Search Results (82)

Emerald ash borer (EAB, Agrilus planipennis Fairmaire) is an Asian woodborer that is a destructive pest of ash (Fraxinus spp.) trees throughout North America and in parts of Asia and Europe. It has killed hundreds of millions of ash trees worldwide in the past two decades and has shown some ability to infest novel hosts, most notably white fringetree (Chionanthus virginicus L.). Here, I review the evidence that this beetle can succeed on cultivated olive (Olea europaea L), a close relative of white fringetree. Studies and observations thus far indicate that, while young trees are largely resistant to EAB larval development, adults will oviposit on olive trees, can feed on their foliage and produce viable eggs, and that larger, older and possibly stressed trees have the potential to support larval development to the adult stage in the field. Emerald ash borer will soon interact with cultivated olive trees in the wild in parts of the U.S. and in Europe, and the realized risk to olives by this beetle will be revealed. Full article

The emerald ash borer (EAB), Agrilus planipennis Fairmaire, is an invasive forest pest that is causing a rapid decline in ash (Fraxinus spp.). As EABs spread across North America to 35 U.S. states and 5 Canadian provinces, detection of the pest has proven difficult, especially at low population density sites. Panel traps have been commonly used in detection and monitoring of EAB populations. Over two sampling periods from 2016 through 2019, adult catches and detection rates were compared among four combinations of panel trap color, lure, and crown placement in southern Arkansas, northern Louisiana, and eastern Texas. The four combinations were as follows: (1) dark purple baited with (Z)-3-hexenol alone in the mid–upper crown; (2) light green with (Z)-3-hexenol plus (3Z)-lactone in the mid–upper crown; (3) dark purple with (Z)-3-hexenol in the lower crown; and (4) dark purple with (Z)-3-hexenol plus (3Z)-lactone in the lower crown. Mid–upper tree crown placement, ~13 m, of panel traps were more effective for EAB detection and adult capture, especially of males. The sex pheromone (3Z)-lactone deterred females but attracted males, while (Z)-3-hexenol attracted females. The green panel trap with both lures and mid–upper crown placement did not drastically increase male catches, contrary to previous studies at low EAB densities. The use of (3Z)-lactone on dark purple traps at low crown placements, such as those used in the National Survey Program, is not recommended for EAB detection due to its repellent effect on EAB females. Full article

The early identification of forest wood-boring pests is essential for effective pest management. However, detecting infestation in the early stages is difficult, as larvae, such as the emerald ash borer (EAB), Agrilus planipennis Fairmaire (Coleoptera: Buprestidae), usually feed inside the trees. Acoustic sensors can detect the pulse signals generated by larval feeding or movement, but these sounds are often weak and easily masked by background noise. To address this, we propose a dual-branch time-frequency multi-dilated dense network (DBMDNet) for noise reduction. Our model decouples two denoising training objectives: a magnitude masking decoder for coarse denoising and a complex spectral decoder for further magnitude repair and phase correction. Additionally, to enhance global time-frequency modeling, we use three different multi-dilated dense blocks to effectively separate clean signals from noisy data. Given the difficult acquisition of clean larval activity signals, we describe a self-supervised training procedure that utilizes only noisy larval activity signals directly collected from the wild, without the need for paired clean signals. Experimental results demonstrate that our proposed approach achieves the optimal performance on various evaluation metrics while requiring fewer parameters (only 98.62 k) compared to competitive models, achieving an average signal-to-noise ratio (SNR) improvement of 17.45 dB and a log-likelihood ratio (LLR) of 0.14. Furthermore, using the larval activity signals enhanced by DBMDNet, most of the noise is suppressed, and the accuracy of the recognition model is also significantly improved. Full article

The emerald ash borer (EAB) was found in Kharkiv (Ukraine) in 2022, infesting ash trees in the permanent focus of the ash black sawfly. We aimed to recognize the characteristics of trees that attract EAB. Ash tree defoliation, dieback, epicormic shoots, health condition class, and ash bark beetle infestation were analyzed with EAB presence or absence. The EAB preferred to infest the trees with higher defoliation, epicormic shoots, and ash bark beetle infestation more than in the trees without these symptoms. Despite the deterioration in the health of most trees in the EAB outbreak, some specimens have maintained and even improved their health. This confirms the possibility of selecting resistant trees with subsequent reproduction. Full article

The emerald ash borer (EAB) is an invasive beetle that has killed hundreds of millions of ash trees throughout North America since its arrival. The use of entomopathogenic fungi as part of integrated pest management approaches is considered effective against a wide range of insect pests. The aim of this study was to screen and select locally adapted EAB-associated entomopathogenic fungi with ovicidal effect on EAB eggs under laboratory conditions. The pathogenicity of nine fungal strains, previously isolated from EAB galleries, and the commercial Beauveria bassiana strain GHA was tested. Three of these, Akanthomyces muscarius 48-27, Lecanicillium longisporum 66-14 Lecanicillium psalliotae 59-2, and GHA B. bassiana strain consistently showed significant ovicidal effects and a high percentage of inoculum recovery both from eggs and neonate larvae. The high levels of inoculum recovery from neonate larvae demonstrate that, even after emergence, larvae were infected. The possibility of disrupting EAB’s life cycle at the egg stage through microbial control represents a potential management opportunity that should be explored in future field studies. Future work should also study the effect of EPF on neonate larvae survival and performance. To our knowledge, this is the first study to evaluate the effect of entomopathogenic fungi against the egg stage of EAB. Full article

Wood-boring pests are difficult to monitor due to their concealed lifestyle. To effectively control these wood-boring pests, it is first necessary to efficiently and accurately detect their presence and identify their species, which requires addressing the limitations of traditional monitoring methods. This paper proposes a deep learning-based model called BorerNet, which incorporates an attention mechanism to accurately identify wood-boring pests using the limited vibration signals generated by feeding larvae. Acoustic sensors can be used to collect boring vibration signals from the larvae of the emerald ash borer (EAB), Agrilus planipennis Fairmaire, 1888 (Coleoptera: Buprestidae), and the small carpenter moth (SCM), Streltzoviella insularis Staudinger, 1892 (Lepidoptera: Cossidae). After preprocessing steps such as clipping and segmentation, Mel-frequency cepstral coefficients (MFCCs) are extracted as inputs for the BorerNet model, with noisy signals from real environments used as the test set. BorerNet learns from the input features and outputs identification results. The research findings demonstrate that BorerNet achieves an identification accuracy of 96.67% and exhibits strong robustness and generalization capabilities. Compared to traditional methods, this approach offers significant advantages in terms of automation, recognition efficiency, and cost-effectiveness. It enables the early detection and treatment of pest infestations and allows for the development of targeted control strategies for different pests. This introduces innovative technology into the field of tree health monitoring, enhancing the ability to detect wood-boring pests early and making a substantial contribution to forestry-related research and practical applications. Full article

Endophytes, prevalent in plants, mediate plant–insect interactions. Nevertheless, our understanding of the key members of endophyte communities involved in inhibiting or assisting EAB infestation remains limited. Employing ITS and 16S rRNA high-throughput sequencing, along with network analysis techniques, we conducted a comprehensive investigation into the reaction of endophytic fungi and bacteria within F. bungeana phloem by comparing EAB-infested and uninfected samples. Our findings reveal that EAB infestation significantly impacts the endophytic communities, altering both their diversity and overall structure. Interestingly, both endophytic fungi and bacteria exhibited distinct patterns in response to the infestation. For instance, in the EAB-infested phloem, the fungi abundance remained unchanged, but diversity decreased significantly. Conversely, bacterial abundance increased, without significant diversity changes. The fungi community structure altered significantly, which was not observed in bacteria. The bacterial composition in the infested phloem underwent significant changes, characterized by a substantial decrease in beneficial species abundance, whereas the fungal composition remained largely unaffected. In network analysis, the endophytes in infested phloem exhibited a modular topology, demonstrating greater complexity due to an augmented number of network nodes, elevated negative correlations, and a core genera shift compared to those observed in healthy phloem. Our findings increase understanding of plant–insect–microorganism relationships, crucial for pest control, considering endophytic roles in plant defense. Full article

This research presents a classification methodology for the detection of new or emerging stress in trees using indices derived from hyperspectral data and tests whether existing hyperspectral indices are effective when used as the classification features for this problem. We tested six existing indices—Water Band Index (WBI), Gitelson–Merzlyak B Index (GMb), Normalized Phaeophytization Index (NPQI), Combined Carotenoid/Chlorophyll Ratio Index (CCRI), Photochemical Reflectance Index (PRI), and Red-Edge Chlorophyll Index (CIre)—along with a seventh Test Index—generated as a composite of PRI and Cire—as classification features. Analysis was conducted using data collected from trees with and without emerald ash borer (EAB) infestation to develop a methodology that could be adapted to measure emerging stress from other pathogens or invasive pests in other tree species. Previous work has focused specifically on the identification of damage or stress symptoms caused by a specific pathogen. In this study, we adapted that work to develop a system of classification that can be applied to the identification of stress symptoms from a range of sources, measurable in trees based on spectral response and, in some cases, detectable prior to the onset of visible symptoms that can be measured through human observation. Our data indicate that existing indices derived from hyperspectral data are effective as classification features when measuring spectral responses indicative of emerging stress in trees. Full article

Wood borers, such as the emerald ash borer and holcocerus insularis staudinger, pose a significant threat to forest ecosystems, causing damage to trees and impacting biodiversity. This paper proposes a neural network for detecting and classifying wood borers based on their feeding vibration signals. We utilize piezoelectric ceramic sensors to collect drilling vibration signals and introduce a novel convolutional neural network (CNN) architecture named Residual Mixed Domain Attention Module Network (RMAMNet).The RMAMNet employs both channel-domain attention and time-domain attention mechanisms to enhance the network’s capability to learn meaningful features. The proposed system outperforms established networks, such as ResNet and VGG, achieving a recognition accuracy of 95.34% and an F1 score of 0.95. Our findings demonstrate that RMAMNet significantly improves the accuracy of wood borer classification, indicating its potential for effective pest monitoring and classification tasks. This study provides a new perspective and technical support for the automatic detection, classification, and early warning of wood-boring pests in forestry. Full article

The Emerald ash borer (EAB), Agrilus planipennis Fairmaire, 1888 (Coleoptera: Buprestidae), an invasive phloem-boring beetle, was first detected in the Luhansk Region of Ukraine in 2019. Subsequently, it rapidly expanded its presence to encompass a significant portion of the Kharkiv region and the parks of Kyiv. Previous research has established that the climatic conditions in Luhansk and its neighboring regions are conducive to the EAB, and the absence of a host plant (Fraxinus sp.) does not act as a deterrent to the pest’s expansion in Ukraine. Recognizing the urgency of identifying infested trees, our current research aimed to identify the most attractive EAB forest subcompartments based on forest site conditions and stand structure. Utilizing the MaxEnt model, we achieved an average performance in predicting the potential distribution of the EAB (AUC = 0.842). The six most impactful variables, contributing to 88.2% of the model, include “age of trees, years”, “area of forest subcompartment, ha”, “mean height of trees, m”, “proportion of Fraxinus excelsior in the stand composition, %”, “hygrotope index (humidity level), point”, and “number of neighboring-non-forest subcompartments”. Most likely, EAB occurrence is expected in the driest forest site conditions; the well-lit and warmed-up parts of stands, in particular; small subcompartments surrounded by non-forest landscapes; and forest shelter belts near roads and fields. However, the data obtained can be considered preliminary. To enhance the accuracy of our forecasting, it may be imperative to consider data on road localization, along which the pest can spread passively, as well as dominant wind speed. Full article

Green ash (Fraxinus pennsylvanica) and white ash (F. americana) populations are currently experiencing major declines across their native ranges in North America due to infestation by the exotic insect pest emerald ash borer (Agrilus planipennis). The development of a reliable method for the long-term storage of green and white ash germplasm in the form of embryogenic cultures using cryopreservation would be a considerable aid to ash conservation efforts. We compared recovery percentages of cryopreserved green and white ash embryogenic cultures using vitrification versus slow cooling methods. Three Plant Vitrification Solution 2 (PVS2) exposure durations (40, 60, and 80 min) for vitrification and three DMSO concentrations (5%, 10%, and 15%) for slow cooling were tested for their effects on the percentage of cultures that regrew following cryostorage. Vitrification resulted in a higher overall culture recovery percentage (91%) compared to cultures that were cryostored using the slow cooling approach (39%), and a more rapid initiation of regrowth (5 days versus 2–3 weeks) resulted. Recovery from cryostorage by cultures using the slow cooling approach varied significantly (p < 0.05) between experiments and with genotype (p < 0.05). The recovery of vitrified tissue from cryostorage did not vary with genotype, species, or PVS2 exposure duration (p > 0.05). The vitrification cryopreservation protocol provides a reliable and versatile alternative to the traditional slow cooling method, strengthening our ability to preserve valuable ash germplasm for conservation and restoration. Full article

Ash trees are an important component of both forests and the countryside. Emerging new diseases like ash dieback poses new challenges to Fraxinus spp., which not only have to adapt to global warming but also defend themselves against new threats from pathogenic fungi and insect pests. A new species of fungus, Hymenoscyphus fraxineus, has arrived in Europe from Asia and has severely damaged shoots which alters the structure of ash tree crowns. While some older trees have survived, younger trees are dying en masse, so the only hope is that the surviving trees will produce a younger generation that may be more resistant to the new diseases. The fine roots of ash trees are also attacked by pathogenic oomycetes, and others by Armillaria spp. The current stressed condition of ash trees in Europe is exacerbated by a new threat from insects. Agrillus planipennis, emerald ash borer, migrating from the east (from near Moscow airport) towards the borders of the European Union, killing thousands of ash trees on its way. This raises the question of future prospects for ash cultivation in Europe. This article takes a closer look at the information described in the literature. Full article

Trunk borers are among the most destructive forest pests. The larvae of some species living and feeding in the trunk, relying solely on the tree’s appearance to judge infestation is challenging. Currently, one of the most effective methods to detect the larvae of some trunk-boring beetles is by analyzing the vibration signals generated by the larvae while they feed inside the tree trunk. However, this method faces a problem: the field environment is filled with various noises that get collected alongside the vibration signals, thus affecting the accuracy of pest detection. To address this issue, vibration signal enhancement is necessary. Moreover, deploying sophisticated technology in the wild is restricted due to limited hardware resources. In this study, a lightweight vibration signal enhancement was developed using EAB (Emerald Ash Borer) and SCM (Small Carpenter Moth) as insect example. Our model combines CRN (Convolutional Recurrent Network) and Transformer. We use a multi-head mechanism instead of RNN (Recurrent Neural Network) for intra-block processing and retain inter-block RNN. Furthermore, we utilize a dynamic pruning algorithm based on sparsity to further compress the model. As a result, our model achieves excellent enhancement with just 0.34M parameters. We significantly improve the accuracy rate by utilizing the vibration signals enhanced by our model for pest detection. Our results demonstrate that our method achieves superior enhancement performance using fewer computing and storage resources, facilitating more effective use of vibration signals for pest detection. Full article

RNA interference (RNAi) is a cellular mechanism triggered by double-stranded RNA (dsRNA), in which gene expression is reduced in a sequence-specific manner, allowing development of pest-specific control strategies. Effective delivery of the dsRNA is a hurdle, particularly in systems with endophagous insects such as the emerald ash borer (EAB) Agrilus planipennis, an invasive phloem-feeding beetle that develops beneath the bark of ash trees, Fraxinus spp., causing rapid tree death. We evaluated uptake and bioactivity of dsRNA in green ash (F. pennsylvanica) growing in a greenhouse to investigate the feasibility of delivery through the host plant. To assess dsRNA persistence and distribution, seedlings were exposed to EAB-specific dsRNA using foliar spray and sectioned into different tissue types at selected time-points; RT-PCR and Sanger sequencing were used to detect the exogenous dsRNA. We found dsRNA persistence in plant tissues 21 days after treatment. To evaluate bioactivity, neonate EAB were exposed to treated seedlings and assessed for gene expression and feeding behavior. Results demonstrate gene silencing and a 24% (p = 0.03) reduction in cambial consumption. Our findings provide proof-of-concept for delivery of RNAi to the target insect through the host plant, suggesting the feasibility of RNAi functioning as a sustainable approach for tree protection against EAB. Full article

Emerald ash borer (EAB), Agrilus planipennis, is a phloem-boring beetle, native to East Asia that has become a serious invasive pest of ash (Fraxinus spp.) trees in North America and European Russia since the early 2000s. In 2019, EAB was detected in Ukraine. It had spread over 300 km from the entry point over two years and killed hundreds of Fraxinus excelsior and F. pennsylvanica trees. EAB poses a threat to the ash forests of neighboring European countries, which have already been damaged by the invasive fungus Hymenoscyphus fraxineus. The purpose of this research was (i) to reveal the traits of EAB and the climatic variables that affect its survival; (ii) to predict the EAB expansion range in Ukraine and westward; and (iii) to compare the most significant bioclimatic variables in the native, invasive ranges of EAB, as well as outside these ranges. The results demonstrated the following: (i) in all ranges, EAB has adapted to the seasonal temperature variations; (ii) the MaxEnt model predicted the potential distribution of EAB with high accuracy (AUC = 0.988); the predicted area of EAB invasion covered 87%, 48%, and 32% in Luhansk, Kharkiv, and Donetsk regions, respectively; and (iii) the ranges of climatic variables in EAB-inhabited regions demonstrated the high ecological plasticity of this pest. However, the predictions could be improved by considering forest structure, as well as the localization of roads. Full article