Voronezh, Russian Federation
Voronezh, Voronezh, Russian Federation
Voronezh, Russian Federation
Voronezh, Russian Federation
UDK 630 Лесное хозяйство. Лесоводство
Most often, restoration of forest landscapes in the Russian Federation is carried out on the lands of the first group (forest lands not covered with forest), less often – the second group (non-forest lands of the forest fund). Afforestation of the lands of the third group – lands that currently do not belong to the forest fund, but after carrying out measures to plant forests and successfully implement them, in the future with prospects for transition to the lands of the forest fund – occurs locally. We analyzed standard projects on afforestation and reforestation, studied normative legal acts (Rules of afforestation, Rules of reforestation), local orders and resolutions in the field of afforestation, tax descriptions of forest taxing allotments, scientific works and recommendations of domestic and foreign authors in the field of reforestation and afforestation, on the design of technologies for afforestation and reforestation, the influence of soils on the choice of machines, mechanisms and technologies of afforestation. Based on the analysis, the classification of forest lands was clarified for the selection of adaptive restoration technology. We found some contradictions in the classification of soil types, which have a direct impact on the choice of technology and technical means, confirming the relevance of creating a unified classification convenient for the development of reforestation or afforestation projects. A statistical assessment of the degree of influence of the physical and mechanical properties of the soil, as well as the degree of dependence of the choice of technical means and the degree of controllability of soil properties (1 - weak, 2 – moderate, 3 – strong) in the decision–making process on the choice of technology for adaptive restoration of forest landscapes was carried out using hierarchical clustering by the method of J. Ward Jr. using the Minkowski measure, which is sufficiently resistant to emissions, at the significance level α = 0.05. Taking into account the analyzed input parameters, a basic algorithm for the functioning of the FLR system was formed, on the basis of which software will be developed to support management decision-making in the implementation of projects for adaptive restoration of forest landscapes.
forest landscape restoration technologies, adaptive reforestation, algorithm, reference system, technical means, machines and mechanisms
1. Novikova, T. P. Razrabotka spravochnoy informacionnoy sistemy dlya adaptivnogo vosstanovleniya lesnyh landshaftov (FLR-library) // NIR: grant № 23-26-00102. Rossiyskiy nauchnyy fond. 2023. https://www.elibrary.ru/item.asp?id=53916036
2. Novikova, T. P. The choice of a set of operations for forest landscape restoration technology / T. P. Novikova // Inventions. – 2022. – Vol. 7, No. 1. – DOI: https://doi.org/10.3390/inventions7010001.
3. Novikova, T. P. Ocenka kachestva lesosemennogo materiala na eksperimental'nom uchastke sosny obyknovennoy (Pinus sylvestris L.) pri adaptivnom vosstanovlenii lesnyh landshaftov / T. P. Novikova // Lesotehnicheskiy zhurnal. – 2023. – T. 13, № 1(49). – S. 112-128. – DOIhttps://doi.org/10.34220/issn.2222-7962/2023.1/8. URL: https://www.elibrary.ru/rvwowr.
4. Novikova, T. P. Spravochnaya informacionnaya sistema FLR-Library dlya adaptivnogo lesovosstanovleniya: klasternyy analiz deskriptorov / T. P. Novikova, A. I. Novikov, E. P. Petrischev // Lesotehnicheskiy zhurnal. – 2023. – T. 13, № 3(51). – S. 164-179. – DOIhttps://doi.org/10.34220/issn.2222-7962/2023.3/12. URL: https://www.elibrary.ru/uzokyx.
5. Novikova, T. P. Vliyanie izmeneniya klimata na upravlenie lesovosstanovleniem / T. P. Novikova, T. V. Novikova, A. I. Novikov // Nauka i innovacii v sovremennom mire : Materialy Nacional'noy nauchno-prakticheskoy konferencii, Voronezh, 22 yanvarya 2024 goda. – Voronezh: Voronezhskiy gosudarstvennyy lesotehnicheskiy universitet im. G.F. Morozova, 2024. – S. 53-58. – DOIhttps://doi.org/10.58168/SIMW2024_53-58. URL: https://www.elibrary.ru/kokewa.
6. Hanina, L.G. Klassifikaciya tipov lesorastitel'nyh usloviy po indikatornym vidam Vorob'eva-Pogrebnyaka: baza dannyh i opyt analiza lesotaksacionnyh dannyh // Voprosy lesnoy nauki, № 4. – 2019. DOIhttps://doi.org/10.31509/2658-607x-2019-2-4-1-28. URL: https://www.elibrary.ru/wymkha.
7. Ekspress-analiz semyan v lesohozyaystvennom proizvodstve: teoreticheskie i tehnologicheskie aspekty / M. V. Drapalyuk [i dr.]. – Voronezh, 2022. – 176 s. URL: https://www.elibrary.ru/item.asp?id=48309574.
8. Vliyanie individual'noy massy semyan sosny obyknovennoy (Pinus sylvestris L.) sorta «Negorel'skaya» na 30-dnevnoe prorastanie v 40-yacheistyh SideSlit-konteynerah / S.V. Rebko [i dr.] // Lesotehnicheskiy zhurnal. – 2023. – Vol. 13. – № 2 (50). – P. 59-86. – DOI: https://doi.org/10.34220/issn.2222-7962/2023.2/4.
9. Razrabotka algoritma i modeli funkcionirovaniya informacionnoy sistemy dlya malogo sel'skohozyaystvennogo predpriyatiya / T. V. Novikova [i dr.] // Modelirovanie sistem i processov. – 2020. – T. 13, № 4. S. 53-58. – DOIhttps://doi.org/10.12737/2219-0767-2021-13-4-53-58. – URL: https://www.elibrary.ru/qdcyjv.
10. Novikov, A.I. The effect of seed coat color grading on height of one-year-old container-grown Scots pine seedlings planted on post-fire site / A. I. Novikov, V. Ivetic // IOP Conference Series: Earth and Environmental Science. 2019. – Vol. 226, – Article 012043. – DOIhttps://doi.org/10.1088/1755-1315/226/1/012043. – EDN XOPMBD.
11. Jančo, M., Danko, M., Sleziak, P., Holko, L. Estimation of the leaf area index in a decline spruce forest in the Western Tatra Mountains for determination of rainfall interception // Acta Hydrologica Slovaca, 2024; 25 (1): 106-114. DOI: https://doi.org/10.31577/ahs-2024-0025.01.0012.
12. Carbon emissions from selective logging in the southern Yucatan Peninsula, Mexico / S. Armenta-Montero, E.A. Ellis, P.W. Ellis et al. // Madera y Bosques. – 2020. – Vol. 26. – № 1. – DOI: https://doi.org/10.21829/myb.2020.2611891.
13. Elias, B.C.H. The application of gap planting technology to rehabilitate degraded natural forest / Elias, B.C.H. Simangunsong // IOP Conference Series: Earth and Environmental Science. – 2023. – Vol. 1220. – № 1. – P. 012029. – DOI: https://doi.org/10.1088/1755-1315/1220/1/012029.
14. Patent 2714705 Rossiyskaya Federaciya, MPK A 01 G 23/00. Sposob vosstanovleniya lesa / Zayavitel' i patentoobladatel' Voronezh. gos. lesotehn. un-t. – № 2019115418 ; zayavl. 20.05.2019 ; opubl. 19.02.2020, Byul. №5. Rezhim dostupa: https://elibrary.ru/gzdlvj.
15. Tendencii razvitiya operacionnoy tehnologii aeroseva bespilotnymi letatel'nymi apparatami v lesovosstanovitel'nom proizvodstve / S.V. Sokolov [i dr.] // Lesotehnicheskiy zhurnal. – 2017. – T. 7. – № 4. – S. 190-205. – DOI: https://doi.org/10.12737/article_5a3d040dc79c79.94513194.
16. Novikov, A.I. Aerial seeding of forests in Russia: A selected literature analysis / A.I. Novikov, B.T. Ersson // IOP Conference Series: Earth and Environmental Science. – 2019. – Vol. 226. – № 1. – Article 012051. – DOI: https://doi.org/10.1088/1755-1315/226/1/012051.
17. UAV-Supported Forest Regeneration: Current Trends, Challenges and Implications / M. Mohan, G. Richardson, G. Gopan et al. // Remote Sensing. – 2021. – Vol. 13. – № 13. – Art. 2596. – DOI: https://doi.org/10.3390/rs13132596.
18. Novye optoelektronnye sistemy ekspress-analiza semyan v lesohozyaystvennom proizvodstve / S. V. Sokolov [i dr.] // Lesotehnicheskiy zhurnal. 2019; 9 (2): 5-13. DOI: https://doi.org/10.34220/issn.2222-7962/2019.2/1. URL: https://www.elibrary.ru/CNXAWZ.
19. Performance of Scots pine seedlings from seeds graded by colour / V. A. Zelikov [et al.] // Forests. 2019; 10 (12): 1064. DOIhttps://doi.org/10.3390/F10121064.
20. How to Increase the Analog-to-Digital Converter Speed in Optoelectronic Systems of the Seed Quality Rapid Analyzer / S. V. Sokolov, V. V. Kamensky [et al.] // Inventions. – 2019. – Vol. 4, No. 4. – P. 61. – DOI https://doi.org/10.3390/inventions4040061. URL: https://elibrary.ru/dkxphx.
21. The Effect of Motion Time of a Scots Pine Single Seed on Mobile Optoelectronic Grader Efficiency: A Mathematical Patterning / M.V. Drapalyuk, O.R. Dornyak [et al.] // Inventions. – 2019. – Vol. 4. – № 4. – P. 55. – DOI: https://doi.org/10.3390/inventions4040055.
22. Analiz operacionnyh mehanizirovannyh tehnologiy separacii semyan pri iskusstvennom lesovosstanovlenii / M. V. Drapalyuk [i dr.] // Lesotehnicheskiy zhurnal. – 2018. – T. 8, № 4(32). – S. 207-220. – DOIhttps://doi.org/10.12737/article_5c1a3237290288.22345283. – EDN AKVBNM.
23. Mechanization of coniferous seeds grading in Russia: a selected literature analysis / B.T. Ersson, V.V. Malyshev et al. // IOP Conference Series: Earth and Environmental Science. – 2020. – Vol. 595. – P. 012060. – DOI: https://doi.org/10.1088/1755-1315/595/1/012060.
24. Detection of Scots pine single seed in optoelectronic system of mobile grader: mathematical modeling / M. Tigabu [et al.] // Forests. – 2021. – Vol. 12. – № 2. – P. 240. – DOI: https://doi.org/10.3390/f12020240.
25. Deep-Learning Approach for Fusarium Head Blight Detection in Wheat Seeds Using Low-Cost Imaging Technology / R.C. Bernardes, A. De Medeiros, L. da Silva et al. // Agriculture. – 2022. – Vol. 12. – № 11. – P. 1801. – DOI: https://doi.org/10.3390/agriculture12111801.
26. How Can the Engineering Parameters of the NIR Grader Affect the Efficiency of Seed Grading? / P. Tylek et al. // Agriculture. – 2022. – Vol. 12. – № 12. – P. 2125. – DOI: https://doi.org/10.3390/agriculture12122125.
27. The Root Collar Diameter Growth Reveals a Strong Relationship with the Height Growth of Juvenile Scots Pine Trees from Seeds Differentiated by Spectrometric Feature / P. Tylek, C.B. Mastrangelo et al. // Forests. – 2023. – Vol. 14. – № 6. – P. 1164. – DOI: https://doi.org/10.3390/f14061164.
28. Scots pine seedlings growth dynamics data reveals properties for the future proof of seed coat color grading conjecture / V. Ivetić [et al.] // Data. – 2019. – Vol. 4, No. 3. – P. 106. – DOIhttps://doi.org/10.3390/data4030106. – URL: https://www.elibrary.ru/PAJOVZ.
29. The role of forest reproductive material quality in forest restoration / V. Ivetić [et al.] // Forestry Engineering Journal. – 2019. – Vol. 9. – № 2. – P. 56-65. – DOI: https://doi.org/10.34220/issn.2222-7962/2019.2/7.
30. Novikov, A. I. Sovershenstvovanie tehnologii polucheniya vysokokachestvennogo lesosemennogo materiala : 05.21.01 : avtoref. dis. … d-ra tehn. nauk. – Voronezh, 2021. – 32 s. – URL: https://www.elibrary.ru/qgemiu.
31. Priyatkin, N. S. Neinvazivnaya ekspress-ocenka raznokachestvennosti i hozyaystvennoy prigodnosti semennogo materiala na osnove ispol'zovaniya instrumental'nyh fizicheskih metodov : dis. … d-ra biol. nauk. – SPb, 2024. – 253 s. – URL: https://www.elibrary.ru/aseotz.
32. Coat Colour Grading of the Scots Pine Seeds Collected from Faraway Provenances Reveals a Different Germination Effect / I. V. Bacherikov, D. E. Raupova, A. S. Durova [et al.] // Seeds. – 2022. – Vol. 1, No. 1. – P. 49-73. – DOIhttps://doi.org/10.3390/seeds1010006. – EDN JRLACA.
33. Adaptive measures: integrating adaptive forest management and forest landscape restoration / P. Spathelf, J. Stanturf, M. Kleine et al. // Annals of Forest Science. – 2018. – Vol. 75. – № 2. – P. 55. – DOI: https://doi.org/10.1007/s13595-018-0736-4.
34. Climate warming-induced replacement of mesic beech by thermophilic oak forests will reduce the carbon storage potential in aboveground biomass and soil / J. Kasper, R. Weigel, H. Walentowski et al. // Annals of Forest Science. – 2021. – Vol. 78. – № 4. – P. 89. – DOI: https://doi.org/10.1007/s13595-021-01081-0.
35. Adaptive silviculture for climate change in the Great Lakes- St. Lawrence Forest Region of Canada: Background and design of a long-term experiment / N. Thiffault, J. Fera, M.K. Hoepting et al. // The Forestry Chronicle. – 2024. – Vol. 100. – № 2. – P. 155-164. – DOI: https://doi.org/10.5558/tfc2024-016.
36. Roitberg, B. Tree adaptive growth (TAG) model: a life-history theory-based analytical model for post-thinning forest stand dynamics / B. Roitberg, C. Li, R. Lalonde // Frontiers in Plant Science. – 2024. – T. 15. – № February. – S. 1-14. – DOI: https://doi.org/10.3389/fpls.2024.1344883.
37. Pardos, M. Adaptive Strategies of Seedlings of Four Mediterranean Co-Occurring Tree Species in Response to Light and Moderate Drought: A Nursery Approach / M. Pardos, R. Calama // Forests. – 2022. – Vol. 13. – № 2. – P. 154. – DOI: https://doi.org/10.3390/f13020154.
38. Opportunities and limitations of thinning to increase resistance and resilience of trees and forests to global change / G. Moreau, C. Chagnon, A. Achim et al. // Forestry: An International Journal of Forest Research. – 2022. – № 95. – P. 595-615. – DOI: https://doi.org/10.1093/forestry/cpac010.
39. Prokhorova, N. To the question of improving the methods of adaptive forest management / N. Prokhorova, Z. Govedar // Forestry Engineering Journal. – 2021. – Vol. 11. – № 2. – P. 59-68. – DOI: https://doi.org/10.34220/issn.2222-7962/2021.2/6.
40. Multi-actor perspectives on afforestation and reforestation strategies in Central Europe under climate change / R. Hazarika, A. Bolte, D. Bednarova et al. // Annals of Forest Science. – 2021. – Vol. 78. – № 3. – P. 60. – DOI: https://doi.org/10.1007/s13595-021-01044-5.
41. Forest adaptation and restoration under global change / A. Bolte, S. Mansourian, P. Madsen i dr. // Annals of Forest Science. – 2023. – T. 80. – № 1. – S. 6-9. – DOI: https://doi.org/10.1186/s13595-022-01172-6. – Rezhim dostupa: https://doi.org/10.1186/s13595-022-01172-6.
42. Desired REgeneration through Assisted Migration (DREAM): Implementing a research framework for climate-adaptive silviculture / A.A. Royo, P. Raymond, C.C. Kern et al. // Forest Ecology and Management. – 2023. – Vol. 546. – № October. – P. 121298. – DOI: https://doi.org/10.1016/j.foreco.2023.121298.
43. Peterson St-Laurent, G., Hagerman, S. & Kozak, R. What risks matter? Public views about assisted migration and other climate-adaptive reforestation strategies. Climatic Change 151, Pp. 573–587, (2018). https://doi.org/10.1007/s10584-018-2310-3.
44. Muller, J.J. Forest adaptation strategies aimed at climate change: Assessing the performance of future climate-adapted tree species in a northern Minnesota pine ecosystem / J.J. Muller, L.M. Nagel, B.J. Palik // Forest Ecology and Management. – 2019. – Vol. 451. – P. 117539. – DOI: https://doi.org/10.1016/j.foreco.2019.117539.
45. Rekomendacii po proektirovaniyu i tehnologiyam lesorazvedeniya v zaschitnyh lesah malolesnoy zony evropeyskoy chasti Rossii pri oblesenii peskov i ovrazhno-balochnyh sklonov : Metodicheskie rekomendacii / N. E. Prokazin, S. A. Rodin, V. I. Kazakov [i dr.] ; Vserossiyskiy nauchno-issledovatel'skiy institut lesovodstva i mehanizacii lesnogo hozyaystva (FBU VNIILM). – Pushkino : Vserossiyskiy nauchno-issledovatel'skiy institut lesovodstva i mehanizacii lesnogo hozyaystva, 2021. – 68 s. – Rezhim dostupa: https://www.elibrary.ru/yraino.
46. Simulating Growth and Competition on Wet and Waterlogged Soils in a Forest Landscape Model / E.J. Gustafson, B.R. Miranda, A.Z. Shvidenko, B.R. Sturtevant // Frontiers in Ecology and Evolution. – 2020. – Vol. 8. – № December. – P. 1-19. – DOI: https://doi.org/10.3389/fevo.2020.598775.
47. Revisiting the Functional Zoning Concept under Climate Change to Expand the Portfolio of Adaptation Options / S. Royer-Tardif, J. Bauhus, F. Doyon et al. // Forests. – 2021. – Vol. 12. – № 3. – P. 273. – DOI: https://doi.org/10.3390/f12030273.
48. Monitoring and control of forest seedling quality in Europe / M. Mataruga, B. Cvjetković, B. De Cuyper et al. // Forest Ecology and Management. – 2023. – Vol. 546. – № August. – P. 121308. – DOI: https://doi.org/10.1016/j.foreco.2023.121308.