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Volume 14   Issue 1   Year 2019
Parameterization of Productivity Model for the Most Common Trees Species in European Part of Russia for Simulation of Forest Ecosystem Dynamics

Shanin V.N.1, 2, 3 , Grabarnik P.Ya.1, Bykhovets S.S.1, Chertov O.G.4, Priputina I.V.1, Shashkov M.P.1, 3, Ivanova N.V.1, 3, Stamenov M.N.1, Frolov P.V.1, Zubkova E.V.1, Ruchinskaya E.V.2

1Institute of Physicochemical and Biological Problems in Soil Science of the Russian Academy of Sciences
2Center for Forest Ecology and Productivity of the Russian Academy of Sciences
3Institute of Mathematical Problems of Biology – the Branch of the Keldysh Institute of Applied Mathematics of the Russian Academy of Sciences
4University of Applied Sciences Bingen

Abstract. The proposed model is the version of well-known biomass production model 3-PG (Physiological Principles Predicting Growth), which allows for calculation of biomass production in dependence of consumed soil nitrogen and available solar radiation. The model utilizes the concept of modifiers, i.e. functions describing the effect of tree age and environmental factors (air temperature and humidity, soil moisture, carbon dioxide concentration) on productivity. To make the model applicable to mixed forests of European Russia, the substantial modifications were implemented. In particular, more detailed response functions to air temperature, soil moisture and absorbed nitrogen were introduced. We also implemented new procedure of calculation of light use efficiency taking into account the difference between shade-tolerant and shade-intolerant tree species. The rank distribution equation was used for the description of an increment allocation to different tree biomass compartments. Model parameters were estimated for the 12 most common tree species of European Russia. The model was implemented as sub-routine for calculation of biomass production in forest ecosystem model EFIMOD 2. The model performance was tested against the wide range of environmental conditions.

 

 

key words: productivity, response functions, mixed forests, allocation of increment.

Table of Contents Original Article
Math. Biol. Bioinf.
2019;14(1):54-76
doi: 10.17537/2019.14.54
published in Russian

Abstract (rus.)
Abstract (eng.)
Full text (rus., pdf)
References
Supplementary data

 

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