A bark beetle infestation predictive model based on satellite data in the frame of decision support system TANABBO

doi:10.3832/ifor3271-013

A bark beetle infestation predictive model based on satellite data in the frame of decision support system TANABBO

Renata Duračiová⁽¹⁾, Milan Muňko⁽¹⁾, Ivan Barka⁽²⁾, Milan Koreň⁽³⁾, Karolina Resnerová⁽⁴⁾, Jaroslav Holuša⁽⁴⁾, Miroslav Blaženec⁽⁵⁾, Mária Potterf⁽⁶⁾, Rastislav Jakuš^(4-5)

iForest - Biogeosciences and Forestry, Volume 13, Issue 3, Pages 215-223 (2020)
doi: https://doi.org/10.3832/ifor3271-013
Published: Jun 06, 2020 - Copyright © 2020 SISEF

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Geo-mapping

The European spruce bark beetle Ips typographus L. causes significant economic losses in managed coniferous forests in Central and Northern Europe. New infestations either occur in previously undisturbed forest stands (i.e., spot initiation) or depend on proximity to previous years’ infestations (i.e., spot spreading). Early identification of newly infested trees over the forested landscape limits the effective control measures. Accurate forecasting of the spread of bark beetle infestation is crucial to plan efficient sanitation felling of infested trees and prevent further propagation of beetle-induced tree mortality. We created a predictive model of subsequent year spot initiation and spot spreading within the TANABBO decision support system. The algorithm combines open-access Landsat-based vegetation change time-series data, a digital terrain model, and forest stand characteristics. We validated predicted susceptibility to bark beetle attack (separately for spot initiation and spot spreading) against beetle infestations in managed forests in the Bohemian Forest in the Czech Republic (Central Europe) in yearly time steps from 2007 to 2010. The predictive models of susceptibility to bark beetle attack had a high degree of reliability (area under the ROC curve - AUC: 0.75-0.82). We conclude that spot initiation and spot spreading prediction modules included within the TANABBO model have the potential to help forest managers to plan sanitation felling in managed forests under pressure of bark beetle outbreak.

Keywords

Spatial Predictive Model, Bark Beetle Infestation, GIS, ROC Curve, Norway Spruce

Authors’ address

(1)

0000-0002-9061-6567

Faculty of Civil Engineering, Slovak University of Technology in Bratislava, Bratislava (Slovakia)

(2)

0000-0002-2364-8542
National Forest Centre, Forest Research Institute, Zvolen (Slovakia)

(3)

0000-0002-2956-944X
Faculty of Forestry, Technical University in Zvolen, Zvolen (Slovakia)

(4)

0000-0003-1459-0331
0000-0003-2280-1952
Faculty of Forestry and Wood Sciences, Czech University of Life Sciences, Prague (Czech Republic)

(5)

0000-0001-9743-614X
0000-0003-2280-1952
Institute of Forest Ecology, Slovak Academy of Sciences, Zvolen (Slovakia)

(6)

0000-0001-6763-1948
Department of Biological and Environmental Sciences, University of Jyvaskyla, Jyvaskyla, Finland

Corresponding author

Rastislav Jakuš
jakus@fld.czu.cz

Citation

Duračiová R, Muňko M, Barka I, Koreň M, Resnerová K, Holuša J, Blaženec M, Potterf M, Jakuš R (2020). A bark beetle infestation predictive model based on satellite data in the frame of decision support system TANABBO. iForest 13: 215-223. - doi: 10.3832/ifor3271-013

Academic Editor

Massimo Faccoli

Paper history

Received: Oct 17, 2019
Accepted: Apr 05, 2020

First online: Jun 06, 2020
Publication Date: Jun 30, 2020
Publication Time: 2.07 months

Open Access

This article is distributed under the terms of the Creative Commons Attribution-Non Commercial 4.0 International (https://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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