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• 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 (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]

• 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]

• No study verified the factors affecting the dispersal of shoot beetles in Southwest China. • Landscape-level variables are the more important predictor, the roles of the stand-level variables are also important. • The prediction of damage severity distribution of Tomicus spp. highlights the need for forest management improvement. The outbreaks of shoot beetles (Tomicus yunnanensis Kirkendall and Faccoli and Tomicus minor Hartig) have caused widespread tree mortality in Southwest China. However, multi-scale variables explaining the shoot damage ratio (SDR) caused by shoot beetles have never been studied. The objective of this study was to determine the effects of stand-level and landscape-level variables on SDR during outbreaks of shoot beetles in Yunnan pine forests. Sixty-five plots were generated during 2015–2017 based on beetle infestation maps derived from multi-data Landsat images and field survey. Nine explanatory variables were quantified to explain the SDR severity. The forest cover was obtained from a Worldview-3 high‐resolution image. We used the forest resource planning and design survey data to develop landscape context variables. The beetle pressure variable was calculated using beetle infestation maps. The relative importance of the explanatory variables was analyzed using multi-model inference. We established that SDR was higher in the plots that were closer to roads and severely damaged forest areas in the previous year. SDR was negatively affected by edge density (ED) and forest cover, but positively affected by the mean shape index (SHAPE MN) and aspect. Landscape-level variables are probably the more important predictor, stand-level variables also had a significant effect on the shoot beetle outbreak. The prediction models including stand-level variables and landscape-level variables were built. Identifying variables that drive beetle-caused SDR contributed to the improvement of the existing strategies for outbreak control. [ABSTRACT FROM AUTHOR]

• Manipulated infestation revealed the crown spectral signature under pine shoot beetle attack. • 4 weeks' pine shoot beetle shoot-feeding attack turned most shoots from green to red. • Crown heterogenous discoloration resulted in a decline of chlorophyll and water content. • Shoot damage influenced the retrieval accuracy of physiological parameter via hyperspectral data. • 35 spectral variables were evaluated in random forest for identifying shoot damage ratio. Pine shoot beetle (PSB, Tomicus spp.) outbreaks cause widespread Yunnan pine (Pinus yunnanensis Franch) mortality in southwestern China. Early identification of PSB attacks could help forest managers mitigate the infestation before it turns into an outbreak. However, the subtle spectral changes and complex process of PSB-induced crown discoloration make the remote sensing approach difficult. This study employed a manipulated insect infestation experiment to reveal suitable monitoring indicators. Healthy Yunnan pine crowns were infested with PSB adults at different preset densities (light, moderate, and severe) using the bagging method. The crown damage parameters, physiological properties, and corresponding spectral data were systematically measured in time series. Partial least squares regression (PLSR) was used to retrieve crown chlorophyll a+b (Cab) and relative water content (RWC) via band reflectance. Random forest (RF) was used to determine the optimum spectral variables capable of capturing dynamic variations in crown shoot damage ratio (SDR). Results showed that (1) after four weeks' PSB shoot feeding attack, SDR reached saturated (26%-50%) for all damage levels, indicating a crown discoloration "switch point". (2) A continuous decline was found in Cab and RWC at both shoot and crown levels during the whole infestation process, and the crown level decrease was smaller than the shoot level due to crown heterogeneous discoloration. (3) For PLSR retrieving crown Cab and RWC, estimation accuracy of healthy crowns could reach R2 = 0.70, RMSE cv = 14.60 mg/m2 for Cab, and R2 = 0.82, RMSE cv = 1.25% for RWC, respectively. However, PSB early attack impacted these retrieval accuracies. (4) Spectral differences were evident in the visible region (530–600 nm) and near-infrared (NIR) plateau (780–1300 nm) among the preset damage levels. Significant differences in spectral variables (AMP, CI, OSAVI, RD, and SR) were observed between healthy and moderately damaged crowns. (5) In RF modeling, the importance of spectral variables for SDR estimation varied throughout the shoot feeding process. OSAVI, CI, MSI, PSRI, and SR2 were the top indicators that were suitable for identifying SDR ranging from 5% to 50%. SDR could be estimated with an accuracy of R2 = 0.71, RMSE cv = 8.92%, after 4 weeks' infestation. Simultaneously, with the RF model, 4 preset damage levels could be differentiated with an out-of-bag error of 14.94% and a kappa coefficient of 0.8835. In conclusion, this study mainly examined the physiological and spectral signatures of PSB early attacked crowns, and provided optimum spectral variables and models which will further help unmanned aerial vehicle (UAV) and satellite remote sensing identify PSB infestation at the early stages. [ABSTRACT FROM AUTHOR]

• Pine wilt disease was systematically and accurately divided into four stages. • Faster R-CNN and YOLOv4 were used to detect pine wilt disease. • Early-stage infected trees were identified from multispectral images. • Considering of broadleaf trees can improve the accuracy of early-stage detection. • Proposing a feasible method to detect pine wilt disease in mixed forests. Pine wilt disease (PWD) is a global devastating threat to forest ecosystems. Therefore, a feasible and effective approach to precisely monitor PWD infection is indispensable, especially at the early stages. However, a precise definition of "early stage" and a rapid and high-efficiency method to detect PWD infection have not been well established. In this study, we systematically divided the PWD infection into green, early, middle, and late stages based on the needle color, the resin secretion, and whether the pine wood nematode (PWN) was carried. Simultaneously, an unmanned aerial vehicle (UAV) equipped with multispectral cameras was used to obtain images. Two target detection algorithms (Faster R-CNN and YOLOv4) and two traditional machine learning algorithms based on feature extraction (random forest and support vector machine) were employed to realize the recognition of infected pine trees. Moreover, we took into consideration of the influence of green broad-leaved trees on the identification of pine trees at the early stage of PWD infection. We obtained the following results: (1) the accuracy of Faster R-CNN (60.98–66.7%) was higher than that of YOLOv4 (57.07–63.55%), but YOLOv4 outperformed in terms of model size, processing speed, training time, and testing time; (2) although the traditional machine learning models had higher accuracy (73.28–79.64%), they were not able to directly identify the object from the images; (3) the accuracy of early detection of PWD infection showed an increase of 3.72–4.29%, from 42.36–44.59% to 46.08–48.88%, when broad-leaved trees were considered. In this study, the combination of UAV-based multispectral images and target detection algorithms allowed us to monitor the occurrence of PWD and obtain the distribution of infected trees at an early stage, which can provide technical support for the prevention and control of PWD. [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]

Abstract In insects, olfaction plays a critical role in locating hosts, recognizing mates, and selecting oviposition sites. The Asian long-horned beetle (Anoplophora glabripennis Motschulsky) feeds on 43 species of trees in 15 families, but its chemosensory mechanisms are poorly understood. Herein, genes encoding 61 odorant-binding proteins (OBPs) were identified from the published genome and our previous A. glabripennis transcriptomic data. To investigate their physiological functions, we performed expression profiling of all Agla OBPs in the antennae, legs, and maxillary palps of both sexes. Phylogenetic analysis clustered A. glabripennis OBPs into four subgroups, comprising 29 Minus-C OBPs, 15 Antennae-binding proteins (ABPIIs), 10 Classic OBPs, and one Plus-C OBP. 12 Agla OBP genes were expressed specifically in antennae, and Agla OBP3, Agla OBP18, Agla OBP21, Agla OBP33, Agla OBP41, Agla OBP45, and Agla OBP47 were particularly highly expressed in male antennae. These proteins may function in the detection of female sex pheromones. Agla OBP23 and Agla OBP44 were preferentially expressed in maxillary palps. Expression profiling suggests that many OBPs may be involved in olfaction and gustation, in addition to carrying hydrophobic molecules. The Agla OBPs family has acquired functional diversity concurrently with functional constraints, and further investigation could provide insight into the roles of OBPs in chemoreception. Highlights • glabripennis OPBs were identified and revised from the genome and previous transcriptomic data. • Phylogenetic analysis clustered A. glabripennis OBPs into four subgroups. • Expression profiling revealed numerous antennae-specific OBPs, especially in males. • OBPs may function in olfaction and gustation, besides carrying hydrophobic molecules. [ABSTRACT FROM AUTHOR]

Chlorophorus caragana Xie & Wang is a destructive wood-boring beetle that damages Caragana spp. bushes and is distributed in desert areas in north-west China. Using scanning electron microscopy and transmission electron microscopy, we observed the morphology and ultrastructure of antennal and posterior abdominal sensilla in C. caragana females, to discuss the putative functions of these sensilla in host location and oviposition behaviors. In total, seven types (24 subtypes) of sensilla were located on the antenna and posterior abdomen. On the antenna, there were Böhm's bristles (BB.); four subtypes of sensilla chaetica (Ch.1–Ch.4) characterized by non-porous surfaces and sensillum-lymph cavities without dendrites; two subtypes of sensilla trichodea (Tr.1 and Tr.2) with a tip pore and dendrites surrounded by dendritic sheaths; dome-shaped sensilla (Dom.) emerging from a deep cavity with one tip pore; four subtypes of sensilla basiconica (Ba.1–Ba.4) and one type of sensilla auricillica (Au.) with a porous cuticular surface and dendrites in the sensillum-lymph cavity; and one type of sensilla styloconica (Sty.) with grooves on the cuticular wall. On the posterior abdomen, there were four subtypes of sensilla chaetica (Ch.5–Ch.8); three subtypes of sensilla trichodea (Tr.3–Tr.5); and three subtypes of sensilla basiconica (Ba.5–Ba.7; Ba.5 had no groove in the cuticular wall, Ba.6 had one tip pore, and Ba.7 was located in a cuticular cavity). The antennal sensilla were believed to be mechanosensitive, chemosensitive, and sensitive to humidity and temperature, and to play roles in mating, host location and oviposition. The abdominal sensilla are believed to be related to oviposition behaviors. [ABSTRACT FROM AUTHOR]

Abstract: In plants attacked by insects, metabolic changes can reflect the direct and indirect ability of those plants to resist infestation. However, the metabolic pathways involved in this process remain unclear, especially for plants which belong to ancient Tertiary relict taxon. To analyze the changes in metabolites and identify specific metabolic patterns induced by herbivorous and continuous mechanical wounding, the metabolism of Ammopiptanthus mongolicus seedlings damaged by Orgyia ericae Germar or continuous mechanical wounding were analyzed using nuclear magnetic resonance (NMR) combined with multivariate data analysis (MVDA). Principal component analysis (PCA) and orthogonal signal correction projections to latent structure discriminate analysis (OPLS-DA) showed that O. ericae feeding and mechanical wounding induced different changes in the metabolic profile of A. mongolicus both in local and systemic leaves. O. ericae feeding was associated with higher concentrations of many primary and secondary metabolites in local and systemic leaves than continuous mechanical wounding. In this way, the response of A. mongolicus to wounding was shown to be both specific to the metabolism, systemic, and to involve both primary and secondary metabolic pathways. [Copyright &y& Elsevier]

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]