Participatory ground data are complementary to satellite bark beetle detection

Abstract

Abstract Key message During pest outbreaks, mapping tools play an important role. Participatory projects can provide useful ground data, which have a high accuracy in detecting early-stage infestations and small spots of the European spruce bark beetle Ips typographus. However, satellite approaches are fundamental to clearly estimate infestation occurrence because ground data are spatially biased. Here, we show how a participatory approach involving nonspecialized staff and based on GIS-based app may contribute ground truth data that are fully complementary to satellite data. Context In Europe, bark beetle outbreaks were recently triggered by windstorms and heat waves, with the European spruce bark beetle Ips typographus. as the most important pest species. Huge efforts are needed for continuous mapping and monitoring of affected areas, especially during an incipient large-scale infestation. This is particularly difficult in mountain landscapes because of the rugged topography. Aims In addition to the use of remote sensing techniques, ground surveys are still an important source of data, providing detailed information on the symptoms of the affected trees and the stage of the attacks. Unfortunately, these surveys are extremely time demanding and require intensive field work. We wanted to assess how a participatory approach based on nonspecialized staff may contribute to data collection. Methods Georeferenced outbreak data were collected in the field in the Southern Alps (Italy) using a smartphone application based on ArcGIS platform. The survey was based on a participatory approach on a voluntary basis, involving citizens aware of forest practices. Visual analysis of satellite images was performed monthly to assess the visibility of reported infestations. Using a binomial model, we tested how the type of report (i.e., on-site/off-site), size of spot, stage of infestation, and their interactions affect detectability. In addition, spot occurrences within a study area were mapped for comparison with ground surveillance. Closeness to roads was tested between reported and unreported spots. Results WebGIS platform allowed us to retrieve near real-time information on bark beetle outbreaks and to compare the results with satellite imagery. Using visual analysis of satellite images, we detected only ~ 50% of the spots observed in the field, and detectability decreased dramatically for smaller and early-stage spots. Field observations were mostly concentrated near roads and covered only ~ 10% of the spots detected on satellite images. Conclusion The participatory approach is particularly helpful in mapping early-stage and small infestations, while satellite images are better suited at covering large areas and detect large and advanced-stage spots. The integration of those approaches is promising, and it can greatly improve the overall understanding of bark beetle outbreaks under emergency situations. A greater effort in developing smart applications for ground detection will benefit future monitoring of forest pests.

Keywords

• Bark beetle
• Citizen science
• Digital technology
• GIS
• Smartphone application