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

iForest - Biogeosciences and Forestry

Potterf M¹  Munko M²  Duračiová R²  Jakuš R³  Resnerová K³  Holuša J³  Koren M⁴  Blaženec M⁵  Barka I⁶ 

[1] Department of Biological and Environmental Sciences, University of Jyvaskyla, Jyvaskyla, Finland;Faculty of Civil Engineering, Slovak University of Technology in Bratislava, Bratislava (Slovakia);Faculty of Forestry and Wood Sciences, Czech University of Life Sciences, Prague (Czech Republic);Faculty of Forestry, Technical University in Zvolen, Zvolen (Slovakia);Institute of Forest Ecology, Slovak Academy of Sciences, Zvolen (Slovakia);National Forest Centre, Forest Research Institute, Zvolen (Slovakia);

关键词: spatial predictive model;    bark beetle infestation;    gis;    roc curve;    norway spruce;   

DOI  :  10.3832/ifor3271-013

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown