Beetle Infestation Research Articles

An intelligent system for determining the degree of tree bark beetle damage based on the use of generative-adversarial neural networks.

The increasing prevalence of tree bark beetle infestations poses a significant threat to forest ecosystems, leading to detrimental impacts on biodiversity, carbon storage, and timber resources. This study addresses the pressing need for innovative solutions to enhance forest management practices through early detection and assessment of tree health. We developed an intelligent system leveraging multispectral images and generative-adversarial networks (GANs) to accurately determine the extent of bark beetle damage. Recognizing the challenges posed by traditional neural networks, which require vast amounts of labeled training data, we proposed a novel approach that utilizes a GAN architecture. In this system, a discriminator functions as a classifier, effectively trained on both real and synthetically generated data. Our methodology not only reduces the dependency on extensive labeled datasets but also enhances the robustness of the classification process. The results indicate a classification accuracy of 87.5%, demonstrating significant promise for improving detection capabilities even with limited training resources. The implications of this research are profound, offering potential benefits for the forestry industry through optimized management strategies and economic gains. Furthermore, our findings contribute to the preservation of critical ecosystem services by providing a means to monitor forest health effectively. However, the responsible implementation of this technology is paramount. Continuous refinement of the model, integration with traditional ecological knowledge, and ensuring transparency and equitable access to the developed system are essential for maximizing societal benefits. Additionally, addressing risks such as misinterpretation of data, overreliance on technology, and privacy concerns is crucial to minimize unintended consequences. Overall, this research presents a significant advancement in the field of forest health monitoring and establishes a foundation for future developments in intelligent ecological management systems.

Shifts in geographic vulnerability of US corn crops under different climate change scenarios: corn flea beetle (Chaetocnema pulicaria) and Stewart’s Wilt (Pantoea stewartii) bacterium

Abstract Changing climate patterns will likely affect insect pressure on many agricultural crops. Mild winters may decrease the number of insects that experience reduced fecundity or that are killed during hard freezes. This may result in larger populations in subsequent years and allow for range expansion. Direct effects from pests are compounded by indirect effects, such as crop damage resulting from insect-vectored diseases. Corn flea beetle (Chaetocnema pulicaria) infestations have both direct and indirect effects on crops. This beetle is a pest on all types of corn in the United States, including sweet corn and grain corn (sometimes referred to as dent corn). It is responsible for damage to plant foliage and also serves as the primary overwintering vector for Pantoea stewartii bacterium, which causes Stewart’s Wilt, a disease that can severely impact the health and productivity of corn. Evidence suggests that warmer winters will contribute to a geographic range expansion for the corn flea beetle. Here we show the projected northward expansion of economically damaging crop losses caused by Stewart’s Wilt: (A) from 1980 to 2011, (B) projected by mid-century, and (C) projected by end-century. Our work suggests that climate change and associated increasing winter temperatures in the United States will lead to a dramatic increase in the probability of severe damage from corn flea beetle across the United States, including the Corn Belt. Predicted increases in pest and disease pressure will have negative ramifications for corn production and are likely to exacerbate issues associated with specific management tactics, such as pesticide application.

A CARS-SPA-GA Feature Wavelength Selection Method Based on Hyperspectral Imaging with Potato Leaf Disease Classification.

Early blight and ladybug beetle infestation are important factors threatening potato yields. The current research on disease classification using the spectral differences between the healthy and disease-stressed leaves of plants has achieved good progress in a variety of crops, but less research has been conducted on early blight in potato. This paper proposes a CARS-SPA-GA feature selection method. First, the raw spectral data of potato leaves in the visible/near-infrared light region were preprocessed. Then, the feature wavelengths were selected via competitive adaptive reweighted sampling (CARS) and the successive projection algorithm (SPA), respectively. Then, the two sets of wavelengths were reorganized and duplicates were removed, and secondary feature selection was conducted with genetic algorithm (GA). Finally, the feature wavelengths were fed into different classifiers and the parameters were optimized using a real-coded genetic algorithm (RCGA). The experimental results show that the feature wavelengths selected by the CARS-SPA-GA method accounted only for 9% of the full band, and the classification accuracy of the RCGA-optimized support vector machine (SVM) classification model reached 98.366%. These results show that it is feasible to classify early blight and ladybug beetle infestation in potato using visible/near-infrared spectral data, and the CARS-SPA-GA method can substantially improve the accuracy and detection efficiency of potato pest and disease classification.

Comparative metagenomic study unveils new insights on bacterial communities in two pine-feeding Ips beetles (Coleoptera: Curculionidae: Scolytinae).

Climate change has recently boosted the severity and frequency of pine bark beetle attacks. The bacterial community associated with these beetles acts as "hidden players," enhancing their ability to infest and thrive on defense-rich pine trees. There is limited understanding of the environmental acquisition of these hidden players and their life stage-specific association with different pine-feeding bark beetles. There is inadequate knowledge on novel bacterial introduction to pine trees after the beetle infestation. Hence, we conducted the first comparative bacterial metabarcoding study revealing the bacterial communities in the pine trees before and after beetle feeding and in different life stages of two dominant pine-feeding bark beetles, namely Ips sexdentatus and Ips acuminatus. We also evaluated the bacterial association between wild and lab-bred beetles to measure the deviation due to inhabiting a controlled environment. Significant differences in bacterial amplicon sequence variance (ASVs) abundance existed among different life stages within and between the pine beetles. However, Pseudomonas, Serratia, Pseudoxanthomonas, Taibaiella, and Acinetobacter served as core bacteria. Interestingly, I. sexdentatus larvae correspond to significantly higher bacterial diversity and community richness and evenness compared to other developmental stages, while I. acuminatus adults displayed higher bacterial richness with no significant variation in the diversity and evenness between the life stages. Both wild and lab-bred I. sexdentatus beetles showed a prevalence of the bacterial family Pseudomonadaceae. In addition, wild I. sexdentatus showed dominance of Yersiniaceae, whereas Erwiniaceae was abundant in lab-bred beetles. Alternatively, Acidobacteriaceae, Corynebacteriaceae, and Microbacteriaceae were highly abundant bacterial families in lab-bred, whereas Chitinophagaceae and Microbacteriaceae were highly abundant in wild I. accuminatus. We validated the relative abundances of selected bacterial taxa estimated by metagenomic sequencing with quantitative PCR. Our study sheds new insights into bacterial associations in pine beetles under the influence of various drivers such as environment, host, and life stages. We documented that lab-breeding considerably influences beetle bacterial community assembly. Furthermore, beetle feeding alters bacteriome at the microhabitat level. Nevertheless, our study revisited pine-feeding bark beetle symbiosis under the influence of different drivers and revealed intriguing insight into bacterial community assembly, facilitating future functional studies.

Stress Responses to Bark Beetle Infestations among Pine (Pinus sylvestris), Fir (Abies alba), and Beech (Fagus sylvatica) Trees

Insect infestation triggers multiple defense responses in plants, both locally at the infection site and systemically throughout the plant, including the production of feeding deterrents, toxins, defensive proteins, enzymes, and secondary metabolites. Our study aimed to compare the endogenous levels of antioxidative enzymes, photosynthetic pigments, phytohormones, total phenols, and flavonoids in bark-beetle-infested and uninfested trees. We evaluated the surviving trees in bark-beetle-infested stands, assessing both the condition and defense of uninfested and infested beech (Fagus sylvatica), pine (Pinus sylvestris), and fir (Abies alba) trees. Sampling was performed at six affected sites in the Czech Republic, targeting trees that were resilient to significant health deterioration caused by abiotic and biotic factors. The results showed different levels of most of the measured compounds in the three species. Among all the tested species, photosynthetic pigment levels showed the strongest association with infestation status, which was generally lower in the infested plants. For chlorophyll a, extremely significant reductions were observed from 123 ± 20.6 to 101 ± 17.9 μg/g dry weight (DW) in pine, from 231 ± 33.1 to 199 ± 22.2 μg/g DW in beech, and from 60 ± 5.66 to 51.3 ± 6.27 μg/g DW in fir. In contrast, enzymatic activities indicated only isolated instances of significant association, whereas antioxidative properties (total phenolic content, flavonoids, and 2,2-diphenyl-1-picrylhydrazyl radical scavenging capacity) were not significantly associated with infestation status. There was a statistically significant increase in glutathione reductase activity in infested fir and pine trees. However, this difference was not statistically significant in beech. In contrast, a significant increase in superoxide dismutase activity was detected in infected beech trees. Phytohormones have emerged as the most diverse group of analyzed compounds. Cytokinins were the most distinct, with many of them being significantly increased in infested pines, whereas both beech and fir showed only one significant association. Additionally, derivatives of jasmonic acid also showed a distinct pattern of change associated with bark beetle infestation, with the levels of three out of the four analyzed jasmonates being significantly decreased in infested pines, whereas no effects were observed in beeches and firs. Notably, many phytohormones were significantly elevated in the infested pine, whereas both beech and fir exhibited only one significant association. Overall, the data showed that pines responded differently to bark beetles than to beeches or firs. The greatest changes in phytohormones were observed in pine, whereas the most significant changes in photosynthetic pigments were observed in beech and fir trees.

The Rhino Shield for The Coconut Palm: An Automated Protection System for Coconut Tree

This paper will provide the concept and installation of the automated Rhino Beetle Sheild system, which defends coconut plants against attacks by rhinoceros beetles, are presented in this work. The system makes use of chemical sprayers that are managed by an Arduino board, poles, pumps and electrical valves. It is talked about how well the technique works to keep the coconut trees healthy and prevents beetle infestations. The Rhino Beetle Sheilds potential for use in agriculture is demonstrated by experimental results.

Synthesis and application of biodegradable seed coatings to assess the infestation of chickpea (Cicer arietinum L.) seeds by pests

Pulses such as chickpeas face significant damage caused by pests during their growth and storage. The overuse of synthetic pesticides on seeds requiring several cycles of active ingredient applications results in increased expenses and environmental risks by contaminating soil, water, and air. These risks of seed damage without use of harmful pesticides can be reduced by coating the seeds with biodegradable seed coatings. The objective of the study was assessing the effectiveness of biodegradable seed coating in managing stored grain pests and to examine its effects on the germination of chickpeas. For this study chickpea (Cicer arietinum L.) seeds were coated with biodegradable coatings like polyvinyl alcohol with multinutrients, neem oil, chitosan and mucilage-starch nanocrystals. The characterization of coatings was carried out using Fourier Transform Infrared Spectroscopy, X-ray Diffraction and Scanning Electron Microscope. Germination of coated and uncoated chickpea seeds was observed by paper-towel method after 5 and 10 days. Chitosan coated seeds had greatest root length (3.10 ± 0.05 cm), shoot length (3.93 ± 0.08 cm), dry weight (0.24 ± 0.05 g), fresh weight (0.43 ± 0.05 g), germination rate (98.87 %) and vigour index (639.09 ± 0.05) followed by polyvinyl alcohol with multinutrients coated seeds, mucilage-starch nano crystals coated seeds and control group after ten days. The lowest root length (0.97 ± 0.14 cm), shoot length (1.53 ± 0.12 cm), dry weight (0.1 ± 0.005 g), fresh weight (0.21 ± 0.14 g), germination rate (65 %) and vigour index (163.75 ± 4.72) were displayed by neem oil-coated seeds. The impact of stored grain pests was evaluated and it was shown that neem oil had the highest efficacy in controlling pulse beetle infestations followed by chitosan, polyvinyl alcohol with multinutrients and mucilage-starch nano crystals. Neem oil coating enhanced pest mortality by 95 % after 15 days, reduced seed damage by 16.3 % and minimized seed weight loss by 10.6 % after 30 and 45 days. Biodegradable seed coating is a cost-effective and environment friendly way to improve seed performance and protect crops sustainably.

Comparative Analysis of Machine Learning Techniques and Data Sources for Dead Tree Detection: What Is the Best Way to Go?

In Central Europe, the extent of bark beetle infestation in spruce stands due to prolonged high temperatures and drought has created large areas of dead trees, which are difficult to monitor by ground surveys. Remote sensing is the only possibility for the assessment of the extent of the dead tree areas. Several options exist for mapping individual dead trees, including different sources and different processing techniques. Satellite images, aerial images, and images from UAVs can be used as sources. Machine and deep learning techniques are included in the processing techniques, although models are often presented without proper realistic validation.This paper compares methods of monitoring dead tree areas using three data sources: multispectral aerial imagery, multispectral PlanetScope satellite imagery, and multispectral Sentinel-2 imagery, as well as two processing methods. The classification methods used are Random Forest (RF) and neural network (NN) in two modalities: pixel- and object-based. In total, 12 combinations are presented. The results were evaluated using two types of reference data: accuracy of model on validation data and accuracy on vector-format semi-automatic classification polygons created by a human evaluator, referred to as real Ground Truth. The aerial imagery was found to have the highest model accuracy, with the CNN model achieving up to 98% with object classification. A higher classification accuracy for satellite imagery was achieved by combining pixel classification and the RF model (87% accuracy for Sentinel-2). For PlanetScope Imagery, the best result was 89%, using a combination of CNN and object-based classifications. A comparison with the Ground Truth showed a decrease in the classification accuracy of the aerial imagery to 89% and the classification accuracy of the satellite imagery to around 70%. In conclusion, aerial imagery is the most effective tool for monitoring bark beetle calamity in terms of precision and accuracy, but satellite imagery has the advantage of fast availability and shorter data processing time, together with larger coverage areas.

An Evaluation of a Winter Mortality Model for the Mountain Pine Beetle

The winter mortality of mountain pine beetle (Dendroctonus ponderosae Hopkins) larvae caused by temperatures below survivable thresholds and sudden decreases in temperature is among the most influential factors limiting population growth. Due to the importance of winter mortality in the demise of mountain pine beetle infestations, a widely used winter mortality model was developed at the Canadian Forest Service and the United States Forest Service. It predicts lethal temperatures and survival probabilities given temperature time series over the winter season. We present a rare and possibly the first peer-reviewed validation of this winter mortality model, wherein we independently tested the model at a new region in Canada by comparing model predictions to the observed lower lethal temperature thresholds and cold-associated mortality. Model predictions were biologically reasonable but slightly biased. Bias was exacerbated by the inaccurate translation of air temperature data from weather stations to temperatures under the bark where larvae develop. The spatial prediction of relative mortality observed across the study area in Banff National Park was poor—likely because the mountainous terrain presents a difficult prediction challenge when under-bark temperatures are not directly observed. Our results will help inform users of model constraints and how to optimize the accuracy of model predictions.

Spruce bark beetle phenological modelling and drought risk within framework of TANABBO II model

Global warming plays a major role in the disruption of forest ecosystems by bark beetle outbreaks. Decreasing precipitation and more frequent droughts create the conditions for water stress in trees. The Eurasian spruce bark beetle (Ips typographus L.) is more dangerous for Norway spruce (Picea abies (L.) Karst.) forests in Central Europe under these conditions, because even healthy trees under water stress have a lower probability of survival during massive spruce bark beetle outbreaks. This critical issue highlights the importance of targeted research and intervention strategies in affected regions; hence, this study has a focus on the Horní Planá region in Central Europe, which is managed by the Military Forests and Farms of the Czech Republic (VLS).The study presents the results of the drought risk assessment of the operational part of TANABBO II and its validation. TANABBO is a high spatial resolution risk assessment tool for spruce bark beetle infestation in Central European forests, incorporating 30 m spatial resolution and extensive meteorological data, which outperforms existing models in its ability to accurately predict bark beetle activity based on the PHENIPS phenological model. The operational part integrates environmental factors such as global radiation, temperature, precipitation and, in particular, water stress, which is assessed by using a transpiration deficit. The drought risk assessment included the calculation of Drought Indices (DI) and Cumulative Transpiration Deficit Indices (CTDI) on a daily basis, and the estimation of spruce bark beetle swarming time using the PHENIPS model. The risk assessment was validated by comparing it with the number of bark beetles caught in traps and the value of the drought index. Generalised additive models (GAM) were used for validation, with the most effective models incorporating the CTDI. The model with the highest predictive accuracy achieved an adjusted R-squared value of 0.478. The study highlights the critical role of high-resolution environmental data in understanding and managing bark beetle outbreaks, particularly in the context of climate change.

Direct and mediated impacts of mixed forests on Norway spruce infestation by European bark beetle Ips typographus

Climate change-induced windfalls and droughts exacerbate bark beetle outbreaks, severely impacting forest ecosystems. Despite extensive research on bark beetle infestation patterns, the question regarding the optimal spatial grid (SG) size for analyzing this phenomenon remains unresolved. The protective potential of natural forest complexity against bark beetles has been underestimated. We used remotely sensed data to fit Generalized Linear Models and structural equation models to explore the direct and environment-mediated effects of mixed forest cover (MFC) on Norway spruce forest infestation in central Europe. We assessed the effectiveness of various spatial grids (from 100 m to 1 km) for studying infestation by Ips typographus. We found a strong non-linear decline in infestation with increasing MFC across different spatial scales. The relationship between infestation and temperature was positive, while elevation had a negative effect on infestation, with higher infestation rates observed below 900 m. Direct effects of environmental predictors on infestation were significant at SGs of 100 m, 300 m, 400 m, and 500 m, but insignificant at 200 m and 1000 m SGs. Slope positively influenced infestation at 300 m and 400 m SGs. MFC exhibited significant indirect effects on infestation mediated by elevation, temperature, potential evapotranspiration, slope, and heat load index. Landscape variables played a significant role in the models at high-resolution spatial grids, whereas climate variables were influential in models at lower spatial grids of infestation data. We argue that mixed forest facilitates cooling, preserves water, enriches symbiotic fungal community, alleviating tree drought stress and mitigating infestation risk. Broad-leave trees’ non-host volatiles presumably disrupt olfactory signals, impeding beetles’ ability to locate host trees effectively. Our results underscore the potential of increasing mixed forest cover as a self-sustainable silvicultural measure for forest protection against I. typographus and for mitigating the effects of climate change.

Satellite monitoring of a pine forest affected by mountain pine beetle

The spread of bark beetles poses a significant threat to forest ecosystems, causing substantial damage to coniferous forests. The mountain pine beetle (Dendroctonus spp.) is considered to be one of the most harmful bark beetles, infesting pine trees and leading to severe consequences for forest ecosystems. This article aims to detect and analyze the dynamics of mountain pine beetle infestation in a pine forest stand, determine its affected area, and evaluate the effectiveness of sanitary and restoration measures. The study utilized satellite data from the Sentinel-2 mission and employed the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Moisture Index (NDMI) to monitor the spread of mountain pine beetle infestation. The analysis was conducted for a pine forest stand in the Ostriv Forestry of the Vyshchedubechanske Forestry Enterprise in Kyiv Oblast, Ukraine. The results demonstrated the effectiveness of using satellite data and vegetation indices for monitoring mountain pine beetle infestation. The combined application of NDVI and NDMI enabled the detection of infested areas in the early stages by capturing changes in the spectral characteristics of tree crowns and vegetation moisture content. The satellite data analysis confirmed the complete infestation of a 0.01 km2 pine forest stand by the mountain pine beetle in 2017. A link between the activation of beetle spread and climate changes, particularly rising temperatures and decreasing precipitation, was observed, leading to the weakening of pine stands. The study revealed that in 2018, sanitary felling of the infested pine stand was carried out, as evidenced by the decrease in NDVI values. In 2019, a project to restore the forest ecosystem through the establishment of a new pine plantation was initiated. Satellite observations in April 2024 demonstrated successful growth of the young pine forest, with NDVI values indicating an increase from 0.25 in April 2020 to 0.45 in April 2024, reflecting active vegetation growth and successful ecosystem restoration. The obtained results highlight the importance of using satellite data for timely detection of pest outbreaks in forest ecosystems, determining the extent of infestation, monitoring the effectiveness of sanitary measures, and assessing the recovery of forest stands after restoration efforts. The study underscores the potential of satellite remote sensing techniques in forest ecosystem monitoring and supports decision-making processes for sustainable forest management.

Early Detection of Southern Pine Beetle Attack by UAV-Collected Multispectral Imagery

Effective management of bark beetle infestations requires prompt detection of attacked trees. Early attack is also called green attack, since tree foliage does not yet show any visible signs of tree decline. In several bark beetle systems, including mountain pine beetle and European spruce bark beetle, unpiloted aerial vehicle (UAV)-based remote sensing has successfully detected early attack. We explore the utility of remote sensing for early attack detection of southern pine beetle (SPB; Dendroctonus frontalis Zimm.), paired with detailed ground surveys to link tree decline symptoms with SPB life stages within the tree. In three of the northernmost SPB outbreaks in 2022 (Long Island, New York), we conducted ground surveys every two weeks throughout the growing season and collected UAV-based multispectral imagery in July 2022. Ground data revealed that SPB-attacked pitch pines (Pinus rigida Mill.) generally maintained green foliage until SPB pupation occurred within the bole. This tree decline behavior illustrates the need for early attack detection tools, like multispectral imagery, in the beetle’s northern range. Balanced random forest classification achieved, on average, 78.8% overall accuracy and identified our class of interest, SPB early attack, with 68.3% producer’s accuracy and 72.1% user’s accuracy. After removing the deciduous trees and just mapping the pine, the overall accuracy, on average, was 76.9% while the producer’s accuracy and the user’s accuracy both increased for the SPB early attack class. Our results demonstrate the utility of multispectral remote sensing in assessing SPB outbreaks, and we discuss possible improvements to our protocol. This is the first remote sensing study of SPB early attack in almost 60 years, and the first using a UAV in the SPB literature.

Effects of Packaging Material and Moisture Contents on Pulse Beetle Infestation under Different Storage Conditions in Chickpea

Chickpea (Cicer arietinum L.) is an important pulse crop grown globally for its nutritional richness and versatility which offers a significant source for both carbohydrates and protein. Chickpea seeds face a significant threat from various insect pests among these pulse beetles or bruchids (Callosobruchus spp.) stand out as the most destructive, inflicting damage ranging from 50% to 60% during storage. Bruchids are considered minor pests in the field, but they pose a serious threat during storage, leading to both quantitative and qualitative losses. The present investigation was carried out with the objective of studying the influence of ambient and cold storage conditions on storability and to assess the pest infestation (pulse beetle) under ambient and cold storage conditions in two chickpea varieties viz., JG-11 (desi) and NBeG-119 (kabuli). The seed was thoroughly sun dried to two moisture levels of seven and nine percent and stored in gunny and grain pro bags (hermetic bags). Gunny bags were kept at ambient storage as well as in the cold storage, while grain pro bags were stored at ambient storage conditions only as these are the hermetic bags and the dry chain technology concept holds good for storage at ambient conditions only. Highest % seed damage (12.11 % in JG-11 and 13.00 % in NBeG-119) was noticed in seeds stored with nine per cent moisture content while, the lowest % seed damage (9.50 % in JG-11 and 9.83 % in NBeG 119) was recorded in seeds with seven per cent moisture content. After 8 months of storage highest per cent fecundity (151.66 and 144.66 in JG-11 and 145.00 and 138.50 in NBeG-119) was recorded in seeds stored in gunny bags kept at ambient storage with nine and seven per cent moisture respectively, followed by the seed stored in grain pro bags at ambient storage with nine percent seed moisture (9.667 in JG-11 and 7.833 in NBeG-119) and no fecundity was recorded in seeds stored in gunny bag at cold storage. At the end of storage period highest adult emergence was recorded in seeds stored in gunny bag at ambient storage with nine (196.83 in JG-11 and 217.17 in NBeG-119) and seven (187.83 in JG-11 and 207.83 in NBeG-119) per cent seed moisture followed by the seed stored in grain pro bags at ambient storage with nine percent seed moisture (11.67 in JG-11 and 13.00 in NBeG-119) and no adult emergence was recorded in seeds stored in gunny bag at cold storage (0.00 in JG-11 and 0.00 in NBeG-119 ) with seven and nine percent moisture at the end of the storage. Highest weight loss % (2.019% in JG-11 and 1.866% in NBeG-119) was recorded in seeds stored with nine per cent moisture content. While, the lowest weight loss % (1.679% in JG-11 and 1.772% in NBeG-119) was noticed in seeds stored with seven per cent moisture at the end of storage period.

Small hive beetle infestation levels correlate with sun exposure but not aggression of honeybee host colonies

AbstractSmall hive beetles (SHB), Aethina tumida, are free‐flying parasites, which actively seek and invade honeybee host colonies. Previous research suggests that SHB prefer colonies in the shade. Further, it has been stated that SHB invade any colony with equal impunity. Though, the impact of colony aggressiveness on SHB infestation levels has never been quantified. Here, we confirm significantly higher SHB infestation levels in shaded colonies and further suggest that host colony aggression is of minor importance only. In the state of Rio de Janeiro, Brazil, local Africanized honeybee colonies at a sunny (N = 10) and at a shaded apiary (N = 11) were tested for aggression and visually screened for SHB infestations using standard methods. Both colony aggression and infestation levels were variable, but not significantly correlated. The results confirm that infestation levels are significantly higher in the shaded apiary than in the sun‐exposed one. However, host colony aggression is unlikely to interfere with SHB infestation levels of colonies. Instead, SHB seem to remain even in aggressive colonies. The underlying mechanisms for the significant differences in colony infestation levels due to sun exposure remain unknown. Beekeepers are advised to prefer sun‐exposed apiary locations in regions, where SHB are a pest of concern.

Remote Sensing of Forests in Bavaria: A Review

In recent decades, climatic pressures have altered the forested landscape of Bavaria. Widespread loss of trees has unevenly impacted the entire state, of which 37% is covered by forests (5% more than the national average). In 2018 and 2019—due in large part to drought and subsequent insect infestations—more tree-covered areas were lost in Bavaria than in any other German state. Moreover, the annual crown condition survey of Bavaria has revealed a decreasing trend in tree vitality since 1998. We conducted a systematic literature review regarding the remote sensing of forests in Bavaria. In total, 146 scientific articles were published between 2008 and 2023. While 88 studies took place in the Bavarian Forest National Park, only five publications covered the whole of Bavaria. Outside of the national park, the remaining 2.5 million hectares of forest in Bavaria are understudied. The most commonly studied topics were related to bark beetle infestations (24 papers); however, few papers focused on the drivers of infestations. The majority of studies utilized airborne data, while publications utilizing spaceborne data focused on multispectral; other data types were under-utilized- particularly thermal, lidar, and hyperspectral. We recommend future studies to both spatially broaden investigations to the state or national scale and to increase temporal data acquisitions together with contemporaneous in situ data. Especially in understudied topics regarding forest response to climate, catastrophic disturbances, regrowth and species composition, phenological timing, and in the sector of forest management. The utilization of remote sensing data in the forestry sector and the uptake of scientific results among stakeholders remains a challenge compared to other heavily forested European countries. An integral part of the Bavarian economy and the tourism sector, forests are also vital for climate regulation via atmospheric carbon reduction and land surface cooling. Therefore, forest monitoring remains centrally important to attaining more resilient and productive forests.

Quarter century of mercury litterfall at a coniferous forest responding to climate change, Central Europe.

This work evaluated the 25-year-long trends (1994-2018) in mercury (Hg) concentrations and fluxes in spruce litterfall at a forest research plot Načetín (NAC) recovering from acidic deposition in the Ore Mountains, Czech Republic. The mean litterfall Hg deposition averaged 51 ± 18µgm-2year-1, which has been the highest litterfall Hg deposition reported up to date on the European continent. In contrast, the wet deposition (2017-2019) was an order of magnitude lower averaging at 2.5 ± 1.5µgm-2year-1. All the spruce litterfall components bark, twigs, needles, cones, and a mixture of unidentified fragments had elevated mean Hg concentrations relative to background sites averaging 256 ± 77, 234 ± 62, 119 ± 23, 95 ± 14, and 44 ± 15µg kg-1, respectively. Elevated litterfall Hg deposition and concentrations were attributed to the nearby local Hg emission source-coal-fired power plants. Temporally, the decrease of Czech Hg emissions since the 1990s was reflected by the decreasing trend of Hg concentrations in litterfall bark, cones, and twigs, while in needles and other material, Hg increased but insignificantly. Total litterfall ratios of Hg/C, Hg/N, and Hg/S were lower than those in soil O horizons averaging at 0.23 ± 0.04, 9.5 ± 2.0, and 170 ± 37μgg-1, respectively. Since the beginning of monitoring, total litterfall Hg/C exhibited no trend, Hg/N decreased, and Hg/S increased. The litterfall biomass deposition averaging at 469 ± 176gm-2year-1 increased through time resulting in an increased Hg litterfall deposition at NAC by 1.1µgm-2year-1 despite the decreases in Czech Hg emissions. Peaks of annual litterfall Hg deposition up to 96µgm-2year-1 at NAC during the 25years of monitoring resulted from weather extremes such as rime-snow accumulation, wind gusts, droughts, and insect infestation, which all significantly affected the annual biomass deposition. Based on our observations, further increases in biomass and litterfall Hg deposition rates can be expected due to the onset of bark beetle infestation and the increasing number of droughts caused by climate change.

Wheat companion plants reduced aphid and flea beetle infestations in Brassica vegetable crops in a multiple-year field study in central Germany

Alternative pest control systems such as companion plants are increasingly gaining importance owing to a reduced range of available synthetic insecticides and more rigorous regulation of their use in the EU. Therefore, we evaluated the effects of Brassica vegetables grown with wheat companion plants on relevant pests, respective natural enemies and harvest weight. Six trials were conducted in white cabbage and three in Chinese cabbage between 2017 and 2021. We identified an overall aphid-regulating effect for Brevicoryne brassicae (L.) and Myzus persicae (Sulz.) (Hemiptera: Aphididae) in white cabbage and a regulating effect on flea beetles (Phyllotreta spp.) (Coleoptera: Chrysomelidae) in both tested Brassica crops. Feeding by cabbage root fly Delia radicum L. (Diptera: Anthomyiidae) larvae on white cabbage roots was not consistently affected. Natural enemies including ladybirds (Coleoptera: Coccinellidae), hoverfly larvae (Diptera: Syrphidae), spiders (Araneida), ground beetles (Coleoptera: Carabidae), and rove beetles (Coleoptera: Staphylinidae) were assessed on crop plants or in pitfall traps. The activity density of rove beetles was increased by wheat companions in both Brassica crops, while that of ground beetles was reduced in white cabbage. The weight of harvested white cabbage was reduced by wheat companions, varying between a mean reduction of 7.67% and 40.08% in different experiments. In conclusion, wheat companion plants can be an additional tool for regulating pests in Brassica vegetables. However, competition effects on crop yield and the compatibility with other cultivation aspects, e.g. crop rotation, have to be considered.

Novel Hydrogen and Biomethanol Production From Pinecone Biomass Using an Integrated Steam Gasification System

This study develops a new biomass-based integrated energy system where a steam gasification process is considered for hydrogen and biomethanol production in a viable manner using woody bioresources from pinecones. The modeling and simulation studies are performed using both The Aspen Plus and Matlab software packages in a combined manner to practically investigate the integrated system's operating and management conditions and potential performance for a strategically identified location in British Columbia where bioresources are widely available, and there is a strong need to create a value out of these. The emphasis is on three main stages: gasification, syngas post-treatment, and methanol production. This comprehensive approach ensures an in-depth understanding of the production process, from resource extraction to end-product progress. A key aspect of the study is estimating essential flow rates, notably CO2, H2, and CH4O, in various operational conditions. The analysis goes beyond product yields, providing a thorough evaluation of mass flow rates for all streams in the system. This enables a more sophisticated evaluation of performance under various operating situations and component varieties. The integrated system's performance is evaluated using rigorous thermodynamic studies. This analytical technique provides details on the efficiencies and environmental impacts of the proposed system. The simulation findings show that the existing system can produce 0.17 kg/s methanol and 0.025 kg/s hydrogen. These findings establish a foundation for further improvement and scalability of the integrated system for practical applications. The study not only helps advance the field of renewable energy era but also provides a practical and sustainable solution to the pressing issue of pine beetle infestation, demonstrating the possibility of combining technology and ecology to benefit the environment.

Urban Forest Resilience: Assessment and Management Strategies for Stressed Trees in Diverse Environments

Variety of trees are found in both urban and wild areas; these trees are indispensable in maintaining ecosystem health and promoting human well-being. However, stressors affect the health of these trees; this makes them face management approaches. In this study, an assessment and management of five (5) different tree species at Southern University and A&M College in Baton Rouge-USA were carried out. The Southern Magnolia, Southern Red Oak, and Live Oak showed symptoms of stress, such as leaning and decay. The identified Loblolly Pine showed symptoms such as bark beetle infestations and resource competition. For each of these species, specific indicators of stress were identified and recommended management approaches. These include the installation of support systems, pruning of diseased branches, soil tillage, and pest control techniques. These practices allow the strengthening of urban forest, which ensures continued health and functioning of our ecosystems.