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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]

The mutualistic symbiosis relationship between the gut microbiome and their insect hosts has attracted much scientific attention. The native woodwasp, Sirex nitobei, and the invasive European woodwasp, Sirex noctilio, are two pests that infest pines in northeastern China. Following its encounter with the native species, however, there is a lack of research on whether the gut microbiome of S. noctilio changed, what causes contributed to these alterations, and whether these changes were more conducive to invasive colonization. We used high-throughput and metatranscriptomic sequencing to investigate S. noctilio larval gut and frass from four sites where only S. noctilio and both two Sirex species and investigated the effects of environmental factors, biological interactions, and ecological processes on S. noctilio gut microbial community assembly. Amplicon sequencing of two Sirex species revealed differential patterns of bacterial and fungal composition and functional prediction. S. noctilio larval gut bacterial and fungal diversity was essentially higher in coexistence sites than in separate existence sites, and most of the larval gut bacterial and fungal community functional predictions were significantly different as well. Moreover, temperature and precipitation positively correlate with most of the highly abundant bacterial and fungal genera. Source-tracking analysis showed that S. noctilio larvae at coexistence sites remain dependent on adult gut transmission (vertical transmission) or recruitment to frass (horizontal transmission). Meanwhile, stochastic processes of drift and dispersal limitation also have important impacts on the assembly of S. noctilio larval gut microbiome, especially at coexistence sites. In summary, our results reveal the potential role of changes in S. noctilio larval gut microbiome in the successful colonization and better adaptation of the environment. [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]

BACKGROUND: Pine wilt disease (PWD) outbreaks have affected extensive areas of South China's forests, but the factors explaining landscape patterns of pine mortality are poorly understood. The objective of this study was to determine the relative importance of stand structure, topography, landscape context, and beetle pressure in explaining PWD severity. During 2020–2021, we identified 66 plots based on mapped PWD infestation severity. We built PWD infestation maps for 2019–2021 through field surveys. Stand structure and topography were obtained from Forest Resources Management 'One Map' and elevation raster data. We then used 'One Map' and PWD infestation maps to determine landscape context and beetle pressure variables at different spatial scales. The relative importance of 12 explanatory variables was analyzed using multi‐model inference. RESULTS: In this study, we show that: (i) 1 km was the best spatial scale related to pine mortality, and (ii) models including landscape context and beetle pressure were much better at predicting pine mortality than models using only stand‐level variables. CONCLUSION: Landscape‐level variables, particularly beetle pressure, were the most consistent predictors of subsequent pine mortality within susceptible stands. These results may help forest managers identify locations vulnerable to PWD and improve existing strategies for outbreak control. © 2023 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Simple Summary: Sirex noctilio, an invasive woodwasp, together with Sirex nitobei, a native woodwasp, are potentially harmful to numerous pines in China. To investigate the flight capacity of these two woodwasp species in China, we performed laboratory measurements with a tethered-flight mill system. Our results indicate that S. noctilio can fly over a great distance and for a longer duration than S. nitobei. Nematode parasitism had no significant effect on the flight capacity of S. noctilio and S. nitobei. For both sexes of S. noctilio, post-eclosion-day (PED) age and body mass significantly influenced their flight capacity, and their flight capacity decreased with PED age. For S. nitobei, PED age did not significantly affect its flight capacity, while body mass significantly affected its flight capacity. From multiple regression analysis, PED age and body mass were major factors influencing the flight capacity of both Sirex species. Sirex noctilio F. is an invasive woodwasp that causes pine mortality in plantations in China. Sirex nitobei M. is a native woodwasp in large areas of China. In this study, the flight capacity of the two woodwasps was studied and compared using a tethered-flight mill system to find individual factors affecting the flight capacity. After flight bioassays, woodwasps were dissected to determine nematode infestation. Post-eclosion-day (PED) age significantly influenced the flight capacity of S. noctilio females and males; as woodwasps become older, their flight capacity decreased. For S. nitobei, PED age did not significantly affect their flight capacity. In general, the flight capacity of S. noctilio was greater than that of S. nitobei. Females flew further and for longer than males for both Sirex species. The Deladenus spp. parasitism status of the two Sirex species did not significantly affect their flight performance parameters. PED age and body mass were key individual factors significantly affecting the flight capacity of the two Sirex species. In this study, detailed and accurate tethered-flight parameters of S. noctilio and S. nitobei were obtained. Although this is different from natural flight, it also provides us substantial laboratory data on their flight capacity, and facilitates risk analysis of the two woodwasp species. [ABSTRACT FROM AUTHOR]

Pine wilt disease (PWD) caused by the pine wood nematode (PWN) is China's most serious forest disease in recent decades. Its complex disease system with unclear pathogenesis and differentiated pathogenicity makes it challenging to manage and control. PWD has spread rapidly in Northeast and Northwest China in recent years, exceeding previous predictions and the traditional understanding of its potential distribution. This paper reviewed the comprehensive risk of PWD in Northeast and Northwest China through the occurrence of influencing factors. Regarding PWN's temperature resistance, all regions of China are suitable for PWD. In terms of altitude, the PWD system is mainly distributed below 1000 m. In China, Pinus and Larix species are confirmed host trees of PWN, while Monochamus alternatus and M. saltuarius are confirmed vector insects of PWN. In this case, PWD may occur in all low-altitude pine forests in China. Northeast China has a higher risk than Northwest China due to its distribution of suitable host trees and vector beetles at low altitudes. To confront the threat, two scientific bottlenecks are required to be demonstrated. The first is the pathogenicity of Chinese PWN strains to Chinese Picea and Abies species. The other is the geographical distribution and highest altitude distribution of other Monochamus species in the Palaearctic region of China and their PWN transmission ability. We also suggest strengthening plant quarantining in Northeast China. In conclusion, this review comprehensively analyzes the risk of PWD in Northeast and Northwest China in terms of temperature, altitude, host trees, and vector insects. It provides a new perspective and reference for the management and research of PWD in China. [ABSTRACT FROM AUTHOR]

Pine wilt disease (PWD) has caused huge economic and environmental losses since it invaded China. Although early monitoring is an effective way to control this hazard, the monitoring window for the early stage is hard to identify, and varies in different hosts and environments. We used UAV-based multispectral images of Pinus thunbergii forest in East China to identify the change in the number of infected trees in each month of the growing season. We built classification models to detect different PWD infection stages by testing three machine learning algorithms—random forest, support vector machine, and linear discriminant analysis—and identified the best monitoring period for each infection stage (namely, green attack, early, middle, and late). From the obtained results, the early monitoring window period was determined to be in late July, whereas the monitoring window for middle and late PWD stages ranged from mid-August to early September. We also identified four important vegetation indices to monitor each infection stage. In conclusion, this study demonstrated the effectiveness of using machine learning algorithms to analyze multitemporal multispectral data to establish a window for early monitoring of pine wilt disease infestation. The results could provide a reference for future research and guidance for the control of pine wilt disease. [ABSTRACT FROM AUTHOR]

The invasive pest Dendroctonus valens has spread to northeast China, causing serious economic and ecological losses. Early detection and disposal of infested trees is critical to prevent its outbreaks. This study aimed to evaluate the potential of an unmanned aerial vehicle (UAV)-based hyperspectral image for early detection of D. valens infestation at the individual tree level. We compared the spectral characteristics of Pinus tabuliformis in three states (healthy, infested and dead), and established classification models using three groups of features (reflectance, derivatives and spectral vegetation indices) and two algorithms (random forest and convolutional neural network). The spectral features of dead trees were clearly distinct from those of the other two classes, and all models identified them accurately. The spectral changes of infested trees occurred mainly in the visible region, but it was difficult to distinguish infested from healthy trees using random forest classification models based on reflectance and derivatives. The random forest model using spectral vegetation indices and the convolutional neural network model performed better, with an overall accuracy greater than 80% and a recall rate of infested trees reaching 70%. Our results demonstrated the great potential of hyperspectral imaging and deep learning for the early detection of D. valens infestation. The convolutional neural network proposed in this study can provide a reference for the automatic detection of early D. valens infestation using UAV-based multispectral or hyperspectral images in the future. [ABSTRACT FROM AUTHOR]

Outbreaks of pine shoot beetles (Tomicus spp.) have caused widespread tree mortality in Southwest China. However, the understanding of the role of climatic drivers in pine shoot beetle outbreaks is limited. This study aimed to characterize the relationships between climate variables and pine shoot beetle outbreaks in the forests of Yunnan pine (Pinus yunnanensis Franch) in Southwest China. The pine shoot beetle-infested total area from 2000 to 2017 was extracted from multi-data Landsat images and obtained from field survey plots. A temporal prediction model was developed by partial least squares regression. The results indicated that multi consecutive year droughts was the strongest predictor, as such a condition greatly reduced the tree resistance to the beetles. The beetle-infested total area increased with spring temperature, associated with a higher success rate of trunk colonization and accelerated larval development. Warmer temperatures and longer solar radiation duration promoted flight activity during the trunk transfer to the shoot period and allowed the completion of sister broods. Multi consecutive year droughts combined with the warmer temperatures and higher solar radiation duration could provide favorable conditions for shoot beetle outbreaks. Generally, identifying the climate variables that drive pine shoot beetle outbreaks could help improve current strategies for outbreak control. [ABSTRACT FROM AUTHOR]

The red turpentine beetle (Dendroctonus valens LeConte) has caused severe ecological and economic losses since its invasion into China. It gradually spreads northeast, resulting in many Chinese pine (Pinus tabuliformis Carr.) deaths. Early detection of D. valens infestation (i.e., at the green attack stage) is the basis of control measures to prevent its outbreak and spread. This study examined the changes in spectral reflectance after initial attacking of D. valens. We also explored the possibility of detecting early D. valens infestation based on spectral vegetation indices and machine learning algorithms. The spectral reflectance of infested trees was significantly different from healthy trees (p < 0.05), and there was an obvious decrease in the near-infrared region (760–1386 nm; p < 0.01). Spectral vegetation indices were input into three machine learning classifiers; the classification accuracy was 72.5–80%, while the sensitivity was 65–85%. Several spectral vegetation indices (DID, CUR, TBSI, DDn2, D735, SR1, NSMI, RNIR•CRI550 and RVSI) were sensitive indicators for the early detection of D. valens damage. Our results demonstrate that remote sensing technology could be successfully applied to early detect D. valens infestation and clarify the sensitive spectral regions and vegetation indices, which has important implications for early detection based on unmanned airborne vehicle and satellite data. [ABSTRACT FROM AUTHOR]

• Multi-temporal hyperspectral images were used to detect the PWN infestation. • Absolute spectral data and seasonal changes data were compared. • The second derivative in the green band (525 nm) and the first derivative in the red-edge region (728 nm) were identified as the most responsive features for early detection of PWN. • The change value is more suitable for detection in the late stage, while the absolute value is more effective in early detection. The pine wood nematode (PWN) is one of the most threatening pests of pine forests in China. An essential management response involves felling and removing the infested trees before the PWN can spread over large areas, but this requires early detection. In this study, we analyzed the temporal changes in the spectral signatures of healthy and infested trees throughout the entire growing season (May to October) using unmanned aerial vehicle (UAV) hyperspectral images (HSI). To explore the potential of these seasonal spectral changes in detecting PWN, we investigated the separability of healthy and infested trees using both absolute values and changes in values. A random forest (RF) classifier was applied to separate healthy and infested trees based on reflectances, derivatives, vegetation indices (VIs), and their seasonal change values. We obtained the following results: (1) the seasonal changes of tree crown spectra following a PWN infestation were similar to those observed using absolute spectral values, though the latter performed better in early detection; (2) in the early stage of infestation (June and July), the green and red-edge regions contained the most sensitive bands, whereas the near-infrared portion played a more important role in later stages; (3) derivatives achieved higher overall accuracy (OA) than the reflectance in the early stage of PWN infestation (June and July); (4) in June, the Pigment Specific Simple Ratio (PSSR) had the highest separability (OA = 0.77) for PWN infestation, followed by the Plant Senescence Reflectance Index (PSRI) and the Normalized Difference Red-edge Index (NDRE), both with a OA of 0.70. In July, PSRI, Red Edge Normalized Difference Vegetation Index (RENDVI), and the Modified Red Edge Simple Ratio (MRESR) had the highest OA of 0.77. These VIs were calculated based on the red-edge regions. In August, RENDVI achieved the best accuracy (0.87), followed by the Normalized Difference Vegetation Index (NDVI, OA = 0.83) and the Plant Stress Index (PSI, OA = 0.80). In September and October, PSRI, PSI, the Greenness Index (GI), and RENDVI showed the strongest separability (0.87 to 0.90). Similar results were obtained using change values of VIs. In June, RENDVI, PSI, and NDVI showed the highest accuracy (OA = 0.73). In July, MRESR had the best accuracy (0.77), followed by RENDVI (0.73) and PSI (0.73). In the late stage of PWN infestation, NDVI, PSRI, PSI, RENDVI, GI, and PSSR obtained the highest accuracies (0.83 to 0.93), surpassing the accuracy achieved using absolute spectra; (5) in RF classification model, seasonal variation values derived from reflectances, derivatives, and VIs performed well in the late stages of the PWN infestation (September and October) but were not as good as absolute values in the early and middle stages (June to August). Our study explored the potential of seasonal changes in UAV spectra for early detection of forest pests. [ABSTRACT FROM AUTHOR]

The Red Turpentine Beetle (Dendroctonus valens) is a forest pest that invaded China from North America. There is few research on the damage characteristics of D. valens in China, particularly given the changes in its biological and ecological characteristics compared to its original habitat. The impact of this exotic bark beetle native insects is also insufficiently studied. In our study, we felled 12 damaged Pinus tabuliformis trees, categorizing them into three stages of attack: green, yellow, and red. Native trunk-boring beetles and natural enemy insects colonizing the roots, trunks, and branches were counted and identified. Our observations revealed a significantly higher density of D. valens in the green-attack stage at the base of Chinese pine trunks compared to the other stages (P =0.028). At the roots, densities of D. valens in the green-attack stage significantly differed from those in the red-attack stage (P =0.048). We identified a total of 13 species of native trunk-boring beetles and 2 species of natural enemy insects colonizing the injured trees. Native beetle abundance, species richness, and Shannon diversity indices increased considerably from the green to yellow stages (with almost all significant differences in roots, trunks and branches). The attack stages were the most significant factor in determining community composition, followed by the relative moisture content of the phloem (including cambium), trunk/branch diameter, relative height above ground, and the section of the tree (trunk/branch). Our research revealed the colonization times and locations of these species as well as the temporal-spatial niches of each species. Additionally, our findings demonstrated that D. valens was more active, and colonized the hosts earlier than all native trunk-boring beetles. Most native species exhibited neither spatial overlap nor competitive interaction with D. valens. Our survey did not identify any natural enemies of D. valens. The invasion by D. valens has resulted in increased mortality and degradation of Chinese pines, thereby creating favorable conditions for the proliferation of native trunk-boring beetles. We recommend the implementation of management strategies during the green-attack stage in newly invaded areas to effectively control D. valens , which could also mitigate its impact on local insect populations. Felling trees in the yellow and red stages does not contribute to the control of D. valens. • Thirteen species of native trunk-boring beetles cohabitate with D. valens on pine. • D. valens established colonization earlier than other native trunk-boring beetles. • The population of D. valens was small when crown of the infested tree turned red. • The invasion of D. valens has led to an increase in native trunk-boring beetles. • Felling trees with discolored crowns does not effectively control D. valens. [ABSTRACT FROM AUTHOR]

Background: Pine wilt disease (PWD) is a major ecological concern in China that has caused severe damage to millions of Chinese pines (Pinus tabulaeformis). To control the spread of PWD, it is necessary to develop an effective approach to detect its presence in the early stage of infection. One potential solution is the use of Unmanned Airborne Vehicle (UAV) based hyperspectral images (HIs). UAV-based HIs have high spatial and spectral resolution and can gather data rapidly, potentially enabling the effective monitoring of large forests. Despite this, few studies examine the feasibility of HI data use in assessing the stage and severity of PWD infection in Chinese pine. Method: To fill this gap, we used a Random Forest (RF) algorithm to estimate the stage of PWD infection of trees sampled using UAV-based HI data and ground-based data (data directly collected from trees in the field). We compared relative accuracy of each of these data collection methods. We built our RF model using vegetation indices (VIs), red edge parameters (REPs), moisture indices (MIs), and their combination. Results: We report several key results. For ground data, the model that combined all parameters (OA: 80.17%, Kappa: 0.73) performed better than VIs (OA: 75.21%, Kappa: 0.66), REPs (OA: 79.34%, Kappa: 0.67), and MIs (OA: 74.38%, Kappa: 0.65) in predicting the PWD stage of individual pine tree infection. REPs had the highest accuracy (OA: 80.33%, Kappa: 0.58) in distinguishing trees at the early stage of PWD from healthy trees. UAV-based HI data yielded similar results: the model combined VIs, REPs and MIs (OA: 74.38%, Kappa: 0.66) exhibited the highest accuracy in estimating the PWD stage of sampled trees, and REPs performed best in distinguishing healthy trees from trees at early stage of PWD (OA: 71.67%, Kappa: 0.40). Conclusion: Overall, our results confirm the validity of using HI data to identify pine trees infected with PWD in its early stage, although its accuracy must be improved before widespread use is practical. We also show UAV-based data PWD classifications are less accurate but comparable to those of ground-based data. We believe that these results can be used to improve preventative measures in the control of PWD. [ABSTRACT FROM AUTHOR]

Background: Anoplophora glabripennis (Motschulsky), commonly known as Asian longhorned beetle (ALB), is a wood-boring insect that can cause lethal infestation to multiple borer leaf trees. In Gansu Province, northwest China, ALB has caused a large number of deaths of a local tree species Populus gansuensis. The damaged area belongs to Gobi desert where every single tree is artificially planted and is extremely difficult to cultivate. Therefore, the monitoring of the ALB infestation at the individual tree level in the landscape is necessary. Moreover, the determination of an abnormal phenotype that can be obtained directly from remote-sensing images to predict the damage degree can greatly reduce the cost of field investigation and management. Methods: Multispectral WorldView-2 (WV-2) images and 5 tree physiological factors were collected as experimental materials. One-way ANOVA of the tree's physiological factors helped in determining the phenotype to predict damage degrees. The original bands of WV-2 and derived vegetation indices were used as reference data to construct the dataset of a prediction model. Variance inflation factor and stepwise regression analyses were used to eliminate collinearity and redundancy. Finally, three machine learning algorithms, i.e., Random Forest (RF), Support Vector Machine (SVM), Classification And Regression Tree (CART), were applied and compared to find the best classifier for predicting the damage stage of individual P. gansuensis. Results: The confusion matrix of RF achieved the highest overall classification accuracy (86.2%) and the highest Kappa index value (0.804), indicating the potential of using WV-2 imaging to accurately detect damage stages of individual trees. In addition, the canopy color was found to be positively correlated with P. gansuensis' damage stages. Conclusions: A novel method was developed by combining WV-2 and tree physiological index for semi-automatic classification of three damage stages of P. gansuensis infested with ALB. The canopy color was determined as an abnormal phenotype that could be directly assessed using remote-sensing images at the tree level to predict the damage degree. These tools are highly applicable for driving quick and effective measures to reduce damage to pure poplar forests in Gansu Province, China. [ABSTRACT FROM AUTHOR]

The woodwasp, Sirex noctilio Fabricius, is an exotic pest of Pinus L. in the southern hemisphere and North America, and it is an emerging threat in northeastern China. Adult woodwasps have numerous insect competitors for oviposition substrates, and developing larvae must compete for resources with other subcortical invaders. Its mutualistic fungus Amylostereum areolatum (Fr.) Boidon, is less competitive than many other fungal colonists present in pine ecosystems. This study investigated the effects of incidental, host-colonizing fungi on the growth and development of woodwasp larvae and A. areolatum. Fungi were isolated from dead S. noctilio larvae within galleries (primarily Trichoderma Pers, Ophiostoma Sydow, and Sphaeropsis Sacc.), and effects of these fungi on woodwasp brood survival were investigated via inoculations of S. noctilio -infested logs. Larval mortality was significantly increased in sample logs inoculated with Ophiostoma minus (Hedgc.) Sydow Phlebiopsis gigantea (Fr.) Jülich, Trichoderma atroviride Bissett, Trichoderma viride Pers, and Trichoderma harzianum Rifai. Inoculation of logs with O. minus resulted in the highest mortality and greatest reductions in wood moisture content. When grown on artificial media, these fungi grew faster than and inhibited growth of A. areolatum mycelium. We propose that the adverse effects of incidental fungi on the survival of S. noctilio larvae may be caused at least in part by an indirect mechanism involving inhibition of the fungal symbiont. The findings provide potentially valuable information for suppressing S. noctilio populations using microbial control agents. [ABSTRACT FROM AUTHOR]

Temperature can be a major factor for the distribution of insects, especially among invasive insects. Sirex noctilio (Hymenoptera: Siricidae) has invaded many regions in China, causing enormous ecological and economic losses. We aimed to explore the trend and potential of diffusion by researching the thermal survival limits of S. noctilio. We measured the supercooling point (SCP), critical thermal temperature (CTmax), high lethal temperature (HLT) and low lethal temperature (LLT) for S. noctilio population in China and assessed life stage-related variation in thermal tolerance. Moreover, we determined the temperature tolerance range of S. noctilio and identified the temperature parameters for its potential invasive distribution risk analysis. The SCP of adults was -11.78 ± 0.67 (mean ± SEM), the CTmax was 37.67 ± 0.54, and those of larvae were -20.77 ± 0.44 and 40.53 ± 0.27, respectively. The LLT increased with exposure time, and the HLT was generally near 43°C. S. noctilio adults can tolerate higher temperatures than larvae, and the larvae showed high resistance to cold temperature. We calculated several temperature indexes based on our results, such as the lower temperature threshold (DV0) at -2.7°C, the upper temperature threshold (DV3) at 31°C, the temperature threshold for both heat stress (TTHS) at 35°C and cold stress (TTCS) at -32.5°C. We observed that, S. noctilio was not resistant to high temperatures, its CTmax is slightly lower than the lethal temperature, and the adults were more tolerant than larvae. Our next goal was to combine the temperature tolerance of symbiotic fungi, information on climate change and the current distribution of this species to predict its potential global distribution. [ABSTRACT FROM AUTHOR]

• The red turpentine beetle (RTB) has infested large areas of pines in North China. • Environmental factors played diverse roles at different stages of RTB infestation. • At the incipient stage, RTB damag. • e was mainly related to stand-level factors. • At the epidemic stage, RTB damage was mainly related to landscape-level factors. The red turpentine beetle (RTB), an invasive pest species, has infested large areas of pine forests and caused extensive tree mortality in North China. The ensuing substantial economic and ecological losses make understanding the development and spread of RTB infestations critical. Although some studies have postulated how multiple factors affect bark beetle damage at different stages of population development, knowledge about this mechanism from empirical research is still limited. In recent years, RTB infestations in Heilihe Town of Inner Mongolia and Dahebei Town of Liaoning Province were at different phases (incipient and epidemic stages), which allowed us to explore the possible change mechanism of influencing factors. The present study aimed to identify the critical factors influencing RTB damage and determine whether the primary influencing factors changed during different RTB infestation stages. We established 42 and 40 sample plots in the Heilihe and Dahebei areas and measured the sample plots' canopy cover, slope, aspect, average diameter at breast height (DBH), elevation and RTB attack rate. Sentinel-2 images and trap data were used to obtain landscape-level variables, including host area, edge density and beetle pressure. We then developed generalized linear models to determine the impact of these explanatory variables on RTB damage. Our results found that the average RTB attack rate of the incipient and epidemic areas was, respectively, 5.35% and 31.45%. At the incipient stage, RTB infestations were mainly related to stand-level factors, including canopy cover and aspect. However, at the epidemic stage, RTB infestations were associated with stand (DBH) and landscape-level factors, in which host area and beetle pressure played an important role. Stand and landscape-level factors played diverse roles during different periods of RTB infestations. Such findings are valuable for understanding the colonization pattern of RTB and taking appropriate management interventions in different infestation stages. [ABSTRACT FROM AUTHOR]

Pine wilt disease ( PWD) is considered as the most destructive forest-invasive alien species in China. We measured gas exchange parameters and foliar carbon isotope ratios (δ13C) of different infection phases of Masson pine in order to investigate the effect of Bursaphelenchus xylophilus infection on photosynthetic responses and resource-use efficiency. The results showed that net photosynthetic rate ( Pn), transpiration rate ( T), stomatal conductance ( gs), and internal CO2 concentrations ( Ci) decreased in the infested trees at photosynthetic photon flux density ( PPFD) levels from 0 to 2,000 μmol m−2 s−1 compared with controls. The maximum net photosynthetic rate ( Pmax) was significantly declined in the infected trees than in controls ( p < .05). There also exist significant differences in dark respiration rate ( Rd) among different infection phases ( p < .05), but the value is highest in the middle infection phase, followed by the control and then the terminal infection phase. This indicates that Pinus massoniana plants need to consume more photosynthetic products during the middle infection phase in order to defend against pine sawyer beetle feeding and PWD infection. Isotopic analysis revealed a significant decrease of the foliar δ13C ( p < .05), as much as 2.5‰ lower in the infected trees. The mean leaf N content was about 12.94% less in the middle infection phase and 27.06% less in the terminal infection phase, causing a significant increase of the foliar C:N ratio in infested trees. Both of the net photosynthetic rates and foliar δ13C were linearly correlated with the foliar N content. We also found a significant decrease ( p < .05) of resource-use efficiency in PWD-induced P. massoniana plants, which can be attributed to the closure of stomatal pores and the inactivation or loss of both Rubisco and other key Calvin cycle enzymes. This study highlights the impact of photosynthetic characteristics, foliar carbon isotope ratios, and resource-use efficiency of PWD-induced trees, which can help identify PWD infestations at the photosynthetic and physiological levels so as to better facilitate management actions. [ABSTRACT FROM AUTHOR]

• Infestation patterns of red turpentine beetle were studied at the incipient population levels. • In undisturbed stands, the main driving factors of red turpentine beetle infestations were stand aspect and canopy cover. • In disturbed stands, red turpentine beetle infestations were related to fire and logging intensity, stand mean diameter at breast height and host connectivity. • The preference discrepancies of red turpentine beetle in different stands require timely targeted management measures to control beetle populations. The red turpentine beetle (RTB) Dendroctonus valens is an alien invasive bark beetle that has become one of the most important pests of pine forests in China. In recent years, RTB has spread to the Heilihe area of northern China, where, within a short period of time, its population density has reached an incipient level. Understanding the attack behavior of RTB in the early stages of an infestation can help contain its population and avoid the transition from incipient to outbreak levels. In addition, numerous wildfires and illegal selective logging events in the Heilihe area give us the opportunity to study the attack behavior of RTB in forest stands with different disturbances. In the present study, we explored the infestation pattern of RTB in 20 wildfire-disturbed forests, 19 selectively logged forests and 42 undisturbed forests at the incipient population level. We measured stand and landscape-level variables, including stand mean diameter at breast height (DBH), canopy cover, aspect, elevation, slope and host connectivity. The landscape-level variable of host connectivity was extracted from a Sentinel-2 image through graph theory. In disturbed stands, we also measured bole scorch height and the number of stumps as proxies for fire and logging intensity. Generalized linear models were used to determine the relative importance of these explanatory variables in RTB infestations. Our results showed that wildfire-disturbed and logged stands had higher RTB infestation levels than undisturbed stands and disturbance intensity was the most important predicting variable across all factors. Furthermore, stand mean DBH had a positive relationship with RTB attacks in disturbed stands. In undisturbed stands, stand-level factors such aspect and canopy cover were the main driving factors of RTB attacks rather than host connectivity. However, the role of host connectivity shifted in wildfire-disturbed stands with high fire intensity, where interconnected stands promoted RTB infestations at the 500 m and 700 m scales. Our findings are valuable for identifying stands that are more vulnerable to RTB attacks and prioritizing management interventions aimed at controlling beetle populations. [ABSTRACT FROM AUTHOR]

Contents and Methods: Here we present a detailed analysis of the life history, mobility and habitat requirements of the butterfly Sericinus montelus on the basis of extensive field observations, experimental breeding, capture-mark- recapture (CMR) and transect surveys. Life History: We found that S. montelus has three generations per year and overwinters as pupae on shrub branches in Xiaolongshan. The adults of first generation have a peak of emergence in late April. The second generation emerges at the end of June and the third in early to middle August. Within the study region, larvae of S. montelus are monophagous on Aristolochia contorta. Adults fly slowly and lay eggs in clusters. Key Factors: Life tables show that natural enemies and human activities such as mowing, weeding and trampling during the egg and larval stages are key factors causing high mortality, killing up to 43% of eggs and 72% of larvae thereby limiting population growth and recovery. Population Ecology: The populations of S. montelus in Xiaolongshan have a rather patchy distribution. According to CMR data, adults fly a maximum distance of 700m within a lifespan of 6 days. The host plant A. contorta, grows along the low banks of fields, irrigation ditches and paths, and can be highly affected by agricultural activities, like mowing, weeding and herding, which impact larval survival. Population Maintenance: For S. montelus should mainly focus on reducing agricultural threats to the host plant A. contorta and on increasing habitat connectivity. [ABSTRACT FROM AUTHOR]

As one of the most devastating disasters to pine forests, pine wilt disease (PWD) has caused tremendous ecological and economic losses in China. An effective way to prevent large-scale PWD outbreaks is to detect and remove the damaged pine trees at the early stage of PWD infection. However, early infected pine trees do not show obvious changes in morphology or color in the visible wavelength range, making early detection of PWD tricky. Unmanned aerial vehicle (UAV)-based hyperspectral imagery (HI) has great potential for early detection of PWD. However, the commonly used methods, such as the two-dimensional convolutional neural network (2D-CNN), fail to simultaneously extract and fully utilize the spatial and spectral information, whereas the three-dimensional convolutional neural network (3D-CNN) is able to collect this information from raw hyperspectral data. In this paper, we applied the residual block to 3D-CNN and constructed a 3D-Res CNN model, the performance of which was then compared with that of 3D-CNN, 2D-CNN, and 2D-Res CNN in identifying PWD-infected pine trees from the hyperspectral images. The 3D-Res CNN model outperformed the other models, achieving an overall accuracy (OA) of 88.11% and an accuracy of 72.86% for detecting early infected pine trees (EIPs). Using only 20% of the training samples, the OA and EIP accuracy of 3D-Res CNN can still achieve 81.06% and 51.97%, which is superior to the state-of-the-art method in the early detection of PWD based on hyperspectral images. Collectively, 3D-Res CNN was more accurate and effective in early detection of PWD. In conclusion, 3D-Res CNN is proposed for early detection of PWD in this paper, making the prediction and control of PWD more accurate and effective. This model can also be applied to detect pine trees damaged by other diseases or insect pests in the forest. [ABSTRACT FROM AUTHOR]

Simple Summary: The cold tolerance strategy of Sirex noctilio overwintering larvae was freeze-avoidance and their supercooling points adjusted seasonally to avoid icing damage. The cold hardiness between different populations varied on a spatiotemporal scale; specifically, the harsher the environment, the stronger the cold tolerance of overwintering Sirex noctilio larvae. A tunnel played a certain protective role but did not affect the low temperature parameters limiting the distribution of S. noctilio. We provide experimentally determined low temperature limiting parameters of Sirex noctilio and prove it has the opportunity to spread and colonize in other regions. Sirex noctilio (Hymenoptera: Siricidae) is an invasive pest that has spread and established in many regions worldwide. However, its cold tolerance strategy is still unclear. We measured the supercooling point (SCP) and the lower lethal temperature (LLT) of overwintering S. noctilio larvae during three overwintering periods in four geographically separated populations in China. In addition, using the statistical analysis of the local historical temperature data, we also conducted comprehensive studies of S. noctilio cold tolerance variations and strategies. We measured the SCP of all samples as S. noctilio could survive at its SCP during a short period of exposure (<48 h) and its cold tolerance strategy was freeze-avoidance. The average SCPs of the groups in different spatiotemporal scales were significantly related to average temperature variation with most individuals exhibiting stronger cold hardiness at low ambient temperatures. S. noctilio exhibited a strong cold tolerance and it has the ability to withstand lower temperatures in cold environments. The geographic population showed a positive tendency as the ambient temperature decreased, which would increase its chance of developing in cold regions. [ABSTRACT FROM AUTHOR]

The moth Eogystia hippophaecolus (Hua et al.) is a major threat to sea buckthorn plantations in China. Specific and highly efficient artificial sex pheromone traps have been developed and used to control this pest species. However, the biosynthesis of sex pheromones Z7-14: Ac and E3-14:Ac remains poorly understood. We investigated the female pheromone gland transcriptome of E. hippophaecolus and identified two pheromone biosynthesis-activating neuropeptides (PBANs), two pheromone biosynthesis-activating neuropeptide receptors (PBANrs), five acetyl-CoA carboxylases (ACCs), six fatty acid synthases (FASs), 16 Acyl-CoA desaturases (DESs), 26 reductases (REDs), 13 acetyltransferases (ACTs), one fatty acid transport protein (FATP), one acyl-CoA-binding protein (ACBP), and five elongation of very long-chain fatty acid proteins (ELOs) in pheromone biosynthesis pathways. Additionally, we identified 11 odorant-degrading enzymes (ODEs) and 16 odorant-binding proteins (OBPs), 14 chemosensory proteins (CSPs), two sensory neuron membrane proteins (SNMPs), three odorant receptors (ORs), seven ionotropic receptors (IRs), and six gustatory receptors (GRs). 77 unigenes involved in female pheromone biosynthesis, 31 chemoreception proteins and 11 odorant degradation enzymes were identified, which provided insight into the regulation of the pheromone components and pheromone recognition in the sex pheromone gland, and knowledge pertinent to new integrated pest management strategy of interference pheromone biosynthesis and recognition. Unlabelled Image • Identified 77 unigenes involved in female pheromone biosynthesis • Elucidation of the molecular mechanisms of sex pheromone biosynthesis • Chemoreception proteins were identified indicating pheromone recognition may occur in the sex pheromone gland. [ABSTRACT FROM AUTHOR]

Sirex noctilio F. (Hymenoptera: Siricidae: Siricinae), a new invasive species in China, is a significant international forestry pest which, transported via logs and related wood packing materials, has led to environmental damage and substantial economic loss in many countries around the world. It was first detected in China in 2013, and since then infestations have been found in 18 additional sites. Using a 322 bp fragment of the mitochondrial barcode gene COI, we studied the genetic diversity and structure of S. noctilio populations in both native and invaded ranges, with a specific focus in China. Twelve haplotypes were found across the native and invaded distribution of the pest, of which three were dominant; among these there were only one or two mutational steps between each pair of haplotypes. No obvious genetic structure was found other than in Chinese populations. China has a unique and dominant haplotype not found elsewhere, and compared with the rest of the world, the genetic structure of Chinese populations suggested a multiple invasion scenario. [ABSTRACT FROM AUTHOR]

In recent years, the red turpentine beetle (RTB) (Dendroctonus valens LeConte) has invaded the northern regions of China. Due to the short invasion time, the outbreak of tree mortality corresponded to a low level of damage. Important information about tree mortality, provided by remote sensing at both single-tree and forest stand scale, is needed in forest management at the early stages of outbreak. In order to detect RTB-induced tree mortality at a single-tree scale, we evaluated the classification accuracies of Gaofen-2 (GF2) imagery at different spatial resolutions (1 and 4 m) using a pixel-based method. We also simultaneously applied an object-based method to 1 m pan-sharpened images. We used Sentinel-2 (S2) imagery with different resolutions (10 and 20 m) to detect RTB-induced tree mortality and compared their classification accuracies at a larger scale—the stand scale. Three kinds of machine learning algorithms—the classification and regression tree (CART), the random forest (RF), and the support vector machine (SVM)—were applied and compared in this study. The results showed that 1 m resolution GF2 images had the highest classification accuracy using the pixel-based method and SVM algorithm (overall accuracy = 77.7%). We found that the classification of three degrees of damage percentage within the S2 pixel (0%, <15%, and 15% < x < 50%) was not successful at a forest stand scale. However, 10 m resolution S2 images could acquire effective binary classification (<15%: overall accuracy = 74.9%; 15% < x < 50%: overall accuracy = 81.0%). Our results indicated that identifying tree mortality caused by RTB at a single-tree and forest stand scale was accomplished with the combination of GF2 and S2 images. Our results are very useful for the future exploration of the patterns of spatial and temporal changes in insect pest transmission at different spatial scales. [ABSTRACT FROM AUTHOR]

Sirex noctilio, the Sirex woodwasp, is an invasive pest that causes significant economic damage to native and commercial conifer stands through the introduction of a fungal wood decay pathogen. We combined the latitudes and longitudes of S. noctilio distribution points with historical climate data to predict its potential global distribution using a maximum entropy model implemented in the Maxent software. The annual mean temperature, the mean temperature of the warmest quarter, and the precipitation of the wettest month were important meteorological factors that affected the predictions, probably because they have a strong effect on the development of S. noctilio. Our predictions cover the most recent occurrence sites of S. noctilio in China. We predict that suitable habitats for S. noctilio are currently concentrated between 30° N to 60° N and 25° S to 55° S on the world map. All continents except for Antarctica contain suitable areas for S. noctilio, and such areas account for approximately 26% of the total area of these six continents. Predictions for 2050 and 2070 show that global climate change will affect the distribution of S. noctilio. With a decrease in carbon dioxide emissions, areas of moderate to high habitat suitability for S. noctilio will increase; with an increase in emissions, these areas will decrease. [ABSTRACT FROM AUTHOR]

Abstract: The parasitoid beetle Dastarcus helophoroides (Fairmaire) (Coleoptera: Bothrideridae) is an important parasite of longicorn beetles (Cerambycidae), and has been used in China for the biological control of the Asian longicorn beetle and the Japanese pine sawyer. In this study the antennal morphology and sensillar ultrastructure of D. helophoroides were observed using scanning electron microscopy and transmission electron microscopy. Two types of sensilla trichodea (Tr. 1 and Tr. 2), two types of sensilla basiconica (Ba. 1 and Ba. 2), three types of sensilla chaetica (Ch. 1, Ch. 2 and Ch. 3), and Bohm''s bristles were identified according to the morphology and fine structure of each type of sensilla in both sexes. Ultrastructural studies revealed porous structures on the cuticle wall and dendritic branches in the inner lumen of Tr. 1, Tr. 2, Ba. 1, and Ba. 2, thereby suggesting chemoreceptor functions. No difference in shape, structure, sensilla distribution and typology was observed between the sexes. These structures likely have roles in the host locating and habitat searching behavior of adult D. helophoroides, and suggest future studies on the olfaction and host location behavior of D. helophoroides and other coleopteran parasitoids. [Copyright &y& Elsevier]

Background: Monochamus carolinensis is an important vector of pinewood nematodes in North America that is under quarantine in several countries worldwide. The distribution of M. carolinensis was previously thought to be limited to North America; however, we discovered it during trapping in China in 2022. Using this discovery and information regarding the area of origin, we applied a machine-learning algorithm based on the maximum entropy principle to predict the current and future (2050s, 2070s) potential distribution areas of M. carolinensis using bioclimatic variables., Results: The biological suitability of M. carolinensis was mainly driven by precipitation factors (BIO18, BIO15, BIO19), with 87.18% of the potential distribution areas located in South America, Asia, North America and Africa. Future potential distribution areas of M. carolinensis are predicted to expand to high latitudes, with an average increase of 10 245 874.88 km 2 , and only 6.89% of the current suitable areas will become unsuitable. The potential distribution areas in 2070 are largest under the SSP585 scenario, with a 41.40% predicted increase (52 309 803.61 km 2 ) above the current distribution, mainly reflecting an increase of the marginally and highly suitable areas., Conclusion: The determination of dominant climatic factors and potential distribution areas will help provide an early warning for an M. carolinensis invasion, as well as provide a scientific basis for the spread and outbreak, facilitating development of effective governmental prevention and control measures. © 2023 Society of Chemical Industry., (© 2023 Society of Chemical Industry.)

Monochamus saltuarius (Coleoptera: Cerambycidae) was reported as the vector beetle of the pine wood nematode (PWN, Bursaphelenchus xylophilus) in Japan and Europe. It was first reported to transmitted the PWN to native Pinus species in 2018 in Liaoning Province, China. However, the lack of genomic resources has limited the in-depth understanding of its interspecific relationship with PWN. Here, we obtained a chromosome-level reference genome of M. saltuarius combining Illumina, Nanopore and Hi-C sequencing technologies. We assembled the scaffolds into ten chromosomes (including an X chromosome) and obtained a 682.23 Mb chromosome-level genome with a N50 of 73.69 Mb. In total, 427.67 Mb (62.69 %) repeat sequences were identified and 14, 492 protein-coding genes were predicted, of which 93.06 % were annotated. We described the mth/mthl, P450, OBP and OR gene families associated with the vector beetle's development and resistance, as well as the host selection and adaptation, which serve as a valuable resource for understanding the host adaptation in insects during evolution. This high quality reference genome of M. saltuarius also provide new avenues for researching the mechanism of this synergistic damage between vector beetles and PWN., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Interactions between the decline of Mongolian pine woodlands and fungal communities and invasive pests in northeastern China are poorly understood. In this study, we investigated the fungal communities occurring in three tree samples: the woodwasp Sirex noctilio infested, healthy uninfested and unhealthy uninfested Mongolian pine trees. We analyzed the relationships of the Mongolian pine decline with fungal infection and woodwasp infestation. Twenty-six fungal species were identified from the sampled trees. Each tree sample harbored a fungal endophyte community with a unique structure. Pathogenic fungi richness was four times higher in infested and unhealthy un-infested trees compared to that in healthy uninfested trees. Sphaeropsis sapinea was the most dominant pathogenic fungus in the sampled Mongolian pine trees. The number of S. noctilio was higher than native bark beetles in the declining Mongolian pine trees. The invasion of the woodwasp appeared to be promoted by the fungal infection in the Mongolian pine trees. The incidence of S. noctilio infestation was higher in the fungi infected trees (83.22%) than those without infection (38.72%). S. sapinea population exhibited positive associations with within-tree colonization of S. noctilio and bark beetle. Collectively, these data indicate that the fungal disease may have caused as the initial reason the decline of the Mongolian pine trees, and also provided convenient conditions for the successful colonization of the woodwasp. The woodwasps attack the Mongolian pine trees infected by fungi and accelerated its decline., (© 2021. The Author(s).)

Since 1989, China has established a system of powerful laws and regulations aimed to preserve its rich natural flora and fauna. However, this legislative framework still has shortcomings, in terms of sentencing standards across related crimes and the extent of scientific basis for sentences. Here, we review Chinese biodiversity protection laws and some example cases with the goal of suggesting ways to increase law compliance and thus better protect biodiversity. In particular, our suggestions involve regular updates of threat assessments based on scientific evidence including herbaceous plants, fungi and algae; considering ecological differences among the species groups and ensuing ecological damage and financial profit gained; and a differentiation of punishment between organized and individual crimes, with a preference for custodial sentences for the former and monetary fines for the latter, to comply better with international standards and to minimize the incentive to engage in such conduct.

Eogystia hippophaecolus (Hua et al.) is an important boring pest that primarily damages sea buckthorn, causing large ecological and economic damages in China. In this study, we used scanning electron microscopy to investigate the sensilla on six olfactory tissues of male E. hippophaecolus: antennae, labial palps, external genitals, propodeum, mesopodium, and metapedes. On the antennae, two types of sensillum trichodea, two types of sensillum basiconica, a type of sensillum coeloconica, and Böhm's bristles were found. The labial palps had sensilla trichodea and chaetica. On the external genitals, three types of sensilla trichodea were the only sensilla. Böhm bristles were found on the base of the tibia and at the terminus of the tarsus. Most sensilla were distributed on the tarsus of the three pairs of legs, and notably, a majority of which were sensilla trichodea and sensilla chaetica, were on the pretarsus and telotarsus of the three pairs of legs. In this study, the distribution, number, type, and morphology of the sensilla on six olfactory organs of E. hippophaecolus were determined, which established the foundation for a future immunohistochemical search of olfactory proteins. RESEARCH HIGHLIGHTS: Eogystia hippophaecolus is a serious pest of seabuckthorn. The distribution, number, type, and morphology of olfactory sensilla of E. hippophaecolus are determined. The function and distribution of sensilla are compared with those of other insects., (© 2018 Wiley Periodicals, Inc.)

The gypsy moth from Asia (two subspecies) is considered a greater threat to North America than European gypsy moth, because of a broader host range and females being capable of flight. Variation within and among gypsy moths from China (nine locations), one of the native countries of Asian gypsy moth, were compared using DNA barcode sequences (658 bp of mtDNA cytochrome c oxidase subunit 1 [COI] sequence), together with two restriction site mtDNA markers (NlaIII and BamHI in COI), which is the standard system used to distinguish European gypsy moths from Asian gypsy moths. Relatedness of these populations to gypsy moths from seven other world areas was also examined. The restriction site markers showed that two Chinese populations had both Asian and European haplotypes. DNA barcode sequence divergence between the Asian populations and the European populations was three times greater than the variation within each group. Using Bayesian and parsimonious network analyses, nine previously unknown barcode haplotypes were documented from China and a single haplotype was found to be shared by 55% of the Chinese and some Far Eastern Russian and Japanese individuals. Some gypsy moths from two Chinese populations showed genetic affinity with mtDNA haplotypes from Siberia, Russia, suggesting there could be a cryptic new subspecies in Lymantria dispar (L.) or human-aided movement of moths between these two locations at an earlier point in time. The previously unknown haplotype patterns may complicate efforts to identify Asian gypsy moth introductions and require changes in monitoring and exclusion programs., (© The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

The Eurasian woodwasp Sirex noctilio F. was first detected in Daqing, Heilongjiang Province, in the northeast region of China in 2013. Here, we investigated the S. noctilio's fungal symbiont, Amylostereum areolatum, and insect venom produced in its acid (venom) gland. Overall, seven out of 10 fungal isolates obtained from the mycangia of 10 adult S. noctilio females in this study were identified as A. areolatum. The remaining three isolates were identified as Trichoderma viride, Verticillium dahlia, and Geosmithia pallida, which were probably contaminants that entered during the mycangia-spore extraction process. The enzyme activity bioassay showed that the level of laccase activity of A. areolatum YQL03 in liquid medium is prominently enhanced by insect venom, but was relatively low when venom was not available as an inducer. This study confirms the presence of A. areolatum in S. noctilio specimens from China. The putative heat-stable factors identified in S. noctilio venom may contribute novel information about the pathogenic mechanism of the S. noctilio-A. areolatum pine-killing pest complex on host trees., (© The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

This paper summarizes the results of our study of the pinewood nematode (Bursaphelenchus xylophilus). By population genetic analysis, it was determined that there was no genetic bottle caused by the founder effect and genetic drift in the Chinese invasive population. Multiple invasions with large amounts of nematodes from different sources led to rich genetic diversity in the invasive population. Keeping high genetic diversity in the invasive process may be one of the genetic mechanisms in its successful invasion. By testing interspecies competition, it was shown that, with high fecundity and a strong competitive ability, B. xylophilus outcompeted the native species B. mucronatus in the natural ecosystem during the invasion process. Competitive displacement may be one of the ecological mechanisms of B. xylophilus's invasion. In addition, an unequal interspecific hybridization with introgress was in favor of the invasive species which also accelerated the replacement of B. mucronatus by B. xylophilus. The structures, functions and evolutions of a few important genes that are closely related to the ecological adaptation of pinewood nematodes were studied to explore the molecular mechanism of its ecological adaptations. Further, the resistance and resilience mechanism of the pine ecosystem invaded by pinewood nematodes was also investigated. The results of these studies uncovered a portion of the genetic and ecological mechanisms of PWN's successful invasion and laid a foundation for further study to obtain a comprehensive interpretation of the mechanisms of the nematode invasion. The results also provided a scientific basis for effectively controlling the occurrence and spread of pine wilt disease which is caused by nematodes. Various aspects requiring further investigation are considered.