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- Title
Weather Data-Based Prediction of the Siberian Moth Dendrolimus sibiricus Tschetv.: A Case Study.
- Authors
Demidko, D. A.; Goroshko, A. A.; Sultson, S. M.; Kulakova, N. N.; Mikhaylov, P. V.
- Abstract
Outbreak prediction is a crucial component of forest pest management. Weather plays a substantial role in outbreaks of leaf-eating insects. Weather-based prediction models in this field are numerous and more or less precise. We have attempted to create such a model for the Siberian moth (SM) Dendrolimus sibiricus Tschetv., one of the most harmful defoliators in the southern taiga of Siberia. For the territory of interest (the southern taiga and hemiboreal forests of Tomsk oblast, Kemerovo oblast, and Krasnoyarsk krai), the gradient boosting (XBGoost) model was created with an accuracy of 0.952. Temperatures of the vegetation period in the fourth and fifth years before the onset of outbreak are better predictors.
- Subjects
TOMSK (Russia); KRASNOIARSK (Russia); KEMEROVO (Russia); WEATHER forecasting; MOTHS; FOREST management; TAIGAS; PEST control
- Publication
Contemporary Problems of Ecology, 2024, Vol 17, Issue 3, p379
- ISSN
1995-4255
- Publication type
Article
- DOI
10.1134/S1995425524700215