Search Results (39)

The European spruce bark beetle is a major disturbance agent in Norway spruce forests in Europe, and with a changing climate it is predicted that damage will increase. To prevent the bark beetle population buildup, and to limit further spread during outbreaks, it is crucial to detect attacked trees early. In this study, we utilize Sentinel-2 data in combination with a risk map, created from geodata and forestry data, to detect trees predisposed to and attacked by the European spruce bark beetle. Random forest models were trained over two tiles (90 × 90 km) in southern Sweden for all dates with a sufficient number of cloud-free Sentinel-2 pixels during the period May–September in 2017 and 2018. The pixels were classified into attacked and healthy to study how detection accuracy changed with time after bark beetle swarming and to find which Sentinel-2 bands are more important for detecting bark beetle attacked trees. Random forest models were trained with (1) single-date data, (2) temporal features (1-year difference), (3) single-date and temporal features combined, and (4) Sentinel-2 data and a risk map combined. We also included a spatial variability metric. The results show that detection accuracy was high already before the trees were attacked in May 2018, indicating that the Sentinel-2 data detect predisposed trees and that the early signs of attack are low for trees at high risk of being attacked. For single-date models, the accuracy ranged from 63 to 79% and 84 to 94% for the two tiles. For temporal features, accuracy ranged from 65 to 81% and 81 to 92%. When the single-date and temporal features were combined, the accuracy ranged from 70 to 84% and 90 to 96% for the two tiles, and with the risk map included, the accuracy ranged from 83 to 91% and 92 to 97%, showing that remote sensing data and geodata can be combined to increase detection accuracy. The differences in accuracy between the two tiles indicate that local differences can influence accuracy, suggesting that geographically weighted methods should be applied. For the single-date models, the SWIR, red-edge, and blue bands were generally more important, and the SWIR bands were more important after the attack, suggesting that they are most suitable for detecting the early signs of a bark beetle attack. For the temporal features, the SWIR and blue bands were more important, and for the variability metric, the green band was generally more important. Full article

In the Białowieża Forest, Norway spruce is the preferred host tree species for wood ants, both in coniferous and mixed stands; thus, spruce mortality as a consequence of a continuous spruce bark beetle outbreak in the Białowieża Forest since 2012 could have severe consequences for wood ant colonies, as well as their vitality and distribution. The main aim of this study was to assess whether the bark beetle outbreak had any effects on wood ant nest density and abundance and whether we could find any factors affecting the dead spruce distribution around ant nests. A re-inventory of active and abandoned wood ant nests in our study area was conducted from April to July 2022, using the same procedure as the previous inventory performed in 2016. The wood ant nest density was 0.11 per ha and remained practically the same relative to that determined in 2016. Our results indicate that, despite the importance of spruce for wood ants, in situations when only part of the spruce trees die, natural forest disturbances such as bark beetle outbreaks can actually have positive effects because more light can reach the forest floor, thereby promoting the establishment of new nests. Full article

The northern bark beetle, Ips duplicatus, is an emerging economic pest, reportedly infesting various species of spruce (Picea spp.), pine (Pinus spp.), and larch (Larix spp.) in Central Europe. Recent climate changes and inconsistent forest management practices have led to the rapid spread of this species, leaving the current monitoring strategies inefficient. As understanding the molecular components of pheromone detection is key to developing novel control strategies, we generated antennal transcriptomes from males and females of this species and annotated the chemosensory proteins. We identified putative candidates for 69 odorant receptors (ORs), 50 ionotropic receptors (IRs), 25 gustatory receptors (GRs), 27 odorant-binding proteins (OBPs), including a tetramer-OBP, 9 chemosensory proteins (CSPs), and 6 sensory neuron membrane proteins (SNMPs). However, no sex-specific chemosensory genes were detected. The phylogenetic analysis revealed conserved orthology in bark beetle chemosensory proteins, especially with a major forest pest and co-habitant, Ips typographus. Recent large-scale functional studies in I. typographus chemoreceptors add greater significance to the orthologous sequences reported here. Nevertheless, identifying chemosensory genes in I. duplicatus is valuable to understanding the chemosensory system and its evolution in bark beetles (Coleoptera) and, generally, insects. Full article

Effective management of bark beetle infestations requires prompt detection of attacked trees. Early attack is also called green attack, since tree foliage does not yet show any visible signs of tree decline. In several bark beetle systems, including mountain pine beetle and European spruce bark beetle, unpiloted aerial vehicle (UAV)-based remote sensing has successfully detected early attack. We explore the utility of remote sensing for early attack detection of southern pine beetle (SPB; Dendroctonus frontalis Zimm.), paired with detailed ground surveys to link tree decline symptoms with SPB life stages within the tree. In three of the northernmost SPB outbreaks in 2022 (Long Island, New York), we conducted ground surveys every two weeks throughout the growing season and collected UAV-based multispectral imagery in July 2022. Ground data revealed that SPB-attacked pitch pines (Pinus rigida Mill.) generally maintained green foliage until SPB pupation occurred within the bole. This tree decline behavior illustrates the need for early attack detection tools, like multispectral imagery, in the beetle’s northern range. Balanced random forest classification achieved, on average, 78.8% overall accuracy and identified our class of interest, SPB early attack, with 68.3% producer’s accuracy and 72.1% user’s accuracy. After removing the deciduous trees and just mapping the pine, the overall accuracy, on average, was 76.9% while the producer’s accuracy and the user’s accuracy both increased for the SPB early attack class. Our results demonstrate the utility of multispectral remote sensing in assessing SPB outbreaks, and we discuss possible improvements to our protocol. This is the first remote sensing study of SPB early attack in almost 60 years, and the first using a UAV in the SPB literature. Full article

Using the liverwort Hygrobiella laxiflora as an example, this study aims to investigate the impact of climate change on montane species and their ecosystems. The study area is the Elbe Sandstone Mountains in Germany and the Czech Republic, where Hygrobiella laxifolia has an isolated occurrence in deeply carved gorges characterized by a specific microclimate (cellar climate). The focus is on determining the rate at which populations are affected. After little change in the population over a long period, a sudden sharp decline has been observed in recent years. The decline correlates with the mass proliferation of the European spruce bark beetle (Ips typographus) observed since 2017, which has led to a strong thinning of the forests in the area. In many areas of occurrence, the forests now have a much sparser tree layer or none at all. Competition from other, more competitive species also plays an important role as a cause of decline, as these have spread more widely on the sites due to the now higher light levels. The severe bark beetle infestation and the large-scale forest fire of 2022 both represent events that led to the almost complete deforestation of large parts of the study area, which was previously unknown on this scale. Since both the bark beetle infestation and the forest fire are strongly intensified by climate change, we assume that climate change is the main reason for the decline of Hygrobiella laxifolia in the area. The populations of Hygrobiella laxifolia of the Elbe Sandstone Mountains show some morphological peculiarities. As two new species have recently been described within Hygrobiella, we have integrated a sample from the area into a molecular phylogeny of Hygrobiella based on the plastid sequences of trnL-trnF intergenic spacer and matK to clarify the relationships. The sample from Elbe Sandstone Mountains fits well into the clade of Hygrobiella laxifolia. Full article

The widespread tree mortality caused by the European spruce bark beetle (Ips typographus L.) is a significant concern for Norway spruce-dominated (Picea abies H. Karst) forests in Europe and there is evidence of increases in the affected areas due to climate warming. Effective forest monitoring methods are urgently needed for providing timely data on tree health status for conducting forest management operations that aim to prepare and mitigate the damage caused by the beetle. Unoccupied aircraft systems (UASs) in combination with machine learning image analysis have emerged as a powerful tool for the fast-response monitoring of forest health. This research aims to assess the effectiveness of deep neural networks (DNNs) in identifying bark beetle infestations at the individual tree level from UAS images. The study compares the efficacy of RGB, multispectral (MS), and hyperspectral (HS) imaging, and evaluates various neural network structures for each image type. The findings reveal that MS and HS images perform better than RGB images. A 2D-3D-CNN model trained on HS images proves to be the best for detecting infested trees, with an F1-score of 0.759, while for dead and healthy trees, the F1-scores are 0.880 and 0.928, respectively. The study also demonstrates that the tested classifier networks outperform the state-of-the-art You Only Look Once (YOLO) classifier module, and that an effective analyzer can be implemented by integrating YOLO and the DNN classifier model. The current research provides a foundation for the further exploration of MS and HS imaging in detecting bark beetle disturbances in time, which can play a crucial role in forest management efforts to combat large-scale outbreaks. The study highlights the potential of remote sensing and machine learning in monitoring forest health and mitigating the impacts of biotic stresses. It also offers valuable insights into the effectiveness of DNNs in detecting bark beetle infestations using UAS-based remote sensing technology. Full article

Ips typographus, the European spruce bark beetle, is a destructive forest insect that attacks spruce trees. It poses a significant threat to the forestry industry, causing widespread tree mortality and economic losses, and its management through chemical ecology is a promising approach. Attraction relies on aggregation pheromones while repellency is achieved via antiaggregation pheromones combined with mixtures of nonhost volatiles (NHVs), but an effective push and pull strategy has not been established yet. In this study, we observed the beetle colonization dynamic and density comparing pure Norway spruce stacks and Norway spruce stacks with 20% Scots pine logs. We collected the spruce bark volatiles before the beetle colonization and at the end of the trial, and tested the behavioral effects on the beetles of both spruce and pine essential oils in olfactometer trials. In the stacks with Scots pine, we observed a delayed primary colonization and a 65% reduction of the secondary colonization, confirming the colonization disruption mediated by NHVs. Volatile analysis showed a significant change in the bark emission profiles, and the reaching of the antiaggregation phase was marked by the release of verbenone. Behavioral experiments confirmed the attractivity of spruce essential oil and the strong repellency of the pine essential oil. The study supports the use of complex NHVs blends for the beetle behavioral manipulation in the field. Further studies are needed to assess if the same results can be achieved by deploying essential oils in forest stands. Full article

Extreme weather events are increasing in frequency and intensity, posing a threat to forest ecosystems and eliciting forest-pest outbreaks. In the southern Italian Alps, a dramatic windthrow called Vaia occurred in October 2018, shifting populations of the European spruce bark beetle (Ips typographus) from an endemic to an epidemic phase. Remote-sensing methods are often employed to detect areas affected by disturbances, such as forest-pest outbreaks, over large regions. In this study, a random forest model on the Sentinel-2 images acquired over the south-eastern Alps in 2021 and 2022 was used to detect the outbreak spots. The automatic classification model was tested and validated by exploiting ground data collected through a survey conducted in 2021 and 2022 in both healthy and infested spots, characterized by variable sizes and degrees of infestation. The model correctly identified the forest conditions (healthy or infested) with an overall accuracy of 72% for 2022 and 58% for 2021. These results highlight the possibility of locating I. typographus outbreaks, even in small spots (between 5 and 50 trees) or spots intermixed with healthy trees. The prompt detection of areas with a higher frequency of outbreaks could be a useful tool to integrate field surveys and select forest areas in which to concentrate management operations. Full article

Inappropriate forest management activities, above all clear-cutting, are recognized as the major threats to an iconic orchid species—the lady’s slipper orchid (Cypripedium calceolus), the flagship species of nature protection in Europe. Although clear-cutting in protected species’ localities is strongly regulated in many European countries, salvage logging is allowed in some circumstances (e.g., following windstorms, and insect outbreaks) and can threaten C. calceolus populations. In this paper, we review a database of recently registered populations of this species in the Czech Republic and study historical maps, to better understand the history of local habitat conditions and assess threats to C. calceolus populations by bark beetle outbreaks. We found that about one-third of the C. calceolus populations have suffered in coniferous or mixed tree plantations with a high proportion of spruce trees, which are forests with a high risk of bark beetle infestation. We review bark beetle management measures and distinguish management efforts in areas with known C. calceolus populations that result in no damage to the population and, at times, improve habitat conditions for the species. Thus, the bark beetle—usually understood as the enemy—can be transformed into a savior if smart management measures will replace the panic salvage logging. Full article

Forests are increasingly exposed to natural disturbances, including drought, wildfires, pest outbreaks, and windthrow events. Due to prolonged droughts in the last years in Europe, European forest stands significantly lost vitality, and their health condition deteriorated, leading to high mortality rates, especially, but not limited to, Norway spruce. This phenomenon is growing, and new regions are being affected; thus, it is necessary to identify stress in the early stages when actions can be taken to protect the forest and living trees. Current detection methods are based on field walks by forest workers or deploying remote sensing methods for coverage of the larger territory. These methods are based on changes in spectral reflectance that can detect attacks only at an advanced stage after the significant changes in the canopy. An innovative approach appears to be a method based on odor mapping, specifically detecting chemical substances which are present in the forest stands and indicate triggering of constitutive defense of stressed trees. The bark beetle attacking a tree, for example, produces a several times higher amount of defense-related volatile organic compounds. At the same time, the bark beetle has an aggregation pheromone to attract conspecifics to overcome the tree defense by mass attack. These substances can be detected using conventional chemical methods (solid-phase microextraction fibers and cartridges), and it is proven that they are detectable by dogs. The disadvantage of classic chemical analysis methods is the long sampling time in the forest, and at the same time, the results must be analyzed in the laboratory using a gas chromatograph. A potential alternative novel device appears to be an electronic nose, which is designed to detect chemical substances online (for example, dangerous gas leaks or measure concentrations above landfills, volcanic activity, etc.). We tested the possibility of early-stage stress detection in the forest stands using an electronic nose Sniffer4D and compared the individual sensors in it for detecting the presence of attacked and dead trees. Our results indicate the promising applicability of the electronic nose for stress mapping in the forest ecosystem, and more data collection could prove this approach. Full article

The double-spined bark beetle, Ips duplicatus, is an example of a species whose economic importance has increased in many European countries over the past decade. Many aspects of its life cycle remain unknown, complicating its management. I. duplicatus adults overwinter in forest litter, which makes the removal of infested trees during winter ineffective. Therefore, this study focuses on the mechanisms and timing of I. duplicatus overwintering migration into the forest litter. Only 2.2% of adult I. duplicatus overwintered under the bark of spruce logs stored outdoors from August 2016 to March 2017. In all, 94.4% of the beetles emerged and burrowed in forest litter. Migration began in late August, peaked in mid-September, and lasted until mid-October. At that time, forest litter collected at the base of an infested tree contained an average of 154.7 ± 23.9 I. duplicatus. Catches of migrating adults on glue stripes proved that the beetles walked down the trunk on days when the average daily temperature reached 10–15 °C. Based on the results, we suggest that trees infested with I. duplicatus that have completed their development into adults should be removed no later than September. Sanitation cutting in the following months is not effective against this pest. Full article

Various biotic and abiotic stresses are causing decline in forest health globally. Presently, one of the major biotic stress agents in Europe is the European spruce bark beetle (Ips typographus L.) which is increasingly causing widespread tree mortality in northern latitudes as a consequence of the warming climate. Remote sensing using unoccupied aerial systems (UAS) together with evolving machine learning techniques provide a powerful tool for fast-response monitoring of forest health. The aim of this study was to investigate the performance of a deep one-stage object detection neural network in the detection of damage by I. typographus in Norway spruce trees using UAS RGB images. A Scaled-YOLOv4 (You Only Look Once) network was implemented and trained for tree health analysis. Datasets for model training were collected during 2013–2020 from three different areas, using four different RGB cameras, and under varying weather conditions. Different model training options were evaluated, including two different symptom rules, different partitions of the dataset, fine-tuning, and hyperparameter optimization. Our study showed that the network was able to detect and classify spruce trees that had visually separable crown symptoms, but it failed to separate spruce trees with stem symptoms and a green crown from healthy spruce trees. For the best model, the overall F-score was 89%, and the F-scores for the healthy, infested, and dead trees were 90%, 79%, and 98%, respectively. The method adapted well to the diverse dataset, and the processing results with different options were consistent. The results indicated that the proposed method could enable implementation of low-cost tools for management of I. typographus outbreaks. Full article

Various biotic and abiotic factors are the cause of the decline of coniferous forests throughout Europe. Trees weakened by unfavorable weather conditions create an ideal environment for a possible outbreak of bark beetles. The damage caused by bark beetles costs billions of dollars worldwide every year. Extreme climate events are responsible for the enormous forest losses in Tara National Park in the last ten years, leading to a massive bark beetle infestation. The understanding of the diversity and role of mites as biological control agents is still insufficient. In this study, we summarize the current knowledge on the diversity of mites associated with Ips typographus L. in Europe and provide information on the diversity of these mites in Serbia. Paraleius leontonychus, Uroobovella ipidis, Dendrolaelaps quadrisetus, Histiostoma piceae, and Trichouropoda polytricha were detected for the first time in Serbia. Moreover, the occurrence of Paraleius leontonychus represents the southernmost occurrence of this species. Full article

Białowieża Primeval Forest (BPF, approx. 1700 km²) is an important forest area in Europe from the point of view of the protection of natural diversity. BPF is covered with old mixed tree stands of mostly natural origin. Norway spruce is a tree species in BPF and covers approx. 27% of its area. Between 2012 and 2017 a large outbreak of the bark beetle Ips typographus (Linnaeus, 1758) took place in the forest, which transformed the stands and left many dead standing trees. At that time salvage logging had begun but was stopped due to protests by scientists and activists and for legal reasons. As a result of research conducted using a radiotelemetry method in 2020, we found that the Western barbastelle bat Barbastella barbastellus (Schreber, 1774) chooses nursery roosts in dead Norway spruce trees, showing ecological plasticity by colonizing a newly available resource. Based on this, we found that the Western barbastelle has a preference for a type of roost rather than a tree species. Insect outbreaks in forests of primary, natural, or semi-natural origin are one of the natural factors that shape the habitat. Removal of dead standing trees disrupts these processes, and in this particular case results in the disappearance of a newly appeared ecological niche. Full article

Insect outbreaks affect forests, causing the deaths of trees and high economic loss. In this study, we explored the detection of European spruce bark beetle (Ips typographus, L.) outbreaks at the individual tree crown level using multispectral satellite images. Moreover, we explored the possibility of tracking the progression of the outbreak over time using multitemporal data. Sentinel-2 data acquired during the summer of 2020 over a bark beetle–infested area in the Italian Alps were used for the mapping and tracking over time, while airborne lidar data were used to automatically detect the individual tree crowns and to classify tree species. Mapping and tracking of the outbreak were carried out using a support vector machine classifier with input vegetation indices extracted from the multispectral data. The results showed that it was possible to detect two stages of the outbreak (i.e., early, and late) with an overall accuracy of 83.4%. Moreover, we showed how it is technically possible to track the evolution of the outbreak in an almost bi-weekly period at the level of the individual tree crowns. The outcomes of this paper are useful from both a management and ecological perspective: it allows forest managers to map a bark beetle outbreak at different stages with a high spatial accuracy, and the maps describing the evolution of the outbreak could be used in further studies related to the behavior of bark beetles. Full article