Additive biomass models for Quercus spp. single-trees sensitive to temperature and precipitation in Eurasia
DOI:
https://doi.org/10.12775/EQ.2019.021Keywords
oak trees, tree biomass, allometric models, additive biomass equations, mean January temperature, mean annual precipitationAbstract
The analysis of the biomass of oak (genus Quercus spp.) trees on the aboveground component composition based on regression equations having the additive biomass structure is fulfilled. Two trends of changes in the tree biomass structure are revealed: due to the mean January temperature and due to the mean annual precipitation. It was shown for the first time that both trends are mutually determined: the intensity of biomass trend in relation to the temperature is changing when depending on the level of precipitation, and the intensity of biomass trend in relation to precipitation level is changing during to a transition from the cold zone to the warm one and vice versa.
References
Affleck D.L.R. & Diéguez-Aranda U., 2016, Additive nonlinear biomass equations: a likelihood-based approach. Forest Science 62:129–140. (https://doi.org/10.5849/forsci.15-126).
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, [in:] M.L Parry., O.F.
Canziani, J.P. Palutikof, P.J. van der Linden, C.E. Hanson (eds) Climate change. Cambridge University Press, Cambridge: 541–580.
Baskerville G.L., 1972, Use of logarithmic regression in the estimation of plant biomass. Canadian Journal of Forest Research 2: 49-53.
Blunden J., Arndt D.S. & Hartfield G. (eds), 2018, State of the Climate in 2017. Bulletin of the American Meteorological Society 99(8): Si–S332. (https://doi.org/10.1175/2018BAMSStateoftheClimate.1).
Dahlberg U., Berge T.W., Petersson H. & Vencatasawmy C.P., 2004, Modelling biomass and leaf area index in a sub-arctic Scandinavian mountain area. Scandinavian Journal of Forest Research 19: 60-71. (https://doi.org/10.1080/02827580310019266).
Davidson R.L., 1969, Effect of root/leaf temperature differentials on root/shoot ratios in some pasture grasses and clover. Annals of Botany (N.S.) 33(131): 561-569.
de Miguel S., Mehtätalo L. & Durkaya A., 2014, Developing generalized, calibratable, mixed-effects meta-models for large-scale biomass prediction. Canadian Journal of Forest Research 44: 648–656. (https://doi.org/10.1139/cjfr-2013-0385).
Dong L., Zhang L. & Li F., 2015, A three-step proportional weighting system of nonlinear biomass equations. Forest Science 61: 35–45. (https://doi.org/10.5849/forsci.13-193).
Enquist B.J. & Niklas K.J., 2001, Invariant scaling relations across tree-dominated communities. Nature 410: 655-660. (https://doi.org/10.1038/35070500).
Enquist B.J. & Niklas K.J., 2002, Global allocation rules for patterns of biomass partitioning in seed plants. Science 295: 1517-1520. (https://doi.org/10.1126/science.1066360).
Felton A., Nilsson U., Sonesson J., Felton A.M., Roberge J.-M., Ranius T., Ahlström M., Bergh J., Bjorkman C., Boberg J., Drössler L., Fahlvik N., Gong P., Holmström E., Keskitalo E.C.H., Klapwijk M.J., Laudon H., Lundmark T., Niklasson M., Nordin A., Pettersson M., Stenlid J., Sténs A. & Wallertz K., 2016, Replacing monocultures with mixed-species stands: Ecosystem service implications of two production forest alternatives in Sweden. Ambio 45(Suppl. 2): 124–139. (https://doi.org/10.1007/s13280-015-0749-2).
Fischer F.J., Marechaux I. & Chave J., 2019, Improving plant allometry by fusing forest models and remote sensing. New Phytologist 21 March. (https://doi.org/10.1111/nph.15810).
Forrester D.I., Tachauer I.H.H., Annighoefer P., Barbeito I., Pretzsch H., Ruiz-Peinado R., Stark H., Vacchiano G., Zlatanov T., Chakraborty T., Saha S. &, Sileshi G.W., 2017, Generalized biomass and leaf area allometric equations for European tree species incorporating stand structure, tree age and climate. Forest Ecology and Management 396: 160–175. (https://doi.org/10.1016/j.foreco.2017.04.011).
Fu L., Lei X., Hu Z., Zeng W., Tang Sh., Marshall P., Cao L., Song X., Yu L. & 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. (https://doi.org/10.1007/s13595-017-0636-z).
Glebov F.Z. & Litvinenko V.I., 1976, The dynamics of tree ring width in relation to meteorological indices in different types of wetland forests. Lesovedenie 4: 56-62 [in Russian].
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 [in Russian].
Huber B., 1925, Die physiologische Leistungsfähigkeit des Wasserleitungssystems der Pflanze. Berichte der Deutschen Botanischen Gesellschaft 43: 410-418.
Huber B., 1927, Aus der Biologie der Baumkrone. Mitteilungen der Deutschen Den-drologischen Gesellschaft 38: 60-64.
Kazaryan V.О., 1969, Aging of higher plants. Nauka Publ., Moscow [in Russian].
Kozak A., 1970, Methods for ensuring additivity of biomass components by regression analysis. The Forestry Chronicle 46 (5): 402–404. (https://doi.org/10.5558/tfc46402-5).
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. (https://doi.org/10.4236/ajcc.2013.24027).
Lakida P.I., Vasilishin R.D., Blishchik V.I., Bilous A.M., Matushevich L.M., Lashchenko A.G., Bala O.P., Mateiko I.M., Morozyuk O.V., Kovalevskiy S.S., Khan E.Yu., Sitnik S.A., Bokoch V.V., Blishchik I.V., Prilipko I.S., Mel’nik O.M. & Dubrovets B.V., 2017, Deciduous forest stands of the Ukraine: phytomass and experimental data. FOP Gavrishenko V.M., Korsun’-Shevchenkovskiy, 483 pp. [in Ukrainian].
Marklund L., 1987, Biomass functions for Norway spruce (Picea abies (L.) Karst) in Sweden. Report 43, Department of Forest Survey, SLU, Umea, 127 pp.
Molchanov А.А., 1976, Dendroclimatic fundamentals of weather forecasts. Moscow: Nauka Publishing, 168 pp. [in Russian].
Nikitin К.Е., 1965, Forest and mathematics. Lesnoe Khozyaistvo [Forest Management] 5: 25-29 [in Russian].
Parresol B.R., 2001, Additivity of nonlinear biomass equations. Canadian Journal of Forest Research 31: 865–878. (https://doi.org/10.1139/cjfr-31-5-865).
Polikarpov N.P. & Chebakova N.M., 1982, Evaluation of biological productivity of forest species on the ecological basis, [in:] Formation of young-growth stands of coniferous species. Nauka Publishing, Novosibirsk: 25-54 [in Russian].
Poorter H., Jagodzinski A.M., Ruiz-Peinado R., Kuyah S., Luo Y., Oleksyn J., Usoltsev V.A., Buckley T.N., Reich P.B. & Sack L., 2015, How does biomass allocation change with size and differ among species? An analysis for 1200 plant species from five continents. New Phytologist 208(3): 736-749. (https://doi.org/10.1111/nph.13571).
Riedel T. & Kändler G., 2017, Nationale Treibhausgasberichterstattung: Neue Funktionen zur Schätzung der oberirdischen Biomasse am Einzelbaum. Forstarchiv 88 (2): 31–38. (https://doi.org/10.4432/0300-4112-88-31).
Schulze D.-E., Beck E. & Müller-Hohenstein K., 2005, Plant Ecology. Springer-Verlag, Berlin, Heidelberg, New York, 702 pp.
Shinozaki K., Yoda K., Hozumi K. & Kira T., 1964a, A quantitative analysis of plant form – the pipe model theory. 1. Basic analysis. Japanese Journal of Ecology 14 (3): 97-105.
Shinozaki K., Yoda K., Hozumi K. & Kira T., 1964b, A quantitative analysis of plant form – the pipe model theory. 2. Further evidence of the theory and its application in forest ecology. Japanese Journal of Ecology 14 (4): 133-139.
Usoltsev V.A., 1972, Birch and aspen crown biomass in forests of Northern Kazakhstan. Vestnik Selskokhozyaistvennoi Nauki Kazakhstana [Bulletin of Agricultural Science of Kazakhstan] 4: 77-80 [in Russian].
Usoltsev V.A., 1988, Growth and structure of forest stand biomass. Novosibirsk: Nauka Publ. 253 pp. [in Russian]. (http://elar.usfeu.ru/handle/123456789/3352).
Usoltsev V.А., 2007, Some methodological and conceptual uncertainties in estimating the income component of the forest carbon cycle. Russian Journal of Ecology 38 (1): 11–10. (https://doi.org/10.1134/S1067413607010018).
Usoltsev V.A., 2016, Single-tree biomass of forest-forming species in Eurasia: database, climatе-related geography, weight tables. Ural State Forest Engineering University, Yekaterinburg, 336 pp. (http://elar.usfeu.ru/handle/123456789/5696).
Usoltsev V.А., 2018, In basements of the biosphere: What we know about the primary production of tree roots? Eko-Potencial 4(24): 24-77 [in Russian]. (http://elar.usfeu.ru/bitstream/123456789/8024/1/eko4-18-04.pdf).
Usoltsev V.A., Zukow W., Osmirko A.A., Tsepordey I.S. & Chasovskikh V.P., 2019a, Additive biomass models for Larix spp. single-trees sensitive to temperature and precipitation in Eurasia. Ecological Questions 30(2): 57-67. (http://dx.doi.org/10.12775/EQ.2019.012).
Usoltsev V.А., Tsepordey I.S. & Chasovskikh V.P., 2019b, Tree biomass of two-needled pines in Eurasia: additive models in climatic gradients. Sibirskij Lesnoj Zurnal 1: 44–56 [in Russian with English abstract]. (https://doi.org/10.15372/SJFS20190104).
Usoltsev V.A., Shobairi, S.O.R., Tsepordey I.S., Chasovskikh V.P., 2019c, Modelling forest stand biomass and net primary production with the focus on additive models sensitive to climate variables for two-needled pines in Eurasia. Journal of Climate Change 5(1): 41-49. (https://doi.org/10.3233/JCC190005).
Vonderach С., Kändler G. & Dormann C.F., 2018, Consistent set of additive biomass functions for eight tree species in Germany fit by nonlinear seemingly unrelated regression. Annals of Forest Science 75: 49 . (https://doi.org/10.1007/s13595-018-0728-4).
West G.B., Brown J.H. & Enquist B.J., 1997, A general model for the origin of allometric scaling laws in biology. Science 276(5309): 122-126. (https://doi.org/10.1126/science.276.5309.122).
West G.B., Brown J.H. & Enguist B.J., 1999, A general model for the structure and allometry of plant vascular system. Nature 400: 664-667. (https://doi.org/10.1038/23251).
Williams M.S. & Schreuder H.T., 2000, Guidelines for choosing volume equations in the presence of measurement error in height. Canadian Journal of Forest Research 30: 306-310. (https://doi.org/10.1139/x99-215).
World Weather Maps, 2007, URL. (https://www.mapsofworld.com/referrals/weather).
Zeng W.S., Chen X.Y., Pu Y. & Yang X.Y., 2018, Comparison of different methods for estimating forest biomass and carbon storage based on National Forest Inventory data. Forest Research 31(1): 66-71 [in Chinese with English abstract]. (https://doi.org/10.13275/cnki.lykxyj.2017).
Zeng W.S., Duo H.R., Lei X.D., Chen X.Y., Wang X.J., Pu Y. & Zou W.T., 2017, Individual tree biomass equations and growth models sensitive to climate variables for Larix spp. in China. European Journal of Forest Research 136(20): 233–249. (https://doi.org/10.1007/s10342-017-1024-9).
Zhang C., Peng D.-L., Huang G.-S. & Zeng W.-S., 2016, Developing aboveground biomass equations both compatible with tree volume equations and additive systems for single-trees in poplar plantations in Jiangsu Province, China. Forests 7(2): 32. (https://doi.org/10.3390/f7020032).
Zheng C., Mason E.G., Jia L., Wei S., Sun C. & Duan J., 2015, A single-tree additive biomass model of Quercus variabilis Blume forests in North China. Trees 29(3): 705–716 (https://doi.org/10.1007/s00468-014-1148-1).
Zianis D., Muukkonen P., Makipaa R. & Mencuccini M., 2005, Biomass and stem volume equations for tree species in Europe. Silva Fennica Monograph 1–2: 5–63. (https://silvafennica.fi/pdf/smf004.pdf).
Downloads
Published
How to Cite
Issue
Section
Stats
Number of views and downloads: 553
Number of citations: 3