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Dendroctonus valens is one of the main invasive pests in China, causing serious economic and ecological damage. Early detection and control of D. valens can help prevent further outbreaks. Based on unmanned aerial vehicle (UAV) thermal infrared and hyperspectral data, we compared the spectral characteristics of Pinus sylvestris var. mongolica in three states (healthy, early-infested, and dead), and constructed a classification model based on the random forest algorithm using four spectral datasets (reflectance, first derivative, second derivative, and spectral vegetation index) and one temperature parameter dataset. Our results indicated that the spectral differences between healthy and early-infested trees mainly occur in the near-infrared region, with dead trees showing different characteristics. While it was effective to distinguish healthy from early-infested trees using spectral data alone, the addition of a temperature parameter further improved classification accuracy across all datasets. The combination of the spectral vegetation index and temperature parameter achieved the highest accuracy at 93.75%, which is 3.13% higher than using the spectral vegetation index alone. This combination also significantly improved early detection precision by 13.89%. Our findings demonstrated the applicability of UAV-based thermal infrared and combined hyperspectral datasets in monitoring D. valens early-infested trees, providing important technical support for the scientific prevention and control of D. valens. [ABSTRACT FROM AUTHOR]

Sustainable forest management faces challenges from various biotic and abiotic stresses. The Asian longhorned beetle (ALB) and drought stress both induce water shortages in poplar trees, but require different management strategies. In northwestern China, ALB and drought stress caused massive mortality in poplar shelterbelts, which seriously affected the ecological functions of poplars. Developing a large-scale detection method for discriminating them is crucial for applying targeted management. This study integrated UAV-hyperspectral and LiDAR data to distinguish between ALB and drought stress in poplars of China's Three-North Shelterbelt. These data were analyzed using a Partial Least Squares-Support Vector Machine (PLS-SVM). The results showed that the LiDAR metric (elev_sqrt_mean_sq) was key in detecting drought, while the hyperspectral band (R970) was key in ALB detection, underscoring the necessity of integrating both sensors. Detection of ALB in poplars improved when the poplars were well watered. The classification accuracy was 94.85% for distinguishing well-watered from water-deficient trees, and 80.81% for detecting ALB damage. Overall classification accuracy was 78.79% when classifying four stress types: healthy, only ALB affected, only drought affected, and combined stress of ALB and drought. The results demonstrate the effectiveness of UAV-hyperspectral and LiDAR data in distinguishing ALB and drought stress in poplar forests, which contribute to apply targeted treatments based on the specific stress in poplars in northwest China. [ABSTRACT FROM AUTHOR]

The Russian olive (Elaeagnus angustifolia), which functions as a "dead-end trap tree" for the Asian long-horned beetle (Anoplophora glabripennis) in mixed plantations, can successfully attract Asian long-horned beetles for oviposition and subsequently kill the eggs by gum. This study aimed to investigate gum secretion differences by comparing molecular and metabolic features across three conditions—an oviposition scar, a mechanical scar, and a healthy branch—using high-performance liquid chromatography and high-throughput RNA sequencing methods. Our findings indicated that the gum mass secreted by an oviposition scar was 1.65 times greater than that secreted by a mechanical scar. Significant differences in gene expression and metabolism were observed among the three comparison groups. A Kyoto Encyclopedia of Genes and Genomes annotation and enrichment analysis showed that an oviposition scar significantly affected starch and sucrose metabolism, leading to the discovery of 52 differentially expressed genes and 7 differentially accumulated metabolites. A network interaction analysis of differentially expressed metabolites and genes showed that EaSUS1, EaYfcE1, and EaPGM1 regulate sucrose, uridine diphosphate glucose, α-D-glucose-1P, and D-glucose-6P. Although the polysaccharide content in the OSs was 2.22 times higher than that in the MSs, the sucrose content was lower. The results indicated that the Asian long-horned beetle causes Russian olive sucrose degradation and D-glucose-6P formation. Therefore, we hypothesized that damage caused by the Asian long-horned beetle could enhance tree gum secretions through hydrolyzed sucrose and stimulate the Russian olive's specific immune response. Our study focused on the first pair of a dead-end trap tree and an invasive borer pest in forestry, potentially offering valuable insights into the ecological self-regulation of Asian long-horned beetle outbreaks. [ABSTRACT FROM AUTHOR]

Background: Hylurgus ligniperda (Coleoptera: Curculionidae) is a worldwide forest quarantine pest. It is widely distributed, has many host tree species, and possesses strong adaptability. To explore its environmental adaptability and the related molecular mechanisms, we conducted chromosome-level genome sequencing and analyzed the transcriptome under different environmental factors, identifying key expressed genes. Results: We employed PacBio, Illumina, and Hi-C sequencing techniques to assemble a 520 Mb chromosomal-level genome of H. ligniperda, obtaining an N50 of 39.97 Mb across 138 scaffolds. A total of 10,765 protein-coding genes were annotated after repeat masking. Fourteen chromosomes were identified, among which Hyli14 was determined to be the sex chromosome. Survival statistics were tested over various growth periods under high temperature and low humidity conditions. The maximum survival period of adults reached 292 days at 25 °C, 65% relative humidity. In comparison, the maximum survival period was 14 days under 35 °C, 65% relative humidity, and 106 days under 25°C, 40% relative humidity. This indicated that environmental stress conditions significantly reduced adults' survival period. We further conducted transcriptome analysis to screen for potentially influential differentially expressed genes, such as CYP450 and Histone. Subsequently, we performed gene family analysis to gain insights into their functions and interactions, such as CYP450 and Histone. CYP450 genes affected the detoxification metabolism of enzymes in the Cytochrome P450 pathway to adapt to different environments. Histone genes are involved in insect hormone biosynthesis and longevity-regulating pathways in H. ligniperda to adapt to environmental stress. Conclusions: The genome at the chromosome level of H. ligniperda was assembled for the first time. The mortality of H. ligniperda increased significantly at 35 ℃, 65% RH, and 25 ℃, 40% RH. CYP450 and Histone genes played an important role in response to environmental stress. This genome offers a substantial genetic resource for investigating the molecular mechanisms behind beetle invasion and spread. [ABSTRACT FROM AUTHOR]

Simple Summary: The invasive woodwasp Sirex noctilio occasionally shares hosts with the native S. nitobei and other colonizers. The coexistence of these species may significantly impact individual species. We compared coexistence patterns among several colonizers at both stand and tree scales. Spatial scales revealed negative associations (e.g., Asemum striatum, Phaenops sp.) and neutral ones (Ips acuminatus) between woodwasps and other co-colonizing insects. A positive correlation was found between the frequency of woodwasp attacks and the density of trees damaged by Sirex in the current and previous years. At the tree scale, S. noctilio is more abundant in sections where it occurs alone than in sections where it co-occurs with S. nitobei. The distribution and body size of S. noctilio within the tree are unaffected by the presence of S. nitobei. However, S. nitobei was more prevalent in bottom sections when S. noctilio was present and larger in bottom sections where it occurred alone. This result can be attributed to early S. noctilio attacks enhancing the micro-environment of S. nitobei, which provides nutrients for larval development. Sirex noctilio, a European woodwasp, occasionally shares resources with the native S. nitobei and other colonizers in northeast China. The impact of its coexistence on individual species remains unclear. Random sampling was conducted to assess the patterns and extent of insect co-colonization across various spatial scales. Additionally, we analyzed wood sections to determine the density, adult size, and distribution of the two Sirex species. Spatial scales revealed negative associations (Asemum striatum and Phaenops sp.) and neutral ones (Ips acuminatus) between woodwasps and other co-colonizers. Clustering of woodwasps and Phaenops sp. occurred at a small scale (0–7.3 m). Regression analysis showed a positive correlation between the chance of woodwasp attacks and past attacks on the same host, with little impact from other colonization factors. The distribution and body size of S. noctilio within the tree appeared unaffected by S. nitobei's presence. In the presence of S. noctilio, S. nitobei tended to lay eggs in damaged sections. At the stand level, the overall impact of S. noctilio on S. nitobei population density is likely positive because S. nitobei prefer weaker trees, a preference potentially influenced by initial attacks from S. noctilio on healthier hosts. [ABSTRACT FROM AUTHOR]

The pine wood nematode (PWN) uses several Monochamus species as vehicles, through a temporary hitchhiking process known as phoresy, enabling it to access new host plant resources. Monochamus saltuarius acts as a new and major vector of the PWN in Northeastern China, showing lower PWN carrying capacity and a shorter transmission cycle compared to established vectors. The apparently altered symbiotic relationship offers an interesting area for researching the costs and adaptions involved in nematode–beetle, a specialized phoresy. We analyzed the response and fitness costs of M. saltuarius through physiological measurements and transcriptomics. The PWN exerted adverse repercussions on the growth and development of M. saltuarius. The PWN accelerated larval development into pupae, while beetle adults carrying the PWN exhibited an elevated abnormality rate and mortality, and reduced starvation resistance. During the pupal stage, the expression of growth-related genes, including ecdysone-inducible genes (E74EA), cuticle proteins, and chitin genes (CHTs), markedly increased. Meanwhile, the induced immune response, mainly by the IMD and Toll signaling pathways, could be a contributing factor to adult abnormality and mortality. Adult gonads and trachea exhibited enrichment in pathways related to fatty acid elongation, biosynthesis, and metabolism. FASN, ELOVL, and SCD possibly contributed to resistance against PWN. Our research indicated that phoretic interactions between vector beetles and PWN vary throughout the vector's lifespan, particularly before and after entry into the trachea. This study highlighted the fitness costs of immunity and metabolism on the vector beetle, indicating the adaptation mechanisms and evolutionary trade-offs to PWN. [ABSTRACT FROM AUTHOR]

Pine wilt disease (PWD) is known for its high lethality and rapid transmission, earning it the name "cancer of the pine tree". The prompt removal of infested pine trees is an effective measure for preventing and controlling pine wilt disease. Accurate and efficient monitoring technologies are crucial for the scientific prevention and control of this plant disease. Currently, numerous remote sensing monitoring studies have been conducted on pine wilt disease. However, there is limited research on the temporal identification of PWD-infested forest stands over large areas. To build classification models, this study utilized three machine learning algorithms: artificial neural network (ANN), random forest (RF), and support vector machine (SVM). We aimed to investigate the effectiveness of single-temporal and multi-temporal Landsat and Sentinel-2 satellite images PWD-infested forest stands detection. The results indicated that, at a spatial resolution of 30 m, Landsat-9 and Sentinel-2 remote sensing images effectively identified PWD-infested forest stands, with classification accuracies of 77.87% and 78.91%, respectively. Higher spatial resolutions in Sentinel-2 remote sensing images were associated with improved identification capabilities. Furthermore, multi-temporal Landsat satellite data (with a classification accuracy of 85.95%) significantly enhanced the performance of the monitoring model compared to single-temporal Landsat satellite data (with a classification accuracy of 77.87%). The RGI difference was found to be the optimal vegetation index. In conclusion, by combining multi-temporal and single-time-phase Landsat remote sensing data, a monitoring model for PWD-infested forest stands was constructed. It achieved a classification accuracy of 88.26%. In this study, a higher accuracy in identifying pine wilt disease and a lower economic cost were achieved by Landsat and Sentinel images, offering valuable insights for the management of pine wilt disease. [ABSTRACT FROM AUTHOR]

Simple Summary: Symbiotic bacteria play an essential role in the digestion, detoxification, and nutrient supply of bark and ambrosia beetles. They may even promote the invasiveness and adaptability of invasive beetles. However, as a newly invasive pest in China, the diversity and community structure of bacteria associated with Hylurgus ligniperda is still unclear. This hinders our ability to comprehend their invasion mechanism and ecological adaptability. Therefore, this study revealed the differences in the diversity and community composition of associated bacteria in the beetle's elytra, prothorax, and gut. Our findings revealed that the microbial population of the elytra was distinct from that of the prothorax and gut. Additionally, gender disparities existed throughout the bacterial population of elytra. The distribution of associated bacteria in different organs of males and females may indicate that they undertake different ecological functions. This study will help to understand the bacterial communities that may play important roles in Hylurgus ligniperda. Hylurgus ligniperda (Fabricius) (Curculionidae: Scolytinae) is a new invasive pest beetle in China, which colonized the Shandong province, causing devastating damage. Originating in Europe, it has spread to Oceania, Asia, North and South America. Bacterial associates have been frequently reported to play a vital role in strengthening the ecological adaptations of bark and ambrosia beetles. The environmental adaptability of H. ligniperda may be supported by their associated bacteria. Bacterial communities colonizing different body parts of insects may have different functions. However, little is known about the bacteria associated with H. ligniperda and their potential involvement in facilitating the adaptation and invasion of the beetles into new environments. In this study, we employed high-throughput sequencing technology to analyze the bacterial communities associated with male and female adults of H. ligniperda by comparing those colonizing the elytra, prothorax, and gut. Results showed that the bacterial communities of male and female adults were similar, and the elytra samples had the highest bacterial diversity and richness, followed by the gut, while the prothorax had the lowest. The dominant phyla were Proteobacteria, Firmicutes, and Actinobacteriota, while the dominant genera were Serratia, Lactococcus, Rhodococcus, unclassified Enterobacteriaceae, and Gordonia. Among these, Rhodococcus and Gordonia were the specific genera of endobacteria and ectobacteria, respectively. Differences in the distribution of associated bacteria may suggest that they have different ecological functions for H. ligniperda. The results of functional prediction showed that bacteria were enriched in terpenoid backbone biosynthesis, degradation of aromatic compounds, limonene and pinene degradation, neomycin, kanamycin and gentamicin biosynthesis, indicating that they may assist their beetles in synthesizing pheromones, degrading toxic secondary metabolites of host trees, and antagonizing pathogenic fungi. These results help us understand the interaction between H. ligniperda and bacteria and highlight possible contributions to the invasion process. [ABSTRACT FROM AUTHOR]

The Asian longhorn beetle (ALB) Anoplophora glabripennis is one of the most successful and most feared invasive insect species worldwide. This review covers recent research concerning the distribution of and damage caused by ALB, as well as major efforts to control and manage ALB in China. The distribution and destruction range of ALB have continued to expand over the past decade worldwide, and the number of interceptions has remained high. Detection and monitoring methods for the early discovery of ALB have diversified, with advances in semiochemical research and using satellite remote sensing in China. Ecological control of ALB in China involves planting mixtures of preferred and resistant tree species, and this practice can prevent outbreaks. In addition, strategies for chemical and biological control of ALB have achieved promising results during the last decade in China, especially the development of insecticides targeting different stages of ALB, and applying Dastarcus helophoroides and Dendrocopos major as biocontrol agents. Finally, we analyze recommendations for ALB prevention and management strategies based on native range and invasive area research. This information will hopefully help some invaded areas where the target is containment of ALB. [ABSTRACT FROM AUTHOR]

Wood-boring beetles are among the most destructive forest pests. The larvae of some species live in the trunks and are covered by bark, rendering them difficult to detect. Early detection of these larvae is critical to their effective management. A promising surveillance method is inspecting the vibrations induced by larval activity in the trunk to identify whether it is infected. As convenient as it seems, it has a significant drawback. The identification process is easily disrupted by environmental noise and results in low accuracy. Previous studies have proven the feasibility and necessity of adding an enhancement procedure before identification. To this end, we proposed a small yet powerful boring vibration enhancement network based on deep learning. Our approach combines frequency-domain and time-domain enhancement in a stacked network. The dataset employed in our study comprises the boring vibrations of Agrilus planipennis larvae and various environmental noises. After enhancement, the SNR (signal-to-noise ratio) increment of a boring vibration segment reaches 18.73 dB, and our model takes only 0.46 s to enhance a 5 s segment on a laptop CPU. The accuracy of several well-known classification models showed a substantial increase using clips enhanced by our model. All experimental results proved our contribution to the early detection of larvae. [ABSTRACT FROM AUTHOR]