Insects

RNA viruses are common in tephritid fruit flies including the Queensland fruit fly, Australias most significant horticultural pest. For many their transmission, tissue tropism and load across host development remain unexplored. Yet these factors are important for host biology, ecology and pest management. We investigated Bactrocera tryoni orbivirus (OV), Bactrocera tryoni xinmovirus (XV), Bactrocera tryoni toti-like virus (TLV) and Bactrocera tryoni iflavirus species 2 (IVsp.2) that commonly coinfect B. tryoni laboratory populations. OV and XV transmission was vertical within and on eggs, while TLV transmission was vertical within eggs. IVsp.2 was not detected in eggs but was present in adults; however, IVsp.2 was horizontally transmitted, with viral load increasing with cohabitation time with infected flies. Horizontal transmission was not observed for the other viruses. OV had a similar load across all tissues, while XV was consistently more abundant in ovaries. TLV had a high viral load in the brain whereas IVsp.2 was abundant in the thorax, foregut and midgut. Besides differences in eggs, the viruses were detected in all other developmental stages, but viral load patterns differed: viral load remained constant for TLV, fluctuated for OV and XV, and was low in pre-adult stages and high in adults for IVsp.2. Our findings demonstrate distinct transmission strategies and tissue tropism among the viruses, providing new insights into their epidemiology and role in host biology. Furthermore, contrary to prevailing views that viruses are generally horizontally transmitted, most known RNA viruses of B. tryoni are vertically transmitted affecting the evolution of host-virus interactions.

Iron is an essential nutrient for all types of organisms, including insects and the microbes that infect them. We predicted that insects fed an iron-supplemented diet would accumulate more iron in their hemolymph, and, because infectious microbes acquire iron from their hosts, that this extra iron would increase the severity of bacterial infections. To test this hypothesis, we studied the effects of dietary iron supplementation on infection outcomes in Manduca sexta (tobacco hornworm). Larvae were fed an artificial diet, with or without antibiotics, or the same diets supplemented with 10 mM iron. Control and iron-treated larvae were inoculated with non-pathogenic Escherichia coli or the entomopathogenic Enterococcus faecalis, and bacterial load and larval survival were measured. We found that dietary iron supplementation increased the iron content of hemolymph by approximately 20 fold; however, contrary to our prediction, this increase in iron did not result in an increase in the bacterial load of either E. coli or E. faecalis. The effect of iron supplementation on survival was more complicated. As expected, for larvae inoculated with nonpathogenic E. coli, iron supplementation had no effect. For larvae inoculated with E. faecalis, the effect of iron supplementation depended on whether antibiotics were present in the diet. Without antibiotics, iron supplementation prolonged larval survival; with antibiotics, iron supplementation decreased larval survival. The results of this study do not support the hypothesis that dietary iron supplementation increases infection severity in M. sexta. Instead, the results support the viewpoint that the relationship between dietary iron and infection outcome is complex.

Methods for estimating and modeling the long-term and short-term adult flight dynamics of the conifer silk moth Dendrolimus superans (Lepidoptera: Lasiocampidae) are examined. The analysis uses light trap adult catch data collected over 21 years, from 2005 to 2025. Three models of adult flight are considered: a flight-initiation model driven by weather factors, an autoregressive model of long-term catch dynamics, and a binary model of seasonal catch. For the flight-initiation model, we propose estimating the accumulated temperature sum ST from the date when the first derivative of the remote sensing vegetation index NDVI becomes positive until the date of the first adult capture of the season. ST is shown to be sufficiently stable across all years of observation, with flight each year beginning after this temperature sum is reached. The second model demonstrates that the long-term light trap catch time series is well described by a second-order autoregressive model AR(2), in which the catch of the current year depends on catches from the two preceding years. This long-term series is compared with a previously studied larval population density series of the Siberian silk moth; both are shown to be AR(2) series with similar coefficient values, which suggesting that adult catch data may serve as a proxy for absolute larval population density. In the third model, we describe the transition from absolute-scale seasonal catch dynamics (number of adults per day) to a binary scale (0, 1), where 0 denotes days on which no adults were attracted to the trap, and 1 denotes days on which at least one individual was captured. The seasonal absolute catch series is thereby transformed into a binary series of zeros and ones, and relationships between adjacent values in such a binary series are examined. A linear relationship between the absolute and binary seasonal dynamics series is demonstrated, making it possible to estimate absolute catches from binary catch values and to analyze seasonal flight in sparse pest populations. This potentially opens new avenues for understanding how outbreak populations function at chronically low density. Author summaryForest pests can cause catastrophic damage, yet predicting their outbreaks remains challenging. During periods of low population density, standard monitoring methods become labor-intensive and uninformative, while the transition to an outbreak often occurs unexpectedly. Using a 21-year dataset of adult Siberian silk moth (Dendrolimus superans) captures from light traps, we developed an approach combining three complementary models. First, we showed that moth flight begins upon reaching a specific temperature sum, with the starting point determined by NDVI vegetation index dynamics rather than a calendar date--making the forecast more ecologically relevant. Second, long-term adult population dynamics follow a second-order autoregressive model AR(2), matching the dynamics previously observed for larval populations. This establishes light trap data as a reliable proxy for absolute population density when ground surveys are impractical. Third, we introduced a method to analyze seasonal flight using binary data (presence/absence of moths per day), which we showed is linearly related to absolute abundance. This enables studying population dynamics during periods of extremely low density, when traditional methods fail. Our approach opens new possibilities for early warning systems to detect when a population risks transitioning from a latent state to an outbreak phase.

Accurate species identification is crucial to assess the medical and veterinary relevance of a mosquito specimen, but it requires high experience of the observers and well-equipped laboratories. This study aimed to evaluate whether low-cost imaging in combination with geometric wing morphometrics can provide accurate identification of invasive, morphologically similar Aedes species. The right wings of 670 female specimens covering 184 Ae. aegypti, 156 Ae. albopictus, 166 Ae. j. japonicus and 164 Ae. koreicus, were removed, mounted and photographed with a professional stereomicroscope (Olympus SZ61, Olympus, Tokyo, Japan) and a macro lens (Apexel-24XMH, Apexel, Shenzhen, China) attached to a smartphone. The coordinates of 18 landmarks on the vein crosses were digitalized by a single observer for each image. In addition, the landmarks of 20 specimens per species and imaging device were digitalized by six different observers to assess the degree of the observer error. The superimposed shape variables were used to compare the species classification accuracy of linear discriminant analysis (LDA), support vector machine (SVM), Random Forest (RF), and XGBoost. In the single-observer landmark data, the LDA achieved the best classification results with a mean accuracy of 95 % for landmarks from microscope images and 92 % for those obtained from smartphone images. In the multi-observer landmark data, LDA consistently performed worse than the other three classifiers, and the reduction in the accuracy was more pronounced for smartphone images than for microscope images. This pattern was associated with a higher degree of observer error for smartphone images, as confirmed by a landmark-wise comparison across all landmarks. Geometric wing morphometrics provides a reliable method to distinguish the most common invasive Aedes species in Europe. Thereby, the image quality obtained by smartphones equipped with a macro lens is sufficient and represents a cost-effective alternative to professional microscopes. However, due to the greater degree of observer variation for smartphone images, landmark coordinates for such images should ideally be collected by a single observer.

Plant parasitic nematodes (PPNs) are microscopic soil dwelling pests that infect crops, using a lance-like organ, the stylet, to hatch, invade plant roots, and establish feeding sites. Stylet function is underpinned by pharyngeal muscle contraction and relaxation cycles, making it an attractive route to disrupt the PPN lifecycle. However, knowledge of pharyngeal regulation in PPNs is relatively limited. In the free-living nematode Caenorhabditis elegans, the nicotinic receptor EAT-2 stimulates pharyngeal contraction to facilitate feeding. Here we hypothesize that EAT-2 orthologues may regulate a similar function in PPNs. A phylogenetic analysis reveals that EAT-2 and its orthologues in other nematode species cluster as a distinct group suggesting that EAT-2 is exclusive of other animal species. We identified eat-2 in the genome of the potato cyst nematode Globodera rostochiensis and used in situ hybridization to establish an anterior expression pattern consistent with a pharyngeal function. In vitro pharmacological assays directly compared the response of C. elegans pharynx and G. rostochiensis stylet to cholinergic compounds. Both pharyngeal and stylet activity were stimulated by acetylcholine and nicotine, and these responses were blocked by the nicotinic receptor antagonists, mecamylamine and tubocurarine. These data are consistent with a conserved cholinergic pathway mediated by EAT-2 regulating pharyngeal muscle function. It highlights EAT-2 as a potential determinant of stylet thrusting and a promising pharmacological target to selectively mitigate PPN infections.

O_LIAlthough ecological research has long focused on the effects of temperature on population growth, arthropod pests are exposed to a wide variety of environmental factors that affect their performance, such as chemical pesticides targeted against them. Moreover, these environmental factors likely do not act in isolation. Identifying the extent to which abiotic factors interact to affect pest population dynamics can strengthen current and future pest management programs. C_LIO_LIHere, we investigated the extent to which temephos, a common pesticide applied to aquatic environments for mosquito control, influences the thermal performance of juvenile survival and development rate, as well as the intrinsic population growth rate, of the invasive mosquito pest, Aedes aegypti. We implemented a response surface experimental design to measure these traits across seven temperatures and five temephos concentrations and fit temperature- and insecticide-dependent performance curves to assess impacts on the overall performance and the thermal optimum, minimum, and maximum. C_LIO_LITemephos exposure profoundly altered the thermal performance of juvenile survival by reducing survival across all temperatures, shrinking the thermal breadth, and shifting the thermal optimum to warmer temperatures. Through this, temephos also altered the thermal performance of population growth primarily by reducing its thermal breadth. C_LIO_LISynthesis and applications: Our findings demonstrate that interactions between temperature and insecticide exposure can fundamentally reshape pest population dynamics, rather than acting as independent stressors. By quantifying this interaction, we showed that temphos is most effective below the pests thermal optimum, suggesting that larvicides may yield the greatest population suppression in cooler regions or during cooler periods of the year. Incorporating such temperature-dependent efficacy into pest management strategies could improve the timing and spatial targeting of control efforts. More broadly, these results highlight the need to integrate anthropogenic stressors with climatic drivers when predicting pest risk and optimizing management under ongoing environmental change. C_LI

BackgroundThe malaria transmission potential and the vulnerability of Anopheles mosquitoes to different vector control methods depend, among other factors, on the endophily, endophagy, anthropophagy and survival of each species. Local information on these bionomic parameters is generally unavailable. MethodsTo address this, we estimated species-specific values of these parameters using an augmented version of the global database of bionomics data by Massey et al. (2016). We applied inclusion and exclusion criteria to select eligible studies with relevant experimental designs that minimise bias from collection methods for parous, sac, endophagy, and endophily rates as well as for the resting duration. For the human blood index (HBI), we separated data from indoor and outdoor collections. We fitted hierarchical Bayesian models with levels based on Anopheles taxonomy to estimate these quantities. Based on the estimated bionomics, we quantified the expected vectorial capacity reduction after the introduction of a pyrethroid-pyrrole insecticide-treated net (ITN) for 57 Anopheles species. ResultsWe identified 26 eligible studies for endophagy and 61 for the parous rate, leading to a Bayesian posterior average for the Anopheles genus of 42% (95% credible interval: 18-70) and 55% (32-77) respectively. HBI values widely varied depending on the location of collection, except for some species showing strong anthropophilic behaviours. Resting duration was estimated to be 2.1 days (1.2 - 4.8) at the genus level. Few studies were available to estimate the sac and endophily rates, which prevented us from deriving precise estimates for the whole Anopheles genus. Our estimates of the vectorial capacity reduction following the introduction of a pyrrole-pyrethroid ITN ranged between 48% and 76% across species, highlighting the important differences among mosquito species in vulnerability to vector control interventions. ConclusionThis work demonstrates how data from both Anopheles species complexes and individual species can be leveraged to generate species-specific estimates of bionomic parameters, capturing the local characteristics and behaviour of malaria vectors. The dataset is readily updatable as new data become available. However, more frequent and standardised field surveys are still needed to accurately characterise local vector behaviour.

O_LIPhenological shifts are a major ecological consequence of climate change, yet studies often focus on single life stages meaning that the potential for carryover effects between life stages remains poorly understood. Failing to account for these effects may lead to inaccurate estimates of phenological shifts, with consequences for predicted synchrony among interacting species. This is especially relevant for temperate systems where climate warming is occurring unevenly across the year. C_LIO_LIHere, we investigated how temperature experienced the previous autumn and winter (during the pupal and egg stage) influences spring phenology in the winter moth (Operophtera brumata), a herbivorous insect with distinct life stages. Using 50 years of local climate data to create five experimental temperature regimes, we first quantified phenotypic plasticity in the duration and temporal variability of pupal and egg development. We then examined how timing of adult moth emergence affects timing of offspring hatching. C_LIO_LIWe found divergent effects of temperature on different life stages; pupal development time was shortest at intermediate temperatures while egg development time decreased linearly with increasing temperature. Furthermore, phenological shifts due to the conditions experienced by the mother were carried over to influence the phenology of her offspring. While this carryover effect was partially compensated during subsequent stages, compensation decreased under warming conditions. C_LIO_LIThese results refine our understanding of the sensitivity of the annual cycle of winter moth phenology to variation in temperature with potential implications for population dynamics and interspecific interactions. Overall, our findings highlight the need to consider the impacts of warming across multiple life stages so that carryover effects can be properly accounted for. Doing so will improve predictions of phenological shifts under future climates. C_LI

BackgroundThe cotton bollworm Helicoverpa armigera is a major global pest controlled by genetically engineered crops expressing Bacillus thuringiensis (Bt) toxins, including Vip3Aa. While Vip3Aa is widely deployed, the genetic basis of resistance remains poorly understood. Previous work identified disruption of a thyroglobulin-like gene (HaVipR1) as one mechanism of resistance, suggesting additional loci may be involved. ResultsUsing linkage analysis, transcriptomics, long-read sequencing, and CRISPR-Cas9 gene editing, we identify a second thyroglobulin-like gene, HaVipR2, as a novel mediator of Vip3Aa resistance. Resistance in a field-derived H. armigera line was shown to be monogenic, recessive, and autosomal, mapping to chromosome 29. Long-read sequencing revealed a [~]16 kb transposable element insertion disrupting HaVipR2, which was undetectable using standard short-read approaches. CRISPR-Cas9 knockout of HaVipR2 conferred >900-fold resistance, confirming its causal role. Comparative analyses show that HaVipR1 and HaVipR2 share conserved domain architecture, indicating that thyroglobulin-domain proteins represent a recurrent target of resistance evolution. ConclusionsOur findings establish thyroglobulin-domain proteins as a new class of Bt resistance genes in Lepidoptera and demonstrate that transposable element insertions can drive adaptive resistance while evading detection by conventional methods. These results highlight the importance of long-read sequencing and accurate genome annotation for resistance monitoring and provide new insights into the molecular basis and evolution of Vip3Aa resistance.

BackgroundOviCol has recently been proposed as a disruptive strategy for the surveillance and control of synanthropic Aedes mosquitoes, vectors of dengue, Zika, and chikungunya viruses. The approach integrates monitoring and control through ultra-low-cost ovitraps ([~]0.2 USD), bioattractants, and egg inactivation using hot water. However, large-scale ovitrap surveillance generates thousands of egg substrates that require time-consuming manual counting, creating a major operational bottleneck. To address this limitation, we developed Col-Ovo, an artificial intelligence-based tool for automated counting of Aedes aegypti eggs from real field samples, together with OviLab, a digital platform for annotation, curation, and management of entomological image datasets. Methodology/Principal FindingsThe detection model was trained using YOLOv11m on a dataset of 275 oviposition substrates (20.5 cm strips) collected under routine operational conditions. Images were captured in situ without preprocessing and included substrates heavily stained by bioattractants such as blackstrap molasses and dry yeast (Saccharomyces cerevisiae), as well as sand and particulate debris, reflecting realistic field conditions. The system was designed to operate with standard smartphone images and tolerate compression artifacts produced by messaging platforms such as WhatsApp. Performance was evaluated by comparing automated egg counts with expert manual counts and with virtual-human counts conducted in OviLab using >200% image magnification. Col-Ovo achieved >95% agreement with expert counts and 88% agreement with OviLab while reducing processing time from approximately 15 minutes to <3 seconds per sample. Conclusions/SignificanceCol-Ovo enables rapid, scalable quantification of Ae. aegypti eggs from smartphone images, addressing a critical operational barrier in ovitrap-based surveillance. The system requires no image preprocessing or specialized hardware and is accessible through a lightweight web interface supported by an AI architecture that allows retraining for new ecological contexts or additional Aedes species. Integrated with OviLab, this platform provides a flexible digital infrastructure that can strengthen routine vector surveillance and community-level control programs across regions where Aedes mosquitoes continue to expand. Author SummaryMosquitoes that transmit dengue, Zika, and chikungunya are expanding in many parts of the world. Monitoring their populations is essential for guiding prevention and control actions. A common surveillance method uses small traps where female mosquitoes lay their eggs. By counting the eggs collected in these traps, health programs can estimate mosquito abundance and detect increases in risk. However, the eggs are extremely small: about 0.065 mm{superscript 2}, and are usually counted manually under magnification. This process is slow, requires trained personnel, and limits how many samples can be analyzed in routine surveillance. In this study, we developed a digital tool that automatically counts mosquito eggs from photographs taken with a smartphone. The system was trained using images collected under real field conditions, including samples with stains, dirt, and other materials commonly found in mosquito traps. The tool can analyze images even when they are compressed and shared through WhatsApp. By reducing counting time from 15 minutes to only a 25 seconds, this approach can help strengthen mosquito surveillance and support faster responses to mosquito-borne disease risks.

The tropical house cricket Gryllodes sigillatus is a major species used in the edible insect farming industry. Despite the rapid expansion of this sector, diagnostic tools for detecting infections in these species remain limited. The lack of validated reference genes compromises the reliability of RT-qPCR-based gene expression analyses, which are essential for the development of molecular tools for disease diagnosis and health monitoring in insect production systems. To address this gap, we evaluated the expression stability of six candidate reference genes (ACTB, EF1, GAPDH, HisH3, RPL5, and 18SrRNA) across four body parts (abdomen, head, legs, and whole body) using a combination of complementary statistical approaches, including geNorm, NormFinder, BestKeeper, the {Delta}Ct method, the R statistical environment, and the integrated RefFinder tool. Candidate genes were identified and annotated using the recently published G. sigillatus genome, through sequence comparisons with closely related insect species using BLAST and reciprocal BLAST analyses, multiple sequence alignments. All procedures complied with MIQE 2.0 guidelines to ensure methodological rigor and transparency. The results showed that ACTB, EF1, RPL5, and 18SrRNA exhibited stable and consistent expression across all analyzed tissues, whereas GAPDH and HisH3 displayed high variability and were generally unsuitable for normalization, except in head tissue where GAPDH remained stable. This study provides the first validated set of reference genes for G. sigillatus, establishing a robust foundation for accurate, reproducible, and comparable gene expression analyses. Furthermore, these findings support the development of RT-qPCR-based diagnostic tools, contributing to improved health monitoring and biosafety in insect production systems.

Myrmecocystus honeypot ants rely on specialized workers, repletes, to store dissolved carbohydrates in their crops long term. The repletes store this liquid, which does not spoil in their crops, for many months at a time. When resources are scarce, repletes redistribute the stored nutrients to their colony members via trophallaxis. While we suspect that the gut microbiome of honeypot ants may aid in spoilage prevention, before we can investigate this, we must first characterize it. Here, we used 16S rRNA gene sequencing to determine the microbial community composition across six Myrmecocystus honeypot ant species, sampling multiple colonies, castes, and organs. We found that microbiome community composition was strongly shaped by species, with variation between colonies in M. arenarius, M. depilis, and M. mexicanus. Organ level differences were observed in the crop and midgut in M. mexicanus. Caste differences were observed in M. flaviceps and M. mexicanus. Replete crops of M. mexicanus and M. depilis were enriched in Fructilactobacillus, other lactic acid bacteria, and acetic acid bacteria, whereas halophiles were more prominent in the gut of species such as M. flaviceps and M. wheeleri. In this study we demonstrate that Myrmecocystus ants host species-specific gut microbiomes and identify an association between lactic acid bacteria, acetic acid bacteria, and halophiles within replete crops. While much work remains in understanding the roles of the microbes in the symbiosis with their host ants, the dominance of these particular taxonomic groups suggests an association with a high sugar environment and a potential microbial role in preventing spoilage of the crop contents.

Understanding behavioral differences between non-native and closely related endangered species could be important to aid conservation management. In volume 169 of Zoology, Bels et al. (2025) reported on their comparison of display-action-patterns (DAP) between native Iguana delicatissima and non-native iguanas present on islands of the Guadeloupe Archipelago in the Caribbean Lesser Antilles. Here, we address conceptual and methodological concerns about their work and reanalyze their data given our proposed corrections, primarily a literature-informed adjustment of their "species" category. We additionally utilize online videos from South American mainland I. iguana populations, from where the non-native iguanas in the Guadeloupe Archipelago originate, to better understand the different DAPs between native and non-native iguanas in the Guadeloupe Archipelago. Significant differences in DAP characteristics among "species" categories (native I. delicatissima, non-native iguanas, and hybrids) show that Bels et al. (2025) oversimplified their data analyses by merging all non-native populations into one group. This result indicates the presence of behavioral variation among subpopulations within widely hybridizing iguanid populations, which has been poorly studied. Additionally, videos from mainland populations across two major mitochondrial clades of Iguana iguana show that non-native iguanas on Guadeloupe retained DAP characteristics of those populations from which they originate. We discuss these findings in light of the proposed hypotheses put forward by Bels et al. (2025), of which two can be excluded. Overall, our reanalysis shows that studies focusing on characteristics within settings of complex hybridization in diverse species should acknowledge this complexity.

Stingless bees are key pollinators in tropical ecosystems, yet their ecological dynamics remain poorly understood in highly seasonal environments such as the seasonally dry tropical forests of Ecuador. These ecosystems experience pronounced climatic seasonality, with sharp transitions between dry and wet periods that strongly affect floral resource availability. Understanding interspecific competition and niche partitioning in such systems is critical, particularly given the global decline of pollinators. We investigated resource use and niche dynamics in two native stingless bees, Melipona mimetica and Scaptotrigona sp., by quantifying pollen, nectar, and resin collection across seasons. Log-linear models were used to test the effects of species, season, and their interaction on resource use, while non-metric multidimensional scaling (NMDS) assessed niche overlap. Contrary to the expectation that niche overlap increases under resource scarcity, we found greater overlap during the wet season, when resources are more abundant. This suggests that both species converge on high-quality floral resources during peak availability, reflecting an adaptive response to strong environmental seasonality. Pollen use remained stable across seasons, consistent with generalist foraging behavior. In contrast, nectar collection increased significantly during the wet season, while resin exhibited a shared seasonal peak, likely associated with synchronized nest construction or maintenance. These findings reveal context-dependent competition dynamics and highlight the role of environmental seasonality in shaping pollinator interactions. Our study provides new insights into the ecology of threatened stingless bees and contributes to their conservation in tropical dry forest ecosystems.

BACKGROUNDThe two-spotted spider mite, Tetranychus urticae Koch, is a major agricultural pest with a rapid propensity for developing acaricide resistance. Bifenazate targets mitochondrial cytochrome b (CYTB). While the G126S mutation is frequently associated with resistance, its independent role remains unclear as it often occurs with other substitutions. This study explores the molecular basis of bifenazate resistance in a Russian laboratory strain derived from a St. Petersburg greenhouse population. RESULTSDisruptive selection with increasing bifenazate concentrations generated resistant and susceptible isofemale lines. AlphaFold2 structural modeling of CYTB indicated that G126S causes a steric clash, leading to conformational destabilization, whereas other reported mutations primarily affect the ligand-binding pocket. Oxford Nanopore sequencing revealed a very low initial frequency of the G126S allele (<1%; 226/35,895 reads) in the unselected population. After one year of stepwise selection (0.00005-0.031% a.i.), the mutant allele frequency surged to 90% (7,272/8,056 reads). No other known resistance-associated mutations were found in the analyzed cytb fragment. CONCLUSIONWe report the first identification of the G126S mutation in a Russian T. urticae population and demonstrate its rapid fixation under bifenazate selection. Within this genetic background, G126S alone appears sufficient to confer high-level resistance, emphasizing the population-specific nature of resistance evolution and the critical need for local monitoring.

Pollen is a robust and widespread substance that captures a historical snapshot of a specific time and place, and it can be used to track movements through space by examining the pollen deposited on various objects. Palynology, the study of pollen, is used across fields such as conservation, natural history, and forensics, where it is particularly useful for tracing the origin and movement of objects. However, pollen has remained underutilized due to the difficulty of distinguishing many pollen taxa beyond the family level and limited pollen reference material to support location predictions. With recent developments in pollen DNA metabarcoding these issues have been rectified, but much of the available pollen data are primarily from wind-pollinated species, which are widespread and less informative of specific sample locations. Bee-collected pollen presents an untapped resource in training predictive models to geolocate sample origin. Here we compiled bee-collected pollen DNA sequence relative abundance data from three projects in the western U.S. and assessed the accuracy of supervised machine learning models to predict the location of sample origin based solely on pollen assemblage, without the need of incorporating additional data. Random Forest and k-Nearest Neighbors models yielded high accuracy across all projects. We also found that models trained on taxonomically clustered pollen assigned sequence variants (ASVs) performed slightly better than those trained on raw sequence data, but the difference was minor, indicating that models trained on raw sequence data can reliably predict location and avoid the time-consuming taxonomic assignment process. Our results demonstrate the utility of repurposing bee-collected pollen for geolocation and provide a framework for employing supervised machine learning in future geolocation efforts. HighlightsO_LIBee-collected pollen metabarcoding data was used to accurately predict sample origin C_LIO_LIRandom Forest and k-Nearest Neighbors algorithms were most accurate with lowest error C_LIO_LITaxonomically-classified and raw DNA sequence data training sets performed comparably C_LI

Sentinel behaviour occurs when individuals use raised positions to scan for predators while the rest of the group forages. Here, we investigated whether a colonial cooperatively breeding species that forages in large groups, the sociable weaver, Philetairus socius, displays sentinel behaviour. This behaviour has been reported in species with similar ecology, behaviour and foraging habits, (e.g. ground foraging in open habitats where aerial predators are common) and, hence, we expected that it could occur in sociable weavers. On the other hand, sentinel behaviour appears to be less common in species that live in very large groups. We used an experimental set-up consisting of an artificial feeding station and perches to assess occurrence of sentinel related behaviours: (i) perching events > 30s on an elevated position, (ii) head-movements and (iii) alarm calling. Birds were seldom observed perching while others fed, and those that did, perched for periods that were too short to be considered as sentinel behaviour (less than 5s on average). Our results suggest that this behaviour is uncommon or even absent in sociable weavers. We discuss whether other factors such as foraging in very large groups, or interspecific foraging associations might make sentinel behaviour less important in this species.

The tobacco hornworm moth (Manduca sexta) is evaluated as a model of bacterial virulence and host-pathogen dynamics. Infections of Pseudomonas aeruginosa were established by injection of 5th-instar larvae, and multiple assays of virulence were evaluated. Infected larvae exhibited dose-dependent mortality, reduced growth, melanization, behavioral changes, and altered frass constitution. Even low-dose infections that were not fatal exhibited impaired growth, but individual growth trajectories revealed considerable heterogeneity among worms given the same dose. Twice-daily antibiotic treatment with gentamicin or cefepime improved survival four- to five-fold but did not rescue 100%. Heat-killed cells and filtered culture supernatant alone induced significant morbidity and mortality, suggesting secreted bacterial products are important to pathogenesis. Bacterial burden analysis revealed a shifting bacterial distribution over time, with decreasing hemolymph titers and increasing localization in fat body, gut, and carcass. Hornworms thus offer a more sensitive analysis of bacterial infection dynamics and consequences than do larvae of the more commonly used wax moth.

Honeypot ants represent an example of convergent evolution, where a group of workers specialized in storing liquid food in their crops (i.e., stomach) has independently evolved multiple times across different ant genera. While seasonal resource scarcity and arid conditions are thought to drive the evolution of repletism, the role of environmental variables in this process has not been tested. With this is mind, species ensemble models were computed to assess suitability and richness areas, and the importance of predictors. Predictor importance was compared between genera and groups occupying a similar geographical area. Niche overlap and similarity between honeypot ant species were also evaluated to determine whether they occupy similar environmental spaces. Similarity was mainly found within genera, and Leptomyrmex and Myrmecocystus showed striking niche differences. Overall, Leptomyrmex distribution was mainly influenced by atmospheric bioclimatic variables like precipitation and temperature, while Myrmecocystus had soil bioclimatic variables as the most important predictors for their current distribution. Our results indicate that honeypot ants species currently do not occupy the same environmental space, and are not experiencing the same contemporary environmental stressors. While our results suggest that contemporary environmental factors cannot explain the convergence of honeypot ants, future research will examine past climatic conditions along with investigations into the ant genomes to understand more about the causes and consequences of the convergence.

The western honey bee (Apis mellifera) is an essential pollinator facing unprecedented threats from pesticide exposure. While pesticide resistance evolution is well documented in agricultural pests, our understanding of genetic variation in honey bee detoxification systems remains limited. This represents a missed opportunity, as harnessing naturally occurring detoxification diversity could provide new avenues for pollinator protection. Cytochrome P450 monooxygenases (CYPs), which are central to xenobiotic metabolism, offer a promising starting point. Here, we present the first comprehensive analysis of CYP genetic diversity in A. mellifera. We analysed the CYPome of 1,467 individuals representing 18 A. mellifera subspecies from 25 countries and identified 5,756 single-nucleotide polymorphisms (SNPs) in 46 CYP genes. Imputed McDonald-Kreitman testing revealed that 56% of non-synonymous CYP substitutions were driven by positive selection. Of the 1,302 haplotypes identified, 84% resided in CYP3, concentrated in the CYP9 and CYP6AS subfamilies implicated in xenobiotic detoxification. Population-level analysis of nucleotide diversity, Tajimas D selection signatures, FST-based differentiation, and McDonald-Kreitman testing pointed to CYP3 clan genes as the primary locus of adaptive variation. This work provides the first step toward building a comprehensive pharmacogenomic resource for honey bees, enabling the prediction of population-specific pesticide vulnerabilities and leveraging naturally occurring detoxification variants to enhance pollinator resilience - a critical step toward sustainable pollinator management.