ESTIMATION OF THE YIELD OF WILD BERRIES TAKING INTO ACCOUNT THE LEVEL OF ILLUMINATION OF THE GROUND COVER BY SIMULATION METHODS

A. A. Kolycheva¹, S. I. Chumachenko²

¹Center for Forest Ecology and Productivity of the RAS

Profsoyuznaya st. 84/32 bldg. 14, Moscow, 117997, Russia

Е-mail: anna_dulina@bk.ru

²MB of Bauman Moscow State Technical University

1st Institutskaya street, 1, Mytischi, Moscow region, 141005, Russia

 

Received: 18.10.2021

Revised: 10.11.2021

Accepted: 19.11.2021

Relevance and purpose. Currently known methods of accounting for berry yields are not applicable for multi-species forests of different ages with the presence of undergrowth and undergrowth, widespread in Russia. Difficulties arise due to a set of input parameters, including type of forest growing conditions, breed, age, completeness, but not describing the illumination at the level of the grass-shrub layer, which is the determining factor in the yield of blueberries, cranberries, raspberries. The purpose of this study is to develop an approach to calculating the yield of wild berries, taking into account the illumination at the ground cover level by simulation methods. Material and methods. For the forecast, the FORRUS-S model of forest plantation dynamics is used. The yield data is taken from an existing reference book, which shows productivity in clean plantations without undergrowth and undergrowth. The use of an additional predictor of berry yield, namely, illumination at the level of ground cover, made it possible to predict yields in forests of a more complex structure: multi-species, of different ages, with undergrowth and undergrowth. Results and conclusion. An original approach to calculating the yield of wild berries has been developed. The above approach allows us to estimate the yield of the most common berries in the European part of Russia: blueberries, raspberries, lingonberries. Universal equations have been obtained that make it possible to predict the productivity of berry bushes based on the taxation characteristics of the stand and the illumination calculated in the model.

Key words: multifunctional forest management, modeling of the yield of forest berries, forest berries, illumination, yield

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