Abstract Life table analyses in entomology are primarily age‐structured, despite many insect species having distinct life stages (e.g., egg, larva, pupa, adult). Stage‐specific parameters are frequently reported in studies using age‐structured models, even though these parameters are not directly incorporated into the analyses A key challenge in stage‐structured modelling is accurately representing stage duration distributions. Simplified assumptions, such as geometric distributions, are often used for convenience but can introduce bias and lead to inaccurate conclusions. This study introduces a method to directly incorporate arbitrary stage duration distributions into stage‐structured models without relying on approximations. The approach is demonstrated with an example and validated through simulations. The method effectively captures population dynamics with non‐standard stage duration distributions. Properly parameterized stage‐structured models enable the identification of critical targets for applications, such as pest management, which is challenging with age‐structured models.

Abstract The spotted‐wing drosophila, Drosophila suzukii , is one of the most damaging invasive fruit pests in the world. It infests a wide range of wild and crop host plants, impacting natural habitats and causing significant economic losses. Leptopilina japonica , a predominant larval parasitoid of D. suzukii in the native areas of the fly, is now spontaneously expanding into non‐native areas of its fly host. This study documents the presence and genetic structure of L. japonica collected from various wild and cultivated fruits across 11 sites in France in 2023. Leptopilina japonica emerged from 15% of fruit samples and was strongly positively associated with D. suzukii , showing parasitism rates of up to 38.5%, notably in Lonicera fruits. Despite this, D. suzukii remained dominant, indicating a limited current biocontrol effect, while native parasitoids were nearly absent from samples. Molecular analyses using COI markers revealed 10 distinct haplotypes of the L. j. japonica subspecies in France that clustered into three groups, suggesting multiple introductions and/or migration routes into France from Asia, North America and neighbouring European countries. The lack of nuclear diversity measured from ITS2 markers suggests that the colonization is recent and that the populations experienced a bottleneck process. Nevertheless, a more extensive sampling combined with the use of additional genetic markers would be needed to better understand the origin and spread of L. japonica and its consequences on the equilibrium of Drosophila communities.

Abstract Monitoring hover fly populations is essential for establishing richness and diversity and their potential links to ecosystem service provision. While pan traps and hand netting are widely used in monitoring insects in natural habitats, their comparative performance in estimating hover fly (Diptera: Syrphidae) diversity in Afrotropical agroecosystems remains understudied. This study assessed the effectiveness of yellow pan traps and hand netting in estimating the richness and diversity of hover flies over two consecutive years (2022–2023) in a cucurbit agroecosystem in Morogoro, Tanzania, across two contrasting landscapes (plateau and mountainous zones). Weekly sampling was conducted for eight consecutive weeks during both the rainy (April–June) and dry (September–November) seasons across 20 cucurbit plots. In each plot, nine yellow pan traps were deployed for 48 h, and hand netting was conducted along three 15‐m transects for 45 min per session. Hand netting consistently recorded higher hover fly diversity than pan traps across all Hill numbers— q = 0 (species richness), q = 1 (Shannon diversity) and q = 2 (Simpson diversity). Species accumulation curves reached asymptotes more rapidly with hand netting, indicating greater sampling efficiency and community coverage. Although more labour‐intensive, hand netting provided a more comprehensive estimation of hover fly richness, abundance and diversity in both agroecological zones. In contrast, pan traps captured only a few additional low‐abundance species overlooked by netting, which are unlikely to contribute significantly to ecosystem service provision. Therefore, the study provides evidence that hand netting is the most robust and cost‐effective method for monitoring hover flies in this agroecosystem context, offering practical guidance for selecting appropriate sampling methods for monitoring insect species delivering ecosystem services in tropical agricultural landscapes.

Abstract The global food crisis remains a critical issue that requires urgent intervention, particularly through increased food production. As the third most important staple crop, rice plays a crucial role in sustaining global food security. However, rice cultivation in many regions around the world is severely threatened by the pest Laodelphax striatellus (Hemiptera: Delphacidae), resulting in significant losses in yield. Therefore, identifying the geographical distribution of this pest is essential for developing effective management strategies In this study, a MaxEnt model was employed using global distribution and environmental data to predict the current and future potential distribution of L. striatellus and assess spatial and temporal dynamics. Furthermore, changes in rice‐growing regions affected by this pest were analysed. The results revealed that the mean temperature of the driest quarter (BIO9) was the most influential environmental factor restricting the distribution of L. striatellus . Currently, suitable habitats of L. striatellus are widespread, predominantly across Asian and European countries. Under future climate scenarios, the total area suitable for this pest is projected to expand, although the extent of infested rice‐growing regions may decline. Among the 20 countries with the largest rice‐growing areas, only China's infected area is expected to continue increasing in the future, suggesting that it will become a priority area for control. These predictions provide essential insights for the strategic management of L. striatellus in the context of climate change, and contribute to ongoing efforts to manage its impact on rice production and global food security.

Abstract Recent progress in machine learning, particularly in convolutional neural networks, has greatly improved insect pest identification. Eurygaster integriceps , a highly polymorphic true bug and major wheat pest across the Western Palearctic, remains difficult to distinguish from its congeners even for specialists. Misidentifications reduce monitoring accuracy and hinder cost‐effective pest control. To support reliable identification by non‐experts while maintaining high classification accuracy, we trained the MobileNetV2 model on a large dataset combining images captured under controlled conditions with various devices, including a budget smartphone and photographs taken in the wild. The trained model demonstrated high classification metrics in identifying Eurygaster species, with macro precision, recall and F1‐score values of 0.901, 0.930 and 0.912, respectively. Based on this model, we developed an open‐source, web‐based application with a microservice architecture, allowing automated species identification from user‐uploaded images. Publicly accessible at https://eurygaster.ru , this tool supports faster and more accurate field identification, helping improve pest management decisions and reduce economic losses caused by misidentification.

Abstract Understanding the spatial and demographic structure of local outbreaks is critical for identifying the ecological mechanisms underlying invasive forest insect dynamics. We investigated a population outbreak of Sirex noctilio within a pine plantation in Patagonia by integrating spatial analyses of infestation patterns with quantification of oviposition behaviour and adult performance. At the plot level, the distribution of infested trees shifted from a highly clustered pattern in previous seasons to a more spatially dispersed one of newly attacked trees Logs sampled from S. noctilio ‐infested trees located in the outbreak epicentre and periphery showed no significant differences in total oviposition drills or estimated egg numbers; however, single (non‐reproductive) drills were more frequent in the periphery. Emergence of S. noctilio adults were higher in the periphery, though individuals were smaller, suggesting spatial variation in offspring performance within the outbreak area. These findings highlight spatial variation in oviposition behaviour and larval performance, suggesting the role of localized feedback and host availability in shaping outbreak trajectories. Our study emphasizes the importance of spatial structure in modulating demographic responses during a population outbreak, offering insights into context‐dependent regulatory mechanisms of invasive forest insect populations in simplified plantation systems.

Abstract Entomopathogenic nematodes (EPNs) are exempt from pesticide registration requirements in several countries due to their excellent safety profile regarding the surrounding ecosystem. Nonetheless, biocontrol agents (BCAs) remain among the least commercialised agro‐inputs. This is further evidenced by eight Steinernema and six Heterorhabditis species being commercialised from the identified 114 and 22 species, respectively. Notwithstanding the benefits of EPNs, there are several obstacles preventing their commercial application. To emphasise the need for increased commercially available EPNs products, this systematic study followed Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) to evaluate factors contributing to the lesser‐marketed EPNs. After a comprehensive search of databases including Science Direct, Scopus and Google Scholar, 3547 records were found, from which 101 articles met the inclusion criteria. The results showed that two primary obstacles for less commercialised EPNs are (i) their relatively high cost and (ii) inconsistent effectiveness. Increasing the manufacturing efficiency of EPNs, appropriate formulations and application technologies pose challenges to their market competency. To maximise the widespread use of EPNs, these methods are discussed together with their benefits and drawbacks. As such, initiatives to develop EPNs should be exponentially increased and founded on two key strategies: increasing the effectiveness and commercial competency of EPNs. This review is distinctive in synthesising ecological insights on EPNs diversity, survival and symbiotic relationships with their commercialisation status and policy frameworks, thereby highlighting actionable pathways to transform ecological knowledge into market‐ready, sustainable pest management solutions.

Abstract The western cedar bark beetle ( Phloeosinus punctatus LeConte) colonizes giant sequoia ( Sequoiadendron giganteum (Lindl.) J. Buchh.) branches and may build up large populations in broken or shed branches and woody debris, necessitating a possible need for intervention strategies. This study evaluates tarping treatments for managing P. punctatus populations in recently fallen branches in giant sequoia forests. A field experiment tested beetle emergence from debris piles relative to tarping treatments (covered or uncovered by a 4 mm clear polyethylene tarp) using a paired design, and the effects of several environmental factors on emergence were modelled. Tarping treatment resulted in a 53% reduction in mean beetle emergence; standardized beetle emergence was 9.8 ± 2.6 beetles/kg in the treatment group, 19.2 ± 5.6 beetles/kg in the control group and an average of 14.5 for the study. Mean temperatures were 21.8°C in tarped piles, compared to 19.7°C in control piles, indicating that tarping altered the thermal environment to impact emergence. No emergence occurred when the mean ambient temperature exceeded 24°C. Canopy openness also affected mean temperature in debris piles, with temperatures increasing sharply under more open canopy conditions. These results suggest that tarping is a simple and cost‐effective treatment for reducing P. punctatus populations in giant sequoia debris and may be a useful tool in integrated pest management strategies targeting this species.

Abstract Wireworms within the genus Agriotes (Coleoptera: Elateridae) can cause substantial damage to agricultural crops. The vertical movements of these pest insects in the soil make the timing of control measures a difficult task. The forecast model SIMAGRIO‐W utilizes soil temperature and moisture data to predict the migration of Agriotes wireworms to the upper soil layer. The model distinguishes between two risk levels: low risk (less than 30% of the wireworm population in the upper soil layer) and high risk (more than 30%), which are considered adequate for practical purposes. In German field sites, the model demonstrated an 80% success rate across four soil types. The SIMAGRIO‐W model was tested under the warm and dry climate in eastern Austria. The validation process revealed an overall accuracy of just 46%, primarily due to the fact that SIMAGRIO‐W assumes a maximum activity level for wireworms at 11°C. However, high activity levels were observed at soil temperatures of up to 26°C at the experimental sites. The discrepancy in the prediction power of the model between the German and Austrian field sites may be explained by differences in temperature tolerance between the Agriotes species occurring in eastern Austria (e.g. A. ustulatus) and in western Germany (e.g. A. obscurus). Our findings demonstrate that the thermal preferences of different wireworm species must be taken into account to make the SIMAGRIO‐W model a widely applicable decision support tool for predicting vertical movements of Agriotes wireworms.