Prescribed burns can trigger Diplodia shoot blight in pine forests

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Authors: Francesc Serradó, Maria Caballol, Oriol Vendrell, Darío Domingo, Juan de la Riva, Jonàs Oliva
Cited by: 1
References: 31

Abstract

Climate change has increased the risk of wildfires, making fuel reduction a key objective in forest management. Prescribed burning is a widely used forest management practice to reduce fuel loads and wildfire risk. In NE Spain, prescribed burns were conducted in a Pinus nigra stand in autumn 2023 and winter 2024, after which extensive crown dieback resembling shoot blight symptoms was observed. Diplodia shoot blight is a disease that affects conifers around the world, particularly pine species. Diplodia shoot blight is caused by the fungus Diplodia sapinea , which shifts from an endophytic to a pathogenic state when the host is under physiological stress such as drought. To determine whether prescribed fire can trigger Diplodia shoot blight, we compared the severity of Diplodia shoot blight in areas subjected to prescribed burns with that of neighbouring control areas. Ground disease assessments were combined with satellite and drone-based multispectral and LiDAR measures. Shoot blight symptoms in burned areas were more than twice as severe as those in unburned areas. Diplodia sapinea was isolated from approximately 70% of pines showing shoot blight symptoms in burned areas. Temporal reconstruction of the outbreak using satellite-based normalised difference vegetation index values showed that the disease appeared after prescribed burning. Drone multispectral imagery combined with a random forest model was a reliable method for large-scale assessment of disease symptoms. When planning prescribed burns in pine forests, managers need to take Diplodia shoot blight into consideration to mitigate the risks of an outbreak. • Prescribed fire can trigger Diplodia shoot blight outbreaks. • Diplodia shoot blight severity in burned areas double that of unburned areas. • NDVI and RI best explain shoot blight severity from drone imagery. • Random forest model can accurately assess disease severity. • Severe outbreak areas can be efficiently detected using drone-based mapping.

Fields of Study & Subjects

Plant Pathogens and Fungal Diseases Plant and Fungal Interactions Research Bioactive Natural Diterpenoids Research

Publication details

Journal / source
Forest Ecology and Management
Publisher
Elsevier BV
Volume
613
Pages
123779–123779
Publication date
18 April 2026
Language
EN