Yu. P. Demakov, O. V. Sheikina^*, E. S. Sharapov

          Volga State University of Technology,

Lenina Square, 3, Yoshkar-Ola City, Republic of Mari El, 424000, Russia

^*E-mail: ShejkinaOV@volgatech.net

Received: 11.06.2023

Revised: 15.09.2023

Accepted: 25.09.2023

The article presents the results of assessment of Scots pine (Pinus sylvestris L.) wood (216 pc), bark (29 pc), needle (127 pc) specimens for the content of 13 chemicals (Ca, K, Mg, Mn, Zn, Fe, Cu, Sr,Ni,Pb, Cr, Co, Cd), which were tested using an AAnalyst 400 atomic absorption spectrometer. The specimens were taken from the stands of different ages, origin and forest-growth conditions in the Republic of Mari El. It shows that the elemental composition of organ tissues of this tree species is its essential ecological and physiological characteristic that represents the peculiarities of the metabolism process in trees and a degree of tree adaptation to the environment. In comparison with the wood, the bark contains seven to eight times more calcium and strontium, four times more cadmium, two times more iron and zinc. As for the content of other elements, the bark does not differ much from the wood, however its ash content is 6.4 times greater. The ash content of the needles is 6.7 times greater than that of the wood, but the needles have a significantly higher concentration of К, Mn, Са, Zn, and in comparison with the bark a higher concentration of Sr, Ni, Pb. The contents of each chemical element in the tissues and organs of pine trees vary within wide ranges due to the environmental factors and individual features of trees. The variation of the Ni content in the wood is the greatest (СV = 92.1%), it is followed by Mg, Pb, Co and Fe (СV = 83%-89%). The Ca and ash contents in the wood vary the least (СV = 38 % and СV = 26.5%, respectively). The bark has the greatest variation of the Cd and Ni concentrations (СV = 172%), and they are followed by Sr, Mg, K (СV = 88%-111%). The Ca, Cu and ash contents in the bark vary the least (СV = 55%-62 %). The needles have the most significant variation in the Sr, Ni, Co contents (СV = 85%-96%) and the least variation in the K and ash contents (СV = 18%-24%). The contents of ash, Ca, Mg, Zn, K, Mn in the Scots pine wood, bark and needles as well as the ratios of К:Mn and Zn:Mn may be used for selection of economically valuable samples along with the other phenotypic characteristics of trees. It is cocluded that the ash composition of tree tissues, especially wood, is not suitable for biomonitoring purposes, since it largely depends on intracenotic factors, rather than technogenic pollution. For this purpose, it is better to evaluate the gross content of chemical elements in the litter and soil of biogeocenoses.

Keywords: the Republic of Mari El, Scots pine, wood, bark, needles, ash content, elemental composition, variation, causes

REFERENCES

Abdullina D. S., Petrova I. V., Differenciacija populjacij sosny obyknovennoj po fenotipicheskim priznakam na severo-vostochnom predele areala (Phenotypic differentiation of the Scots pine populations on the northern-eastern boundary of the habitat), Agrarnyj vestnik Urala, 2012, No 9, pp. 34–36.

Avessalomova I. A., Biogeoximiya landshaftov (Biogeochemistry of landscapes). Moscow: MGU, 2007. 162 p.

Adamenko V. N., Zhuravleva E. L., Chetverikov A. F., Himicheskij sostav godichnyh kolec derev’ev i sostojanie prirodnoj sredy (Chemical composition of tree annual rings and the state of the natural environment), Doklady AN SSSR, 1982, Vol. 265, No 2. pp. 507–512.

Alekseenko V. A., Jekologicheskaja geohimija (Environmental geochemistry), M.: Logos, 2000, 626 p.

Alekseenko V. A., Osnovnye faktory nakoplenija himicheskih jelementov organizmami (Main factors of chemical element accumulation by organisms), Sorosovskij obrazovatel’nyj zhurn, 2001, No 8, pp. 20–24.

Archegova I. B., Kuznecova E. G., Vlijanie drevesnyh rastenij na himicheskij sostav at-mosfernyh osadkov v processe vosstanovlenija srednetaezhnyh lesov (The influence of ligneous plants on the chemical composition of precipitation in the regeneration process of the Middle-Taiga forests), Lesovedenie, 2011, No 3. pp. 34–43.

Baes C. F., McLaughlin S. B., Trace Elements in Tree Rings: Evidence of Recent and Historical Air Pollution, Science, 1984, Vol. 224, No 4648, pp. 494–497.

Bargal`i R., Biogeoximiya nazemny`x rastenij (Biogeochemistry of terrestrial plants), Moscow: GEOS, 2005, 454 p.

Bazilevich N. I., Titljanova A. A., Bioticheskij krugovorot na pjati kontinentah: azot i zol’nye jelementy v prirodnyh nazemnyh jekosistemah (The biotical cycle on five continents: nitrogen and ash elements in the natural terrestrial ecosystem), Novosibirsk: Izd-vo SO RAN, 2008, 381 p.

Bindler R., Renberg I., Klaminder J., Emteryd O., Tree Rings as Pb Pollution Archives? A Comparison of 206Pb/207Pb Isotope Ratios in Pine and Other Environmental Media, Science of The Total Environment, 2004, Vol. 319, No 1-3, pp. 173–183.

Bjusgen M., Stroenie i zhizn’ nashih lesnyh derev’ev (The structure and life of our forest trees), M.-L.: Goslesbumizdat, 1961, 424 p.

Bondietti E. A., Baes III C. F., McLaughlin S. B., Radial Trends in Cation Ratios in Tree Rings as Indicators of the Impact of Atmospheric Deposition on Forests, Canadian Journal of Forest Research, 1989, Vol. 19 (5), pp. 586–594.

Bowen H. J. M., Trace elements in Ьiogeochemistry, N.Y.; L.: Acad. press, 1966, 241 р.

Bozhok A. A., Vnutrividovaja izmenchivost’ sosny obyknovennoj v razlichnyh jekologi-cheskih uslovijah L’vovskoj oblasti. Avtoref. diss. kand. s.-h. nauk (The intra-species variability of Scots pine in the different environmental conditions of the Lvov Region. Abstract of candidate’s thesis), Riga, 1979, 16 p.

Butuzova O. V., O soderzhanii zol’nyh jelementov v razlichnyh chastjah derev’ev sosny i eli (The content of ash elements in the different parts of pine and spruce trees. The structure and life of our forest trees), Botanicheskij zhurn, 1964, Vol. 49, pp. 7–12.

Buzy`nny`j M. G., Demchuk V. V., Los` I. P., Nesvetajlo V. D., Osobennosti raspredeleniya 90Sr v drevesine (Features of the distribution of <sup>90</sup>Sr in wood), Radioaktivnost` i radioaktivny`e e`lementy` v srede obitaniya che-loveka: materialy` II Mezhdunarodnoj konferencii, Tomsk, 22–24 maya 1996, Tomsk: Izd-vo TPU, 1996, pp. 403–407.

Chetverikov A. F., Himicheskij sostav godichnyh sloev prirosta derev’ev i uslovija prirodnoj sredy (The chemical composition of annual layers in the tree increment and the natural environment), [in:] Dendrohronologija i dendroklimatologija, Novosibirsk: Nauka, 1986, pp. 126–130.

Dejneko I. P., Dejneko I. V., Belov L. P., Issledovanie himicheskogo sostava kory sosny (Study of the chemical composition of pine bark), Himija rastitel’nogo syr’ja, 2007, No 1, pp. 19–24.

Demakov Ju. P., Vlijanie faktorov sredy na rost derev’ev v sosnjakahRespubliki Marij El (The impact of the environmental factors on a tree growth in the pine stands of the Republic of Mari El), Joshkar-Ola: Povolzhskij gosudarstvennyj tehnologicheskij universitet, 2023, 480 p.

Demakov Ju. P., Isaev A. V., Izmenenie valovogo soderzhanija himicheskih jelementov v hode jevoljucii pochv lesnyh biogeocenozov Srednego Povolzh’ja (Changes in the total content of chemical elements in soil evolution of the forest biogeocenoses in the Middle Volga region), Vestnik Povolzhskogo gos-udarstvennogo tehnologicheskogo universiteta, Serija Lesnaya jekologija. Prirodopol’zovanie, 2021, No 3 (51), pp. 79–99.

Demakov Ju. P., Isaev A. V., Jelementnyj sostav peschanyh pochv lesnyh biogeocenozov Marijskogo Zavolzh’ja (The elemental composition of the sandy soils in the forest biogeocenoses in the Mari trans-Volga region), Vestnik Povolzhskogo gosudarstvennogo tehnologicheskogo universiteta, Serija Lesnaya jekologija. Prirodopol’zovanie, 2021, No 4 (52), pp. 54–69.

Demakov Ju. P., Isaev A. V., Gareev B. I., Batalin G. A., Ispol’zovanie rentgenofluorescentnogo analiza dlja ocenki soderzhanija himiche-skih jelementov v pochve lesnyh biogeocenozov (Assessing chemical elements in soil of forest biogeocenoses can be achieved through the use of X-ray fluorescence analysis), Nauchny`e trudy` gosudarstvennogo prirodnogo zapovednika «Bol’shaja Kokshaga», 2017, No 8, 2017, pp. 56–75.

Demakov Ju. P., Isaev A. V., Shvecov S. M., Potreblenie i vynos drevesnymi rastenija-mi zol’nyh jelementov v pojmennom biotope (The consumption and extraction of ash elements by ligneous plants in the bottom-land biotope), Vestnik Povolzhskogo gosudarstvennogo teh-nologicheskogo universiteta, Serija Lesnaya jekologija. Prirodopol’zovanie, 2013, No 1 (17), pp. 36–49.

Demakov Ju. P., Isaev A. V., Talancev V. I., Ispol’zovanie tkanevyh povjazok dlja ocen-ki ajeral’nyh postuplenij zol’nyh jelementov (The use of textile bandages for assessment of the aerial intake of ash elements), Nauchny`e trudy` gosudarstvennogo prirodnogo zapovednika «Bol’shaja Kokshaga», 2013, No 6, pp. 48–55.

Demakov Ju. P., Majshanova M. I., Goncharov E. A., Bogdanov G. A., Krasnobaev Ju. P., Shvecov S. M., Chemeris A. N., Vozdejstvie zavoda silikatnogo kirpicha na sostojanie i strukturu sosnovogo biogeocenoza (The impact of vehicle emissions on the natural environment (The impact of the sand-lime brick factory on the state and structure of the pine biogeocenose), Joshkar-Ola: PGTU, 2013, 192 p.

Demakov Ju. P., Majshanova M. I., Shvecov S. M., Izmenenie zol’nogo sostava hvoi, ko-ry i drevesiny sosny v zone vybrosov zavoda silikatnogo kirpicha (Changes in the ash composition of the pine needles, bark and wood in the area affected by the emissions from a sand-lime brick factory), Vestnik Povolzhskogo gosudarstvennogo tehnologicheskogo universiteta, Serija Lesnaya jekologija. Prirodopol’zovanie, 2012, No 1 (13), pp. 85–95.

Demakov Ju. P., Safin M. G., Shvecov S. M., Sosnjaki sfagnovye Marijskogo Poles’ja: struktura, rost i produktivnost’ (Sphagnum pine forests of Mari Polessie: structure, growth and productivity), Joshkar-Ola: PGTU, 2012, 276 p.

Demakov Ju. P., Safin M. G., Vinokurova R. I., Talancev V. I., Shvecov S. M., Hvoja kak indikator sostojanija sosnovyh molodnjakov na oligotrofnyh bolotah (Needles as an indicator of the young pine forest condition in the oligotrophic moors), Vestnik Marijskogo gosudarstvennogo tehnicheskogo universiteta, Serija Lesnaya jekologija. Prirodopol’zovanie, 2010, No 3, pp. 95–107.

Demakov Ju. P., Shvecov S. M., Soderzhanie zol’nyh jelementov v godichnyh slojah dere-v’ev sosny v priozernyh biotopah Nacional’nogo parka «Marij Chodra» (The ash elements content in annual layers of pine trees in lakeside biotopes of the «Mari Chodra» National Park), Jeko-potencial, 2013, No 3–4, pp. 127–135.

Demakov Ju. P., Shvecov S. M., Safin M. G., Soderzhanie zol’nyh jelementov v torfe verhovyh bolot Marijskogo Poles’ja (The ash element contents in the high-moor peats of Mari Polesye), [in:] Bolotnye jekosistemy: fundamental’nye aspekty ohrany i racional’nogo prirodopol’zovanija, Joshkar-Ola: PGTU, 2012, pp. 156–161.

Demakov Ju. P., Shvecov S. M., Shvecov A. M., Soderzhanie zol’nyh jelementov v torfe verhovyh bolot Marijskogo Poles’ja (The ash element contents in the high-moor peats of Mari Polesye), Aktual’nye problemy lesnogo kompleksa, 2012, No 31, pp. 125–129.

Demakov Ju. P., Shvecov S. M., Talancev V. I., Kalinin K. K., Dinamika soderzhanija zol’nyh jelementov v godichnyh slojah starovozrastnyh sosen, proizrastajushhih v pojmennyh biotopah (Dynamics of the ash element contents in the annual layers of old-aged pines growing in the bottom-land biotopes), Vestnik Marijskogo gosudarstvennogo tehnicheskogo universiteta, Serija Lesnaya Jekologija. Prirodopol’zovanie, 2011, No 3, pp. 25–35.

Demakov Ju. P., Vinokurova R. I., Talancev V. I., Shvecov S. M., Izmenchivost’ soderzhanija zol’nyh jelementov v drevesine, kore i hvoe sosny obyknovennoj (Variability of the ash element contents in the Scots pine wood, bark and needles), Lesnye jekosistemy v uslovijah izmenjajushhegosja klimata: biologicheskaja produktivnost’, moni-toring i adaptacionnye tehnologii: Proc. International Conference s jelementami nauch-noj shkoly dlja molodjozhi, Joshkar-Ola: MarGTU, 2010, pp. 32–37.

Dobrovol’skij V. V., Osnovy biogeohimii (Basics of biogeochemistry), M.: Vysshaja shkola, 1998, 413 p.

Drejper N., Smit G., Prikladnoj regressionnyj analiz (Applied regression analysis), M.: Statistika, 1973, 392 p.

Elpat’evskij P. V., Geohimija migracionnyh potokov v prirodnyh i prirodno-tehnogennyh geosistemah (Geochemistry of migration flows in natural and natural-technogenic geosystems), Moscow: Nauka, 1993, 252 p.

Ermakov A. I., Arasimovich V. V., Yarosh N. P., Metody biogeohimicheskogo issledovanija rastenij (Methods of biogeochemical research of plants), Leningrad: Agropromizdat, 1987, 450 p.

Ermakov V. V., Geohimicheskaja jekologija kak sledstvie sistemnogo izuchenija biosfery (Geochemical ecology as a consequence of the systematic study of the biosphere), Tr. biohimicheskoj laboratorii, 1999, Vol. 23, pp. 152–158.

Ermakov V. V., Massa i jelementnyj himicheskij sostav zhivogo veshhestva (Mass and elemental chemical composition of living substance), Biogeohimija himicheskih jelementov i soedinenij v prirodnyh sredah: Materialy 3-rd International Seminar molodyh issledovatelej, Tyumen’: Izdatel’stvo Tjumenskogo gosudarstvennogo universiteta, 2018, pp. 11–26.

Ermakov V. V., Tjutikov S. F., Geohimicheskaja jekologija zhivotnyh (Animals and their geochemical ecology), Moscow: Nauka, 2008, 310 p.

Fokin A. D., Rol’ rastenij v pereraspredelenii veshhestv po pochvennomu profilju (Forest arabesques, or Essays on the life of our trees), Pochvovedenie, 1999, No 1, pp. 109–116.

Forrest W. G., Ovington J. D., Variations in dry weight and mineral nutrient content of Pinus radiate progeny, Silvae genetica, 1971, Vol. 20, pp. 174–179.

Gavrikov V. L., Fertikov A. I., Sharafutdinov R. A., Vaganov E. A., Izmenchivost’ jelementnogo sostava godichnyh kolec hvojnyh porod IVUZ (The element composition of annual conifer rings varies), Lesnoj zhurnal, 2021, No 6, pp. 24–37.

Goddard R. E., Zobel B. J., Hollis C. A., Response of Pinus taeda and Pinus elliotti to varied nutrition, [in:] Tree physiology and yield improvement, N.Y.: Akad. Press, 1976, pp. 449–462.

Gribovskaja I. V., Sulimova O. A., Ustjugova T. T., Jekologicheskaja izmenchivost’ mikro-jelementnogo sostava drevesiny sosny v sravnenii s sezonnoj i individual’noj, Biofi-zicheskie metody issledovanija jekosistem (Variability of the microelement composition of pine wood: ecological vs. seasonal or individual), Novosibirsk: Nauka, 1984, pp. 104–114.

Grinin A. S., Orehov N. A., Novikov V. N., Matematicheskoe modelirovanie v jekologii (Mathematical modeling in the ecology), Moscow: JuNITI-DANA, 2003, 269 p.

Grishina L. A. Biologicheskij krugovorot i ego rol’ v pochvoobrazovanii (Biological cycle and its function in soil formation), Moscow: Izd-vo Mosk. un-ta, 1974, 128 p.

Hall G. S., Yamaguchi D. K., Rettberg T. M., Multielemental Analyses of Tree Rings by Inductively Coupled Plasma Mass Spectrometry, Journal of Radioanalytical and Nuclear Chemistry, 1990, Vol. 146, pp. 255–265.

Hantemirov R. M., Bioindikacija zagrjaznenija sredy v proshlom na osnove analiza so-derzhanija himicheskih jelementov v godichnyh slojah drevesiny (Biogeochemical migration of elements and soil formation in the forests of the Kola Peninsula), [in:] Problemy jekologicheskogo monitoringa i modelirovanija jekosistem, Leningrad: Gidrometeoizdat, 1996, Vol. 16, pp. 153–164.

Hantemirov R. M., Soderzhanie himicheskih jelementov v godichnyh slojah drevesiny sosny obyknovennoj i vozmozhnosti ego ispol’zovanija v retrospektivnoj bioindikacii tehnogennyh zagrjaznenij. Aftoreferat diss. cand. nauk (The chemical element contents in the annual layers of Scots pine wood and the possibilities to use the content data for retrospective bioindication of technogenic pollution. Abstract of candidate’s thesis), Sverdlovsk, 1991, 25 p.

Hoh A. N., Izmenchivost’ jelementnogo sostava drevesiny sosny obyknovennoj v zavi-simosti ot mesta proizrastanii (Variability of the elemental composition of Scots pine wood due to a habitat), In: Voprosy jekologii. Nauka, obrazovanie, praktika, Volgograd: VGAPO, 2018, pp. 175–177.

Hoh A. N., Poznjak S. S., Dinamika nakoplenija mikrojelementov v drevesine sosny obyknovennoj v zavisimosti ot uslovij mestoproizrastanija i fazy vegetacii, (Dynamics of microelement accumulation in Scots pine wood due to the habitat environment and vegetation phases), [in:] Saharovskie chtenii 2019 goda: jekologicheskie problemy XXI veka, Minsk: Mezhdunarodnyj gosudarstvennyj jekologicheskij institut im. A. D. Saharova, 2019, pp. 204–207.

Hoh A. N., Zvjagincev V. B., Osobennosti jelementnogo sostava drevesiny sosny obykno-vennoj (Specifics of the elemental composition of Scots pine wood), Izvestija Saratovskogo universiteta. Novaja serija. Serija: Himija. Biologija. Jekologija, 2022, Vol. 22, No 1, pp. 47–56.

Hramchenkova O. M., Drozdov D. N., Novikov R. I., Savchenko A. M., Vysotnoe raspredelenie zol’nosti i jelementnogo sostava korki sosny obyknovennoj Pinus sylvestris L. (Altitude distribution of the ash content and elemental composition of Scots pine bark), Vestnik Polesskogo gosudarstvennogo universiteta, Seriya biologicheskie nauki, 2016, No 2, pp. 34–38.

Hvostov I. V., Koval’skaja G. A., Pavlov V. E., Jelementnyj sostav godovyh kolec sosny obyknovennoj iz rajonov Chernobylja i Podkamennoj Tunguski (The elemental composition of annual rings of Scots pines from the Chernobyl and Stony Tunguska districts), Himija rastitel’nogo syr’ja, 2011, No 2, pp. 153–158.

Il’in V. B., Jelementnyj himicheskij sostav rastenij (Plants chemical composition is essential), Novosibirsk: Nauka, 1985, 129 p.

Il’in V. B., Tjazhelye metally v sisteme pochva-rastenija (The soil-plant system contains heavy metals), Novosibirsk: Nauka, 1991, 151 p.

Iroshnikov A. I., O genotipicheskom sostave populjacij sosny obyknovennoj v jugo-vostochnoj chasti ee areala (The genetic composition of Scots pine populations in the southern portion of its range is being investigated), [in:] Selekcija hvojnyh porod Sibiri, Krasnojarsk: ILiD SO AN SSSR, 1978, pp. 76–95.

Jekologo-fiziologicheskie osnovy produktivnosti sosnovyh lesov evropejskogo Severo-Vostoka (Ecological and physiological bases of productivity of pine forests of the European North-East) / Pod red. K. S. Bobkovoj, Syktyvkar: Komi filial UNC RAN, 1993, 174 p.

Kabata-Pendias A., Pendias H., Mikrojelementy v pochvah i rastenijah (Identify elements present in both soils and plants), M.: Mir, 1989, 439 p.

Kamanina I. Z., Savvateeva O. A., Vozdejstvie avtotransporta na okruzhajushhuju sredu g. Dubny (The impact of Dubny’s environment is due to road transport), Fundamental’nye issledovanija, 2014, No 7–8, pp. 1612–1616.

Karpachevskij L. O., Zubkova T. A., Projsler T., Kennel M., Gitl G., Goncharuk N. Yu., Minaeva T. Yu., Vozdejstvie pologa el’nika slozhnogo na himicheskij sostav osadkov (The impact of the canopy of a composite spruce forest on the chemical composition of precipitation), Lesovedenie, 1998, No 1, pp. 50–59.

Kazimirov N. I., Morozova R. M., Biologicheskij krugovorot veshhestv v el’nikah Karelii (Cadastres of chemical element concentrations in the plants of the Karelian), Leningrad: Nauka, 1973, 176 p.

Kazimirov N. I., Volkov A. D., Zjabchenko S. S., Ivanchikov A. A., Morozova R. M., Obmen veshhestv i jenergii v sosnovyh lesah Evropejskogo Severa (The exchange of substances and energy in the pine stands of the European North), Leningrad: Nauka, 1977, 304 p.

Kiljusheva N. V., Feklistov P. A., Ezhova N. V., Bolotov I. N., Filippov B. Ju., Sravnitel’nyj analiz soderzhanija mineral’nyh jelementov v drevesine sosny i eli (A comparative study of the mineral element contents in pine and spruce wood), Lesnoy zhurnal, 2017, No 5, pp. 64–72.

Kim Dzh. O., M’juller Ch. U., Klekka U.R., Enyukov I. S., Faktornyj, diskriminantnyj i klasternyj analiz (Factor, discriminant and cluster analysis), Moscow: Finansy i statistika, 1989, 215 p.

Kist A. A., Fenomenologija biogeohimii i bioneorganicheskoj himii (Phenomenology of Biogeochemistry and bioorganic chemistry), Tashkent: Fan, 1987, 236 p.

Kleinsmit J., Foliar concentration of ten mineral nutrients in nine Pinus radiate clones during 15-month period, New Zealand Journal of Forestry Science, 1978, Vol. 8, pp. 351–368.

Korbukova I. V., Osobennosti himicheskogo sostava korki i luba Pinus sylvestris L. (Specifics of the chemical composition of the Pinus sylvestris L bark and phloem). Avtoref. diss. kand. nauk, SPb, 1996, 24 p.

Kovalevskij A. L., Biogeohimija rastenij (Biogeochemistry of plants), Novosibirsk: Nauka, 1991, 294 p.

Koval’skij V. V., Geohimicheskaja jekologija (Geochemical ecology), Moscow: Nauka, 1974, 298 p.

Kozhevnikova N. D., Vtorova V. N., Biologicheskij krugovorot veshhestv v el’nikah Severnogo Tjan’-Shanja (Biological circulation of substances in the spruce forests of the Northern Tien Shan), Frunze: Ilim, 1988, 346 p.

Kozlov V. A., Issledovanie jelementarnogo sostava zoly suhostojnyh derev’ev sosny metodom jemissionnogo spektral’nogo analiza (The study of the elemental composition of ash obtained from dead standing pine trees by emission spectroscopy), [in:] Fiziko-himicheskie issledovanija drevesiny i ee kompleksnoe ispol’zovanie, Petrozavodsk, 1978, pp. 67–79.

Kozubov G. M., Vnutrividovoe raznoobrazie sosny obyknovennoj Pinus sylvestris L. v Karelii i na Kol’skom poluostrove. Avtoref. diss. kand. s.-x. nauk (In-species diversity of Scots pine (Pinus sylvestris L.) in Karelia and Kola peninsula. Abstract of candidates agr. sci thesis), Leningrad: LGU, 1962, 20 p.

Kretovich V. L., Biohimija rastenij (Plant biochemistry), M.: Vysshaja shkola, 1980, 445 p.

Kurdiani S. Z., Delenie Pinus sylvestris na rasy (The division of Pinus sylvestris into races), Lesopromyshlennyj vestnik, 1908, No 26, pp. 237–240.

Kuz’min S. I., Fedenja V. M., Rud’ A. V., Ocenka jekologicheskogo sostojanija pochv v pri-dorozhnyh polosah avtomagistralej (na primere Minskoj obl.) (Assessment of the ecological condition of soils in road lanes), [in:] Sovremennye problemy geohimii, geologii i poiskov mestorozhdenij poleznyh iskopaemyh, Minsk: «Izdatel’skij centr BGU», 2007, pp. 127–128.

Lakin G. F., Biometrija (Biometrics), Moscow: Vysshaja shkola, 1990, 352 p.

Leyton L., Armson K. A., Mineral composition of the foliage in relation to the growth of Scots pine, Forest science, 1955, Vol. 1, No 3, pp. 210–218.

Lukina N. V., Nikonov V. V., Biogeohimicheskie cikly v lesah Severa v uslovijah ajero-tehnogennogo zagrjaznenija (Biogeochemical cycles in the forests of the North under conditions of aerotechnogenic pollution): V 2 ch. Apatity: KNC RAN, 1996, Ch. 1. 213 p.; Ch. 2. 192 p.

Lukina N. V., Nikonov V. V., Pitatel’nyj rezhim lesov severnoj tajgi: prirodnye i tehnogennye aspekty (Nutritional regime of northern taiga forests: natural and technogenic aspects), Apatity: KNC RAN, 1998, 316 p.

Lukina N. V., Nikonov V. V., Pajtio H., Himicheskij sostav hvoi sosny na Kol’skom poluostrove (Chemical composition of pine needles on the Kola Peninsula), Lesovedenie, 1994, No 6, pp. 10–21.

Mamaev S. A., Formy vnutrividovoj izmenchivosti drevesnyh rastenij na primere Pinaceae na Urale (Forms of intraspecific variability of woody plants: on the example of the Pinaceae family in the Urals), Moscow: Nauka, 1972, 284 p.

Manakov K. N., Nikonov V. V., Biologicheskij krugovorot mineral’nyh jelementov i pochvoobrazovanie v el’nikah Krajnego Severa (The biological cycle of mineral elements and soil formation in the spruce forests of the Extreme North region), Leningrad: Nauka, 1981, 196 p.

Markert B., Fränzle S., Wünschmann S., Chemical Evolution: The Biological System of the Elements. Springer International Publishing, Switzerland, 2015, 295 p.

Market B., Vtorova V. N., Kadastry koncentracij himicheskih jelementov rastenij lesnyh jekosistem Vostochnoj Evropy (Cadastres of chemical element concentrations in the plants of the Eastern Europe ecosystems), Izvsetiya RAN. Seriya Biologicheskaya, 1995, No 5, pp. 545–553.

Marunich S. V., Burov A. S., Kuznecova Ju. N., Nedogarko I. V., Transformacija himicheskogo sostava atmosfernyh osadkov pologom drevostoja juzhno-taezhnyh lesov (Transformation of the chemical composition of precipitation by a stand canopy in the Southern-Taiga forests), Izvestija RAN. Serija geograficheskaja, 2006, No 4, pp. 52–57.

McClenahen J. R., Vimmerstedt J. P., Scherzer A. J., Elemental Concentrations in Tree Rings by PIXE: Statistical Variability, Mobility, and Effects of Altered Soil Chemistry, Canadian Journal of Forest Research, 1989, Vol. 19, No 7, pp. 880–888.

Medvedev I. F., Derevjagin S. S., Kozachenko M. A., Gusakova N. N., Ocenka soderzhanija himicheskih jelementov v drevesine razlichnyh porod derev’ev (Assessment of chemical elements in wood of different tree species), Agrarnyj nauchnyj zhurnal, 2015, No 11, pp. 12–14.

Mejstrik V., Soderzhanie barija, marganca, kobal’ta, zheleza i cinka v hvoe sosny Pinus sylvestris L. (The content of barium, manganese, cobalt, iron and zinc in pine needles (Pinus sylvestris L.), E`kologicheskaya kooperaciya, 1988, No 1, pp. 66–69.

Metodika vypolnenija izmerenij valovogo soderzhanija medi, kadmija, cinka, svinca, nikelja, marganca, kobal’ta, hroma metodom atomno-absorbcionnoj spektroskopii (A measurement method for a total content of copper, cadmium, zinc, lead, nickel, manganese, cobalt, and chromium by atomic absorption spectroscopy), Moscow: FGU FCAO, 2007, 20 p.

Mina V. N., Vyshhelachivanie nekotoryh veshhestv atmosfernymi osadkami iz drevesnyh rastenij i ego znachenie v biologicheskom krugovorote (Leaching of certain substances from ligneous plants by atmospheric precipitations and its importance in the biological cycle), Pochvovedenie, 1965, No 6, pp. 7–17.

Mirkin B. M., Rozenberg G. S., Tolkovyj slovar’ sovremennoj fitocenologii (Explanatory dictionary of modern phytocenology), Moscow: Nauka, 1983, 134 p.

Mironova A. S., Himicheskij jelementnyj sostav godovyh kolec sosny obyknovennoj Pinus sylvestris L. razlichnyh territorij proizrastanija (Chemical elemental composition of annual rings of Scots pine (Pinus sylvestris L.) of various growing areas), Severnaja Pal’mira: Proc. Conference 9-rd Molodezhnoj jekologicheskoj konferencii, SPb.: NICJeB RAN, 2018, pp. 78–82.

Mironova A. S., Rihvanov L. P., Baranovskaja N. V., Sudyko A. F., Godovye kol’ca sosny obyknovennoj (Pinus sylvestris L.) – indikator geohimicheskoj obstanovki i hronologicheskogo izmenenija himicheskogo jelementnogo sostava okruzhajushhej sredy (Annual rings of Scots pine (Pinus sylvestris L.) as an indicator of the geochemical situation and chronological changes in the chemical composition of the environment), Izvestija Tomskogo politehnicheskogo universiteta. Inzhiniring georesursov, 2020, Vol. 331, No 1, pp. 106–116.

Mishukov N. P., Izmenchivost’ sosny obyknovennoj v Priobskih borah Novosibirskoj oblasti i ee znachenie dlja lesnogo semenovodstva. Avtoref. diss. kand. nauk (Variability of Scots pine in the Ob-River pine stands in the Novosibirsk Region and its importance for the forest seed industry. Abstract of candidates sci. thesis), Sverdlovsk, 1966, 26 p.

Mitrofanov D. P., Soderzhanie makro-i mikrojelementov v lesnyh fitocenozah sred-nej tajgi Sibiri (The content of macro- and microelements in the forest phytocenoses of the middle taiga of Siberia), Krasnojarsk, 1973, pp. 28–38.

Nikitin M. A., Proisxozhdenie zhizni (The origin of life), M.: Al`pina non-fikshn, 2016, 542 p.

Nikonov V. V., Lukina N. V., Vlijanie eli i sosny na kislotnost’ i sostav atmosfer-nyh vypadenij v severo-taezhnyh lesah industrial’no-razvitogo rajona (The influence of spruce and pine on the acidity and composition of precipitations in the Northern-Taiga forests of an industrially developed region), Jekologija, 2000, No 2, pp. 97–105.

Nikonov V. V., Lukina N. V., Bazel’ V. S., Rassejannye jelementy v boreal’nyh leash (Trace elements in the boreal forests), Moscow: Nauka, 2004, 616 p.

Padilla K. L., Anderson K. A., Trace Element Concentration in Tree-Rings Biomonitoring Centuries of Environmental Change, Chemosphere, 2002, Vol. 49, No 6, pp. 575–585.

Perel’man A. I., Geohimija landshafta, Moscow: Vysshaja shkola, 1975, 340 p.

Perel’man A. I., Geohimija, Moscow: Vysshaja shkola, 1989, 526 p.

Perel’man A. I., Kasimov N. S., Geohimija landshafta, Moscow: Astreja-2000, 1999, 768 p.

Petrunina N. S., Garanina N. S., Vnutrividovaja izmenchivost’ rastenij v jekstremal’nyh geohimicheskih uslovijah (Intraspecific variability of plants under extreme geochemical conditions), [in:] Jekologija populjacij. Struktura i dinamika, Moscow: RASHN, 1995, Vol. 2, pp. 884–893.

Pravdin L. F., Sosna obyknovennaja. Izmenchivost’, vnutrividovaja sistematika i selekcija (Scottish pine. Variability, intraspecific taxonomy and selection), Moscow: Nauka, 1964, 192 p.

Pristova T. A., Vlijanie drevesnogo pologa listvenno-hvojnogo nasazhdenija na himi-cheskij sostav osadkov (The influence of a tree canopy in a deciduous and coniferous stand on the chemical composition of precipitation), Lesovedenie, 2005, No 5, pp. 49–55.

Pristova T. A., Fedorkov A. L., Jelementnyj sostav Pinus contorta Dougl. i Pinus sylvestris L. v jeksperimental’nyh kul’turah Syktyvkarskogo lesnichestva Respubliki Komi (The chemistry of sediment is dependent on the tree canopy), Izvestija Sankt-Peterburgskoj lesotehnicheskoj akademii, 2023, No 245, pp. 55–70.

Pugachev A. A., Biologicheskij krugovorot i pochvoobrazovanie v landshaftah Krajnego Severo-Vostoka Rossii (Biological cycle and soil formation in the landscapes of the Far North-East of Russia), Magadan: SVNC DVO RAN, 2009, 116 p.

Remezov N. P., Bykova L. N., Smirnova K. M., Potreblenie i krugovorot azota i zol’-nyh jelementov v lesah evropejskoj chasti SSSR (The consumption and cycle of nitrogen and ash elements in the forests of the European part of the USSR), Moscow: Izd-vo Mosk. un-ta, 1959, 284 p.

Rixvanov L. P., Arxangel`skaya T. A., Zamyatina Yu. L., Dendroradiografiya kak metod ret-rospektivnoj ocenki radioe`kologicheskoj situacii (Dendroradiography as a method of retrospective assessment of the radioecological situation), Tomsk: Del`taplan, 2015, 148 p.

Rixvanov L. P., Arxangel`skaya T. A., Nesvetajlo V. D., Izuchenie urovnya i dinamiki nakopleniya delyashhixsya radionuklidov v godovy`x kol`czax derev`ev (Study of the level and dynamics of accumulation of fissile radionuclides in annual tree rings), Geoximiya, 2002, No 11, pp. 1238–1245.

Robakidze E. A., Bobkova K. S., Najmushina S. I., Jelementnyj sostav dominirujushhih vidov rastenij v srednetaezhnyh sosnjakah raznogo vozrasta (na primere Respubliki Komi) (The elemental composition of dominant plant species in the Middle Taiga pine forests of different ages), Rastitel’nye resursy, 2020, Vol. 56, No 1, pp. 53–65.

Robakidze E. A., Gormonova N. V., Bobkova K. S., Himicheskij sostav zhidkih atmosfer-nyh osadkov v starovozrastnyh el’nikah srednej tajgi, (The chemical composition of liquid precipitation in the old-aged spruce forests of the Middle Taiga), Geohimija, 2013, No 1, pp. 72–78.

Rodin L. E., Bazilevich N. I., Dinamika organicheskogo veshhestva i biologicheskij kru-govorot zol’nyh jelementov i azota v osnovnyh tipah rastitel’nosti zemnogo shara (Dynamics of an organic substance and the biological cycle of ash elements and nitrogen in the main types of global vegetation), Moscow-Leningrad: Nauka, 1965, 253 p.

Rogozin M. V., Golikov A. M., Zhekin A. V., Komarov S. S., Zhekina N. V. Selekcija eli finskoj (Picea×fennica (Regel) Kom.): dissimmetriya i xemomarkery` (Selection of Finnish spruce (Picea×fennica (Regel) Kom.): dissymmetry and chemomarkers), Perm’: Permskij gos. nac. issledovatel’skij un-t, 2017, 121 p.

Rogozin M. V., Zhekina N. V., Ustojchivyj rost potomstva eli finskoj i himicheskij sostav hvoi (A sustainable growth of Finnish spruce offspring and the chemical composition of needles), Uspehi sovremennogo estestvoznanija, 2016, No 5, pp. 79–84.

Rogozin M. V., Zhekina N. V., Komarov S. S., Kuvshinskaja L. V., Himicheskie jelementy hvoi v potomstve kul’tur i estestvennyh populjacij eli finskoj (The chemical elements of needles taken from the offspring of Finnish spruce cultures and natural populations), Vestnik Permskogo universiteta. Serija Biologija, 2014, No 3, pp. 44–50.

Romankevich E. A., Zhivoe veshhestvo Zemli. Biogeohimicheskie aspekty problem (The living substance of the Earth. Biogeochemical aspects of the problem), Geohimija, 1988, No 2, pp. 292–306.

Romanovskij M. G., Polimorfizm drevesnyh rastenij po kolichestvennym priznakam (Quantitative polymorphism of ligneous plants), Moscow: Nauka, 1994, 96 p.

Romanovskij M. G., Shhjokalev R. V., Sistema vida u drevesnyh rastenij (The species system of ligneous plants), Moscow: Tovarishhestvo nauchnyh izdanij KMK, 2014, 212 p.

Shheglov A. I., Biogeoximiya texnogenny`x radionuklidov v lesny`x e`kosistemax: po materialam 10-letnix issledovanij v zone vliyaniya avarii na ChAE`S (Biogeochemistry of technogenic radionuclides in forest ecosystems: based on the materials of 10 years of research in the zone of influence of the Chernobyl accident), Moscow: Nauka, 1999, 268 p.

Shul’ga V. V., Vnutrividovaja izmenchivost’ sosny obyknovennoj na juge ee areala (v Kazahstane) (Intraspecies variability of Scots pine in the south of its habitat) [in:] Lesa i drevesnye porody Severnogo Kazahstana, Leningrad: Nauka, 1974, pp. 66–71.

Sibirkina A. R., Soderzhanie kadmija v organah sosny obyknovennoj lentochnyh borov Priirtysh’ja Respubliki Kazahstan (The cadmium content in Scots pine organs in the ribbon-like pine forests in Irtysh Land of the Republic of Kazakhstan), Vestnik Voronezhskogo gosudarstvennogo universiteta. Serija: Himija. Biologija. Farmacija, 2013, No 2, pp. 130–137.

Sokolov A. A., Himicheskij sostav atmosfernyh osadkov, proshedshih skvoz’ polog elo-vogo i berezovogo drevostoja (The chemical composition of precipitation passing through the canopy of a spruce or birch stand), Lesovedenie, 1972, No 3, pp. 103–106.

Suhareva T. A., Lukina N. V., Himicheskij Sostav i morfometricheskie harakteristiki hvoi eli sibirskoj na Kol’skom poluostrove v processe degradacionnoj sukcessii lesov (The chemical composition and morphometrical characteristics of Siberian spruce needles on the Kola Peninsula in the forest degradation succession process), Lesovedenie, 2004, No 2, pp. 36–43.

Sviridova I. K., Rezul’taty izuchenija vymyvanija azota i zol’nyh jelementov dozhde-vymi osadkami iz kron drevesnyh porod (The study results of nitrogen and ash element leaching from wood species crowns by rain precipitation), Paper AN SSSR, 1960, Vol. 133, No 3, pp. 706–708.

Sysuev V. V., O mehanizme izmenenija himicheskogo sostava atmosfernyh vod pod po-logom lesa (The mechanism of changes in the chemical composition of precipitation water under the forest canopy), Vestnik MGU. Ser. Geografija, 1975, No 5, pp. 107–110.

Tarakanov V. V., Chankina O. V., Kucenogij K. P., Naumova N. B., Makarikova R. P., Milyutin L. I., Rogovcev R. V., Efimov V. M., Vliyanie geograficheskix populyacij sosny` na e`lementny`j sostav fitomassy` i pochv (The influence of geographical pine populations on the elemental composition of phytomass and soils), Poverxnost`. Rentgenovskie, sinxrotronny`e i nejtronny`e issledovaniya, 2011, No 11, pp. 72–78.

Tarakanov V. V., Miljutin L. I., Kucenogij K. P., Koval’skaja G. A., Ignat’ev L. A., Samsonova A. E., Jelementnyj sostav hvoi v raznyh klonah sosny obyknovennoj (The elemental composition of needles in the different clones of Scots pine), Lesovedenie, 2007, No 1, pp. 28–35.

Tarhanov S. N., Birjukov S. Ju., Formovoe raznoobrazie Pinus sylvestris (Pinaceae) v bassejne Severnoj Dviny (The form diversity of Pinus sylvestris (Pinaceae) in the Northern Dvina basin), Rastitel’nye resursy, 2013, No 4, pp. 481–489.

Tarhanov S. N., Korovin V. V., Shhjokalev R. V., Formovoe raznoobrazie hvojnyh na evro-pejskom severe Rossii (The form diversity of conifers in the European North of Russia), Lesnoj Vestnik, 2006, No 5, pp. 89–95.

Titljanova A. A., Universal’nost’ processov bioticheskogo krugovorota (Universalism of the biological cycle processes), Pochvovedenie, 2014, No 7, pp. 771–780.

Ushakova G. I., Biogeohimicheskaja migracija jelementov i pochvoobrazovanie v lesah Kol’skogo poluostrova (Biogeochemical migration of elements and soil formation in forests of the Kola Peninsula), Apatity: Karel. nauch. centr RAN, 1997, 150 p.

Usol’cev V. A., Jetjudy o nashih lesnyh derev’jah (Sketches about our forest trees), Ekaterinburg: Bank kul’turnoj in-formacii, 2008, 188 p.

Usol’cev V. A., Lesnye arabeski, ili Jetjudy iz zhizni nashih derev’ev (Forest arabesques, or Sketches from the life of our trees), Ekaterinburg: Ural’skij gos. lesotehnich. un-t, 2014, 161 p.

Varaksina T. N., Hol’kin Ju. I., Bazhenov V. A., O zavisimosti himicheskogo sostava drevesiny ot uslovij proizrastanija IVUZ (Dependence of the chemical composition of wood on the growing conditions), Lesnoy zhurnal, 1967, No 2, pp. 137–139.

Veretennikov A. V., Fiziologija rastenij s osnovami biohimii (Plant physiology with basics of biochemistry), Voronezh: VGU, 1987, 256 p.

Vernadskij V. I., Zhivoe veshhestvo i biosfera (Living things and the biosphere), M.: Nauka, 1994, 671 p.

Vinogradov A. P., Izbranny`e trudy`. Ximicheskij e`lementarny`j sostav organizmov morya (Selected works. Chemical elementary composition of marine organisms), Moscow: Nauka, 2001, 619 p.

Vinokurova R. I., Zakonomernosti nakoplenija i raspredelenija himicheskih jelementov v fitomasse elovo-pihtovyh nasazhdenij zony smeshannyh lesov Srednego Povolzh’ja.Diss. doct. biol. nauk (Regular patterns in the accumulation and distribution of chemical elements in the phytomass of the spruce and abies stands in the mixed forest zone in the Middle Volga region. Doctoral’s boil. sci. thesis)., Joshkar-Ola: MarGTU, 2003, 277 p.

Vinokurova R. I., Andrijanova O. V., Latypova V. Z., Parametry biologicheskogo krugo-vorota himicheskih jelementov v srednevozrastnyh elovo-pihtovyh nasazhdenijah Respubliki Marij Jel, Jekologicheskie osnovy racional’nogo lesopol’zovanija v Srednem Povolzh’e (Parameters of the biological cycle of the chemical elements in the middle-aged spruce and abies stands in the Republic of Mari El), Materialy nauchno-prakt. konf., Joshkar-Ola: MarGTU, 2002, pp. 188–193.

Vinokurova R. I., Osipova V. Ju., Latypova V. Z., Soderzhanie mikrojelementov v struk-turnyh chastjah hvojnyh derev’ev, Jekologicheskie problemy i puti ih reshenija v zone Srednego Povolzh’ja (The microelement contents in the structural parts of conifer trees. The influence of pine geographical populations on the elemental composition of the phytomass and soils), Materialy Vseros. nauch. konf., Saransk, 1999, pp. 61–62.

Vozdejstvie vybrosov avtotransporta na prirodnuju sredu (Impact of car emissions on the natural environment), Pod red. Kachalovoy O. L., Riga: Zinatne, 1989, 137 p.

Vtorova V. N., Market B., Mul’tijelementnyj analiz rastenij lesnyh jekosistem Vostochnoj Evropy (Multielemental analysis of plants from the forest ecosystems of Eastern Europe), Izvsetiya RAN. Seriya Biologicheskaya, 1995, No 4, pp. 447–454.

Zamyatina Yu. L., Izuchenie istorii postupleniya radionuklidov v okruzhayushhuyu sredu na osnove f-radiograficheskogo analiza godichny`x kolecz derev`ev. Aftoreferat diss. cand. geol.-mineral. nauk (Study of the history of radionuclide release into the environment based on f-radiographic analysis of annual tree rings, Abstract of candidate’s geol.-mineral. sci. thesis), Tomsk, 2008, 26 p.

А. I. Kuznetsova^1*, V. A. Kuznetsov², E. V. Tikhonova¹, D. N. Tebenkova¹

¹Centre for Forest Ecology and Productivity of the RAS

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

²Lomonosov Moscow State University

Leninskiye Gori 1, Moscow, 119991, Russia

*E-mail: nasta472288813@yandex.ru

Received: 11.08.2024

Revised: 15.09.2024

Accepted: 25.09.2024

The soil temperature regime is an important regulatory ecosystem function on which many biogeochemical processes depend. This article assesses the variation in the average monthly temperature of the surface organic soil horizon and litter stock in the Spruce-broadleaved and Lime-birch forest types of the Valuev Moscow Forest Park, taking into account intra- and interbiogeocenotic variability for 2019-2022. In all studied summer periods, the litter temperature of the oak-spruce forest is lower than that of the birch-linden forest. The variability of the litter temperature in winter depends on the depth of the snow cover, the onset of stable snow cover and litter reserves. A close negative relationship was found between the litter reserves and its temperature in summer, and a positive relationship in winter. In the presence of a thick snow cover, the litter temperature of the undercrown spaces is higher than the litter temperature of the window, which is characterized by low reserves. Further studies on the effect of woody vegetation on the characteristics of the soil surface temperature regime can be used to assess the rate of litter decomposition and greenhouse gas emission.

 Keywords: quality of litter, mosaic elements, coniferous-broadleaf forests

 REFERENCES

Akkumuljacija ugleroda v lesnyh pochvah i sukcessionnyj status lesov (Carbon accumulation in forest soils and successional status of forests), Moscow: Tovarishhestvo nauchnyh izdanij KMK, 2018, 232 p.

Belova A. I., Lebedev E. V., Hamitov R. S., Vlijanie meteorologicheskih uslovij na rost kul’tur eli s zakrytoj kornevoj sistemoj (Influence of meteorological conditions on spruce crops growth with root-balled tree system), Forestry Bulletin, 2023, Vol. 27, No 5, pp. 100–108, DOI: 10.18698/2542-1468-2023-5-100-108.

Bitjukov N. A., Temperaturnyj rezhim buryh lesnyh pochv pod buknjakami (Temperature conditions of brown forest soils under beech forests), Izvestija Sochinskogo gosudarstvennogo universiteta, 2012, Vol. 21, No 3, pp. 219–223.

Demakov Ju. P., Isaev A. V., Sharafutdinov R. N., Rol’ lesnoj podstilki v borah Marijskogo Zavolzh’ja i variabel’nost’ ee parametrov (Forest cover role in pine forests of Mari trans-volga region and variability of soil cover parameters), Nauchnye trudy gosudarstvennogo prirodnogo zapovednika «Bol’shaja Kokshaga», 2017, Vol. 8, pp. 15–43.

Dymov A. A., Startsev V. V., Changes in the temperature regime of podzolic soils in the course of natural forest restoration after clearcutting, Eurasian Soil Science, 2016, Vol. 49, pp. 551–559.

Kashulinа G. M., Litvinova T. I., Korobeinikova N. M., Comparative analysis of soil temperature in the O horizon on two variously degraded sites of the technogenic ecosystem of nickel industrial complex (Kola Peninsula), Eurasian Soil Science, 2020, Vol. 53, pp. 1311–1321.

Komarov A. V., Ershov D. V., Tikhonova E. V., Informativeness of the Spectral and Morphometric Characteristics of the Canopy-Gap Structure Based on Remote Sensing Data // Contemporary Problems of Ecology, 2021, Vol. 14, pp. 733–742, DOI: 10.1134/S1995425521070076.

Kuznecova A. I., Rol’ rastitel’nosti v akkumuljacii pochvennogo ugleroda v hvojno-shirokolistvennyh lesah evropejskoj chasti Rossii (The role of vegetation in the accumulation of soil carbon in coniferous-deciduous forests of the European part of Russia), Moscow: «Cifrovichok», 2022, 109 p.

Lukina N. V., Geraskina A. P., Gornov A. V., Shevchenko N. E., Kuprin A. V., Chernov T. I., Chumachenko S. I., Shanin V. N., Kuznecova A. I., Teben’kova D. N., 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, pp. 1–90.

Mahatkov I. D., Ermolov Ju. V., Osobennosti temperaturnogo rezhima lesnyh pochv severnoj tajgi Zapadnoj Sibiri (Spatial variation of the root zone layer temperature in the northern taiga of West Siberia), Pochvy i okruzhayushchaya sreda, 2020, Vol. 2, No 4, pp. 1–11.

Orlova M. A., Lukina N. V., Smirnov V. Je., Metodicheskie podhody k otboru obrazcov lesnoj podstilki s uchetom mozaichnosti lesnyh biogeocenozov (Methodology of forest litter sampling taking into account the patchiness of forest biogeocoenoses), Lesovedenie, 2015, No 3, pp. 214–221.

Pristova T. A., Vlijanie drevesnoj rastitel’nosti na fizicheskie pokazateli snezhnogo pokrova srednej tajgi Respubliki Komi (Woody vegetation influence on snow cover (middle taiga of Komi Republic), Forestry Bulletin, 2024, Vol. 28, No 1, pp. 68–79, DOI: 10.18698/2542-1468-2024-1-68-79

Tarasov P. A., Ivanov V. A., Ivanova G. A., Osobennosti temperaturnogo rezhima pochv v sosnjakah srednej tajgi, projdennyh nizovymi pozharami (Features of the temperature regime of soils in middle taiga pine forests subject to ground fires), Hvojnye boreal’noj zony, 2008, No 3-4, pp. 300–304.

Tihonova E. V., Tihonov G. N., Mozaichnost’ fitocenozov hvojno-shirokolistvennyh lesov Valuevskogo lesoparka (Forest cover mosaics of coniferous-deciduous forests in the Valuevsky forest park), Voprosy lesnoj nauki, 2021, Vol. 4, No 3, pp. 52–87.

]]> https://jfsi.ru/en/7-3-2024-kulakova_kurganova/ Mon, 09 Dec 2024 12:22:06 +0000 https://jfsi.ru/?p=6943

          N. Yu. Kulakova^1*, I. N. Kurganova²

 ¹Institute of Forest Science RAS,

Sovetskaya st. 21, Uspenskoe village, 143030 Moscow Region, Russia

 ²Institute of Physicochemical and Biological Problems of Soil Science RAS

FRC PSCBI RAS, Institutskaya st., bldg. 2, k. 2, 142290, Pushchino, Russia

^*E-mail: nkulakova@mail.ru

Received: 14.08.2024

Revised: 14.09.2024

Accepted: 22.09.2024

The relationships between the fluctuating asymmetry indices (FAI) of English oak leaves and the sanitary condition of trees, the concentration of Mg, P, K, Ca, Fe, Zn in leaves; Mg, P, K, Ca, Fe, Cu, Zn, Pb in branches and Na, Mg, P, K, Ca, Fe, Cu, Zn, Pb in the soil directly under the tree were studied. 28 trees located in places with different pollution levels (10–30 m from the Moscow Ring Road and Uzkoe forest park, Moscow) were examined. In the full sample of trees, significant positive correlations were found between the FAI of leaves and the concentration of Ca, Zn, S, Fe in them, as well as between the FAI of leaves and the concentration of Ca, Cu, Na, Fe, Zn in the soil. Negative dependencies were found between the FAI of leaves, the concentration of P in branches and the vital condition of trees. In the case of small samples (n = 10), the presence of correlations between the leaf PFA and the vital condition of trees was noted only in the group of trees in poor vital condition.

 Keywords: vehicle pollution, biodiagnostics, vital state of trees, powdery mildew, oak stands

REFERENCES

Alves-Silva E., Del-Claro K., Herbivory causes increases in leaf spinescence and fluctuating asymmetry as a mechanism of delayed induced resistance in a tropical savanna tree, Plant Ecology and Evolution, 2016, Vol. 149, No 1, pp. 73–80, DOI: 10.5091/plecevo.2016.1093.

 Cornelissen T., Stiling P., Drake B., Elevated CO2 decreases leaf fluctuating asymmetry and herbivory by leaf miners on two oak species, Global Change Biology, 2004, Vol. 10, No 1, pp. 27–36, DOI: 10.1046/j.1529-8817.2003.00712.x. 

 Cornelissen T., Stiling P., Similar responses of insect herbivores to leaf fluctuating asymmetry, Arthropod-Plant Interactions, 2011, Vol. 5, No 1, pp. 59–69, DOI: 10.1007/s11829-010-9116-1. 

Gavrikov D. E.,  Zverev V., Rachenko M. A., Pristavka A. A.,  Kozlov M. V., Experimental evidence questions the relationship between stress and fluctuating asymmetry in plants, Symmetry, 2023, Vol. 15,  No 2, pp. 339,  DOI: 10.3390/sym15020339.

Alykov N. N., Sergeeva E. Ju., Savel’eva E. S., Vlijanie dioksidov sery i azota na soderzhanie fotosinteticheskih pigmentov v list’jah drevesnyh rastenij, Juzhno-rossijskij vestnik geologii, geografii i global’noj jenergii, 2006, Vol. 5(18), рр. 91–95. 

Doklad o sostoyanii okruzhayushchej sredy v gorode Moskve v 2023 godu (Report on the state of the environment in the city of Moscow in 2023), 169 p, URL: clck.ru/3EQH3f (September 10, 2024).

Fedorov N. I., Lesnaja fitopatologija: uchebnik dlja vuzov (Forest Phytopathology: Textbook for Universities), Minsk: Izd-vo BGTU, 2004, 439 p.

Fedorova T. A., Fluktuirujushhaja asimmetrija lista lipy melkolistnoj (Tilia cordata Mill.) kak bioindikacionnyj parametr ocenki kachestva sredy (Fluctuating leaf asymmetry of small-leaved linden (Tilia cordata Mill.) as a bioindication parameter for assessing environmental quality), Vestnik Kurganskogo gosudarstvennogo universiteta, 2013, No 3, pp. 41–43.

Geras’kina N. P., Ocenka stabil’nosti razvitija duba chereshchatogo na territorii nacional’nogo parka «Orlovskoe poles’e» (Evaluation of the stability of the development of English oak in the territory of the «Orlovskoye Polesie National Park»), Samarskaja Luka: problemy regional’noj i global’noj jekologii, 2009, Vol. 18, No 3, pp. 240–244.

Ginijatullin R. H., Kulagin A. Ju., Osobennosti soderzhanija svinca v organah u zdorovyh i oslablennyh derev’ev berezy povisloj (Betula pendula Roth) v uslovijah promyshlennogo zagrjaznenija, Izvestija Ufimskogo nauchnogo centra RAN, 2018, Vol. 3, рр. 39–44.

 Kaplina N. F., Selochnik N. N., Tekushhee i dolgovremennoe sostojanie duba chereshchatogo v treh kontrastnyh tipah lesa juzhnoj lesostepi (Current and long-term status of English oak in three contrasting forest types of the southern forest-steppe), Lesovedenie, 2015, No 3,  pp. 191–201.

Konstantinov E. L., Osobennosti fluktuirujushhej asimmetrii listovoj plastinki berezy povisloj (Betula pendula Roth.) kak vida bioindikatora Dis… kand. biol. nauk (Features of fluctuating asymmetry of the leaf blade of silver birch (Betula pendula Roth.) as a bioindicator species (Candidate’s biol. sci.), Kaluga, 2001, 126 p.

Kozlov M. V., Issledovanija fluktuirujushhej asimmetrii rastenij v Rossii: mifologija i metodologija (Research of fluctuating asymmetry of plants in Russia: mythology and methodology), Jekologija, 2017, No 1, pp. 3–12, DOI: 10.7868/S0367059717010103.

Kravec E. A., Grodzinskij D. M., Shilina Ju. V., Ovsjannikova L. G., Mehanizmy indukcii asimmetrii organogeneza rastenij (Mechanisms of induction of asymmetry of plant organogenesis), Izvestija TSHA, 2007, Vol. 5, pp. 120–124.

Kulakova N. Ju., Kolesnikov A. V., Kurganova I. N., Shujskaja E. V., Mironova A. V., Skorobogatova D. M., Izmenenie biohimicheskih i morfologicheskih pokazatelej sostojanija derev’ev duba chereshchatogo (Quercus robur L.) pod vlijaniem avtotransportnogo zagrjaznenija (Changes in biochemical and morphological indicators of the condition of English oak trees (Quercus robur L.) under the influence of road pollution), Lesovedenie, 2021, No 4, pp. 393–405.

Kulakova N. Ju., Shabanova N. P., Zasolenie pochv – odna iz problem gorodskogo ozelenenija (Soil salinization is one of the problems of urban greening) Aktual’nye problemy lesnogo kompleksa, 2019, No 54, pp. 127–131.

Lajus D. L., Grjem D. H., Katolikova M. V., Jurceva A. O., Fluktuirujushhaja asimmetrija i sluchajnaja fenotipicheskaja izmenchivost’ v populjacionnyh issledovani – jah: istorija, dostizhenija, problemy, perspektivy (Fluctuating asymmetry and random phenotypic variability in population studies: history, achievements, problems, prospects), Vestn. S.-Peterburg. un-ta. Ser. 3: Biologija, 2009, No 3, pp. 98–110.

Man S. R., Oroian I., Odagiu A., Man A., Braşovean I., Influence of Fertilizations upon the Intensity of Microsphaera abbreviata Attack in Oak // Bulletin of University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca. Agriculture, 2012, Vol. 69, No 2, Article number 148.

Nazarova N. M., K voprosu o perspektivnosti ispol’zovanija S. Vulgaris l. v kachestve vida – bioindikatora tehnogennogo zagrjaznenija urbosredy g. Orenburga (On the prospects of using S. Vulgaris l. as a bioindicator species of technogenic pollution of the urban environment of Orenburg), Prirodnoresursnyj Potencial, Jekologija i Ustojchivoe Razvitie Regionov Rossii, (Natural resource potential, ecology and sustainable development of Russian regions), Collection of articles Proc. Conf., Penza: Penza State Agrarian University, 24–25 January, 2019, pp. 129–133.

Pavlov I. I., Izuchenie sorbcii ftora v list’jah drevesnyh rastenij (Study of fluorine sorption in leaves of woody plants), Himija rastitel’nogo syr’ja, 1999, Vol. 2, рр. 37– 43.

Poljakova L. V., Litvinenko V. I., Znachenie vtorichnyh metabolitov v formirovanii ustojchivosti k muchnistoj rose derev’ev 16 – letnih kul’tur duba chereshchatogo (The Importance of Secondary Metabolites in the Formation of Resistance to Powdery Mildew in 16-Year-Old English Oak Crop Trees), Lesovedenie, 2019, No 2, pp. 128–137, DOI: 10.1134/S0024114819010108.

 Poljakova L. V., Saltykov A. N., Zhurova P. T., Dinamika pokazatelej ustojchivosti k vrediteljam i boleznjam list’ev duba chereshchatogo na fone izmenchivosti biohimicheskih priznakov (Dynamics of indicators of resistance to pests and diseases of leaves of English oak against the background of variability of biochemical traits), Biological Diversity and Sustainability of Forest and Urban Ecosystems. The First International Readings in Memory of GF Morozov, Coll. art. Simferopol, 12–16 September, 2019, рp. 79–84.

Polonskij V. I., Poljakova I. S., Fluktuirujushhaja asimmetrija list’ev: mehanizm formirovanija i primenenie v fitoindikacii (Fluctuating leaf asymmetry: mechanism of formation and application in phytoindication), Problems of Botany of Southern Siberia and Mongolia, Proc. Conf. Barnaul, 23–26 May, 2016, pp. 506–510.

Titov A. F., Kaznina N. M., Talanova V. V., Tjazhelye metally i rastenija (Heavy Metals and Plants), Petrozavodsk: Karel’skij nauchnyj centr RAN, 2014, 194 p.

 Zaharov V. M, Baranov A. S., Borisov V. I., Valeckij A. V., Krjazheva N. G., Chistjakova E.K., Chubinishvili A.B. Zdorov’e sredy: metody ocenki (Environmental Health: Assessment Methods), Moscow: Psihologija, 2000, 66 p.

Zheleznova O. S., Chernyh N. A., Tobratov S. A., Cink i kadmij v fitomasse drevesnyh rastenij lesnyh jekosistem: zakonomernosti translokacii, akkumuljacii i bar’ernyh mehanizmov (Zinc and cadmium in the phytomass of woody plants of forest ecosystems: patterns of translocation, accumulation and barrier mechanisms), Vestnik Rossijskogo universiteta druzhby narodov. Serija: Jekologija i bezopasnost’ zhiznedejatel’nosti, 2017, Vol. 25, No 2, pp. 253–270, DOI 10.22363/2313-2310-2017-25-2-253-270.

Zorina A. A., Korosov A. V., Harakteristika fluktuirujushhej asimmetrii lista dvuh vidov berez v Karelii (Characteristics of fluctuating leaf asymmetry of two birch species in Karelia), Trudy Karel’skogo nauchnogo centra Rossijskoj akademii nauk, 2007, No 11, pp. 28–36. 

]]> https://jfsi.ru/en/7-3-2024-nikitina-pdf/ Fri, 15 Nov 2024 09:04:23 +0000 https://jfsi.ru/?p=6897

Original Russian Text © 2024 A. D. Nikitina published in Forest Science Issues Vol. 7, No 2, Article 146. 

© 2024                                                                 А. D. Nikitina

Center for Forest Ecology and Productivity of the RAS

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

E-mail: nikitina.al.dm@gmail.com

Received: 18 May 2024

Revised: 05 June 2024

Accepted: 22 June 2024

This article presents the results of applying an improved method for automatic segmentation of RGB imagery (orthophotos) obtained using consumer-grade unmanned aerial vehicles (UAVs) based on the Mask R-CNN neural network. Preparation and post-processing blocks for raster and vector files were developed for geospatial data processing. The model was trained on 7,000 tree crowns identified in pine forest of drained habitats in the mixed coniferous-broadleaved forest subzone. Training was carried out using cross-validation. Additional data on 1,337 crowns were used for verification. Sequential filtering by area, score, and duplicate segments improved the quality of the final segmentation results for all age groups of pine forests. The model produced an average precision of 0.87, a recall of 0.81, and an F1-score of 0.83. The obtained results demonstrate the high efficiency of the filtering algorithm in reducing segment redundancy and increasing data reliability. The Mask R-CNN automatic segmentation method is an effective tool for studying the characteristics of pine forest stands based on RGB orthophotos obtained during UAV surveys; using this method, it is possible to reproduce the results of visual interpretation with high precision. This method is particularly effective for scaling studies to large areas, where manual interpretation would be labor-intensive.

Keywords: Mask R-CNN, automatic segmentation, tree detection, pine forest, RGB imagery, UAVs, environmental monitoring, remote sensing

In the context of global climate change, the issues of carbon balance and carbon stocks in forest ecosystems are becoming increasingly relevant. Effective monitoring of these parameters in forest ecosystems and forest resource management require obtaining detailed and accurate information about forest structure and condition (Espíndola, 2023). Within this context, the use of highly detailed GPS survey opens up new opportunities for environmental research and increases the efficiency of data collection and analysis. Forests with a predominance of Scotch pine (Pinus sylvestris L.) are common in the temperate latitudes of the Northern Hemisphere. This species is adaptable to diverse growing conditions and highly resistant to environmental stresses such as droughts and fires. Pine forests with their high ecological tolerance and significant contribution to the carbon cycle are an important object of environmental studies.

Existing studies (Medvedev et al., 2020; Tuominen et al., 2017; Nevalainen et al., 2017; Puliti et al., 2017; Ocer et al., 2020; Diez et al., 2021; Ball et al., 2023; Zhou et al., 2023) outline the prospects of UAV and neural network applications in image processing for accurate and efficient study of forests. However, there are relatively few studies on forests of complex structure with a closed canopy, hence the need for further studies and higher accuracy of methods used in these conditions. It is also essential to take into account the potential for use of mass-market UAVs, since their availability and widespread use make these methods applicable in applied and research practice for a wider range of users. The purpose of this study is to evaluate the effectiveness of the automatic segmentation method using the Mask R-CNN neural network to identify individual trees in pine forest of different structures based on RGB orthophotos obtained using UAVs. In this study, segmentation of ‘pine forests’ primarily focuses on the upper canopy layer, where the crowns of pine trees form the dominant component.

MATERIALS AND METHODS

Objects of research. The objects of research are pine forests in the drained habitats of the coniferous-broadleaved forest subzone of the western part of the Russian Plain in the following protected areas: the Kurshskaya Kosa National Park (NP), the Smolenskoye Poozerye NP, the Bryansky Les State Natural Biosphere Reserve (SNBR). Three age groups were identified in the forests under study: young (10–40 years old), middle-aged (40–80 years old) and old (over 80 years old). Some studies (Nezami et al., 2020; Diez et al., 2021) show that segmentation algorithms demonstrate the highest learning efficiency on single-species and structurally simple forests. With the data obtained in the Kurshskaya Kosa NP, it is possible to better adjust the model, as the studied pine forests of this park mainly have a single-species composition with a 10C stand formula. In accordance with the Guide to Identifying Forest Types in the European Russia (http://cepl.rssi.ru/bio/forest/index.htm), the young pine forests fall into the group of xerophytic green-moss and green-moss-lichen pine forest types. Xerophytic green-moss pine forests are predominant in both middle-aged and old forests. Data obtained in the pine forests of the Smolenskoye Poozerye and Bryansky Les improve the quality of annotation for segmentation algorithms applied to forest stands of mixed composition and complex structure, making these algorithms more versatile. In the Smolenskoye Poozerye NP, the studied areas in middle-aged and old forests are dominated by low shrub-green-moss pine forests, whereas the young forests are mainly represented by small-grass-green-moss pine forests, with a closeness of 40–90%. Within the studied areas of the Bryansky Les Biosphere Reserve, middle-aged low shrub-green-moss pine forests and complex old pine forests with linden and oak are predominant, with a closeness of 70–80%.

Aerial survey using UAVs. In this study, the results of survey carried out using Phantom 3 Advanced and Mavic Pro UAVs by DJI were used. These devices are affordable and equipped with RGB cameras. Flight tasks were simulated using DroneDeploy software. The flights were performed at an altitude of 100–200 m depending on the complexity of the terrain and the height of the forest canopy with a longitudinal and transverse overlap of 90% with constant calm weather (wind velocity up to 10 m/s) at about 11:00 to 16:00 local time. The survey area using such parameters is ~15 hectares per battery.

Aerial images processing was carried out using Agisoft Metashape software and included the following main stages: uploading images; image alignment; building a dense point cloud; building a digital terrain model (DTM); building an orthophoto; rasterizing the DTMs and the orthophotos. The calculated spatial resolution of the DTMs varied from 15 to 32 cm/pixel depending on the altitude of the flight, whereas that of orthophotos was from 2 to 8 cm/pixel. The total number of initial images used to create orthophotos exceeded 20,000, with an average orthophoto resolution of 5.9 cm/pixel and DTM resolution of 23.6 cm/pixel. The total number of orthophotos was 55.

Visual interpretation. During interpretation, the boundaries of the crowns of individual trees were delineated manually using the QGIS software. Annotation is necessary to create training and validation datasets. It is carried out for the central sections of orthophotos ranging in size from 20×20 m (for young trees) to 100×100 m (for middle-aged and old forests). As a result, files with spatial vector data (.shp) with the crowns of individual trees in pine forest, as well as in additional key areas of diverse composition, were obtained to expand the training set during further segmentation. The final set of visual annotation data included ~8,300 individual crowns and covered 55 key sites. The most crowns were identified in pine forest — 6,799, including 3,330 in middle–aged forests, 2,325 in old forests, and 1,144 in young forests. Auxiliary areas with other species make up a smaller part (broadleaved forests — 562, spruce forests — 823, small-leaved forests — 141).

Automatic segmentation using the Mask R-CNN neural network. The ultra-precision Mask R-CNN neural network developed in 2017 (He et al., 2017) is used to identify individual tree crowns on aerial images. It expands the capabilities of the Faster R-CNN neural network due to the added module that predicts segmentation masks for regions of interest (RoI). This module works together with the classification and regression of the Bounding box. One of the features of Mask R-CNN is pixel-to-pixel alignment, which is not implemented in Fast/Faster R-CNN.

The following tools, frameworks and libraries were used to create the project: CUDA, Jupyter Notebook, QGIS, PyTorch, Rasterio, fiona, and Matplotlib. The study was carried out using the Mask R-CNN model in the Python PyTorch machine learning framework, pre-trained on the COCO dataset which includes more than 330,000 images and 1.5 million objects. The pre-trained model is able to identify the boundaries of objects in images. However, additional training is required for tree crown detection. This process is simpler and faster than learning from scratch, it reduces the risk of getting stuck in local minima and reduces the number of necessary adjustments. The neural network parameters were reconfigured for the classification of regions of interest, creation of bounding boxes, and mask segmentation.

Creating a dataset for model training. The first step is to create a specialized dataset. The following source data were used for this task: UAV orthophotos (in GeoTIFF .tiff format); manually selected vector boundaries of tree crowns (in .shp format); boundaries of the areas under study (in .shp format). The model was trained on the contours of seven thousand tree crowns (84%) obtained during visual annotation from all the studied areas. The size of the validation set was 1,337 crowns (16%) from key sites of pine forests, stratified taking into account the object and the age of the stand.

Preparation stages for the data set included checking and adjustment of the vector file geometry (irregular shapes of objects, self-intersections, etc.), data reprojection; conversion of images to 24-bit format; ensuring the correct alignment of input data using uniform boundaries of the studied sites. The model accepts input images as a [W, H, 3] matrix (where W and H stand for width and height, respectively, and 3 is the number of RGB channels), therefore the original images were split into components of equal size based on the optimal grid. The width and height of each component were determined as the minimum among all images (Fig. 1).

(a)

(b)

Figure 1. (a) A schematic diagram for splitting the source raster images
into separate components, where W and H stand for width and height, respectively, and 3 is the number of RGB channels, and (b) individual components after splitting.

A set of binary images of each segment (crown) where pixels have a value of [0] for the background and [1] for the crown was used for annotation (Fig. 2).

Figure 2. Converting an input dataset into a multidimensional array format.

Thus, files with visual annotation were transformed into multidimensional arrays, with each tree crown saved as a separate image. The final dataset accepted by the model included raster orthophotos (.png), information about the boundaries of the sites with the transformation configuration (.json), annotation masks in the form of rasters where each crown corresponds to a certain numerical pixel value (.png), and orthophotos cropped along the extended boundary for the correct identification of marginal objects (.png). Additionally, vector annotation data were loaded, which are not involved in training and are used at the stage of evaluation of the model performance.

Training of the Mask R-CNN neural network model. To train the model, a prepared dataset was used, which was divided into training and validation subsets. Validation data were not used in the learning process. Repeated k-fold cross-validation was used for training data (k=10). The learning parameters of the neural network included the initial learning rate (LR), the LR schedule, the LR factor, the regularization coefficient, and the Stochastic Gradient Descent (SGD) parameter. The model was trained over 9 epochs, with the entire dataset passing through the neural network in each epoch, and the model weights adjusted. Transformations of the input image to enlarge the dataset included rotations as well as contrast, saturation, and brightness adjustments with a total probability of change 0.1. To prevent overfitting, the model was regularly evaluated using a validation dataset. Neural network functioning resulted in the creation of a multidimensional stack of monochrome images of each object with an indication of the confidence level ranging from 0 to 1. This indicator reflects the probability that the output object belongs to a given class (crown).

Processing of data obtained by the model. To analyze the data of the trained neural network, orthophotos of various test areas in the .tiff format with the boundaries of key sites and the results of visual interpretation were transmitted for subsequent calculation of model quality metrics. Considering that the model works with images in pixel coordinates, an additional metadata file was created with information about the coordinate system, coordinates of the corners of the segmented area and the geographical reference.

Due to the limitation of the model to process no more than 100 segments (crowns) per image, it was necessary to divide the source raster into parts (patches) so that each of them had less than 100 crowns. However, when dividing images strictly according to the grid, distortions in segments at the boundaries of the sections are possible (Fig. 3).

a)

b)

Figure 3. An example of a) splitting an image into patches and b) a possible error in segmentation of marginal areas.

The problem of marginal crowns which occurs when splitting an image in accordance with a grid was solved by creating a 50% overlap between patches and defining a zone of ignored boundaries to rule out edge effects. The offset information was saved to further restore the coordinates of the components in the original full-size image. The use of a pyramid of patches, where the size of components doubles at each level, provided adaptation to different scales of objects. The resulting segments were converted into images, and then into a vector format using the marching squares algorithm (confidence threshold = 0.5) implemented in the Skimage library. Crowns falling in the zone of ignored boundaries were removed from the results, thus reducing the number of duplicated and marginal crowns. The remaining segments were combined into a single dataset, where the score was indicated for each identified crown.

Filtering of the segmentation data. Filtering in the context of neural network data processing is an important step aimed at improving the quality of results. During the splitting of images into separate components, a large overlap is assumed, which prevents the model from missing the marginal crowns of trees; however, when assembling the segmentation results into one dataset, duplicates of the same crown are created. In addition to possible duplicates, there may be objects with an irregular shape, unreliable area, or with a low confidence level. All this requires careful filtering which includes the analysis of various parameters in order to determine the optimal criteria for removing unwanted segments.

Optimal parameters for the filtering algorithm were calculated based on data with the calculated Intersection over Union (IoU) metric, which measures the degree of intersection between the crowns predicted by the neural network and the crowns identified visually. These data consisted of a set of points, where each point corresponded to a detected crown with several parameters (area, score, IoU). During the scatter plot analysis (Fig. 4), the threshold for filtering segments with a small area is clearly seen. This filtering step significantly reduced the number of excessively segmented crowns (28%) without significant loss of precision. The scatter plot also shows that the majority of segments with the minimal IoU values also have a low score, so it is advisable to use the score as a filtering parameter in the future.

Figure 4. A scatter plot showing the relationship between the area of a segment (√S, pixels), its score, and the degree of intersection of the segment predicted by the neural network with the reference segment of the annotation (IoU).

To remove duplicate crowns, filtering was used based on the degree of intersection and reliability of the data. If there is a significant overlap between two crowns, the one with a higher score of the neural network is selected. If there is one large and multiple small overlapping segments, only the large one remains if its score is higher. If its score is lower, such a segment is excluded. Therefore, if there is high confidence in smaller segments, a large crown is discarded (Fig. 5a), and vice versa (Fig. 5b). Removing duplicates also contributed to a significantly higher precision.

Figure 5. Filtering options for overlapping crowns with different confidence levels (green segments are saved in the final list, whereas red ones are removed).

The developed sequential filtering included criteria for area and score, and then for segment duplicates. This made it possible to preserve high-quality segments, minimizing loss in recall.

Creation of the final vector layer. To transform the coordinates of the segments into geographical ones and create the final vector file in the .shp format, a metadata file created during the data processing stage was used. Figure 6 shows the neural network’s crown segmentation results, demonstrating the precision of coordinate transformation.

Figure 6. An example of a sample site, where (a) is an orthophoto without annotation, (b) is visual interpretation, (c) is the result of automatic segmentation without filtering, and (d) is the result of automatic segmentation after filtering.

The diagram (Fig. 7) shows the final data processing process for the segmentation of pine tree crowns using the Mask R-CNN algorithm. The upper part of the diagram reflects the research stages, including the creation of a training dataset, actual training of the Mask R-CNN model and selection of the filtering parameters. These steps are performed once to set up the model. The lower part of the diagram demonstrates the processing stage. It begins with uploading raster files, and then the input data is prepared, followed by segment selection and filtering of the results. As a result, a vector file is created that can be used for further analysis.

Figure 7. Data processing steps for automatic crown detection.

Model quality metrics. To evaluate the precision of the neural network in recognizing tree crowns, the results of visual interpretation of orthophotos were used. The crown was considered to be detected correctly if the IoU exceeded 0.5, which is the standard value found in studies on segmentation (Aubry-Kientz et al., 2019; Hao et al., 2021; Ball et al., 2023). For the model quality evaluation, standard error matrices were calculated: TP (true positive) — correct determination of a crown; FP (false positive) — incorrect determination of an object as a crown; FN (false negative) — incorrect exclusion of a crown; TN (true negative) — equal to 0 in segmentation tasks. Based on these data, key metrics were calculated as follows: precision — the proportion of correctly identified crowns among all recognized ones; recall — the proportion of correctly identified crowns from all actually existing ones; F1-score — the harmonic mean between precision and recall, which ensures a balance of these parameters.

RESULTS AND DISCUSSION

At all key sites, the initial results of neural network segmentation had high recall (0.91 for all sites) values and low precision (0.31) and F1-score (0.46) values; segment redundancy can also be seen in the ratio of the number of segmented crowns to visual detection data. Filtering significantly improved the final average precision (0.87) and F1-score (0.83), while the final recall slightly decreased (recall = 0.81).

The chart (Fig. 8) reflecting the change in the F1-score at different filtering stages for different age groups of pine forest shows that after all filtering stages, the median values of the F1-score increase for all age groups, which is evidence of improved quality of segmentation for the entire sample. However, the improvement after filtering is most pronounced for old pine forests (over 80 years old). This is indicatory of the effectiveness of the applied filtering approach to improve the quality of segmentation results, reducing redundancy and increasing data reliability.

Figure 8. Changes in F1-score at different filtering stages for pine forests of different age groups.

The analysis of the training and validation samples used to control overfitting when setting up the model showed the greatest differences in the group of young pine forests (F1_training = 0.81, F1_validation = 0.70) with a median value of 0.8 for all key sites. Middle-aged and old pine forest have high F1-scores for both the training (0.84 and 0.88, respectively) and validation sets (0.83 and 0.82, respectively) of the sites, with a median F1-score of 0.88 for both groups.

The spread of model quality values in pine forests was 0.53–0.96 with an average value of 0.83 and a median value of 0.85. In young forests, the spread of results (F1 = 0.53–0.89) shows lower adaptability of the model to some stands of this age, whereas the results are high on average (F1_average = 0.77, F1_median = 0.8). This may be due to the low quality of the survey (for low stands, it would make sense to carry out UAV surveys at an altitude below 120–180 m when using mass-market UAVs), difficulties with detecting individual trees in dense stands, and a smaller training sample for sample sites with young pine forests. The results were more stable (F1 = 0.7–0.96) for old forests with an average value of F1 = 0.86 (F1_median = 0.88).

The study showed that the adapted Mask R-CNN model provides high precision of results in different age groups of pine forest with different values of closeness, since the indicators of segmentation quality in key sites remain high for all datasets. An example of segmentation results is shown in Figure 9.

a)

b)

c)

Figure 9. An example of a key site where (a) is visual interpretation, (b) is the result of segmentation without filtering, and (c) is the result of segmentation after filtering.

In studies on segmentation of individual trees in stands, closeness of the stands under study is an important factor. N. E. Ocer et al. (2020) carried out a study on detection of individual trees using the Mask R-CNN and Feature Pyramid Nets (FPNs) and obtained F1-scores within 0.82–0.91 for three test images. Sparse stands were analyzed in the study by N. V. Ivanova et al. (Ivanova et al., 2021), where watershed and region growing methods were applied and F1-scores of 0.7–0.9 were obtained. More closed stands are considered in the paper by X. Chen et al. (2023), with F1-scores between 0.71 and 0.79. The study by M. Beloiu et al. (2023) is focused on closed and diverse species stands with F1-scores ranging from 0.44 to 0.92. Studies show that the effectiveness of crown segmentation depends on the closeness of stands, and with its increase, the precision of segmentation becomes more variable.

CONCLUSIONS

The method of automatic image segmentation using the Mask R-CNN neural network is an effective tool for research of pine forest that can reproduce the results of visual interpretation with high precision. The splitting of RGB orthophotos made it possible to take into account individual tree crowns in a closed canopy to the fullest extent possible. The initial results had high recall values; however, a result filtering unit was developed to increase precision. Filtering made it possible to eliminate redundant segments and improve the precision of the results, while maintaining a high degree of crown recognition. For all age groups of pine forests, there was an increase in F1-score after filtering. The final model demonstrates consistently high segmentation quality (F1-score = 0.83) of pine forest.

FINANCING

The work was carried out with support from the Laboratory of Forest Climate-regulating Functions (project 122111500023-6) of the Center for Forest Ecology and Productivity of the RAS (CEPF RAS).

REFERENCES

Agisoft Metashape, available at: http://www.agisoft.com (2024, 01 June).

Aubry-Kientz M., Dutrieux R., Ferraz A., Saatchi S., Hamraz H., Williams J., A comparative assessment of the performance of individual tree crowns delineation algorithms from ALS data in tropical forests, Remote Sensing, 2019, Vol. 11, No 9, pp. 1086 (1–21).

Ball J. G., Hickman S. H., Jackson T. D., Koay X. J., Hirst J., Jay W., Coomes D. A., Accurate delineation of individual tree crowns in tropical forests from aerial RGB imagery using Mask R-CNN, Remote Sensing in Ecology and Conservation, 2023, Vol. 9, No 5, pp. 641–655.

Beloiu M., Heinzmann L., Rehush N., Gessler A., Griess V. C., Individual Tree-Crown Detection and Species Identification in Heterogeneous Forests Using Aerial RGB Imagery and Deep Learning, Remote Sensing, 2023, Vol. 15, p. 1463.

Chen X., Shen X., Cao L., Tree Species Classification in Subtropical Natural Forests Using High-Resolution UAV RGB and SuperView-1 Multispectral Imageries Based on Deep Learning Network Approaches: A Case Study within the Baima Snow Mountain National Nature Reserve, China, Remote Sensing, 2023, Vol. 15, p. 2697.

Diez Y., Kentsch S., Fukuda M., Caceres M. L. L., Moritake K., Cabezas M., Deep Learning in Forestry Using UAV-Acquired RGB Data: A Practical Review, Remote Sens., 2021, Vol. 13, p. 2837.

Espíndola R. P., Ebecken N. F. F., Advances in remote sensing for sustainable forest management: monitoring and protecting natural resources, Revista Caribeña de Ciencias Sociales, 2023, Vol. 12, No 4, pp. 1605–1617.

Hao Z., Lin L., Post C.J., Mikhailova E.A., Li M., Chen Y. et al., Automated tree-crown and height detection in a young forest plantation using mask region-based convolutional neural network (Mask R-CNN), ISPRS Journal of Photogrammetry and Remote Sensing, 2021, Vol. 178, pp. 112–123.

He K., Gkioxari G., Dollár P., Girshick R., Mask R-CNN, Proceedings of the IEEE International Conference on Computer Vision, 2017, pp. 2961–2969.

https://cepl.rssi.ru/bio/forest/index.htm (2024, 1 June).

Ivanova N. V., Shashkov M. P., Shanin V. N., Study of pine forest stand structure in the priosko-terrasny state nature biosphere reserve (Russia) based on aerial photography by quadrocopter, Nature Conservation Research, 2021, Vol. 6, No 4, pp. 1–14.

Medvedev A. A., Tel’nova N. O., Kudikov A. V., Alekseenko N. A., Analiz i kartografirovanie strukturnyh parametrov redkostojnyh severotajozhnyh lesov na osnove fotogrammetricheskih oblakov tochek (Use of photogrammetric point clouds for the analysis and mapping of structural variables in sparse northern boreal forests), Sovremennye problemy distancionnogo zondirovanija Zemli iz kosmosa, 2020, Vol. 17, No 1, pp. 150–163.

Nevalainen O., Honkavaara E., Tuominen S., Viljanen N., Hakala T., Yu X., Hyyppä J., Saari H., Pölönen I., Imai N. N., Tommaselli A. M. G., Individual tree detection and classification with UAV-based photogrammetric point clouds and hyperspectral imaging, Remote Sensing, 2017, Vol. 9, No 3, p. 185.

Nezami S., Khoramshahi E., Nevalainen O., Pölönen I., Honkavaara E., Tree species classification of drone hyperspectral and RGB imagery with deep learning convolutional neural networks, Remote Sensing, 2020, Vol. 12, No. 7, p. 1070.

Ocer N. E., Kaplan G., Erdem F., Matci D.K., Avdan U., Tree extraction from multi-scale UAV images using Mask R-CNN with FPN, Remote Sensing, 2020, Vol. 11, p. 847–856.

Puliti S., Ene L. T., Gobakken T., Næsset E., Use of partial-coverage UAV data in sampling for large scale forest inventories, Remote Sensing of Environment, 2017, Vol. 194, pp. 115–126.

Tuominen S., Näsi R., Honkavaara E., Balazs A., Hakala T., Viljanen N., Reinikainen J., Tree species recognition in species rich area using UAV-borne hyperspectral imagery and stereo-photogrammetric point cloud, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2017, Vol. XLII-3/W3, pp. 185–194.

Zhou J., Chen X., Li S., Dong R., Wang X., Zhang C., Zhang L., Multispecies individual tree crown extraction and classification based on BlendMask and high-resolution UAV images, Journal of Applied Remote Sensing, 2023, Vol. 17, No 1, p. 016503.

Reviewed by: Candidate of Geographical Sciences N. V. Malysheva

     O. I. Evstigneev^1,2

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

 ²Center for Forest Ecology and Productivity of the RAS, Profsoyuznaya st. 84/32 bldg. 14, Moscow, 117997, Russia

E-mail: quercus_eo@mail.ru

Received: 16.08.2024

Revised: 24.09.2024

Accepted: 27.09.2024

O. V. Smirnova is a professor, doctor of biological sciences, and a leading scientist in the field of plant demography, population biology, and forest biogeocenology. O. V.Smirnova’s biogeocenotic views are based on ideas about the population organization of living cover, which were formed under the influence of her teacher, prof. A. A. Uranov. Within the framework of this system of views, O. V. Smirnova made a significant contribution to the development of concepts of the biological age of plants and the population strategy of plants, to the creation of the theory of coenopopulations and the population organization of biogeocenoses, as well as to the formation of ideas about modern zonality as an anthropogenic phenomenon. The article provides a complete bibliography of O. V. Smirnova’s papers, including the titles of her PhD students’ dissertations.

Keywords: biological age of plants, coenopopulation, forest biogeocenology, forest ecology, historical ecology, modern zonality, population strategy of plants

REFERENCES

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

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

Rabotnov T. A., Zhiznennyj cikl mnogoletnih travjanistyh rastenij v lugovyh ceno-zah (Life cycle of perennial herbaceous plants in meadow cenoses), Geobotanika, 1950, No 6, pp. 7–204.

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

Zaugol’nova L. B., Struktura populyacij semennyh rastenij i problemy ih monito-ringa (Structure of seed plant populations and problems of their monitoring), Avtoref. dis. … dok. biol. nauk v forme nauchnogo doklada, SPb, St Petersburg University, 1994, 70 p.