The frequent outbreaks of European spruce bark beetle Ips typographus (L.) have destroyed huge amounts of Norway spruce Picea abies (L.) forests in central and Northern Europe. Identifying the risk factors and estimating the damage level is important for strategic damage control. The risk factors of forest damage by spruce bark beetles have mostly been analyzed on the landscape scale, while the in-stand risk factors have been less investigated. This study aims at exploring the local-scale risk factors in a flat area with spruce-dominated forest in southern Sweden. The investigated factors include four abiotic factors, i.e., soil wetness, solar radiation, slope gradient, and aspect, and three biotic factors, i.e., the number of deciduous trees and trees that died from attacks in previous years that remained (TreesLeft) and removed (TreesRemoved) from the forest stand. We put up 24 pheromone bags in six stands attacked by bark beetle in the previous years, resulting in different numbers of infested trees in each plot. We explored in which microenvironment a pheromone bag resulted in more colonization, the impact radius of each factor, and the necessary factors for a risk model. The environmental factors were obtained from remote sensing-based products and images. A generalized linear model (GLM) was used with the environmental factors as the explanatory variables and the damage levels as the response variables, i.e., the number of attacked trees for the plot scale, and healthy/infested for the single-tree scale. Using 50 m and 15 m radius of the environmental factors resulted in the best fit for the model at plot and individual tree scales, respectively. At those radii, the damage risk increased both at plot and individual tree level when spruce were surrounded by more deciduous trees, surrounded by dead trees that had been removed from the forest, and spruces located at the north and east slopes (315 degrees-135 degrees of aspect, > 2 degrees slope). Soil wetness, solar radiation, and remaining standing dead trees in the surrounding did not significantly impact the damage level in the microenvironment of the study area. The GLM risk model yielded an overall accuracy of 0.69 in predicting individual trees being infested or healthy. Our efforts to investigate the risk factors provide a context for wall-to-wall mapping in-stand infestation risks, using remote sensing-based data.

Bark beetle outbreaks are a significant cause of high tree mortality rates, dramatically impacting the resilience of forests. Understanding the triggers and impacts of these outbreaks is critical for effective forest management strategies. In this context, we studied windfall and bark beetle outbreaks in the period 2015-2021 in the southern part of Kurilskiy Nature Reserve, North Pacific Ocean region. Massive bark beetle outbreaks on Kunashir Island were not previously studied. The dominant tree species are Yezo spruce (Picea jezoensis) and Sakhalin fir (Abies sachalinensis), which collectively form spruce -fir forests on Kunashir Island. Glehn spruce (Picea glehnii), although less common on the island, forms pure spruce forests. Typically, spruce bark beetle (Ips typographus L.) attacks Yezo and Glehn spruce, and fir bark beetle (Polygraphus proximus) attacks Sakhalin fir. Significant tree mortality was observed in the aftermath of a substantial bark beetle outbreak, induced by gale -force winds. The total disturbance area was 620.5 ha, which is about 4% of the study area, 72% of the windfall area, and 28% of the bark beetle -infested area. Utilising a forest loss dataset (Global Forest Change dataset) and Sentinel 2 imagery, we identified windfall areas and standing tree mortality through unsupervised classification, accompanied by field sampling. Subsequently, the authors analysed the main drivers of disturbances caused by wind and bark beetle outbreaks using datasets combined with forest inventory data. Field data showed a pattern of tree infestation by both bark beetle species at the tree level, and the potential infestation of Sakhalin fir by the spruce bark beetle. We used boosted regression tree (BRT) models to analyse the main drivers using the presence and severity of wind damage and bark beetle outbreaks by phases. As predictors, we used a set of forest characteristics (tree species percentage, height, diameter of trunk, age, growth class) and environmental characteristics (slope, elevation, potential solar radiation, soil pH). The bark beetle outbreak was split into two phases: the first phase (2017-2019) involved the transition of bark beetles from colonised downed trees to standing trees, and the second phase (2020-2021) occurred during the spreading of beetles in standing trees. Stand tree characteristics were of greater significance for the likelihood of a bark beetle outbreak than environmental characteristics, across both phases for the southern part of the reserve. The percentage and the age of Glehn spruce and Yezo spruce were the main influencing factors for the presence and severity of an outbreak.

Disturbances caused by the European spruce bark beetle (SBB; Ips typographus L.) on Norway spruce ( Picea abies (L.) H. Karst.), have increased immensely across Central and Northern Europe, and are expected to increase further as a result of climate change. While this trend has been noted in Finland, so far limited research has been published. To support proper SBB risk management in Finland, we compared stand properties between salvage loggings due to SBB damage during 2012-2020 (4691 cases) and spruce stands free of SBB damage. Also, we explored the role of landscape attributes as drivers of SBB damage. We considered the forest stand attributes of site fertility class, stand development class, soil type, stand mean diameter at breast height and mean stand age. Considered forest landscape attributes were the distance from SBB-damaged stands to the closest clear-cut, to previous -year SBB-damaged stands and to the previous -year wind -damaged stand. We used nationwide forest logging and forest stock data, and analysed forest stand attributes using Chi -squared and Mann -Whitney U tests and landscape attributes using generalised linear mixed models. Based on our findings, the SBB didn't damage stands randomly, but prevailed in mature stands (high age and high mean diameter at breast height), in herb -rich heath forest site types and in semi -coarse or coarse heath forest soil soils. We found correlation between the landscape variables and the number of salvage loggings, with a higher number of loggings due to SBB damage close to clear -cuts. Our results help to find risk areas of SBB damage.