Potential Forest Distribution over the South Siberian and North Mongolian Mountains Related to Predicted Climate Change by the Midcentury
https://doi.org/10.31857/S2587556623070129
EDN: ACDUUB
Abstract
The South Siberian and North Mongolian Mountains have enormous forests potential; however, more and more territories of forests disturbed by cutting and fire appeared during the late twenty years. One more negative phenomenon has been observed in unique dark-needle forests across the South Siberian Mountains: massive dieback of dark-needled forests that was related to climate aridization by many researchers. Our goal was to study predicted climate change impacts on the montane vegetation (altitudinal vegetation belts, AVB) transformation in a changing climate across the South Siberian and North Mongolian Mountains (window 48°–58° N and 80°–120° E). We based on outputs of the general circulation model the of the Computing Mathematics Institute, RAS (INM-CM5-0) and recent climate change scenarios (IPCC 2022) at 2050: the moderate ssp126 and extreme ssp585. Predictions of climate anomalies at 2050 were July temperatures 2– 5°С, January temperature 1–4°С and annual precipitation 50–125 mm. According to this climate change, potential AVB may undergo transformation as follows: tundra, subalpine and “podgolets” open forest (under bare uplands) would significantly shrink; montane taiga would shrink 1.7-fold from the moderate scenario and 2.3-fold from the extreme scenario. Dark-needled AVB would remain on the same areas at the expense of subalpine AVB. Potential forest space including forest-tundra and forest-steppe ecotones would change insignificantly: would not change under the moderate scenario and would 10% decrease under the extreme scenario. Forest-steppe AVB would twice increase at the expense of light-needled AVB. One third of foreststeppe would favor broad-leaved forest-steppe. Steppe and semidesert would extend.
Keywords
About the Authors
E. I. ParfenovaRussian Federation
Krasnoyarsk
N. M. Tchebakova
Russian Federation
Krasnoyarsk
References
1. Antamoshkina O., Bryukhanov A., Trofimova N. Intact Forest areas in the Altai-Sayan ecoregion. Ustoichivoe Lesopol., 2016, vol. 46, no. 2, pp. 39–45. (In Russ.).
2. Bazhina E.V., Storozhev V.P., Tret’yakova I.N. Dieback of fir-siberian stone pine forests under technogenic pollution in the Kuznetsky Alatau mountains. Lesoved., 2013, no. 2, pp. 15–21. (In Russ.).
3. Booth T.H., Nix H.A., Busby J.R., Hutchinson M.F. BIOCLIM: the first species distribution modelling package, its early applications and relevance to most current MAXENT studies. Divers. Distrib., 2014, no. 20, pp. 1–9. https://doi.org/10.1111/ddi.12144
4. Elith J., Phillips S.J., Hastie T., Dudik M., Chee Y.E., Yates C.J. A statistical explanation of MaxEnt for ecologists. Divers. Distrib., 2011, no. 17, pp. 43–57.
5. Gvozdetskii N.A., Mikhailov N.I. Fizicheskaya Geografiya SSSR: Aziatskaya Chast’ [Physical Geography of the USSR: Asian Part]. Moscow: Vysshaya Shkola Publ., 1987. 448 p.
6. Hijmans R.J., Cameron S.E., Parra J.L., Jones P.G., Jarvis A. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol., 2005, no. 25, pp. 1965–1978. https://doi.org/10.1002/joc.1276
7. Huang B., Mao J., Zhao Y., Sun Y., Cao Y., Xiong Z. Similar Pattern of Potential Distribution of Pinus yunnanensis Franch and Tomicus yunnanensis Kirkendall under Climate Change in China. Forests, 2022, no. 13, art. 1379. https://doi.org/10.3390/f13091379
8. Hutchinson M.F. Interpolating mean rainfall using thin plate smoothing splines. Int. J. Geogr. Inf. Syst., 1995, no. 9, pp. 385–403.
9. Hutchinson M.F. ANUSPLIN version 4.3, 2011. Centre for Resource and Environmental Studies, Australian National University. Available at: http://fennerschool.anu.edu.au/research/products/anusplin (accessed: 05.03.2023).
10. IPCC, 2021. Summary for Policymakers. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Masson-Delmotte V., Zhai P., Pirani A., Connors S.L., Péan C., Berger S., Caud N., Chen Y., Goldfarb L., Gomis M.I., Huang M., Leitzell K., Lonnoy E., Matthews J.B.R., Maycock T.K., Waterfield T., Yelekçi O., Yu R., Zhou B., Eds. Cambridge; New York: CUP, 2021, pp. 3−32. https://doi.org/10.1017/9781009157896.001
11. Isaev A.P., Borisov B.Z., Nikiforova E.N. Bioclimatic modeling of the distribution of Scotch pine (Pinus sylvestris L.) in Yakutia. Prir. Resur. Arkt. Subarkt., 2019, vol. 24, no. 3, pp. 121–133. (In Russ.). https://doi.org/10.31242/2618-9712-2019-24-3-11
12. Kharuk V.I., Im S.T., Petrov I.A., Golyukov A.S., Ranson K.J., Yagunov M.N. Climate-induced mortality of Siberian pine and fir in the Lake Baikal Watershed, Siberia. For. Ecol. Manag., 2017, no. 384, pp. 191–199. https://doi.org/10.1016/j.foreco.2016.10.050
13. Landshaftnaya karta SSSR: Masshtab 1 : 4000000 [Landscape Map of the USSR: 1 : 4000000]. Isachenko A.G., Ed. Moscow: GUGK Publ., 1988.
14. Lesa Mongol’skoi narodnoi Respubliki: geografiya i tipologiya [Forests of Mongolian People Republic: Geography and Tipology]. Lavrenko E.M., Sokolov V.E., Eds. Moscow: Nauka Publ., 1978. 128 p.
15. Mikhailov N.I. Gory Yuzhnoi Sibiri [Mountains of the Southern Siberia]. Moscow: Geografgiz Publ., 1961. 238 p.
16. Monserud R.A., Tchebakova N.M. A Vegetation model for the Sayan Mountains, Southern Siberia. Can. J. For. Res., 1996, no. 26, pp. 1055–1068.
17. Myachkova N.A. Klimat SSSR [Climate of the USSR]. Moscow: Mosk. Univ. Publ., 1983. 192 p.
18. Nazimova D.I., Molokova N.I., Dzhanseitov K.K. Altitudinal belts and climate in the Southern Siberia mountains. Geogr. Prir. Resur., 1981, no. 2, pp. 68–78. (In Russ.).
19. Nazimova D.I., Danilina D.M., Stepanov N.V. Biodiversity of Rain-Barrier Forest Ecosystems of the Sayan Mountains. Botanica Pacifica, 2014, vol. 3, no. 1, pp. 39–47.
20. Nazimova D.I., Korotkov I.A., Cherednikova Y.S. Basic Forest altitudinal subdivisions of the forest cover in the South Siberian mountains and their diagnostic signs. In Chteniya pamyati akademika V.N. Sukacheva. V. Struktura i funktsionirovanie lesnykh biogeotsenozov Sibiri [Readings in Memory of Academician V.N. Sukachev. V. Structure and Functioning of Siberian Forest Biogeocenoses]. Moscow: Nauka Publ., 1987, pp. 30–64. (In Russ.).
21. Nazimova D.I., Ponomarev E.I., Konovalova M.E. A role of the altitudinal-belt basis and remote sensing data in the sustainable management of the mountain forests. Lesoved., 2020, no. 1, pp. 3–16. (In Russ.).
22. Olonova M.V., Gudkova P.D. Bioklimaticheskoe modelirovanie: zadaniya dlya prakticheskoi raboty i metodicheskie ukazaniya k ikh vypolneniyu [Bioclimatic Modeling: Tasks for Practical Exercises and Methodogical Instructions]. Tomsk: Izd. Tomsk. Gos. Univ., 2017. 50 p.
23. Parfenova E.I., Tchebakova N.M. Possible vegetation change in the Mountain Altai under climate warming and prognostic mapping. In Geobotanicheskoe kartografirovanie 1998–2000 gg. [Geobotanical Mapping in 1998–2000]. St. Petersburg: BIN RAN, 2000, pp. 26–31. (In Russ.).
24. Parfenova E.I., Tchebakova N.M. Bioclimatic models of primary mountain forests in Southern Siberia. Lesoved., 2009, no. 5, pp. 34–42. (In Russ.).
25. Petrenko T.Y., Korznikov K.A., Kislov D.E., Belyaeva N.G., Krestov P.V. Modeling of cold-temperate tree Pinus koraiensis (Pinaceae) distribution in the Asia-Pacific region: Climate change impact. For. Ecosyst., 2022, no. 9, art. 100015. https://doi.org/10.1016/j.fecs.2022.100015
26. Polikarpov N.P., Tchebakova N.M., Nazimova D.I. Klimat i gornye lesa Yuzhnoi Sibiri [Climate and Mountain Forests of the Southern Siberia]. Novosibirsk: Nauka Publ., 1986. 225 p.
27. Preobrazhenskii V.S., Fadeeva N.V., Mukhina L.I., Tomilov G.M. Tipy mestnosti i prirodnoe raionirovanie Buryatskoi ASSR [Terrain Types and Natural Zoning of the Buryat ASSR]. Moscow: Izd. Akad. Nauk SSSR, 1959. 218 p.
28. Saigin I.A., Bartalev S.A., Stytsenko F.V. Detection method of long-term dieback of dark needled forests of Russia on the base of remote sensing data. In Materialy 17 Vseross. otkrytoi konf. “Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa” [Proc. of the 17th all-Russia Open Conf. “Modern Problems of Earth Remote Sensing from Space”]. Moscow: IKI RAN, 2019. Available at: http://conf.rse.geosmis.ru/files/pdf/17/7902_IKI_konf2019_3(2)(1)__1.pdf (accessed: 05.03.2023). (In Russ.).
29. Samoilova G.S. Landshaftnaya karta Altae-Sayanskogo ekoregiona. Masshtab 1 : 200000 [Landscape Map of the Altai-Sayan Ecoregion. 1 : 200000]. Moscow: IGEM RAN, 2001.
30. Sandanov D.V., Dugarova A.S., Selyutina I.Yu. Species distribution modeling for the section Xerobia Bunge of the genus Oxytropis DC. on the territory of Central Asia under past and future climate change. Vestn. Tomsk. Gos. Univ. Biol., 2020, no. 52, pp. 85–104. (In Russ.). https://doi.org/10.17223/19988591/52/5
31. Spravochnik po klimatu SSSR. Vyp. 17, 20–24, ch. 1–4 [Reference Book on Climate of the USSR. Vol. 17, 20–24, Part 1–4]. Leningrad: Gidrometeoizdat, 1967–1970.
32. Tchebakova N.M., Bazhina E.V., Parfenova E.I., Senashova V.A. Erratum to: “In Search of an X Factor: A Review of Publications on the Issue of Dark-needled Forest Decline/Dieback in Northern Eurasia”. Russ. Meteorol. Hydrol., 2022, no. 47, art. 485. https://doi.org/10.3103/S1068373922060097
33. Tchebakova N.M., Blyakharchuk T.A., Parfenova E.I. Reconstruction and prediction of climate and vegetation change in the Holocene in the Altai-Sayan mountains, Central Asia. Environ. Res. Lett., 2009, no. 4, art. 045025. https://doi.org/10.1088/1748-9326/4/4/045025
34. Tchebakova N.M., Parfenova E.I. Vegetation redistribution in the lake Baikal basin by possible climate warming. Geogr. Prir. Resur., 2000, no. 1, pp. 64–68. (In Russ.).
35. Tchebakova N.M., Parfenova E.I., Korets M.A., Conard S.G. Potential change in forest types and stand heights in central Siberia in a warming climate. Environ. Res. Lett., 2006, no. 11, art. 03501. https://doi.org/10.1088/1748-9326/11/3/035016
36. Tchebakova N.M., Parfenova E.I., Bazhina E.V., Soja A.J., Groisman P.Ya, Droughts Are Not the Likely Primary Cause for Abies sibirica and Pinus sibirica Forest Dieback in the South Siberian Mountains. Forests, 2022, vol. 13, no. 8, art. 1378. https://doi.org/10.3390/f13091378
37. Tipy lesov gor Yuzhnoi Sibiri [Forest Types of the Southern Siberia Mountains]. Smagin V.N., Ed. Novosibirsk: Nauka Publ., 1980. 336 p.
38. Vlasenko V.A., Turmunkh D., Nazyn C.D., Vlasenko A.V. Modelling the niche and peculiarities of the coprobiont fungi distribution in Asia: a case study by Cyathus stercoreus. Samar. Nauch. Vestn., 2021, vol. 10, no. 3, pp. 41–46. (In Russ.). https://doi.org/10.17816/snv2021103105
39. Volodin E.M. Possible Climate Change in Russia in the 21st Century Based on the INM-CM5-0 Climate Model. Russ. Meteorol. Hydrol., 2022, no. 47, pp. 327–333. https://doi.org/10.3103/S1068373922050016
40. Voronin V.I., Sofronov A.P., Morozova T.I., Oskolkov V.A., Sukhovol’skii V.G., Kovalev A.V. The landscape-specific occurrence of bacterial diseases in dark-coniferous forests on Khamar-Daban range (southern Cisbaikaliya). Geogr. Prir. Resur., 2019, no. 4, pp. 56–65. (In Russ.). https://doi.org/10.21782/GIPR0206-1619-2019-4(56-65)
41. Zischg A.P., Frehner M., Gubelmann P., Augustin S., Brang P., Huber B. Participatory modelling of upward shifts of altitudinal vegetation belts for assessing site type transformation in Swiss forests due to climate change. Appl. Veg. Sci., 2021, no. 24, art. e12621. https://doi.org/10.1111/avsc.12621
Review
For citations:
Parfenova E.I., Tchebakova N.M. Potential Forest Distribution over the South Siberian and North Mongolian Mountains Related to Predicted Climate Change by the Midcentury. Izvestiya Rossiiskoi Akademii Nauk. Seriya Geograficheskaya. 2023;87(7):1019-1031. (In Russ.) https://doi.org/10.31857/S2587556623070129. EDN: ACDUUB