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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]

BACKGROUND: Semanotus bifasciatus Motschulsky (Coleoptera: Cerambycidae) is one of the most destructive wood‐boring pests of Platycladus trees in East Asia, threatening the protection of antique cypresses and urban ecological safety. Early identification of Semanotus bifasciatus attacks can help forest managers mitigate the infestation before it turns into an outbreak. Acoustic detection technology is a non‐destructive and continuous monitoring method with the potential to early identify and accurately evaluate the wood‐boring damage. However, few studies have focused on the detection timing and corresponding acoustic features. In this study, we employed a manipulated insect infestation experiment to identify time windows in which early instar Semanotus bifasciatus larvae are most actively boring and feeding within logs and to identify acoustic features that distinguish larval sounds from typical background noise. RESULTS: The Semanotus bifasciatus larvae produced sounds most frequently between 13:00 and 20:00 while sounds were detectable from the first to the third instar during the larval growth stage, indicating a suitable time window for early detection. The stepwise regression (SR) model was optimal for detecting the larval instar [coefficient of determination (R2) = 0.71, root mean squared error of prediction (RMSEp) = 0.42, and relative percent deviation (RPD) = 3.38] while the best model for predicting larval population size was the partial least squares regression (PLSR) model (R2 = 0.97, RMSEp = 61.96, and RPD = 28.87). CONCLUSION: This study developed an acoustic method for identifying the early attack of Semanotus bifasciatus (including detection time window, feature variables and models for larval instar prediction and population size estimation). This technology integrated with internet of things (IoT) framework can be of value in developing an automated monitoring system for forest wood borer, and provide necessary guidance for integrated pest management (IPM). © 2022 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Acoustic detection technology is a new method for early monitoring of wood-boring pests, and the effective denoising methods are the premise of acoustic detection in forests. This paper used sensors to record Semanotus bifasciatus larval feeding sounds and various environmental noises, and two kinds of sounds were mixed to obtain the noisy feeding sounds with controllable noise intensity. Then, the time domain denoising models and frequency domain denoising models were designed, and the denoising effects were compared using the metrics of a signal-to-noise ratio (SNR), a segment signal-noise ratio (SegSNR), and log spectral distance (LSD). In the experiments, the average SNR increment could achieve 17.53 dB and 11.10 dB using the in the test data using the time domain features and frequency domain features, respectively. The average SegSNR increment achieved 18.59 dB and 12.04 dB, respectively, and the average LSD between pure feeding sounds and denoised feeding sounds were 0.85 dB and 0.84 dB, respectively. The experimental results demonstrated that the denoising models based on artificial intelligence were effective methods for S. bifasciatus larval feeding sounds, and the overall denoising effect was more significant, especially at low SNRs. In view of that, the denoising models using time domain features were more suitable for the forest area and quarantine environment with complex noise types and large noise interference. [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 cytochrome P450 enzymes encoded by the Halloween genes - spook ( spo), phantom ( phm), disembodied ( dib), shadow ( sad), and shade ( shd) - catalyze a series of hydroxylation steps resulting in the active molting hormone 20-hydroxyecdysone (20E). This study investigated 20E and ecdysone titers and the expression profile of Halloween genes and ecdysone receptor ( EcR) during larval, pupal, and adult stages in seabuckthorn carpenterworm, Holcocerus hippophaecolus Hua ( Lepidoptera: Cossidae). Hh-spo, Hh-phm, Hh-dib, and Hh-sad showed predominant expression in the prothoracic gland at the larval stage, whereas Hh-shd and Hh-EcR were significantly expressed in the fat body. The mRNA levels of Hh-spo, Hh-phm, Hh-dib, Hh-shd, Hh-sad, and Hh-EcR were lowest from late October to middle April, when the insects were in overwintering dormancy, but began to increase from May each year, when the insects were terminating quiescence. Concomitant with the changes in these genes, 20E and ecdysone titers gradually increased during the 4-year life cycle of H. hippophaecolus. These data indicate that the seasonal expressions of Hh-spo, Hh-phm, Hh-shd, and Hh-EcR play crucial roles in quiescence of the overwintering period, and are responsible for the long larval phase and the exact timing and amplitude of the ecdysteroid titer required for the coordination of growth and development in H. hippophaecolus. [ABSTRACT FROM AUTHOR]

Ginkgo biloba is a typical relic plant that rarely suffers from pest hazards. This study analyzed the pattern of G. biloba pest hazards in Beijing; tested the antifeedant activity of G. biloba extracts, including ginkgo flavonoids, ginkgolide, and bilobalide, against Hyphantria cunea larvae; determined the activities of glutathione transferase (GSTs), acetylcholinesterase (AChE), carboxylesterase (CarE) and mixed-functional oxidase (MFO), in larvae after feeding on these G. biloba secondary metabolites; and screened for effective botanical antifeedants in the field. In this study, no indicators of insect infestation were found for any of the examined leaves of G. biloba; all tested secondary metabolites showed significant antifeedant activity and affected the activity of the four larval detoxifying enzymes. Ginkgolide had the highest antifeedant activity and the most significant effect on the detoxifying enzymes (P<0.05). Spraying leaves with G. biloba extracts or ginkgolide both significantly repelled H. cunea larvae in the field (P<0.05), although the former is more economical and practical. This study investigated the antifeedant activity of G. biloba secondary metabolites against H. cunea larvae, and the results provide new insights into the mechanism of G. biloba pest resistance. This study also developed new applications of G. biloba secondary metabolites for effective pest control. [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]