Forest stand biomass of Picea spp.: an additive model that may be related to climate and civilisational changes
DOI:
https://doi.org/10.2478/bog-2019-0029Keywords
Picea spp., biological productivity, additive model, hydrothermal indicesAbstract
Since ancient times, climate change has largely determined the fate of human civilisation, which was related mainly to changes in the structure and habitats of forest cover. In the context of current climate change, one must know the capabilities of forests to stabilise the climate by increasing biomass and carbon-depositing abilities. For this purpose, the authors compiled a database of harvest biomass (t/ha) in 900 spruce (Picea spp.) sample plots in the Eurasian area and used the methodology of multivariate regression analysis. The first attempt at modelling changes in the biomass additive component composition has been completed, according to the Trans-Eurasian hydrothermal gradients. It is found that the biomass of all components increases with the increase in the mean January temperature, regardless of mean annual precipitation. In warm zonal belts with increasing precipitation, the biomass of most of the components increases. In the process of transitioning from a warm zone to a cold one, the dependence of all biomass components upon precipitation is levelled, and at a mean January temperature of ˗30°C it becomes a weak negative trend. With an increase in temperature of 1°C in different ecoregions characterised by different values of temperature and precipitation, there is a general pattern of decrease in all biomass components. With an increase in precipitation of 100 mm in different ecoregions characterised by different values of temperature and precipitation, most of the components of biomass increase in warm zonal belts, and decrease in cold ones. The development of such models for the main forest-forming species of Eurasia will make it possible to predict changes in the productivity of the forest cover of Eurasia due to climate change.
References
Alcamo J., Moreno J.M., Nováky B., Bindi M., Corobov R., Devoy R.J.N., Giannakopoulos C., Martin E., Olesen J.E., Shvidenko A. (2007). Europe: impacts, adaptation and vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Parry M.L., Canziani O.F., Palutikof J.P., van der Linden P.J., Hanson C.E. (eds.). Climate change. Cambridge University Press, Cambridge. P. 541–580.
Anderson K.J., Allen A.P., Gillooly J.F., Brown J.H. (2006). Temperature-dependence of biomass accumulation rates during secondary succession. Ecology Letters. 9: 673-682.
Baskerville G.L. (1972). Use of logarithmic regression in the estimation of plant biomass. Canadian Journal of Forest Research. 2: 49-53.
Chetyrkin E.M. (1977). Statistical methods of forecasting. Moscow: “Statistika” Publ. 200 pp.
D’Aprile F., Tapper N., Marchetti M. (2015). Forestry under climate change. Is time a tool for sustainable forest management? Open Journal of Forestry. 5: 329-336.
DeLucia E.H., Maherali H., Carey E.V. (2000). Climate-driven changes in biomass allocation in pines. Global Change Biology. 6 (5): 587-593. DOI: https://doi.org/10.1046/j.1365-2486.2000.00338.x
Dong L., Zhang L., Li F. (2015). A three-step proportional weighting system of nonlinear biomass equations. Forest Science. 61 (1): P. 35-45.
Dylis N.V. (1978). Fundamentals of biogeocenology. Moscow: Moscow State University Publ., 152 pp.
Eggers J., Lindner M., Zudin S., Zaehle S., Liski J. (2008). Impact of changing wood demand, climate and land use on European forest resources and carbon stocks during the 21st century. Global Change Biology. 14: 2288–2303.
Fang O., Yang Wang Y., Shao X. (2016). The effect of climate on the net primary productivity (NPP) of Pinus koraiensis in the Changbai Mountains over the past 50 years. Trees. 30: 281–294. DOI: https://doi.org/10.1007/s00468-015-1300-6
Fatichi S., Pappas C., Zscheischler J., Leuzinge S. (2018). Modelling carbon sources and sinks in terrestrial vegetation. New Phytologist. 1-17. DOI: https://doi.org/10.1111/nph.15451
Fu L., Lei X., Hu Z., Zeng W., Tang Sh., Marshall P., Cao L., Song X., Yu Li., Liang J. (2017) Integrating regional climate change into allometric equations for estimating tree aboveground biomass of Masson pine in China. Annals of Forest Science. 74 (42): 1-15. DOI: https://doi.org/10.1007/s13595-017-0636-z
Golubyatnikov, L.L., Denisenko, Е.А. (2009). Influence of climatic changes on the vegetation of European Russia. News of Russian Academy of Sciences. Geographic series., 2: 57-68.
Han S.H., Kim S., Li G., Chang H., Yun S.J., Jiae An J., Son Y. (2018). Effects of warming and precipitation manipulation on fine root dynamics of Pinus densiflora Sieb. et Zucc. Seedlings. Forests. 9, 14 DOI: https://doi.org/10.3390/f9010014
Huston M.A., Wolverton S. (2009). The global distribution of net primary production: resolving the paradox. Ecological Monographs. 79 (3): 343–377. DOI: https://doi.org/10.1890/08-0588.1
Keeling H.C., Phillips O.L. (2007). The global relationship between forest productivity and biomass. Global Ecology and Biogeography. 16: 618-631. DOI: https://doi.org/10.1111/j.1466-8238.2007.00314.x
Laing J., Binyamin J. (2013). Climate change effect on winter temperature and precipitation of Yellowknife, Northwest Territories, Canada from 1943 to 2011.
American Journal of Climate Change. 2: 275-283. DOI: https://doi.org/10.4236/ajcc.2013.24027
Liang J., Crowther T. W., Picard N., Wiser S., Zhou M., Alberti G., Schulze E.-D., McGuire A. D., Bozzato F., Pretzsch H., de-Miguel S., Paquette A., Hérault B., Scherer-Lorenzen M., Barrett C. B., Glick H. B., Hengeveld G. M., Nabuurs G.-J., Pfautsch S., Viana H., Vibrans A. C., Ammer C., Schall P., Verbyla D., Tchebakova N. M., Fischer M., Watson J. V., Chen H. Y. H., Lei X., Schelhaas M.-J., Lu H., Gianelle D., Parfenova E. I., Salas C., Lee E., Lee B., Kim H. S., Bruelheide H., Coomes D. A., Piotto D., Sunderland T., Schmid B., Gourlet-Fleury S., Sonké B., Tavani R., Zhu J., Brandl S., Vayreda J., Kitahara F., Searle E. B., Neldner V. J., Ngugi M. R., Baraloto C., Frizzera L., Bałazy R., Oleksyn J., Zawiła-Niedźwiecki T., Bouriaud O., Bussotti F., Finér L., Jaroszewicz B., Jucker T., Valladares F., Jagodzinski A. M., Peri P. L., Gonmadje C., Marthy W., O’Brien T., Martin E. H., Marshall A. R., Rovero F., Bitariho R., Niklaus P. A., Alvarez-Loayza P., Chamuya N., Valencia R., Mortier F., Wortel V., Engone-Obiang N. L., Ferreira L. V., Odeke D. E., Vasquez R. M., Lewis S. L., Reich P. B. (2016). Positive biodiversity - productivity relationship predominant in global forests. Science. 354 (6309): 196-208. DOI: https://doi.org/10.1126/science.aaf/8957
Lieth H. (1974). Modeling the primary productivity of the world. International Section for Ecology Bulletin. Vol. 4. P. 11-20.
Miao Z., Li C. (2011). Predicting tree growth dynamics of boreal forest in response to climate change. C. Li et al. (eds.). Landscape Ecology in Forest Management and Conservation. Berlin, Heidelberg: Higher Education Press, Beijing and Springer-Verlag, P. 176-205.
Ni J., Zhang X.-S., Scurlock J.M.O. (2001). Synthesis and analysis of biomass and net primary productivity in Chinese forests. Annals of Forest Science. 58: 351-384. URL: www.edpsciences.org
Paquette A., Vayreda J., Coll L., Messier C., Retana J. (2018). Climate change could negate positive tree diversity effects on forest productivity: A study across five climate types in Spain and Canada. Ecosystems. 21 (5): 960–970. DOI: https://doi.org/10.1007/s10021-017-0196-y
Poudel B.C., Sathre R., Gustavsson L., Bergh J., Lundström A., Hyvönen R. (2011). Effects of climate change on biomass production and substitution in north-central Sweden. Biomass and Bioenergy. 35 (10): 4340–4355.
Schwarz F. (1899). Physiologische Untersuchungen über Dickenwachstum und Holzqualität von Pinus silvestris. Berlin: P. Parey, 404 S.
Shuman J.K., Shugart H.H. (2009). Evaluating the sensitivity of Eurasian forest biomass to climate change using a dynamic vegetation model. Environmental Research Letters. 4 (4): 1–7.
Stegen J.C., Swenson N.G., Enquist B.J., White E.P., Phillips O.L., Jorgensen P.M., Weiser M.D., Mendoza A.M., Vargas P.N. (2011). Variation in above-ground forest biomass across broad climatic gradients. Global Ecology and Biogeography. 20 (5):744–754. DOI: https://doi.org/10.1111/j.1466-8238.2010.00645.x
Strömgren M., Linder S. (2002). Effects of nutrition and soil warming on stem wood production of a boreal Norway spruce stand. Global Change Biology. 8: 1195–1204.
Tang S., Zhang H., Xu H. (2000). Study on establish and estimate method of compatible biomass model. Scientia Silvae Sinica. 36: 19–27 (in Chinese with English abstract).
Usoltsev V.A. (2010). Eurasian forest biomass and primary production data. Yekaterinburg: Ural Branch of Russian Academy of Sciences. 570 pp. ISBN 978-5-7691-2122-7. URL: http://elar.usfeu.ru/handle/123456789/2606
Usoltsev V.A. (2013). Forest biomass and primary production database for Eurasia. CD-version. The second ed. enlarged and re-harmonized. Yekaterinburg: Ural State Forest Engineering University. URL: http://elar.usfeu.ru/handle/123456789/3059
Usoltsev V.A., Shobairi S.O.R., Chasovskikh V.P. (2018). Geographic gradients of forest biomass of two needled pines on the territory of Eurasia. Ecological Questions. Vol. 29. No 2. P. 9-17. DOI: https://dx.doi.org/10.12775/EQ.2018.012
Wilmking M., Juday G.P., Barber V.A., Zald H.S.J. (2004). Recent climate warming forces contrasting growth responses of white spruce at treeline in Alaska through temperature thresholds. Global Change Biology. 10:1724–1736.
World Weather Maps (2007). URL: https://www.mapsofworld.com/referrals/weather
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