Forest Pest Management Research Articles

Trait diversity and spider community composition are associated with lower herbivory in young forest plantations

Spiders constitute a numerically dominant group of generalist predators in forest ecosystems, but their biocontrol function in forest plantations is not well understood. The biocontrol potential of spiders may depend upon interaction among pest type, forest type, season, trait composition, and spider community diversity. Using a correlative approach, we addressed this gap in knowledge in young (10–15 years) oak (Quercus spp.) and ash (Fraxinus spp.) forest plantations. We sampled (N = 103 samples) foliage-dwelling arthropods and leaves during late spring and autumn. We then measured traits of spiders (body size and hunting strategy) and examined two indicators of herbivory (leaf damage and leaf dry biomass). In oak plantations, abundances of Hemiptera negatively correlated with functional diversity of spiders consistently during the two seasons. Abundances of caterpillars negatively correlated with abundances of ambushers and marginally with abundances of orb-web building spiders during late spring. Abundances of herbivorous Coleoptera negatively correlated with functional evenness of spiders in autumn. Moreover, herbivory negatively correlated with abundances of Space-web builders and functional diversity of spiders in spring but with mean spider body size in autumn. In ash plantations, herbivory negatively correlated with spider abundances in autumn. Our findings provide indirect evidence that foliage-dwelling spiders can be useful for the biological control of forest pests. The biocontrol potential of spiders seems to depend on both functional diversity and identity. Therefore, forest pest management should focus not only on spider community composition but also functional trait diversity of spiders.

Oak aphids Tuberculatus annulatus (Hartig, 1841) and Thelaxes dryophila (Schrank, 1801) (Hemiptera: Aphididae) endosymbiont microbiome diversity alters between natural and artificial oak forest regeneration

Abstract In the present study, the bacterial symbionts of two species of oak aphid, Thelaxes dryophila and Tuberculatus annulatus were tested as indicators between naturally and artificially regenerated oak forests. In total, 195 bacterial taxa were identified using the Ion Torrent PGM system. Here, we report for the first time differences in bacterial symbiont diversity between oak forests natural and artificial regeneration sites, and aphid species. Differences in the abundance of the primary obligate endosymbiont Buchnera aphidicola were also detected between the two study aphid species. In the ant attended Thelaxes dryophila, the species was found to harbour a higher density of the facultative symbionts Serratia symbiotica and Wolbachia, while in the non-ant attended Tuberculatus annulatus, the dominant facultative symbionts were Hamiltonella and Rickettsia. In addition, we report the presence of Serratia marcescens and Enterobacter cloacae as symbionts of Thelaxes dryophila and Shigella boydii as a symbiont of Tuberculatus annulatus. We conclude that the two aphid species harbour different facultative symbionts between oak forest regeneration types; these results might have importance in oak forest pest management via aphid adaptation through their endosymbions.

Integration of satellite remote sensing and MaxEnt modeling for improved detection and management of forest pests.

Forest pests pose a major threat to ecosystem services worldwide, requiring effective monitoring and management strategies. Recently, satellite remote sensing has emerged as a valuable tool to detect defoliation caused by these pests. Lymantria dispar, a major forest pest native to Japan, Siberia, and Europe, as well as introduced regions in North America, is of particular concern. In this study, we used Sentinel-2 satellite imagery to estimate the defoliation area and predict the distribution of L. dispar in Toyama Prefecture, central Japan. The primary aim was to understand the spatial distribution of L. dispar. The normalized difference vegetation index (NDVI) difference analysis estimated a defoliation area of 7.89 km2 in Toyama Prefecture for the year 2022. MaxEnt modeling, using defoliation map as occurrence data, identified the deciduous forests between approximately 35° and 50° at elevations of 400m and 700m as highly suitable for L. dispar. This predicted suitability was also high for larval locations but low for egg mass locations, likely due to differences in larval habitats and ovipositing sites. This study is the first attempt to utilize NDVI-based estimates as a proxy for MaxEnt. Our results showed higher prediction accuracy than a previous study based on the occurrence records including larvae, adults, and egg masses, indicating better discrimination of the distribution of L. dispar defoliation. Therefore, our approach to integrating satellite data and species distribution models can potentially enhance the assessment of areas affected by pests for effective forest management.

Do male and female family forest landowners have different training needs? A case study from Georgia, United States

In the southern United States, female forest landowners (FeFLs) are an important stakeholder group as they make up 27% (about 450,000) of family forest landowners and hold 21% (about 30 million acres) of the total forestlands. Despite FeFLs' increasing role in forestry, they are less actively involved in forest management than male forest landowners. This could be attributed to a general lack of understanding about gender-based training needs in sustainable forest management. In this context, we surveyed 246 forest landowners in Georgia, a major forestry state in the United States, to gauge the levels of perceived knowledge and interest in learning about 12 forest management topics. We determined the competency gaps in forest management using the Borich's Needs Assessment Model. Our results indicate that the priority topics of training needs were consistent regardless of the landowners' forest management objective. Gender-based disparities highlighted that FeFLs had a significantly lower perceived knowledge level across 11 out of 12 topics than their male counterparts. Further, FeFLs required training in all 12 topics of forest management. The top five priority topics, in order, were tree disease management, forest insect pest management, timber taxes, nuisance wildlife management, and environmental education. To bolster the competency and capacity of FeFLs in sustainable forest management, we suggest implementing targeted training, encouraging peer-to-peer learning, and elevating female forestry professionals in Georgia and other states in the region.

Enhancing pest control interventions by linking species distribution model prediction and population density assessment of pine wilt disease vectors in South Korea

Pine wilt disease caused by pinewood nematode is one of the most destructive forest diseases, and still spreading in South Korea despite the various control efforts. Japanese pine sawyer (JPS) and Sakhalin pine sawyer (SPS) are the main vectors of the disease. Understanding the distribution and density of the vectors is crucial since the control period is determined by the different emergence periods of the two vectors and the control method by its density and the expected damage severity. In this study, we predicted the distribution of JPS and SPS using Maxent and investigated the relationship between the resulting suitability value and the density. The population densities of JPS and SPS were obtained through a national survey using pheromone traps between 2020-2022. We converted the density data into presence/absence points to externally validate each species distribution model, then we used quantile regression to check the correlation between the suitability and population density, and finally we used three widely used thresholds to convert the model results into binary maps, and tested if they could distinguish the density by comparing the Rb value of biserial correlation. The quantile regression revealed a positive relationship between the habitat suitability and population density sampled in the field. Moreover, the binary map with threshold criteria that maximizes the sum of the sensitivity and specificity had the best density discrimination capacity with the highest Rb. A quantitative relationship between suitability and vector density measured in the field from our study provides reliability to species distribution model as practical tools for forest pest management.

Detection of the Infection Stage of Pine Wilt Disease and Spread Distance Using Monthly UAV-Based Imagery and a Deep Learning Approach

Pine wood nematode (PWN) is an invasive species which causes pine wilt disease (PWD), posing a significant threat to coniferous forests globally. Despite its destructive nature, strategies for the management of PWD spread lack a comprehensive understanding of the occurrence pattern of PWNs. This study investigates the outbreak timing and spread distances of PWD on a monthly scale. Two regions (A and B) in southeastern China, characterized by varying mixed ratios of coniferous and broadleaf trees, were examined. Infected trees were classified into early, middle, late, and dead stages. Monthly unmanned aerial vehicle (UAV) RGB data covering one year and three deep learning algorithms (i.e., Faster R-CNN, YOLOv5, and YOLOv8) were employed to identify the stress stages and positions of the trees. Further, each month, newly infected trees were recorded to calculate spread distances from the location of surrounding trees. The results indicate that the YOLOv5 model achieved the highest accuracy (mean average precision (mAP) = 0.58, F1 = 0.63), followed by Faster R-CNN (mAP = 0.55, F1 = 0.58) and YOLOv8 (mAP = 0.57, F1 = 0.61). Two PWD outbreak periods occurred between September–October and February of the following year, with early and middle-stage outbreaks in August and September and late and dead-tree outbreaks occurring between October and February of the following year. Over one year, the nearest spread distance for PWD-infected trees averaged 12.54 m (median: 9.24 m) for region A in September and 13.14 m (median: 10.26 m) for region B in October. This study concludes that February through August represents the optimal period for PWD control. Additionally, mixed conifer–broadleaf forests with a higher proportion of broadleaf trees prove beneficial in mitigating PWD outbreaks and reducing the number of infected trees. This work demonstrates the effectiveness of integrating monthly UAV-based imagery and deep learning algorithms for monitoring PWD outbreak times and spread distances, offering technical support for forest pest prevention and management.

Entomopathogens in the integrated management of forest insects: from science to practice.

The most important aim of the integrated management of forest insect pests remains the prevention of insect outbreaks, which are a consequence of the interaction of many factors in forest ecosystems, including species composition, age and health of the forest, soil type, the presence of natural enemies, and climatic factors. Integrated pest management until now has been achieved using measures aimed at shaping the functioning of stands in a changing environment. The aim of this review is to summarize research on the use of entomopathogens (microorganisms and nematodes) in the management of forest insect pests and to identify the principal knowledge gaps. We briefly describe the main research directions on the use of pathogens and nematodes to control insect pests and discuss limitations affecting their implementation. Research on entomopathogens for the biocontrol of forest insects has provided a wealth of knowledge that can be used effectively to reduce insect populations. Despite this, few entomopathogens are currently used in integrated pest management in forestry. They are applied in inoculation or inundation biocontrol strategies. While the use of entomopathogens in forest pest management shows great promise, practical implementation remains a distant goal. Consequently, sustainable reduction of forest pests, mainly native species, will be largely based on conservation biological control, which aims to modify the environment to favor the activity of natural enemies that regulate pest populations. This type of biocontrol can be supported by a range of silvicultural measures to increase the resilience of stands to insect infestations. © 2023 Society of Chemical Industry.

Predicting the Temperature-Driven Development of Stage-Structured Insect Populations with a Bayesian Hierarchical Model

The management of forest pests relies on an accurate understanding of the species’ phenology. Thermal performance curves (TPCs) have traditionally been used to model insect phenology. Many such models have been proposed and fitted to data from both wild and laboratory-reared populations. Using Hamiltonian Monte Carlo for estimation, we implement and fit an individual-level, Bayesian hierarchical model of insect development to the observed larval stage durations of a population reared in a laboratory at constant temperatures. This hierarchical model handles interval censoring and temperature transfers between two constant temperatures during rearing. It also incorporates individual variation, quadratic variation in development rates across insects’ larval stages, and “flexibility” parameters that allow for deviations from a parametric TPC. Using a Bayesian method ensures a proper propagation of parameter uncertainty into predictions and provides insights into the model at hand. The model is applied to a population of eastern spruce budworm (Choristoneura fumiferana) reared at 7 constant temperatures. Resulting posterior distributions can be incorporated into a workflow that provides prediction intervals for the timing of life stages under different temperature regimes. We provide a basic example for the spruce budworm using a year of hourly temperature data from Timmins, Ontario, Canada. Supplementary materials accompanying this paper appear on-line.

RNAi-chitosan biopesticides for managing forest insect pests: an outlook

The expanding world population demands superior forest protection to fulfil feasible environmental certainty. The persistent pest infestations negatively influence forest health and cause substantial economic losses. In contrast, the traditional use of conventional pesticides results in a loss of soil microbial biodiversity, a drop in the population of pollinators, and adverse effects on other non-target organisms, including humans. Global forestry is looking for solutions to reduce the adverse environmental effects of current chemical pesticides. RNAi-nanotechnology has recently drawn much attention for its use in pest management. The advantages of engineered RNAi-chitosan nano-formulations in terms of simple digestion and dissolution, non-toxicity, high adsorption power, potential biodegradation in nature, and widespread availability and cost-effectiveness, have been well documented for pest management in agroecosystems. However, deploying such control strategies in forest ecosystems is still pending and demands further research. Hence, we highlight the putative uses of RNAi-chitosan biopesticides and their preparation, characterization, and putative application methods for forest pest management. We also discussed potential environmental risks and plausible mitigation strategies.

Detection of susceptible Norway spruce to bark beetle attack using PlanetScope multispectral imagery

Climate change-related acute or long-term drought stress can weaken forest ecosystems and result in widespread bark beetle infestations. Eurasian spruce bark beetle (Ips typographus L.) infestations have been occurring in Norway spruce [Picea abies (L.) Karst.]-dominated forests in central Europe including the Czechia. These infestations appear regularly, especially in homogeneous spruce stands, and the impact varies with the climate-induced water stress conditions. The removal of infected trees before the beetles leave the bark is an important step in forest pest management. Early identification of susceptible trees to infestations is also very important but quite challenging since stressed tree-tops show no sign of discolouration in the visible spectrum. We investigated if individual spectral bandwidths or developed spectral vegetation indices (SVIs), can be used to differentiate non-attacked trees, assumed to be healthy, from trees susceptible to attacks in the later stages of a growing season. And, how the temporal-scale patterns of individual bands and developed SVIs of susceptible trees to attacks, driven by changes in spectral characteristics of trees, behave differently than those patterns observed for healthy trees. The multispectral imagery from the PlanetScope satellite coupled with field data were used to statistically test the competency of the individual band and/or developed SVIs to differentiate two designated classes of healthy and susceptible trees. We found significant differences between SVIs of the susceptible and healthy spruce forests using the Enhanced Vegetation Index (EVI) and Visible Atmospherically Resistant Index (VARI). The accuracy for both indices ranged from 0.7 to 0.78; the highest among all examined indices. The results indicated that the spectral differences between the healthy and susceptible trees were present at the beginning of the growing season before the attacks. The existing spectral differences, likely caused by water-stress stimuli such as droughts, may be a key to detecting forests susceptible to early infestations. Our introduced methodology can also be applied in future research, using new generations of the PlanetScope imagery, to assess forests susceptibility to bark beetle infestations early in the growing season.

Can morphological traits explain species-specific differences in meta-analyses? A case study of forest beetles.

Meta-analyses have become a valuable tool with which to synthesize effects across studies, but in ecology and evolution, they are often characterized by high heterogeneity, where effect sizes vary between studies. Much of this heterogeneity can be attributed to species-specific differences in responses to predictor variables. Here, we aimed to incorporate a novel trait-based approach to explain species-specific differences in a meta-analysis by testing the ability of morphological traits to explain why the effectiveness of flight-intercept trap design varies according to beetle species, a critical issue in forest pest management. An existing morphological trait database for forest beetles was supplemented, providing trait data for 97 species, while data from a previous meta-analysis on capture rates of bark or woodboring beetles according to different trap designs were updated. We combined these sources by including nine morphological traits as moderators in meta-analysis models, for five different components of trap design. Traits were selected based on theoretical hypotheses relating to beetle movement, maneuverability, and sensory perception. We compared the performance of morphological traits as moderators versus guild, taxonomic family, and null meta-analysis models. Morphological traits for the effect of trap type (panel vs. multiple-funnel) on beetle capture rates improved model fit (AICc ), reduced within-study variance (σ2 ), and explained more variation (McFadden's pseudo-R2 ) compared with null, guild, and taxonomic family models. For example, morphological trait models explained 10% more of the variance (pseudo-R2 ) when compared with a null model. However, using traits was less informative to explain how detailed elements of trap design such as surface treatment and color influence capture rates. The reduction of within-study variance when accounting for morphological traits demonstrates their potential value for explaining species-specific differences. Morphological traits associated with flight efficiency, maneuverability, and eye size were particularly informative for explaining the effectiveness of trap type. This could lead to improved predictability of optimal trap design according to species. Therefore, morphological traits could be a valuable tool for understanding species-specific differences in community ecology, but other causes of heterogeneity across studies, such as forest type and structure, require further investigation.

Trap catch data are poor predictors of damage caused by pine weevil (Hylobius abietis) to conifer seedlings

Damage to planted conifer seedlings caused by the pine weevil Hylobius abietis (L.) is a severe and persistent threat to successful forest regeneration in Europe. Various countermeasures are available, which vary in effectiveness, costs and environmental impact, but none are ideal for all situations. Therefore, there is strong interest in robust assessments of damage risks, as they would enable more cost-effective and environmentally friendly forest pest management. It has been suggested that numbers of adult pine weevils caught in host-odour baited traps placed in regeneration sites may be valuable in such risk assessments. However, published studies provide at most weak support for the hypothesis that trap catch data provide adequate predictions of damage. Therefore, we conducted a two-year field study, designed to determine the relationship between weevil trap catch and subsequent damage at 10 regeneration sites in central Sweden. Site factors that might influence pine weevil feeding on seedlings were recorded and used as explanatory variables in the analysis. Stoniness was the only site factor identified as having a significant effect; damage mainly increased with increases in stoniness. No significant correlation was detected between damage to planted conifer seedlings and numbers of pine weevils trapped in the same locations. We suggest that this lack of correlation between weevil numbers and damage is due to planted seedlings only constituting a minor part of the weeviĺs food intake and considerable between-site variation in availability of food sources other than seedlings. Therefore, assessment of pine weevil numbers appears unlikely to be useful for predicting damage risk at specific regeneration sites.

Evaluating a decade (2011–2020) of integrated forest pest management in the United States

AbstractTo sustain healthy forests in the United States, the USDA Forest Service, Forest Health Protection and cooperators utilize integrated pest management (IPM) programs to prevent, suppress, and eradicate insect and disease outbreaks affecting trees across all land ownerships. Forest pest management projects supported by federal funding from 2011 to 2020 were assessed to determine the most frequently used project types, IPM strategies and tactics, identify the dominant forest pests and associated hosts managed, and identify the most comprehensive forest IPM programs in practice. Forest pest management projects were obtained primarily from two centralized databases and included 2,416 projects that treated a total of 2,284,624 ha. Two project types accounted for most of the forest pest projects (suppression: 63% and prevention: 30%). Native forest pests were targeted more (79%) than non-native pests (21%) in these projects; however, non-native pests accounted for more treatment areas. Forest pest projects were directed mostly at phloem-feeding insects (70%) and subsequently followed by foliage feeders (10%), sap feeders (6%), and all other pest groups (each < 5%), including diseases. Four IPM control strategies (silvicultural: 32%, semiochemical: 22%, chemical: 21%, and physical/mechanical: 18%) accounted for most of the forest pest projects. Foliage feeders possessed the most comprehensive IPM programs that adopted two or more types of control tactics. Few pest programs incorporated microbial/biopesticide control strategies and this represents an area where research is needed. In addition, better-centralized records are needed for genetic control projects, treatment efficacy, and survey and technical assistance activities.

Two Antenna-Enriched Odorant Binding Proteins in Dioryctria abietella Tuned to General Odorants and Insecticides

The management of forest pests has become a significant challenge, particularly for wood borers, because they spend most of the time in the trunks or cones. The coneworm, Dioryctria abietella, is a representative of cone borers as its larvae feed on the cones of Pinaceae plants. The molecular mechanisms underlying the interactions between this species and host plants or habitats can assist in developing strategies for pest control. In this study, we extended the expression profiles of 32 odorant binding proteins (OBPs) in the reproductive tissues of D. abietella, revealing the detectable transcription of 29 genes. Using two DabiOBPs highly expressed in antennae (DabiOBP5 and DabiOBP14) as targets, six compounds with high affinities (dissociation constants < 13 μM) were identified through a reverse chemical ecology strategy, including insecticides widely used for the control of lepidopteran pests. Of these compounds, a floral volatile β-ionone and a pear-produced ester ethyl-(2E,4Z)-decadienoate may serve as behaviorally active compounds in D. abietella. The strong binding of DabiOBPs to insecticides suggested their involvement in insecticide resistance, reflecting sophisticated detoxification mechanisms of this moth. In the molecular simulations, DabiOBP14 possessed stronger interactions with the six ligands compared to DabiOBP5, in which a few key residues within the binding pockets were involved in the formation of hydrogen bonds. This study provides some valuable reference active compounds for the development of lures or repellents in D. abietella and unravels the putative roles of two antenna-dominant DabiOBPs in the perception of plant-derived odorants and insecticides.

Model-Based Identification of Larix sibirica Ledeb. Damage Caused by Erannis jacobsoni Djak. Based on UAV Multispectral Features and Machine Learning

While unmanned aerial vehicle (UAV) remote sensing technology has been successfully used in crop vegetation pest monitoring, a new approach to forest pest monitoring that can be replicated still needs to be explored. The aim of this study was to develop a model for identifying the degree of damage to forest trees caused by Erannis jacobsoni Djak. (EJD). By calculating UAV multispectral vegetation indices (VIs) and texture features (TF), the features sensitive to the degree of tree damage were extracted using the successive projections algorithm (SPA) and analysis of variance (ANOVA), and a one-dimensional convolutional neural network (1D-CNN), random forest (RF), and support vector machine (SVM) were used to construct damage degree recognition models. The overall accuracy (OA), Kappa, Macro-Recall (Rmacro), and Macro-F1 score (F1macro) of all models exceeded 0.8, and the best results were obtained for the 1D-CNN based on the vegetation index sensitive feature set (OA: 0.8950, Kappa: 0.8666, Rmacro: 0.8859, F1macro: 0.8839), while the SVM results based on both vegetation indices and texture features exhibited the poorest performance (OA: 0.8450, Kappa: 0.8082, Rmacro: 0.8415, F1macro: 0.8335). The results for the stand damage level identified by the models were generally consistent with the field survey results, but the results of SVMVIs+TF were poor. Overall, the 1D-CNN showed the best recognition performance, followed by the RF and SVM. Therefore, the results of this study can serve as an important and practical reference for the accurate and efficient identification of the damage level of forest trees attacked by EJD and for the scientific management of forest pests.

Management of Forest Pests and Diseases

The occurrence patterns of forest insect pests and diseases have been altered by global events such as climate change. Recent developments in improved monitoring methods and tools for data analyses provide new opportunities to understand the causes and consequences of such changes. Using a variety of management tools, forest pest management programs can mitigate the influence of global changes on forest health. The goal of this Special Issue is to improve our understanding of the root causes of changes that have induced global changes. Fifteen papers are included in this Special Issue, covering several issues in forest pest management. One paper reviews the causes of Korean oak wilt, and another paper discusses fourteen invasive tree pests in Russia. The remaining thirteen papers cover issues related to the monitoring and management of forest pests. These studies provide a better understanding of the causes of change in the patterns of forest pests under the influence of global changes. These reviews also contribute to the development of forest-pest-management strategies to mitigate such impacts on forests due to global changes.

Using RNAi to silence heat shock protein has congeneric effects in North America’s Dendroctonus bark beetles

Losses associated with forest pest outbreaks are increasing at an alarming rate, exacerbated by fluctuating climate patterns, and unimpeded by traditional management approaches that fail to keep pace with growing pressures. Future forest pest management strategies demand augmentation with next generation approaches. RNA interference, or RNAi, is a naturally occurring eukaryotic immune response to viral infection that works by disrupting the translation of mRNA into protein and can be manipulated to cause insect mortality through the introduction of carefully designed dsRNAs. The effective induction of the RNAi pathway depends on the exact match of a sequence at least sixteen nucleotides in length, making non-target effects unlikely. Thus, RNAi is increasingly praised as a species-specific pest management approach. The southern pine beetle (SPB), Dendroctonus frontalis, and its congener, the mountain pine beetle (MPB), D. ponderosae, are highly destructive forest pests endemic to North and Central America experiencing unprecedented range expansions, with extensive impacts on affected ecosystems. We have demonstrated that oral ingestion of specific dsRNAs induces gene silencing via RNAi and causes rapid and significant mortality in both SPB and MPB. Here we evaluate the ability of dsRNAs targeting SPB to affect gene expression in MPB, and the ability of dsRNAs targeting MPB to affect gene expression in SPB. We found that species-specific dsRNAs designed for gene silencing in one species can silence genes in the reciprocal species, offering the potential for development of RNAi as a Dendroctonus-specific management tool against rapidly expanding bark beetle populations.

Simulating Pine Wilt Disease Dispersal With an Individual-Based Model Incorporating Individual Movement Patterns of Vector Beetles.

Individual movements of the insect vector pine sawyer beetles were incorporated into an individual-based model (IBM) to elucidate the dispersal of pine wilt disease (PWD) and demonstrate the effects of control practices. The model results were compared with the spatial data of infested pine trees in the Gijang-gun area of Busan, Republic of Korea. Step functions with long- and middle-distance movements of individual beetles effectively established symptomatic and asymptomatic trees for the dispersal of PWD. Pair correlations and pairwise distances were suitable for evaluating PWD dispersal between model results and field data at short and long scales, respectively. The accordance between model and field data was observed in infestation rates at 0.08 and 0.09 and asymptomatic rates at 0.16–0.17 for disease dispersal. Eradication radii longer than 20 m would effectively control PWD dispersal for symptomatic transmission and 20–40 m for asymptomatic transmission. However, the longer eradication radii were more effective at controlling PWD. Therefore, to maximize control effects, a longer radius of at least 40 m is recommended for clear-cutting eradication. The IBM of individual movement patterns provided practical information on interlinking the levels of individuals and populations and could contribute to the monitoring and management of forest pests where individual movement is important for population dispersal.

Identifying optimal reference genes for gene expression studies in Eurasian spruce bark beetle, Ips typographus (Coleoptera: Curculionidae: Scolytinae)

Eurasian spruce bark beetle (Ips typographus [L.]) causes substantial damage to spruce forests worldwide. Undoubtedly, more aggressive measures are necessary to restrict the enduring loss. Finishing genome sequencing is a landmark achievement for deploying molecular techniques (i.e., RNA interference) to manage this pest. Gene expression studies assist in understanding insect physiology and deployment of molecular approaches for pest management. RT-qPCR is a valuable technique for such studies. However, accuracy and reliability depend on suitable reference genes. With the genome sequence available and the growing requirement of molecular tools for aggressive forest pest management, it is crucial to find suitable reference genes in Ips typographus under different experimental conditions. Hence, we evaluated the stability of twelve candidate reference genes under diverse experimental conditions such as biotic (developmental, sex and tissues) and abiotic factors (i.e., temperature and juvenile hormone treatment) to identify the reference genes. Our results revealed that ribosomal protein 3a (RPS3-a) was the best reference gene across all the experimental conditions, with minor exceptions. However, the stability of the reference gene can differ based on experiments. Nevertheless, present study provides a comprehensive list of reference genes under different experimental conditions for Ips typographus and contributes to “future genomic and functional genomic research”.

The Impact of Administrative Partitioning on the Regional Effectiveness of Forest Pest Management in Protected Area-Centered Ecosystems

Research Highlights: Forest pest outbreaks that cross jurisdictional boundaries pose particular challenges, since both ecological and social factors influence the effectiveness of management responses. This study found that difficulties emerge from the misalignment of management objectives and policies that deter collaboration. The sharing of resources and collaborative responses to outbreaks may improve management outcomes. Background and Objectives: This study examines if and how boundaries influence the effectiveness of forest pest management within the protected area-centered ecosystems of Rocky Mountain National Park and Grand Canyon National Park, USA. Materials and Methods: Using semi-structured interviews and a survey distributed to forest managers, we explored how partitioning affects pest management effectiveness and identified barriers to and strategies for managing outbreaks that cross boundaries. Results: Cross-boundary outbreaks are uniquely challenging due to federally mandated policies, agency mission misalignment, a lack of formal collaboration, and a lack of public support for timber management programs. Strategies that may improve outcomes include reevaluating problematic policies; ensuring messaging is consistent across agencies; and developing a preventative cross-boundary forest insect outbreak management team. Conclusions: Measures to increase collaboration in multi-jurisdictional landscapes will help managers prepare for future forest pest outbreaks, which are expected to increase in frequency with climate change.