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Semi-empirical models for assessing biological productivity of Northern Eurasian forests

Author

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  • Shvidenko, Anatoly
  • Schepaschenko, Dmitry
  • Nilsson, Sten
  • Bouloui, Yuri

Abstract

The Richards–Chapman growth function was used as an analytical basis for a unified system of semi-empirical models describing the dynamics of the main biometric characteristics of major types of Northern Eurasian forests. The growth function was applied at the stand level using yield tables. The models received satisfactorily describe the diversity of growth patterns for different species and geographical regions of Northern Eurasia. A special type of model of biological productivity (MBP) has been developed combining the above growth models and multi-dimensional regression equations of phytomass (living biomass). The latter have been parametrized for dominant tree species, site indexes and ecological regions based on 3507 sample plots collected in Northern Eurasia's forests. The MBP account for age dynamics of forest ecosystems and simulate dynamics of seven components of phytomass (stem wood over bark, bark, crown wood, foliage, understory, green forest floor, and roots) as well as net primary production. The model system could be used in different ecological applications, in forest inventory and forest management as a semi-empirical reference information on the growth and productivity of Northern Eurasia's forests.

Suggested Citation

  • Shvidenko, Anatoly & Schepaschenko, Dmitry & Nilsson, Sten & Bouloui, Yuri, 2007. "Semi-empirical models for assessing biological productivity of Northern Eurasian forests," Ecological Modelling, Elsevier, vol. 204(1), pages 163-179.
  • Handle: RePEc:eee:ecomod:v:204:y:2007:i:1:p:163-179
    DOI: 10.1016/j.ecolmodel.2006.12.040
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    Cited by:

    1. Viktoriia Lovynska & Yuriy Buchavyi & Petro Lakyda & Svitlana Sytnyk & Yuriy Gritzan & Roman Sendziuk, 2020. "Assessment of pine aboveground biomass within Northern Steppe of Ukraine using Sentinel-2 data," Journal of Forest Science, Czech Academy of Agricultural Sciences, vol. 66(8), pages 339-348.
    2. Krishna, Dyvavani K. & Watham, Taibanganba & Padalia, Hitendra & Srinet, Ritika & Nandy, Subrata, 2023. "Improved gross primary productivity estimation using semi empirical (PRELES) model for moist Indian sal forest," Ecological Modelling, Elsevier, vol. 475(C).
    3. Myroslava Lesiv & Anatoly Shvidenko & Dmitry Schepaschenko & Linda See & Steffen Fritz, 2019. "A spatial assessment of the forest carbon budget for Ukraine," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 24(6), pages 985-1006, August.

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