Adaptation of forest ecosystems to the humidity factor in the Middle Urals

N.S. Ivanova ^a*, E.S. Zolotova ^b**

^aBotanical Garden, Ural Branch, Russian Academy of Sciences, Yekaterinburg, 620144 Russia

^bZavaritsky Institute of Geology and Geochemistry, Ural Branch, Russian Academy of Sciences, Yekaterinburg, 620016 Russia

E-mail: ^*i.n.s@bk.ru, ^**afalinakate@gmail.com

Received January 19, 2019

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DOI: 10.26907/2542-064X.2019.2.293-306

Abstract

For nominally indigenous forests of the Trans-Urals hilly piedmont province of the Middle Urals, the species composition and productivity of the lower layers – as an adaptation to different humidity regimes – were studied. The research is based on three forest types (by the principles of genetic typology): cowberry pine forest, grass pine forest, and dwarf shrub-sphagnum pine forest. The investigated plots constitute a generalized topoecological profile. In the lower layers of the studied pine forests, the species composition differs considerably. The species richness differs significantly between the extreme (periodically dry and permanently humid) and optimal (fresh, periodically humid) habitats. The humidity factor is important. The productivity of the lower layers is stable regardless of the humidification conditions. This indicates that ecosystems have a higher adaptive capacity than individual plant species. To study the mechanisms by which the productivity is maintained, we constructed the rank distributions of the above-ground phytomass of grass species in the all three types of pine forests. We found that a statistically significant increase takes place in the β parameter of the exponential approximating function when the soil humidity decreases as the productivity level of the grass-dwarf shrub layer is maintained.

Keywords: forest type, adaptation of forest ecosystems, nominally indigenous forest, biodiversity, humidity factor, environmental factors, Middle Urals

Acknowledgments. The study was performed as part of the state assignment for the Botanical Garden, Ural Branch, Russian Academy of Sciences, as well as within the framework of the state assignment for the Zavaritsky Institute of Geology and Geochemistry, Ural Branch, Russian Academy of Sciences (state regist. no. AAAA-A18-118052590028-9).

Figure Captions

Fig.1. The species richness of the grass-dwarf shrub layer (per 1 m²) of three forest types in the Trans-Urals hilly piedmont province of the Middle Urals: mean value and 95% interval, results of the analysis of variance: F(2.27) = 119.96, p = 0.0000. Designations: S br. – cowberry pine forest, S rtr. – grass pine forest; S ks.sf. – dwarf shrub-sphagnum pine forest.

Fig. 2. The above-ground phytomass (in absolutely dry condition, g/m²) of the grass-dwarf shrub layer in three forest types in the Trans-Urals hilly piedmont province of the Middle Urals: mean value and 95% interval, results of the analysis of variance: F(2.27) = 0.97893, p = 0.38866. See Fig. 1 for designations.

Fig. 3. The values of the β parameter (degree value) of the approximating power function for the studied  forest types: mean value and 95% interval, results of the analysis of variance: F(2.21) = 5.9077, p = 0.00921. See Fig. 1 for designations.

Fig. 4. The values of the β parameter (degree value) of the approximating exponential function for the studied forest types: mean value and 95% interval, results of the analysis of variance: F(2.21) = 30.449, p = 0.00000. See Fig. 1 for designations.

References

1. Global Biodiversity Outlook 2. Montreal, Secr. Conv. Biol. Diversity. 2006. Available at: https://www.cbd.int/doc/gbo/gbo2/cbd-gbo2-en.pdf.

2. Maiti R., Rodriguez H.G., Ivanova N.S. Autoecology and Ecophysiology of Woody Shrubs and Trees: Concepts and Applications. John Wiley & Sons, 2016. 352 p.

3. Safina G.R., Golosov V.N. The effect of climate change on the annual flow distribution of small rivers in the southern half of the European territory of Russia. Uchenye Zapiski Kazanskogo Universiteta. Seriya Estestvennye Nauki, 2018, vol. 160, no. 1, pp. 111–125. (In Russian)

4. Battisti D.S., Naylor R.L. Historical warnings of future food insecurity with unprecedented seasonal heat. Science, 2009, vol. 323, no. 5911, pp. 240–244. doi: 10.1126/science.1164363.

5. Maiti R., Rodriguez H.G. Kumari Ch.A. Applied Biology of Woody Plants. Am. Acad. Press, 2016. 367 p.

6. Kellomäki S. Managing Boreal Forests in the Context of Climate Change: Impacts, Adaptation and Climate Change Mitigation. CRC Press, 2016, 365 p. doi: 10.1201/9781315166063.

7. Schaphoffa S., Reyera Ch.P.O., Schepaschenko D., Gertena D., Shvidenko A. Tamm Review: Observed and projected climate change impacts on Russia's forests and its carbon balance. For. Ecol. Manage., 2016, vol. 361, no 1, pp. 432–444. doi: 10.1016/j.foreco.2015.11.043.

8. Murray D.L., Peers M.J.L., Majchrzak Y.N., Wehtje M., Ferreira C., Pickles R.S.A. Continental divide: Predicting climate-mediated fragmentation and biodiversity loss in the boreal forest. PLoS ONE, 2017, vol. 12, no. 5, art. e0176706, pp. 1–20. doi: 10.1371/journal.pone.0176706.

9. Haunschild R., Bornmann L., Marx W. Climate change research in view of bibliometrics. PLoS ONE, 2016, vol. 11, no. 7, art. e0160393. doi: 10.1371/journal.pone.0160393.

10. Fedulov Yu.P., Kotlyarov V.V., Dotsenko K.A. Ustoichivost' rastenii k neblagopriyatnym faktoram sredy [Resistance of Plants to Adverse Environmental Factors]. Krasnodar, KubGAU, 2015. 64 p. (In Russian)

11. Maiti R. Essence of plants or crops for adaptation: Learning lessons for sustainable use. In: Bioresource and Stress Management. Maiti R.K. et al. (Eds.). Springer, 2016, pp. 165–177. doi: 10.1007/978-981-10-0995-2_10.

12. Pridacha V.B. 2002. The ratio of N: P: K as a homeostatic indicator of the functional state of plants in various environmental conditions. Extended Abstract of Cand. Biol. Sci. Diss. Petrozavodsk, 2002. 24 p. (In Russian)

13. Gorbunova V.D. Analysis of macroelements content in the leaves of white birch trees and soils along the high gradient in the South Urals. Izv. OGAU, 2012, no. 6, pp. 193–196. (In Russian)

14. Khabarova E.P., Feklistov P.A., Kosheleva A.E. Contents of mineral elements in the dying off needles of Scots pine on drained areas. Lesn. Vestn., 2015, vol. 19, no. 2, pp. 15–20. (In Russian)

15. Rakhmankulova Z.F. The ratio of photosynthesis and respiration as an energy basis for plant adaptation to adverse environmental conditions. Doct. Biol. Sci. Diss. Moscow, 2002. 317 p. (In Russian)

16. Ponomarev A.G., Tatarinova T.D., Alekseev V.A., Perk A.A., Bubyakina V.V. Physiological and biochemical characteristics of Betula platyphylla in connection with the growth conditions on permafrost grounds. Lesn. Vestn.no 2, pp. 12–15. (In Russian)

17. Aganina U.E. Tarkhanov S.N. Variability of biochemical indicators and adaptation of f. (var.) sulfu­ranthera Kozubow forms of the pine (Pinus Sylvestris L.) in the conditions of excess humidification. Izv. Samar. Nauchn. Tsentra Ross. Akad. Nauk vol. 18, no. 1, pp. 10–14. (In Russian)

18. Ghannoum O., Way D.A. On the role of ecological adaptation and geographic distribution in the response of trees to climate change. Tree Physiol., 2011, vol. 31, no 12, pp. 1273–1276.

19. Hänninen H. Climatic adaptation of boreal and temperate tree species. In: Boreal and Temperate Trees in a Changing Climate. Biometeorology. Springer, 2016, pp. 1–13. doi:10.1007/978-94-017-7549-6_1.

20. Eilmann B., Zweifel R., Buchmann N., Fonti P., Rigling A. Drought-induced adaptation of the xylem in Scots pine and pubescent oak. Tree Physiol., 2009, vol. 29, no. 8, pp. 1011–1020. doi: .

21. Guerin G.R., Lowe A.J. Multi-species distribution modelling highlights the Adelaide Geosyncline, 38, no. 4, pp. 427–435. doi: 10.1111/j.1442-9993.2012.02425.x.

22. Bazhenov A.V., Shavnin S.A. Assessment of damage to photosynthesis from aerotechnogenic emissions in Scots pine. Ekologiya no 4, pp. 89–91.

23. Vasfilov S.P. Possible ways of negative influence of acid gases on plants. Zh. Obshch. Biol., 2003, vol. 64, no. 2, pp. 146–159. (In Russian)

24. Bukharina I.L., Dvoeglazova T.M. Bioekologicheskie osobennosti travyanistykh i drevesnykh rastenii v gorodskikh nasazhdeniyakh [Bioecological Features of Herbaceous and Woody Plants in Urban Plantations]. Izhevsk, Izd. Udmurt. Univ., 2010. 184 p. (In Russian)

25. Sukhareva T.A. (In Russian)

26. Mumba M., Kutegeka S., Nakangu B., Munang R., Sebukeera C. Ecosystem-based Adaptation (EbA) of African mountain ecosystems: Experiences from Mount Elgon, Uganda. Climate Change Adaptation Strategies. – An Upstream-downstream Perspective. Springer, 2016, pp. 121–140. doi: 10.1007/978-3-319-40773-9_7.

27. Humphreys L.R. Plant interrelations: Competition and interference. Environmental Adaptation of Tropical Pasture Plants. London, Palgrave, 1981, pp. 185–210. doi: 10.1007/978-1-349-04719-2_9.

28. Maiti R, Rodriguez H.G. Mystry of coexistence and adaptation of trees in a forest ecosystem. For. Res., 2015, vol. 4, no. 4, art. 1000e120, pp. 1–2. doi:10.4172/2168-9776.1000e120.

29. Werners S.E., Szalai S., Zingstra H., Kőpataki É., Beckmann A., Bos E., Civic K., Hlásny T., Hulea O., Jurek M., Koch H., Kondor A.C., Kovbasko A., Lakatos M., Lambert S., Peters R., Trombik J., van de Velde I., Zsuffa I. Climate change adaptation in the Carpathian mountain region. In: Climate Change Adaptation Strategies – An Upstream-Downstream Perspective. Springer, Cham, 2016, pp. 79–99. doi: 10.1007/978-3-319-40773-9_5.

30. Kolesnikov B.P., Zubareva R.S., Smolonogov E.P. Lesorastitel'nye usloviya i tipy lesov Sverdlovsloi oblasti. Prakticheskoe rukovodstvo [Forest Growing Conditions and Types of Forests in Sverdlovsk Region. A Practical Guide]. Sverdlovsk, UNTs Akad. Nauk SSSR, 1973. 176 p. (In Russian)

31. Anuchin N.P. Lesnaya taksatsiya [Forest Taxation]. Moscow, Lesn. Prom., 1982. 552 p.

32. Metody izucheniya lesnykh soobshchestv [Methods of Studying Forest Communities]. Yarmishko V.T., Lianguzova I.V. (Eds.). St. Petersburg, NII Khim. SpbGU, 2002. 240 p. (In Russian)

33. Khalafyan A.A. STATISTICA 6. Statisticheskii analiz dannykh [STATISTICA 6. Statistical Analysis of Data]. Moscow, Binom-Press, 2010. 528 p.

34. Kudrin B.I. Mathematics of coenoses: Species, rank-type, rank-by-parameter hyperbolic H-distributions and the laws of Lotka, Tsipfa, Pareto, Mandelbrot. Matematicheskii apparat strukturnogo opisaniya tsenozov i giperbolicheskie N-ogranicheniya. Tsenologicheskie issledovaniya [Mathematical Tool for Structural Des­cription of Coenoses and Hyperbolic H-Constraints. Coenological Studies]. Moscow, Tsentr Sist. Issled., 2002, no. 19, pp. 357–412. (In Russian)

35. Puzachenko Yu.G. Rank distributions in ecology and nonextensive statistical mechanics. Sb. Tr. Zool. Muz. MGU, 2016, vol. 54, pp. 42–71. (In Russian)

36. Whittaker R. Communities and Ecosystems. Macmillan, 1975. 385 p. (In Russian)

37. Yablonskii A.I. Matematicheskie modeli v issledovanii nauki [Mathematical Models in the Study of Science]. Moskow, Nauka, 1986. 352 p. (In Russian)

38. Shitikov V.K., Zinchenko T.D., Rozenberg G.S. Makroekologiya rechnykh soobshchestv: kontseptsii, metody, modeli [Macroecology of River Communities: Concepts, Methods, and Models]. Togliatti, Cassandra, 2011. 255 p. (In Russian)

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