblom E. C., Harrison R. B., Thinning treatments reduce deep soil carbon and nitrogen stocks in a coastal pacific northwest forest, Forests, 2018, Vol. 9, No 5, Article 238.

Guo L. B., Gifford R. M., Soil carbon stocks and land use change: a meta-analysis, Global change biology, 2002, Vol. 8, No 4, pp. 345–360.

Hanina L. G., Bobrovskij M. V., Komarov A. S., Mihajlov A. V., Byhovec S. S., Luk’janov A. M., Modelirovanie dinamiki raznoobrazija lesnogo napochvennogo pokrova (Modeling the dynamics of diversity of forest ground cover), Lesovedenie, 2006, No 1, pp. 70–80.

Holden S. R., Treseder K. K., A meta-analysis of soil microbial biomass responses to forest disturbances, Frontiers in microbiology, 2013, Vol. 4, Article 163.

Hoffmann T., Schlummer M., Notebaert B., Verstraeten G., Korup O., Carbon burial in soil sediments from Holocene agricultural erosion, Central Europe, Global Biogeochemical Cycles, 2013, Vol. 27, No 3, pp. 828–835.

Hoover C. M., Management impacts on forest floor and soil organic carbon in northern temperate forests of the US, Carbon balance and management, 2011, Vol. 6, No 1, pp. 1–8.

Huang L. Liu J., Shao Q., Xu X., Carbon sequestration by forestation across China: Past, present, and future, Renewable and Sustainable Energy Reviews, 2012, Vol. 16, No 2, pp. 1291–1299.

Hyvönen R., Kaarakka L., Leppälammi-Kujansuu J., Olsson B. A., Palviainen M., Vegerfors-Persson B., Helmisaari H. S., Effects of stump harvesting on soil C and N stocks and vegetation 8–13 years after clear-cutting, Forest Ecology and Management, 2016, Vol. 371, pp. 23–32.

James J., Harrison R., The effect of harvest on forest soil carbon: A meta–analysis, Forests, 2016, Vol. 7, No 12, Article 308.

Johnson K., Scatena F. N., Pan Y., Short- and long-term responses of total soil organic carbon to harvesting in a northern hardwood forest, Forest Ecology and Management, 2010, Vol. 259, pp. 1262–1267.

Johnson D. W., Curtis P. S., Effects of forest management on soil C and N storage: meta-analysis, Forest ecology and management, 2001, Vol. 140, No 2–3, pp. 227–238.

Jurevics A., Peichl M., Olsson B. A., Strömgren M., Egnell G., Slash and stump harvest have no general impact on soil and tree biomass C pools after 32–39 years, Forest Ecology and Management, 2016, Vol. 371, pp. 33–41.

Karpechko Ju. V., Vlijanie rubok na stok s lesopokrytoj chasti vodosbora Onezhskogo ozera (The effect of logging on runoff from the forested part of the Onega Lake catchment), Trudy KarNC RAN, Petrozavodsk, No 2016, pp. 13–20.

Khanina L., Bobrovsky M., Komarov A., Mikhajlov A., Modeling dynamics of forest ground vegetation diversity under different forest management regimes, Forest Ecology and Management, 2007, Vol. 248, pp. 80–94.

Khanina L. G., Bobrovsky M. V., Komarov A. S., Shanin V. N., Bykhovets S. S., Model predictions of effects of different climate change scenarios on species diversity with or without management intervention, repeated thinning, for a site in Central European Russia, [in:] Nitrogen Deposition, Critical Loads and Biodiversity, Springer, 2014, pp. 173–182.

Kalinina L., Chertov O., Frolov P., Goryachkin S., Kuner P., Küper J., Kurganova I., Lopes de Gerenyu V., Lyuri D., Rusakov A., Kuzyakov Y., Giani L., Alteration process during the post-agricultural restoration of Luvisols of the temperate broad-leaved forest in Russia, Catena, 2018, Vol. 171, pp. 602–612.

Katzensteiner K., Effects of harvesting on nutrient leaching in a Norway spruce (Picea abies Karst.) ecosystem on a Lithic Leptosol in the Northern Limestone Alps, Plant and Soil, 2003, Vol. 250, No 1, pp. 59–73.

Keller A. B., Brzostek E. R., Craig M. E., Fisher J. B., Phillips R. P., Root‐derived inputs are major contributors to soil carbon in temperate forests, but vary by mycorrhizal type, Ecology Letters, 2021, Vol. 24, No 4, pp. 626–635.

Kim S., Han S. H., Li G., Yoon T. K., Lee S. T., Kim C., Son Y., Effects of thinning intensity on nutrient concentration and enzyme activity in Larix kaempferi forest soils, Journal of Ecology and Environment, 2016, Vol. 40, No 1, pp. 1–7.

Klein D., Fuentes J. P., Schmidt A., Schmidt H., Schulte A., Soil organic C as affected by silvicultural and exploitative interventions in Nothofagus pumilio forests of the Chilean Patagonia, Forest Ecology and Management, 2008, Vol. 255, No 10, pp. 3549–3555.

Kohout P., Charvátová M., Štursová M., Mašínová T., Tomšovský M., Baldrian P., Clearcutting alters decomposition processes and initiates complex restructuring of fungal communities in soil and tree roots, The ISME journal, 2018, Vol. 12, No 3, pp. 692–703.

Komarov A., Chertov O., Bykhovets S., Shaw C., Nadporozhskaya M., Frolov P., Shashkov M., Shanin V., Grabarnik P., Priputina I., Zubkova E., Romul_Hum model of soil organic matter formation coupled with soil biota activity. I. Problem formulation, model description, and testing, Ecological Modelling, 2017, Vol. 345, pp. 113–124.

Kondrat’ev S. A., Formirovanie vneshnej nagruzki na vodoemy: problemy modelirovanija (Formation of external load on reservoirs: modeling problems), Saint Petersburg: Nauka, 2007, 255 p.

Kondrat’ev S. A., Kazmina M. V., Shmakova M. V., Markova E. G., Metod rascheta biogennoj nagruzki na vodnye ob’ekty (Method of calculation of biogenic load on water bodies), Regional’naja jekologija, 2011, No 3–4, pp. 50–59.

Kondrat’ev S. A., Karpechko Ju. V., Shmakova M. V., Rasulova A. M., Rodionov V. Z., Opyt jeksperimental’nyh issledovanij i matematicheskogo modelirovanija vozdejstvij vyrubki lesa i posledujushhego lesovosstanovlenija na stok i vynos himicheskih veshhestv s lesnyh vodosborov (Experience of experimental research and mathematical modeling of the effects of deforestation and subsequent reforestation on the runoff and removal of chemicals from forest catchments), Regional’naja jekologija, 2019, No 1 (55), pp. 25–53.

Kondrat’ev S. A., Shmakova M. V., Izuchenie formirovanija stoka s rechnyh vodosborov metodami matematicheskogo modelirovanija (na primere bassejna Ladozhskogo ozera) (Studying the formation of runoff from river catchments by mathematical modeling methods (on the example of the Ladoga Lake basin)), Sbornik nauchnyh trudov 12 s”ezda Russkogo geograficheskogo obshchestva (Collection of scientific papers of the 12th Congress of the Russian Geographical Society), Saint Petersburg: Nauka, 2005, Vol. 6, pp. 99–104.

Kuznecova A. I., Gornov A. V., Gornova M. V., Teben’kova D. N., Nikitina A. D., Kuznecov V. A., Ocenka vynosa ugleroda s pochvennymi vodami v dominirujushhih tipah lesa Brjanskogo Poles’ja (Assessment of carbon removal from soil waters in the dominant forest types of the Bryansk Polesie), Pochvovednie, 2022, No 9, pp. 1086–1097.

Kuznetsova A. I., Geraskina A. P., Lukina N. V., Smirnov V. E., Tikhonova E. V., Shevchenko N. E., Gornov A. V., Ruchinskaya E. V., Tebenkova D. N., Linking vegetation, soil carbon stocks, and earthworms in upland coniferous–broadleaf forests, Forests, 2021, No 12 (9), Article 1179.

Kuznecova A. I., Lukina N. V., Gornov A. V., Gornova M. V., Tihonova E. V., Smirnov V. Je., Danilova M. A., Teben’kova D. N., Braslavskaja T. Ju., Kuznecov V. A., Tkachenko Ju. N., Genikova N. V., Zapasy ugleroda v peschanyh pochvah sosnovyh lesov na zapade Rossii (Carbon reserves in sandy soils of pine forests in western Russia), Pochvovedenie, 2020, No 8, pp. 959–969.

Kreutzer K., Deschu E., Hösl G., Vergleichende Untersuchungen uber den Ein-fluβ von Fichte (Picea abies [L.] Karst.) und Buche (Fagus sylvatica L.) auf die Sickerwasserqualität, Forstwissenschaftliches Centralblatt, 1986, Vol. 105, pp. 364–371.

Kulmala L., Aaltonen H., Berninger F., Kieloaho A. J., Levula J., Bäck J., Pumpanen J., Changes in biogeochemistry and carbon fluxes in a boreal forest after the clear-cutting and partial burning of slash, Agricultural and Forest Meteorology, 2014, Vol. 188, pp. 33–44

Laganiere J., Angers D. A., Pare D., Carbon accumulation in agricultural soils after afforestation: a meta-analysis, Global change biology, 2010, Vol. 16, No 1, pp. 439–453.

Lee J. G., Lee D. H., Jeong J. Y., Lee S. G., Han S. H., Kim S. J., Kim H. J., The Effects of Stand Density Control on Carbon Cycle in Chamaecyparis obtusa (Siebold and Zucc.) Endl., Forests, Forests, 2023, Vol. 14 (2), Article 217.

Lemus R., Lal R., Bioenergy crops and carbon sequestration, Critical Reviews in Plant Sciences, 2005, Vol. 24, No 1, pp. 1–21.

Li Y., Bruelheide H., Scholten T., Schmid B., Sun Z., Zhang N., Bu W., Liu X., Ma K., Early positive effects of tree species richness on soil organic carbon accumulation in a large-scale forest biodiversity experiment, Journal of Plant Ecology, 2019, Vol. 12, No 5, pp. 882–893.

Lippke B., Puettmann M., Oneil E., Oliver C. D., The plant a trillion trees campaign to reduce global warming — Fleshing out the concept, Journal of Sustainable Forestry, 2021, Vol. 40. No 1, pp. 1–31.

Lippke B., Puettmann, M. E., Oneil, E., CORRIM Tech Note 1. Effective uses of forest derived products to reduce carbon emissions, The Consortium for Research on Renewable Industrial Materials, 2020, available at: https://corrim.org/use–of–forest–products–to–reduce–carbon–emissions/ (June 24, 2022).

Lukina N. V. Geraskina A. P., Kuznecova A. I., Smirnov V. Je., Gornov A. V., Shevchenko N. E., Tihonova E. V., Teben’kova D. N., Basova E. V., Funkcional’naja klassifikacija lesov: aktual’nost’ i podhody k razrabotke (Functional classification of forests: relevance and approaches to development), Lesovedenie, 2021, No 6, pp. 566–580.

Mallik A. U., Hu D., Soil respiration following site preparation treatments in boreal mixedwood forest, Forest Ecology and Management, 1997, Vol. 97, No 3, pp. 265–275.

Mayer M., Sandén H., Rewald B., Godbold D. L., Katzensteiner K., Increase in heterotrophic soil respiration by temperature drives decline in soil organic carbon stocks after forest windthrow in a mountainous ecosystem, Functional Ecology, 2017, Vol. 31, No 5, pp. 1163–1172.

Michaelowa A., Hermwille L., Obergassel W., Butzengeiger S., Additionality revisited: guarding the integrity of market mechanisms under the Paris Agreement, Climate Policy, 2019, Vol. 19, No 10, pp. 1211–1224.

Morris D. M., Hazlett P. W., Fleming R. L., Kwiaton M. M., Hawdon L. A., Leblanc J. D., Weldon T. P., Effects of Biomass Removal Levels on Soil Carbon and Nutrient Reserves in Conifer Dominated, Coarse Textured Sites in Northern Ontario: 20 Year Results, Soil Science Society of America Journal, 2019, Vol. 83, pp. 116–132.

Mushinski R. M., Gentry T. J., Boutton T. W., Forest organic matter removal leads to long-term reductions in bacterial and fungal abundance, Applied Soil Ecology, 2019, Vol. 137, pp. 106–110.

Nave L. E., Domke G. M., Hofmeister K. L., Mishra U., Perry C. H., Walters B. F., Swanston C. W., Reforestation can sequester two petagrams of carbon in US topsoils in a century, Proceedings of the National Academy of Sciences, 2018, Vol. 115, No 11, pp. 2776–2781.

Nave L. E., Vance E. D., Swanston C. W., Curtis P. S., Harvest impacts on soil carbon storage in temperate forests, Forest Ecology and Management, 2010, Vol. 259, No 5, pp. 857–866.

Noormets A., Epron D., Domec J. C., McNulty S. G., Fox T., Sun G., King J. S., Effects of forest management on productivity and carbon sequestration: A review and hypothesis, Forest Ecology and Management, 2015, Vol. 355, pp. 124–140.

Oliver C. D., Nassar N. T., Lippke B. R., McCarter J. B., Carbon, fossil fuel, and biodiversity mitigation with wood and forests, Journal of Sustainable Forestry, 2014, Vol. 33, No 3, pp. 248–275.

Oneil E. E., Lippke B. R., Integrating products, emission offsets, and wildfire into carbon assessments of Inland Northwest forests, Wood and Fiber Science, 2010, Vol. 42, pp. 144–164.

Pan Y., Birdsey R. A., Fang J., Houghton R., Kauppi P. E., Kurz W. A., Hayes D. A., Large and persistent carbon sink in the world’s forests, Science, 2011, Vol. 333, No 6045, pp. 988–993.

Pang X., Hu B., Bao W., de Oliveira Vargas T., Tian G., Effect of thinning-induced gap size on soil CO₂ efflux in a reforested spruce forest in the eastern Tibetan Plateau, Agricultural and forest meteorology, 2016, Vol. 220, pp. 1–9.

Parizhskoe soglashenie, 2015, available at: https://golnk.ru/oMxvm, (February 08, 2022)

Paul K. I., Polglase P. J., Nyakuengama J. G., Khanna P. K., Change in soil carbon following afforestation, Forest ecology and management, 2002, Vol. 168, No 1–3, pp. 241–257.

Persson T., Lenoir L., Vegerfors B., Long-term effects of stump harvesting and site preparation on pools and fluxes of soil carbon and nitrogen in central Sweden, Scandinavian Journal of Forest Research, 2017, Vol. 32, No 3, pp. 222–229.

Pötzelsberger E., Hasenauer H., Soil change after 50 years of converting Norway spruce dominated age class forests into single tree selection forests, Forest Ecology and Management, 2015, Vol. 338, pp. 176–182.

Prescott C. E., Blevins L. L., Staley C. L., Effects of clear–cutting on decomposition rates of litter and forest floor in forests of British Columbia, Canadian Journal of Forest Research, 2000, Vol. 30, No 11, pp. 1751–1757.

Pretzsch H., Canopy space filling and tree crown morphology in mixed-pecies stands compared with monocultures, Forest Ecology and Management, 2014, Vol. 327, pp. 251–264.

Pretzsch H., Diversity and productivity in forests: evidence from long-term experimental plots, Forest diversity and function, Springer, Berlin, Heidelberg, 2005, pp. 41–64.

Priputina I. V., Frolova G. G., Shanin V. N., Vybor optimal’nyh shem posadki lesnyh kul’tur: komp’juternyj jeksperiment (Choosing optimal planting schemes for forest crops: a computer experiment), Komp’juternye issledovanija i modelirovanie, 2016, Vol. 8, No 2, pp. 333–343.

Puhlick J. J., Fernandez I. J., Weiskittel A. R., Evaluation of forest management effects on the mineral soil carbon pool of a lowland, mixed–species forest in Maine, USA, Canadian journal of soil science, 2016, Vol. 96, No 2, pp. 207–218.

Pumpanen J., Westman C. J., Ilvesniemi H., Soil CO₂ efflux from a podzolic forest soil before and after forest clear-cutting and site preparation, Boreal Environment Research, 2004, Vol. 9, pp. 199–212.

Resh S. C., Binkley D., Parrotta J. A., Greater soil carbon sequestration under nitrogen-fixing trees compared with Eucalyptus species, Ecosystems, 2002, Vol. 5, No 3, pp. 217–231.

Rezoljucija po itogam nauchnyh debatov “Lesnye klimaticheskie proekty v Rossii”, Moskow, 2021, 19 Oсtober, available at: https://goo.su/ITAB, (February 08, 2022).

Richter D. D., Markewitz D., Trumbore S. E., Wells, C. G., Rapid accumulation and turnover of soil carbon in a re-establishing forest, Nature, 1999, Vol. 400, No 6739, pp. 56–58.

Rytter R. M., Rytter L., Changes in soil chemistry in an afforestation experiment with five tree species, Plant and Soil, 2020, No 456, pp. 425–437.

Rytter R. M., The potential of willow and poplar plantations as carbon sinks in Sweden, Biomass and Bioenergy, 2012, Vol. 36, pp. 86–95.

Schmidt M. G., Macdonald S. E., Rothwell R. L., Impacts of harvesting and mechanical site preparation on soil chemical properties of mixed-wood boreal forest sites in Alberta, Canadian Journal of Soil Science, 1996, Vol. 76, No 4, pp. 531–540.

Shanin V. N., Frolov P. V., Korotkov V. N., Vsegda li iskusstvennoe lesovosstanovlenie mozhet byt’ lesoklimaticheskim proektom (Can artificial reforestation always be a forest-climatic project), Voprosy lesnoj nauki, 2022, Vol. 5, No 2, pp. 103–139.

Shanin V., Juutinen A., Ahtikoski A., Frolov P., Chertov O., Rämö J., Lehtonen A., Laiho R., Mäkiranta P., Nieminen M., Laurén A., Sarkkola S., Penttilä T., Ťupek B., Mäkipää R., Simulation modelling of greenhouse gas balance in continuous-cover forestry of Norway spruce stands on nutrient–rich drained peatlands, Forest Ecology and Management, 2021, Vol. 496, Article 119479.

Special’nye lesoklimaticheskie proekty mogut sposobstvovat’ snizheniju uglerodnogo naloga, kotoryj Evrosojuz planiruet vvesti v 2025 godu (Special forest-climatic projects can contribute to reducing the carbon tax, which the European Union plans to introduce in 2025), 2021, available at: http://www.igras.ru/news/2719 (February 07, 2022).

Streck C., REDD+ and leakage: debunking myths and promoting integrated solutions, Climate Policy, 2021, Vol. 21 (6), pp. 843–52.

Strömgren M., Egnell G., Olsson B. A., Carbon stocks in four forest stands in Sweden 25 years after harvesting of slash and stumps, Forest Ecology and Management, 2013, Vol. 290, pp. 59–66.

Strukelj M., Brais S., Paré D., Nine-year changes in carbon dynamics following different intensities of harvesting in boreal aspen stands, European journal of forest research, 2015, No 134, pp. 737–754.

Tang J., Bolstad P. V., Martin J. G., Soil carbon fluxes and stocks in a Great Lakes forest chronosequence, Global Change Biology, 2009, Vol. 15, No 1, pp. 145–155.

The greenhouse gas protocol. The land use, land-use change, and forestry guidance for GHG project accounting, Washington: Word Resource Institute, 2006, 97 p., available at: https://goo.su/puTzd (September 08, 2022).

Thiffault E., Hannam K. D., Paré D., Titus B. D., Hazlett P. W., Maynard D. G., Brais S., Effects of forest biomass harvesting on soil productivity in boreal and temperate forests—A review, Environmental Reviews, 2011, Vol. 19, pp. 278–309.

Transformacija jekosistem severa v zone intensivnoj zagotovki drevesiny (Transformation of ecosystems of the North in the zone of intensive wood harvesting), Tr. Komi nauchnogo centra UrO RAN, Syktyvkar, 1996. No 154, 160 p.

Vanguelova E. I., Pitman R., Benham S., Perks M., Morison J. I., Impact of tree stump harvesting on soil carbon and nutrients and second rotation tree growth in Mid–Wales, UK, Open Journal of Forestry, 2017, Vol. 7, No 1, Article ID 73642.

Verified Carbon Standard, v 4.2, Issued: 2019, 19 September, available at: https://goo.su/x0mw (June 24, 2022).

Vesterdal L., Dalsgaard M., Felby C., Raulund-Rasmussen K., Jørgensen B. B., Effects of thinning and soil properties on accumulation of carbon, nitrogen and phosphorus in the forest floor of Norway spruce stands, Forest Ecology and Management, 1995, Vol. 77, No 1–3, pp. 1–10.

Vesterdal L., Raulund–Rasmussen K., Forest floor chemistry under seven tree species along a soil fertility gradient, Canadian journal of forest research, 1998, Vol. 28, No 11, pp. 1636–1647.

Vesterdal L., Ritter E., Gundersen P., Change in soil organic carbon following afforestation of former arable land, Forest ecology and management, 2002, Vol. 169, No 1–2, pp. 137–147.

Vesterdal L., Clarke N., Sigurdsson B. D., Gundersen P., Do tree species influence soil carbon stocks in temperate and boreal forests? Forest Ecology and Management, 2013, Vol. 309, pp. 4–18.

Volk T. A., Verwijst T., Tharakan P. J., Abrahamson L. P., White E. H., Growing fuel: a sustainability assessment of willow biomass crops, Frontiers in Ecology and the Environment, 2004, Vol. 2 (8), pp. 411–418.

Walmsley J. D., Jones D. L., Reynolds B., Price M. H., Healey J. R., Whole tree harvesting can reduce second rotation forest productivity, Forest Ecology and Management, 2009, Vol. 257, No 3, pp. 1104–1111.

Warren K. L., Ashton M. S., Change in soil and forest floor carbon after shelterwood harvests in a New England Oak–Hardwood Forest, USA, International Journal of Forestry Research, 2014, Vol. 2014, Article ID 527236.

Wiesmeier M., Prietzel J., Barthold F., Spörlein P., Geuß U., Hangen E., Kögel-Knabner I., Storage and drivers of organic carbon in forest soils of southeast Germany (Bavaria)—Implications for carbon sequestration, Forest ecology and management, 2013, Vol. 295, pp. 162–172.

Zabowski D., Chambreau D., Rotramel N., Thies W. G., Long-term effects of stump removal to control root rot on forest soil bulk density, soil carbon and nitrogen content, Forest Ecology and Management, 2008, Vol. 255, No 3–4, pp. 720–727.

Zakonoproekt N 1116605–7 Ob ogranichenii vybrosov parnikovyh gazov (On limiting greenhouse gas emissions), available at: https://goo.su/LSlh9h (February 08, 2022).

Zhang X. Guan D., Li W., Sun D., Jin C., Yuan F., Wu J., The effects of forest thinning on soil carbon stocks and dynamics: A meta-analysis, Forest Ecology and Management, 2018, Vol. 429, pp. 36–43.

Zhou D., Zhao S. Q., Liu S., Oeding J., A meta-analysis on the impacts of partial cutting on forest structure and carbon storage, Biogeosciences, 2013, Vol. 10, pp. 3691–3703.

]]> https://jfsi.ru/en/5-4-2022-podolskaia/ Wed, 19 Apr 2023 13:01:57 +0000 https://jfsi.ru/?p=5669

E. S. Podolskaia

Center for Forest Ecology and Productivity of the Russian Academy of Sciences

Profsoyuznaya st. 84/32 bldg. 14, Moscow, 117997, Russian Federation

E-mail: podols_kate@mail.ru

Received: 08.10.2022

Revised: 19.12.2022

Accepted: 20.12.2022

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.

Key words: remote sensing data from space, road network, image recognition, forestry, neural networks, convolutional neural networks, Open Source QGIS, plugins, MapFlow

REFERENCES

Akay A. E., Tas I., Using drone with a lidar data capture systems in forestry applications, International Academic Research Congress, INES, 2018, pp. 17–25.

Andreeva O. A., Konon N. I., Ratinskij M. G., K voprosu ispol’zovanija distancionnogo zondirovanija mestnosti pri proektirovanii zheleznyh dorog (To the question of use remote sensing for railways construction), Geodezija i kartografija, 2019, No 5. pp. 47–53. DOI: 10.22389/0016-7126-2019-947-5-47-53.

Ayala C., Aranda C., Galar M., Towards fine-grained roads maps extraction using Sentinel-2 imagery, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XXIV ISPRS Congress (2021 edition), 2021, Vol. 3, pp. 9–14.

Barrile V., Bilotta G., Fotia F., Bernardo E., Road extraction for emergencies from satellite imagery, ICCSA 2020, LNCS, pp. 767–781, DOI: 10.1007/978-3-030-58811-3_55.

Bekturov A. K., Primenenie materialov ajerokosmicheskih s”emok v izyskanijah i proektirovanii avtomobil’nyh dorog v uslovijah vysokogor’ja (Use of aerospace survey materials in the exploration and design of highways under high-altitude conditions), Vestnik Kyrgyzskogo gosudarstvennogo universiteta stroitel’stva, transporta i arhitektury im. N. Isanova, 2015, No 3 (49), pp. 43–48.

Bhil K., Shindihatti R., Mirza S., Latkar S., Ingle Y. S., Shaikh N. F., Prabu I., Pardeshi S. N., Recent progress in object detection in satellite imagery: a review, Sustainable Advanced Computing. Lecture Notes in Electrical Engineering, 2022, Vol. 840, pp. 209–218, DOI: doi.org/10.1007/978-981-16-9012-9_18.

Botelho J. Jr., Costa S. C. P., Ribeiro J. G., Souza C. M. Jr., Mapping roads in the Brazilian Amazon with artificial intelligence and Sentinel-2, Remote Sensing, 2022, Vol. 14, pp. 1–17, DOI: 10.3390/ rs14153625.

Сaliskan E., Sevim Y., Forest road detection using deep learning models, Geocarto International, 2022, Vol. 37, No 20, pp. 5875–5890, DOI: 10.1080/10106049.2021.1926555.

Chelnokov V. V., Meshalkin V. P., Strelkov S. P., Kondrashin K. G., Vizualizacija dannyh distancionnogo zondirovanija dorozhnyh setej v celjah analiza jekologicheskogo i socio-jekologicheskogo vozdejstvija (Visualization of remote sensing data of road networks for the analysis of ecological and socio-ecological impact), Geodezija i kartografija, 2021, No 3, pp. 36–43, DOI: 10.22389/0016-7126-2021-969-3-36-43.

Dolgopolov D. V., Ispol’zovanie dannyh distancionnogo zondirovanija Zemli pri formirovanii geoinformacionnogo prostranstva truboprovodnogo transporta (Use of Earth remote sensing data in the geoinformation space of pipeline transport), Vestnik SGUGiT, 2020, Vol. 25, No 3, pp. 151–159.

Dolgopolov D. V., Nikonov D. V., Polujanova A. V., Melkij V. A., Vozmozhnosti vizual’nogo deshifrirovanija magistral’nyh truboprovodov i ob”ektov infrastruktury po sputnikovym izobrazhenijam vysokogo i sverhvysokogo prostranstvennogo razreshenija (Possibilities of visual decoding of trunk pipelines and infrastructure facilities from satellite images of high and ultra-high spatial resolution), Vestnik SGUGiT, 2019, Vol. 24, No 3, pp. 65–81.

Fedoseev A. A., Miheeva T. I., Saprykin O. P., Mingazov P. P., Raspoznavanie ob”ektov transportnoj infrastruktury na giperspektral’nyh snimkah metodom glubinnogo mashinnogo obuchenija (Recognition of transport infrastructure objects on hyperspectral images by deep machine learning), Informacionnye tehnologii intellektual’noj podderzhki prinjatija reshenij (ITIDS’2016), Trudy IV Mezhdun. konf., Ufa, Izd-vo UGATU, 2016, pp. 39–44.

Fedoseev A. A., Miheeva T. I., Miheev S. V., Postroenie modeli transportnoj infrastruktury na osnove prostranstvenno-spektral’noj ajerokosmicheskoj informacii (Construction of transport infrastructure model based on the spatial-spectral aerospace information), Programmnye produkty i sistemy, 2018, No 1 (31), pp. 25–31.

Filatova A. V., Pozdysheva O. N., Kistineva A. O., Analiz processa deshifrirovanija pri stroitel’stve avtomobil’nyh dorog (Analysis of recognition in the construction of highways), Jelektronnyj nauchnyj zhurnal “Inzhenernyj vestnik Dona”, 2017, No 2, pp. 1–11.

Gecen R., Sarp G., Road detection from high and low resolution satellite images, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2008, Vol. XXXVII, Part B4, Beijing, pp. 355–358.

Gomes O. F. M., Feitosa R. Q., Coutinho H. L., C. Sub-pixel unpaved roads detection in Landsat images, Proceedings of XXXV Congress ISPRS, Committee 3, 2015, pp. 1–5.

Guindon B., Application of spatial reasoning methods to the extraction of roads from high-resolution satellite imagery, IGARSS ‘98. Sensing and Managing the Environment. International Geoscience and Remote Sensing. Symposium Proceedings, 1998, Vol. 2, pp. 1076–1078, DOI: 10.1109/IGARSS.1998.699677.

Gulci S., Akgul M., Akay A. E., Tas I., Using ready-to-use drone images in forestry activities: case study of Cinarpinar in Kahramanmaras, Turkey, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XLII-4/W6, 2017, 4th International GeoAdvances Workshop 14–15 October 2017, Safranbolu, Karabuk, Turkey. pp. 51–53.

Henry C., Azimi S. M., Merkle N., Road segmentation in SAR satellite images with deep fully convolutional neural networks, IEEE Geoscience and Remote Sensing Letters, 2018, pp. 1–6. DOI: 10.1109/LGRS.2018.2864342.

Ignat’ev A. V., Kulikov M. A., Capiev D. N., Tyrin V. V., Metodika avtomaticheskoj klassifikacii dorog s ispol’zovaniem nejronnoj seti Mask R-CNN (Method of automatic classification of roads using the neural network Mask R-CNN), Jelektronnyj nauchnyj zhurnal “Inzhenernyj vestnik Dona”, 2022, No 5, pp. 1–9.

Kobzeva E. A., Jeksperimental’naja ocenka tochnosti i deshifrovochnyh vozmozhnostej kosmicheskih snimkov RapidEye (Experimental evaluation of accuracy and decoding capabilities of RapidEye satellite images), Geomatics, 2010, No 2, pp. 33–36.

Maillard Ph., Cavayas F., Automatic map-guided extraction of roads from SPOT imagery for cartographic database updating, International Journal of Remote Sensing, 1989, No 10 (11), pp. 1775–1787, DOI: 10.1080/01431168908904007.

Mei J., Li R.-J., Gao W., Cheng M.-M., CoANet: Connectivity attention network for road extraction from satellite imagery, IEEE Transactions on Image Processing, 2021, Vol. 30, pp. 8540–8552, DOI: 10.1109/TIP.2021.3117076.

Mena J. B., State of the art on automatic road extraction for GIS update: a novel classification, Pattern Recognition Letters, 2003, Vol. 24, pp. 3037–3058.

Miheeva T. I., Fedoseev A. A., Klasterizacija giperspektral’nyh dannyh monitoringa ob’’ektov transportnoj infrastruktury (Clustering of hyperspectral monitoring data of transport infrastructure facilities), Izvestija Samarskogo nauchnogo centra Rossijskoj akademii nauk, 2014, Vol. 16, No 4 (2), pp. 404–408.

Miheeva T. N., Fedoseev A. A., Identifikacija izmenenij konfiguracii transportnoj seti na osnove kosmicheskoj s”emki (Identification of transport network configuration changes based on satellite imagery), Izvestija Samarskogo nauchnogo centra Rossijskoj akademii nauk, 2016, Vol. 18, No 4 (4), pp. 808–814.

Miroshnichenko S. Ju., Titov V. S., Jashhenko A. A., Metod avtomaticheskoj lokalizacii protjazhennyh geoprostranstvennyh ob”ektov (Method of automatic localization of extended geospatial objects), Izvestija vuzov. Priborostroenie, 2013, Vol. 56, No 6, pp. 17–22.

Muhametshin A. R., Samsonov T. E., Deshifrirovanie kosmicheskih snimkov s ispol’zovaniem mashinnogo obuchenija po dannym OpenStreetMap (Space images interpretation with machine learning based on the OpenStreetMap) Nauchnye issledovanija molodyh uchenyh-kartografov, vypolnennye pod rukovodstvom sotrudnikov kafedry kartografii i geoinformatiki geograficheskogo fakul’teta MGU imeni M. V. Lomonosova: sbornik statej, pod red. A. M. Karpachevskogo, Moscow, “KDU”, “Dobrosvet”, 2022, pp. 64–72.

Nachmany Y., Alemohammad H., Detecting roads from satellite imagery in the developing world, The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019, pp. 84–89.

Oehmcke S., Thrysoe C., Borgstad A., Vaz Salles M. A., Brandt M., Gieseke F., Detecting hardly visible roads in low-resolution satellite time series data, IEEE International Conference on Big Data, 2019, pp. 1–10, DOI:10.1109/BigData47090.2019.9006251.

Orlov V. A., Avtomatizirovannoe raspoznavanie lesnyh dorog po kosmicheskim snimkam (Automated recognition of forest roads based on satellite images), Aktual’nye problemy lesnogo kompleksa, 2006, No 14, pp. 1–4.

Pestunov I. A., Rylov S. A., Segmentacija sputnikovyh izobrazhenij vysokogo razreshenija po spektral’nym i teksturnym priznakam (Segmentation of satellite images of high spatial resolution by spectral and textural features), InterJekspo Geo-Sibir’, 2012, Vol. 1, No 4, pp. 86–91.

Podolskaia E. S., Sezonnost’ dorog v transportnom modelirovanii GIS-proekta lesnogo hozjajstva (Seasonality of roads in the transport modeling of GIS forestry project), Fundamental’nye, poiskovye, prikladnye issledovanija i innovacionnye proekty. Sbornik trudov Nacional’noj nauchno-prakticheskoj konferencii, Moscow, RTU MIRJeA, 2022, pp. 267–271.

Podolskaia E. S., Primenenie kosmicheskih skanernyh snimkov dlja ob”ektivizacii kartograficheskoj generalizacii na obzorno-topograficheskih kartah (Application of space scanner images for objectification of map generalization on the survey-and-topographic maps), Izv. vuzov. Ser. Geodezija i ajerofotos”emka, 2005, No 5, pp. 83–96.

Podolskaia E. S., Ershov D. V., Kovganko K. A., Transportnoe modelirovanie nazemnogo dostupa dlja bor’by s lesnymi pozharami na urovne Federal’nyh okrugov Rossii (Transport modeling of ground access to fight the forest fires at the level of the Federal Districts of Russia), Sbornik statej po itogam nauchno-tehnicheskih konferencij, 2020, No 11, Moscow: MIIGAiK. Prilozhenie k zhurnalu Izvestija vuzov “Geodezija i ajerofotos”emka”, pp. 154–156.

Podolskaia E., Ershov D., Kovganko K., Comparison of data sources on transport infrastructure for the regional forest fire management, Managing forests in the 21^st century: Book of abstracts, Managing forests in the 21^st century, Conference at the Potsdam Institute for Climate Impact Research, Potsdam 2020, 59 p. DOI: 10.2312/pik.2020.002.

Riedl M., Berthold I., Schauer P., Angelhuber M., Fischer P., Canzani E., How many roads? Object segmentation on satellite imagery in a production environment, Proceedings of 2019 Big Data from Space (BiDS’19), 19-21 February 2019, Munich (Germany), pp. 173–176. DOI: 10.2760/848593.

Satyanarayana V. L., Chandana Ch. G., Bindusha K., Padmanabhudu D., Shahanaaz bhanu G., Extraction of roads from satellite resolution images using Matlab, International Journal of Engineering Applied Sciences and Technology, 2020, Vol. 4, No 12, pp. 708–714.

Shoshina K. V., Sistema monitoringa i issledovanija lesnyh dorog (Forest road monitoring and research system), Vestnik Severnogo (Arkticheskogo) Federal’nogo universiteta. Serija: Estestvennye nauki, 2013, No 4, pp. 50–54.

Skripachev V. O., Gujda M. V., Gujda N. V., Zhukov A. O., Issledovanie svertochnyh nejronnyh setej dlja obnaruzhenija ob”ektov na ajerokosmicheskih snimkah (Research of convolutional neural networks to detect objects on the aerospace images), International Journal of Open Information Technologies, 2022, Vol. 10, No 7, pp. 54–64.

Tormozov V. S., Vasilenko K. A., Zolkin A. L., Nastrojka i obuchenie mnogoslojnogo perseptrona dlja zadachi vydelenija dorozhnogo pokrytija na kosmicheskih snimkah goroda (Setup and training of a multilayer perceptron for the task of highlighting the pavement on satellite images of the city), Programmnye produkty i sistemy, 2020, Vol. 33, No 2, pp. 343–348, DOI: 10.15827/0236-235X.130.343-348.

Turk Y., Boz F., Aydin A., Eker R., Evaluation of UAV usage possibility in determining the forest roads pavement degradation: preliminary results. 3rd International Engineering Research Symposium, INERS’19. Comparison of Autonomous and Manual UAV Flights in Determining Forest Road Surface Deformations, European Journal of Forest Engineering, 2022, Vol. 8 (2), pp. 77–84.

Tusikova A. A., Vihtenko Je. M., O raspoznavanii avtomobil’nyh dorog na sputnikovyh snimkah s ispol’zovaniem svertochnyh setej MASK-RCNN (About the recognition of highways on satellite images using convolutional networks MASK-CNN), V Mezhdunarodnaja konferencija “Informacionnye tehnologii i vysokoproizvoditel’nye vuchyslenija” (ITHPC-2019), Habarovsk, Rossija, 2019, pp. 308–314.

Wei X., Fu X., Yun Y., Lv X., Multiscale and multitemporal road detection from high resolution SAR images based attention mechanism, Remote Sensing, 2021, Vol. 13, p. 3149. DOI: 10.3390/rs 13163149.

Zegeye A., Road extraction from satellite imagery based on fully convolutional neural network, IOSR Journal of Computer Engineering (IOSR-JCE), 2020, Vol. 22, No 4, Ser. II, pp. 59–72, DOI: 10.9790/0661-2204035972.

Zhurkin I. G., Badyshev T. T., Analiz izmenenij zheleznodorozhnoj seti po kosmicheskim snimkam (Analysis of changes in the railway network based on satellite images), Izvestija vysshih uchebnyh zvedenij. Geodezija i ajerofotos”emka, 2014, Vol. 3, pp. 83–86.

]]> https://jfsi.ru/en/5-4-2022-savin_et_al/ Fri, 07 Apr 2023 07:13:33 +0000 https://jfsi.ru/?p=5652

Original Russian Text © 2022 M. S. Savin, A. S. Plotnikova, A. N. Narykova published in Forest Science Issues Vol. 5, No 2, Article 105.

© 2022                                   M. S. Savin¹, A. S. Plotnikova², A. N. Narykova²

¹ Faculty of Geography of Moscow State University

² Center for Forest Ecology and Productivity of the RAS

Profsoyuznaya st. 84/32 bldg. 14, Moscow, 117997, Russia

E-mail: odm244@gmail.com

Received: 18.04.2022

Revised: 15.05.2022

Accepted: 25.05.2022

The article presents the experience of using GIS technologies to prepare spatial predictors for their further use in modeling and mapping the dynamics of forest ecosystem functions. The study was conducted on the territory of the Dankovsky district forestry, which is located in the south of the Moscow region. GIS analysis of spatial data containing information about the relief and the hydrographic network of the study area was performed. As a result, morphometric values describing the surface runoff and altitude zonality of the study area have been created. The article describes GIS tools that can be used to create thematic geospatial products: slope exposure, steepness and curvature; direction, distance and length of the flow line, total flow; average altitude above sea level and distance to the river. In addition, the boundaries of river catchment basins have been identified by using GIS analysis, within which it is also planned to model climate-regulating forest functions associated with the carbon cycle.

Keywords: GIS analysis, forests, climate-regulating functions and services, morphometric relief value, DEM, SRTM, OSM

Natural ecosystems are inextricably intertwined with ecosystem processes occurring therein, i. e. physical, chemical and biological forces or events linking organisms and their environment (Ecosystem processes, 2022). The totality of physical, biological, chemical and other processes that support the integrity and maintain the ecosystem is commonly referred to as ecosystem functions (Ansink et al., 2008). Ecosystem services are understood as the benefits that people obtain from ecosystems (Alсamo et al., 2005).

Four categories of ecosystem services are identified based on the types of benefits for humans in accordance with the Millennium Ecosystem Assessment (2005) classification: Provisioning, Regulating, Cultural and Supportive Services. Various mechanisms of ecosystem regulation of environmental indicators are considered as Regulating Services — in particular, climate regulation, hydrological regime regulation, erosion control, pollination and others. Mapping of climate-regulating services of forests is an important issue. It is associated with the functions of biomass production, carbon and nitrogen cycle regulation, formation of natural soil fertility, etc. (Lukina et al., 2020). This approach can be used as a tool for the topics of biodiversity and creating decision support systems.

To date, mapping of ecosystem functions and services at the local level has been most developed in Western Europe (Spain, Italy, Germany, Sweden, etc.) and the USA. The objective of many studies is the assessment and mapping of the ecosystem services, including climate regulation (Burkhard et al., 2009; Palomo et al., 2013; Felipe-Lucia et al., 2014; Istomina, Luzhkova, 2017). There are works on mapping carbon stocks in soils (Chan et al., 2006; Garcia-Pausas et al., 2007); soil stability (Nelson et al., 2009; Felipe-Lucia et al., 2014; Bruno et al., 2021); regulation of runoff (Burkhard et al., 2009; Nedkov et al., 2015) and the quality of water resources (Bruno et al., 2021).

According to current studies, mapping of ecosystem functions and services may include construction of regression models using machine learning methods. The purpose of this work is to create predictors by conducting GIS analysis of spatial data for their further use in modeling and mapping of forest ecosystem functions, including climate-regulating ones.

OBJECTS AND MATERIALS OF THE STUDY

The study investigates the territory of the Dankovsky district forestry, which is located in the south of the Moscow region on the border between the Moskvoretsko-Okskaya and Zaokskaya physiographic provinces (Atlas GUGK, 1976) (Fig. 1). The relief of the southern part of the Moscow region typically has wide, well-developed river valleys and a developed ravine network. There are also karst relief forms such as craters, caves, sinkholes in places close to the surface of carbonate rocks of the Carboniferous period (Vagner, Manucharjanc, 2003). Similar landforms could be found in Prioksko-Terrasny Biosphere Reserve, bordering the study area.

The Moscow region has a fairly dense river network with more than four hundred small and large rivers of the Caspian Sea basin. The Rechma, the Sushka and the Todenka are tributaries of the Oka river, which is one of the largest rivers of the Moscow region. It runs through the Dankovsky forest district, a research territory of interest (Fig. 1). In the soil cover of the forest zone of the Moscow region, sod-podzolic soils and podzols predominate, whereas in the floodplains of rivers, alluvial soils are common (Soil map of the Moscow region, 1985).

Figure 1. Study area — Dankovsky district forestry of the Moscow region

The study included the analysis of spatial data containing information about the relief and the hydrographic network of the object of study by means of a geographic information system (GIS). Open data from the OpenStreetMap (OSM) mapping project were used for GIS analysis of the hydrographic network. OSM data are provided in common geoinformation formats, are divided by layers and have a clear structure of attribute information.

Currently, two types of digital elevation models (DEMs) are most common — raster models with a regular height network (GRID) and TIN models with an irregular triangulation network. Out of the many existing DEMs (GMTED2010, ASTER GDEM2, SPOT DEM, Next Map, NextMap World 30, TanDEM-X Global DEM, etc.), the Shuttle Radar Topography Mission (SRTM) raster model with a grid cell size of 30 × 30 m was selected for the study. The model was obtained by satellite radar imaging with SIR-C and X-SAR instruments and covers the territory of the Earth between 60°N and 54°S (USGS …, 2022). As was noted in the work of Ju. I. Karionov (2010), SRTM has a high degree of correspondence of the relief to topographic maps plotted to a scale of 1:100 000–1:50 000.

GIS TOOLS FOR SPATIAL DATA ANALYSIS

The impact of morphometric values representing surface runoff and altitude zonality should be assessed in models of climate-regulating functions of forests at the local level (Kuznetsova et al., 2020) (Fig. 2). Morphometric value (MV) refers to the numerical characters of the relief defined at each point of the map, such as slope height, steepness or exposure (Sharyj, 2006). This MV, along with the roughness (ruggedness) of the terrain, geometric shapes and thermal regimen of the slopes are one of the main aspects of the effect of relief on the functioning of the ecosystem.

Figure 2. Schematic diagram of preparation of spatial predictors

The research used ESRI (Environmental Systems Research Institute) software — the geographic information system of ArcGIS Desktop, supplemented with the Spatial Analyst module for spatial modeling and analysis. This module allows user to create, analyse and display raster data in the cartographic interface. Spatial Analyst can be used for raster data vectorization as well.

Identification of morphometric values describing surface runoff

The ArcGIS Spatial Analyst module contains tools of the Hydrology toolset used to simulate the movement of water on the surface using a digital elevation model. Thematic tools of this group can be used independently or sequentially to build a network of streams or identify watersheds. The following tools were used: Flow Direction, Flow Distance and Flow Length for the runoff, Flow Accumulation for the total flow (Overview of the Hydrology toolset).

The Flow Direction tool creates a raster layer of flow direction from each pixel of the DEM to its steepest downslope neighbor. The methods of single and multiple flow directions were used. In the case of a single direction, the flow from the cell is running exclusively to one neighboring cell; in the case of multiple directions, the flow is distributed between different neighboring cells. The method of single flow direction D8 was used in the study, implying flow into only one of eight neighboring cells. A detailed description of the Flow Direction tool is given in the article by A. S. Plotnikova et al. (2017).

The Flow Length tool calculates the length of the flow inside the river basin. The input data is a raster layer of the flow direction. The tool makes it possible to choose the direction of measuring the length of the flow line: down or up the slope to the watershed line of the catchment basin area. The results can be applied in solving a wide range of ecological and hydrological problems, in particular, calculating the time of water passage to the outlet or for modeling surface runoff.

The Flow Distance tool calculates the minimum distance following the flow path to the cell into which they flow. The tool analyzes the raster layer of the flow direction D8. For each cell, one possible path downhill to the drain cell is identified, along which the flow distance is measured. In addition to the DEM and the flow direction, raster data of streams are required for the Flow Distance tool. The original vector data of OSM streams were translated into a raster representation using the Polyline to Raster tool of the To Raster toolset of the Conversion Tools data conversion module. The cells of the resulting raster layer are assigned to a particular spatial object as a result of applying the maximum or combined length method. The tool provides an option of interactive method selection.

The Flow Accumulation tool is used to create a raster layer of total flow to each pixel of the DEM. The input data is a raster layer of the flow direction. Pixels of the output raster layer with a high flow accumulation are areas of concentrated flow, where pixels with a flow accumulation of zero are sections of the watershed line (Jenson, Domingue, 1988). The tool requires the user to set the number of pixels involved in the flow analysis. Apart from that, based on the raster layer of the flow direction, the ArcGIS Spatial Analyst module allows to select the boundaries of river catchment basins (Fig. 3). The Basin or Watershed tools are used, which are described in detail in the work by A. S. Plotnikova and A. O. Kharitonova (2018).

The tools of the Surface toolset are used to determine the slope exposure, steepness and curvature. The Aspect tool creates raster surface of the exposure using the 3 × 3 cell “moving window” method. The result reflects the spatial orientation of the elementary slope of the DEM. Measurements are performed clockwise in degrees from 0 (north) to 360 (north again), making a full circle.

The Slope tool identifies the slope steepness, i. e. the degree of surface change in the horizontal and vertical directions. The tool finds the maximum height change per unit distance between the analyzed cell and eight surrounding neighbors. As a result, a raster layer of slope steepness is created in two different units of measurement — degrees or percentage points.

The Curvature tool creates a raster layer of the standard curvature of the slope, taking into account the profile and plan curvature. The profile curvature describes the angle of the maximum slope and is built parallel to the slope. Thus, the curvature of the profile characterizes the flow velocity on the surface. A negative value in the profile output indicates the surface as upwardly convex at the analyzed cell. It means that the flow slows down. A positive value indicates that the surface is upwardly concave, which means the acceleration of the flow. A positive value indicates the surface is upwardly concave — the flow accelerates. A value of 0 indicates the surface is flat and has a constant angle of slope. The plan curvature is perpendicular to the angle of maximum slope. The plan curvature characterizes the horizontal flow direction — convergence and divergence of the flow on the surface. In the planned output, a positive value indicates the surface is upwardly convex at that cell. A negative value indicates the surface is upwardly concave at that cell. A zero value also characterizes a surface with a constant angle of slope. Simultaneous consideration of both types of curvature, called standard curvature, allows us to better understand the patterns of redistribution of matter in liquid or solid form along the slope.

Identification of morphometric values describing altitude zonality

The Zonal Statistics as Table tool of the Zonal toolset is used to find the value of the average altitude above sea level within the forest subcompartment that in the future will serve as a spatial unit for regression modeling of ecosystem functions of the object of study. The SRTM DEM and the vector layer of the boundaries of forest subcompartments are employed as an input dataset for the Zonal Statistics as a Table tool. As an output, we got a table of average heights within the subcompartment.

The final predictor created by GIS analysis of spatial data is the distance to the river, which was calculated in two stages. First, we found the centroid of the polygon of the forest subcompartment. This task was performed using the Feature To Point tool from the Features toolset of the ArcGIS Data Management Tools module. The tool translates input polygonal objects into output points — centroids of polygons. Then, the distance from the centroid of the subcompartment polygon to the object of the hydrological network was calculated using the Near tool of the Proximity toolset of the ArcGIS Analysis Tools data analysis module.

RESULTS AND DISCUSSION

The conducted research resulted in obtaining morphometric values describing surface runoff (direction, distance and length of the flow line, total flow; slope exposure, steepness and curvature) and altitude zonality (average altitude above sea level) of the Dankovsky district forestry. The obtained morphometric values can be considered as predictors for modeling climate-regulating functions, including those related to the carbon stocks and the formation of water runoff.

Figure 3 highlights the boundaries of the catchment basins of the rivers in the area of study. It is apparent that they correlate well with the results obtained in Kazan Federal University (Ermolaev et al., 2017). Kazan researchers propose to use the map of river basins of the European territory of Russia they had created for various geoecological assessments. There are quite a few examples of modern scientific research using the river basin as an object of environmental monitoring (Smolyaninov et al., 2007; Liseckij et al., 2014; Kharitonova et al., 2019).

Figure 3. Highlighted boundaries of river catchment basins

The boundaries of the river basins of the European territory of Russia are identified on the basis of the GMTED2010 DEM with a resolution of 250 m. In addition to the boundaries, the map contains data on the nature, resource potential and ecological condition of the basin. Subject information like this will be useful in assessing the climate-regulating functions of forests related to the carbon cycle — for example, the dynamics of carbon stocks and the formation of the hydrological regime.

The above description of GIS tools used to analyze terrain and hydrographic network data for determining the direction, distance and length of the flow line, as well as exposure, steepness and curvature of the slope is of interest for various environmental studies within the framework of the basin concept of nature management.

FINANCING

The work was carried out as part of an additional agreement to the state task of the CEPF RAS (registration number 122110700044-2) in accordance with the Decree of the Government of the Russian Federation dated September 2, 2022 No 2515-р for the implementation of the most important innovative project of national importance aimed at creation of a unified national monitoring system for climatically active substances.

REFERENCES

Alсamo J., Ash N., Bennett E., Biggs R., Butler C., … & Zurek М., Ecosystems and human wellbeing: a framework for assessment, Washington, D. C., USA, Island Press., 2003, 245 p.

An overview of the Hydrology toolset, ArcGIS for Desktop, URL: https://clck.ru/rL5FL (2022, 17 January).

An overview of the Raster Surface toolset, ArcGIS for Desktop, URL: https://clck.ru/rL6Ao (2022, 25 January).

Ansink E., Hein L., Hasund K. P., To value functions or services? An analysis of ecosystem valuation approaches, Environmental Values, 2008, Vol. 17, No 4, pp. 489–503.

Atlas GUGK, Moscow region, 1976, https://clck.ru/rL4yh (2022, 15 January).

Bruno D., Sorando R., Álvarez-Farizo B., Castellano C., Céspedes V., Gallardo B., … & Comín F. A., Depopulation impacts on ecosystem services in Mediterranean rural areas, Ecosystem Services, 2021, Vol. 52, Article 101369.

Burkhard B., Kroll F., Müller F. Windhorst W., Landscapes’ Capacities to Provide Ecosystem Services — a Concept for Land-Cover Based Assessments, Landscape Online, 2009, No 15, pp. 1–22.

Chan K. M. A., Shaw M. R., Cameron D. R., Underwood E. C., Daily G. C., Conservation planning for ecosystem services, PLoS Biology, 2006, Vol. 4, No 11, 379 p.

Ecosystem processes, GreenFacts URL: https://clck.ru/rL978 (2022, 15 May).

Ermolaev O. P., Mal’cev K. A., Muharamova S. S., Harchenko S. V., Vedeneeva E. A., Kartograficheskaja model’ rechnyh bassejnov Evropejskoj Rossii (Cartographic model of river basins of European Russia), Geografija i prirodnye resursy, 2017, No 2, pp. 27–36.

Felipe-Lucia M. R., Comín F. A., Bennett E. M., Interactions among ecosystem services across land uses in a floodplain agroecosystem, Ecology and Society, 2014, Vol. 19, No 1, Article 20.

Garcia-Pausas J., Casals P., Camarero L. Soil organic carbon storage in mountain grasslands of the Pyrenees: effects of climate and topography, Biogeochemistry. 2007, Vol. 82, No 3, pp. 279–289.

Istomina E. A., Luzhkova N. M., Kartografirovanie jekosistemnyh uslug v Zabaĭkal’skom nacional’nom parke (Mapping of the ecosystem services in Zabaikalskiy National Park) Geodezija i kartografija, 2017, Vol. 78, No 7, pp. 59–67.

Jenson S. K., Domingue J. O., Extracting Topographic Structure from Digital Elevation Data for Geographic Information System Analysis, Photogrammetric Engineering and Remote Sensing, 1988, Vol. 54, No 11, pp. 1593–1600.

Karionov Ju. I. Ocenka tochnosti matricy vysot SRTM (The estimation of the accuracy of the SRTM), Geoprofi, 2010, No 10, pp. 48–51.

Kharitonova A. O., Plotnikova A. S., Ershov D. V., Sovremennye i istoricheskie pozharnye rezhimy Pechoro-Ilychskogo zapovednika i ego okrestnostej (Mapping of terrestrial ecosystems of the Pechora-Ilychsky Reserve and its surroundings), Voprosy lesnoj nauki, 2019, Vol. 2, No 3, pp. 1–17, DOI: 10.31509/2658-607x-2019-2-3-1-17.

Kuznetsova A. I., Lukina N. V., Gornov A. V., Gornova M. V., Tikhonova E. V. … & Genikova N. V., Zapasy ugleroda v peschanykh pochvakh sosnovykh lesov na zapade Rossii (Carbon Stock in Sandy Soils of Pine Forests in the West of Russia), Pochvovedenie, 2020, No 8, pp. 959–969.

Liseckij F. N., Grigor’eva O. I., Kirilenko Zh. A., Nauchnoe soprovozhdenie bassejnovoj organizacii prirodopol’zovanija v Belgorodskoj oblasti, Dvadcat’ devjatoe plenarnoe mezhvuzovskoe koordinacionnoe soveshhanie po probleme jerozionnyh, ruslovyh i ust’evyh processov (The identification of drainage basins borders at local spatial scale), Moscow: Mezhvuzovskij nauchno-koordinacionnyj sovet po probleme jerozionnyh, ruslovyh i ust’evyh processov pri MGU, 2014, pp. 106–107.

Lukina N. V., Geraskina A. P., Gornov A. V., Shevchenko N. E., Kuprin A. V., … & Gornova M. V., Bioraznoobrazie i klimatoregulirujushhie funkcii lesov: aktual’nye voprosy i perspektivy issledovanij (Biodiversity and climate regulating functions of forests: current issues and prospects for research), Voprosy lesnoj nauki, 2020, Vol. 3, No 4, DOI: 10.31509/2658-607x-2020-3-4-1-90.

Millennium Ecosystem Assestment. Ecosystems and Human Well-Being, Washington, DC, USA: Island Press, 2005, Vol. 5, 155 p.

Nedkov S., Boyanova K., Burkhard B., Quantifying, Modelling and Mapping Ecosystem Services in Watersheds, Ecosystem Services and River Basin Ecohydrology, 2015, pp. 133–149.

Nelson E., Mendoza G., Regetz J., Polasky S., Tallis H., … & Shaw M. R., Modeling Multiple Ecosystem Services, Biodiversity Conservation, Commodity Production, and Tradeoffs at Landscape Scales, Frontiers in Ecology and the Environment, 2009, Vol. 7, No 1, pp. 4–11.

Palomo I., Martin-Lopez B., Potschin M., Haines-Young R., Montes C., National Parks, buffer zones and surrounding lands: Mapping ecosystem service flows, Ecosystem Services, 2013, Vol. 4, pp. 104–116.

Plotnikova A. S., Ershov D. V., Kharitonova A. O., Ispol’zovanie GIS-tehnologij pri kartografirovanii pozharnyh rezhimov lesnyh jekosistem Pechoro-Ilychskogo zapovednika (Gis Technologies Application for Forest Fire Regimes Mapping Over Pechora Natural Reserve), Geodezija, kartografija, geoinformatika i kadastry, Ot idei do vnedrenija, Sbornik materialov, St. Petersburg: Politehnika, 2017, pp. 464–470.

Plotnikova A. S., Kharitonova A. O., Vydelenie granic vodosbornyh bassejnov rek na lokal’nom prostranstvennom urovne (Identifocation of drainage basin borders at local spatial level), Voprosy lesnoj nauki, 2018, Vol 1, No 1, pp. 1–10, DOI: 10.31509/2658-607x-2018-1-1-1-10.

Sharyj P. A., Geomorfometrija v naukah o Zemle i jekologii, obzor metodov i prilozhenij (Geomorphometry in Earth Sciences and ecology, review of methods and applications), Izvestija Samarskogo nauchnogo centra RAN, 2006, Vol. 8, No 2, pp. 458–473.

Smolyaninov V. M., Degtjarev S. D., Shherbinina S. V., Jekologo-gidrologicheskaja ocenka sostojanija rechnyh vodosborov Voronezhskoj oblasti (Ecological-hydrological assessment of the Voronezh Region River basins state), Voronezh: Istoki, 2007, 133 p.

Soil map of the Moscow region, 1985, https://clck.ru/rL28X (2022, 25 January)

USGS EROS Archive — Digital Elevation — SRTM Coverage Maps, Earth resources observation and science center, USA, 2022, URL: https://clck.ru/rKuM9 (2022, 15 January).

Vagner B. B., Manucharjanc B. O., Geologija, rel’ef i poleznye iskopaemye moskovskogo regiona (Geology, relief and minerals of the Moscow region), Moscow: MPGU, 2003, pp. 50–65.

Reviewer: Candidate of Technical Sciences V. S. Gruzinov