Predictors of Insect Damage to Forest Stands According to Satellite Data on Example of Siberian Silkmoth Dendrolimis Sibiricus Tschetv

A. V. Kovalev; Ковалев А. В.; P. E. Tsikalova; Цикалова П. Е.

doi:10.31857/S002411482302002X

Predictors of Insect Damage to Forest Stands According to Satellite Data on Example of Siberian Silkmoth Dendrolimis Sibiricus Tschetv

Authors: Kovalev A.V.¹, Tsikalova P.E.¹
Affiliations:
1. Krasnoyarsk Scientific Center, Siberian Branch of the RAS
Issue: No 2 (2023)
Pages: 150-160
Section: RESEARCH
URL: https://ogarev-online.ru/0024-1148/article/view/137857
DOI: https://doi.org/10.31857/S002411482302002X
EDN: https://elibrary.ru/AKBVXY
ID: 137857

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Abstract
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Abstract

Population outbreaks of such species as Dendrolimus sibiricus Tschetv., in Siberian taiga forests begin with areas of several hectares and develop up to hundreds of thousands of hectares, resulting in significant damage to forests. Boundaries of foci change with time depending on external factors, population dynamics, and the state of forage trees. In this regard, it is important to determine the beginning of an outbreak and the affected area in advance as predictors of increasing pest numbers. To assess necessary conditions for an outbreak, a method for assessing state of forest stands is proposed based on remote sensing data. In this regard, it is important to assess risks of outbreaks and to determine in advance their onset times and starting zones. In order to evaluate necessary conditions for an outbreak, a “cascade” of factors is considered: geophysical (solar activity), weather, and the state of forest stands. Each of these factors is characterized by its own area, within the bounds of which any changes in this particular factor affect the insect population.

Keywords

taiga, forest stands, insect pests, Siberian silk moth, population dynamics, outbreaks, factors, monitoring, remote sensing methods

About the authors

A. V. Kovalev

Krasnoyarsk Scientific Center, Siberian Branch of the RAS

Author for correspondence.
Email: sunhi.prime@gmail.com
Russia, 660036, Krasnoyarsk, Akademgorodok, 50

P. E. Tsikalova

Krasnoyarsk Scientific Center, Siberian Branch of the RAS

Email: sunhi.prime@gmail.com
Russia, 660036, Krasnoyarsk, Akademgorodok, 50

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