Sankt-Peterburg, St. Petersburg, Russian Federation
employee
Voronezh, Voronezh, Russian Federation
Sankt-Peterburg, St. Petersburg, Russian Federation
Latakia, Syrian Arab Republic
UDK 630 Лесное хозяйство. Лесоводство
GRNTI 68.47 Лесное хозяйство
Artificial plantations of Brutia pine (Pinus brutia Ten.) in the conditions of two regions of Syria – the provinces of Latakia and Tartus – grow at different heights above sea level. At the research objects, accounting sites of a constant radius of 400 square meter were laid, arranged over an area in such a way as to cover the statistical variability of the studied taxation indicators. The distribution rows of tree trunks at a height of 1.3 m were ranked after 5 cm with the analysis of the indicators of symmetry and kurtosis of rank rows. The taxation indicators of the heights and diameters of the trunks of the trees of the Brutia pine (P. brutia Ten.) in its plantations have a direct correlation of varying strength with both the height of the site above sea level and the amount of precipitation. The indicator of the planting stock has the greatest direct correlation from the height of the plot above sea level and the amount of precipitation, in comparison with the indicator of the average diameter of the stands of the Brutia pine (P. brutia Ten.). The rank structure of the diameters of the trunks of the Brutia pine (P. brutia Ten.) has its own fundamental differences associated with the placement of growing areas above sea level. With an increase in the height above sea level of the plantation area, the number of trees with larger trunks in the plantation increases. An analysis of the asymmetry and excesses of the distribution series of diameters of trunks of the Brutia pine (P. brutia Ten.) revealed that a decrease in the competitive load in plantations of this species is associated with an increase in altitude above sea level. The most optimal conditions for the growth of the Brutia pine (P. brutia Ten.) are on the highest site relative to sea level. The limiting factor in these conditions of growth on infertile soils will be the moisture availability of the site.
Brutia pine, Pinus brutia Ten., forest stand, asymmetry, kurtosis, distribution series, average tree diameter, average tree height, growth stock
1. Alkinzh S., Danilov D. A. Sosna brutiyskaya (Pinus brutia Ten.) kak vazhnyy komponent lesov stran Vostochnogo Sredizemnomor'ya i Chernomorskogo basseyna (obzor). Izvestiya Sankt-Peterburgskoy lesotehnicheskoy akademii. 2022;240:130-148. DOI: https://doi.org/10.21266/2079-4304.2022.240.130-148.
2. Alkinzh S., Danilov D. A. Issledovanie effektivnosti nekotoryh modeley, ispol'zuemyh dlya ocenki vysoty sosen v Sirii. Aktual'nye problemy lesnogo kompleksa. 2021;60:74-78. Rezhim dostupa: https://elibrary.ru/item.asp?id=47200125.
3. Ali M. S., Lezhnin S. A., Vorob'ev O. N., Kurbanov E. A. Monitoring rastitel'nogo pokrova muhafaza Latakiya Siriyskoy Arabskoy Respubliki po snimkam Landsat. Vestnik Povolzhskogo gosudarstvennogo tehnologicheskogo univepsiteta. Seriya: Les. Ekologiya. Prirodopol'zovanie. 2020; 3(47): 19-31. DOI: https://doi.org/10.25686/2306-2827.2020.3.19.
4. Vorob'ev O. N., Ali M. S. Klassifikaciya lesnogo pokrova muhafaza Latakiya Siriyskoy Arabskoy Respubliki po dannym sputnika Sentinel-2 // Lesnye ekosistemy v usloviyah izmeneniya klimata: biologicheskaya produktivnost' i distancionnyy monitoring: sbornik nauchnyh statey. Yoshkar-Ola: PGTU, 2018; 4: 110-122. Rezhim dostupa: https://elibrary.ru/item.asp?id=37423723.
5. Olsson, S., Lorenzo, Z., Zabal-Aguirre, M. et al. Evolutionary history of the mediterranean Pinus halepensis -brutia species complex using gene-resequencing and transcriptomic approaches. Plant Mol Biol 106, 367-380 (2021). https://doi.org/10.1007/s11103-021-01155-7.
6. Ali Kavgaci, Urban Šilc, Saime BaŞaran, Aleksander MarinŠek, Mehmet Ali BaŞaran, Petra KoŠir, Neslihan Balpinar,M'nevver Arslan, Czge Denli, and Andraž Čarni. 2017. Classification of plant communities along postfire succession in Pinus brutia (Turkish red pine) stands in Antalya (Turkey). Turkish Journal of Botany 41:299-307. Available http://journals.tubitak.gov.tr/botany/issues/bot-17-41-3/bot-41-3-8-1609-34.pdf (accessed 2022.03.12).
7. Houminer N, Riov J, Moshelion M, Osem Y, David-Schwartz R. Comparison of Morphological and Physiological Traits between Pinus brutia, Pinus halepensis, and Their Vigorous F1 Hybrids. Forests. 2022; 13(9):1477. https://doi.org/10.3390/f13091477.
8. Houminer, N.; Houminer, N., Doron-Faigenboim, A., Shklar, G. et al. Transcriptome-based single-nucleotide polymorphism markers between Pinus brutia and Pinus halepensis and the analysis of their hybrids. Tree Genetics & Genomes 17, 14 (2021). https://doi.org/10.1007/s11295-021-01496-w.
9. Keten İ., Gülsoy. S Research on site index in the red pine (Pinus brutia Ten.) forests. Bilge International Journal of Science and Technology Research. 2020: 4, 2: 88-102. DOI: https://doi.org/10.30516/bilgesci.740067.
10. Catal Y., Carus S. A 2018 height-diameter model for Brutian pine (Pinus brutia Ten.) plantations in Southwestern Turkey. Applied Ecology and Environmental Research. 16 (2): 1445-1459. DOI: https://doi.org/10.15666/aeer/1602_14451459
11. Abdo HG, Almohamad H, Al Dughairi AA, Al-Mutiry M. GIS-based frequency ratio and analytic hierarchy process for forest fire susceptibility mapping in the Western region of Syria. Sustainability. 2022; 14(8):4668. https://doi.org/10.3390/su14084668.
12. Sakici, O.E., Kucuk, O. & Ashraf, M.I. Compatible above-ground biomass equations and carbon stock estimation for small diameter Turkish pine (Pinus brutia Ten.). Environ Monit Assess 190, 285 (2018). https://doi.org/10.1007/s10661-018-6656-9.
13. Ozbey Alper, Bilir Nebi. Block effect on genetic parameters in a 23-year-old progeny trial of Pinus brutia. Forestry engineering journal. 2022; 12 (2): 5-13. DOI: https://doi.org/10.34220/issn.2222-7962/2022.2/1.
14. Çatal Y., Carus S., 2018. A height-diameter model for brutian pine (Pinus brutia Ten.) plantations in southwestern Turkey. Applied Ecology and Environmental Research 16(2): 1445-1459. https://doi.org/10.15666/aeer/1602_14451459.
15. Sakici, Oytun Emre et al. “Compatible above-ground biomass equations and carbon stock estimation for small diameter Turkish pine (Pinus brutia Ten.).” Environmental Monitoring and Assessment 190 (2018): 1-10. DOI: https://doi.org/10.1007/s10661-018-6656-9.
16. Baysal, Ismail. “Vertical Crown Fuel Distributions in Natural Calabrian Pine (Pinus brutia Ten.) Stands.” Croatian Journal of Forest Engineering 42 (2021): 301-312. DOI: https://doi.org/10.5552/CROJFE.2021.800.
17. Yurtgan M, Baysal I, Küçük O (2022). Fuel characterization and crown fuel load prediction in non-treated Calabrian pine (Pinus brutia Ten.) plantation areas. iForest 15: 458-464. - DOI: https://doi.org/10.3832/ifor4048-015.
18. Bilgili E, Coskuner KA, Usta Y, Saglam B, Kucuk O, Berber T, Goltas M (2019). Diurnal surface fuel moisture prediction model for Calabrian pine stands in Turkey. iForest 12: 262-271. DOI: https://doi.org/10.3832/ifor2870-012.
19. Chernyh, L. V. Aprobaciya metodiki lesovodstvenno-statisticheskogo obosnovaniya sposobov i ob'emov lesovosstanovleniya na lesnom uchastke / L. V. Chernyh, D. V. Chernyh, V. L. Chernyh // Vestnik Povolzhskogo gosudarstvennogo tehnologicheskogo universiteta. Seriya: Les. Ekologiya. Prirodopol'zovanie. - 2021. - № 1(49). - S. 64-81. - DOI: https://doi.org/10.25686/2306-2827.2021.1.64.
20. Alkinzh S., Danilov D. A. Assessment of the growing stock and annual increment of Pinus brutia Ten. stands in Kfardebel, Latakia, Syria // IOP Conference Series: Earth and Environmental Science. 2021; 876: 012004. DOI: https://doi.org/10.1088/1755-1315/876/1/012004.
21. Hung, Bui Manh. “Tree-Size Variable Frequency Distribution Modeling for Tropical Forests in Ba Be, Vietnam.” Biology Bulletin 49 (2022): S135 - S147. DOI: https://doi.org/10.1134/S1062359022140072.
22. Nautiyal R., Tiwari N., Chandra G., Kershaw J., Shaktan T. Alternate ranked set sampling for skewed and mound shaped symmetric distributions: accounting for forestry and environmental research. Mathematical and Computational Forestry and Natural-Resource Sciences. 2021; 13:14-26. DOI: http://www.scopus.com/inward/record.url?eid=2-s2.0-85125084782&partnerID=MN8TOARS
23. Chandra, Girish & Nautiyal, Raman & Chandra, Hukum & Roychoudhury, Nilanjan & Mohammad, Naseer. (2020). Statistical Methods and Applications in Forestry and Environmental Sciences Springer https://doi.org/10.1007/978-981-15-1476-0.
24. Menéndez-Miguélez, María et al. “Improving tree biomass models through crown ratio patterns and incomplete data sources. European Journal of Forest Research. 140 (2021): 675 - 689. DOI: https://doi.org/10.1007/s10342-021-01354-3.
25. Leverett R.T., Ruskin D.N., Masino S.A. Direct Measurement of Trunk Volume in Forest Trees: Focus on White Pine and Comparison to a Statistical Method. bioRxiv. 2020.03.18.995985; DOI: https://doi.org/10.1101/2020.03.18.995985.
26. Hong, S., Lynn, H.S. Accuracy of random-forest-based imputation of missing data in the presence of non-normality, non-linearity, and interaction. BMC Med Res Methodol 20, 199 (2020). https://doi.org/10.1186/s12874-020-01080-1.
27. Petrin, R. D. Indeksy skorosti rosta i koefficienty tipa rosta po vysote listvennyh lesnyh nasazhdeniy / R. D. Petrin // Lesotehnicheskiy zhurnal. - 2022. - T. 12, № 4(48). - S. 47-59. - DOI: https://doi.org/10.34220/issn.2222-7962/2022.4/4.
28. Taksacionnye pokazateli i tovarnaya struktura spelyh smeshannyh drevostoev sosny i eli v zelenomoshnyh tipah lesa / D. A. Danilov, N. V. Belyaeva, D. A. Zaycev, I. M. Anisimova // Lesotehnicheskiy zhurnal. - 2022. - T. 12, № 2(46). - S. 14-29. - DOI: https://doi.org/10.34220/issn.2222-7962/2022.2/2.
29. Smołalski, G. (2020). Identifying the asymmetry of finite support probability distributions on the basis of the first two moments. Measurement, 149, 106968. DOI: https://doi.org/10.1016/J.MEASUREMENT.2019.106968.
30. Svyaz' absolyutno suhoy fitomassy frakciy derev'ev Alnus incana (L.) Moench s taksacionnym diametrom v Severo-taezhnom rayone Arhangel'skoy oblasti / S. V. Tret'yakov, S. V. Koptev, I. V. Cvetkov [i dr.] // Lesotehnicheskiy zhurnal. 2022; 12 (47): 62-78. DOI: https://doi.org/10.34220/issn.2222-7962/2022.3/6.
31. Frontier technique of creating protective forests stands around nurseries on inefficient sites: technological foundations / A. Novikov, V. Ivetich, S. Nikulin [et al.] // Forestry Engineering Journal. - 2022. - Vol. 12, No. 2(46). - P. 115-125. - DOI: https://doi.org/10.34220/issn.2222-7962/2022.2/10.
