The research, led by Felipe Goulart Gonçalves of the University of São Paulo’s Luiz de Queiroz College of Agriculture together with colleagues in Brazil and Ireland, combined field observations with laboratory behavioral assays to map the daily rhythms of emergence and dispersal in this economically important wood-boring beetle. The findings carry immediate practical weight: because the species damages bamboo used for construction, crafts, and livelihoods across Asia and beyond, knowing exactly when adults take to the air could transform how growers and quarantine officials monitor and manage infestations.

To capture the beetles at the moment of emergence, the team relied on a cleverly simple design. Naturally infested culms of Bambusa vulgaris, first exposed in a shaded field site near Atlantic Rainforest remnants in Piracicaba, Brazil, were transferred to the laboratory about a month after the first adult boring holes appeared, ensuring that only the first generation of beetles was followed. The culms were then placed inside black plastic emergence cages with a single opening fitted with a translucent collecting bottle, the only point of light within the enclosure. Newly emerged adults, drawn instinctively toward that light, crawled into the bottle, where researchers could count them every two hours from 06:00 to 20:00, with overnight captures recorded separately.

Flight activity was monitored in parallel using translucent cross-vane panel traps baited with a semiochemical blend of hexanal and decanal, straight-chain aldehydes previously shown to attract both male and female D. minutus. Four traps were suspended along a linear transect at roughly 1.2 meters above the ground, their collection bottles filled with a propylene glycol solution to preserve captured insects. Both experiments ran simultaneously from 18 June to 10 July 2020, with the emergence study yielding ten effective observation days and the trapping study sixteen consecutive collection days.

The results were strikingly consistent. Periodicity analyses using the Lomb–Scargle periodogram, a statistical tool borrowed from astronomy that detects rhythms in unevenly sampled time series, revealed significant daily periodicity in both behaviors, with estimated periods of roughly 23.9 hours for emergence and 23.8 hours for flight. Approximately 65 percent of all emerging adults appeared at the 14:00 sampling interval, while nearly 60 percent of all trap captures occurred at 16:00. Not a single beetle emerged or was captured during the night, marking the species as strictly diurnal in its dispersal behavior.

Cosinor modeling, which fits a sinusoidal curve to rhythmic data and estimates the precise timing of peak activity, sharpened the picture further. The estimated acrophase, the mathematical peak of the daily cycle, fell at approximately 13:42 for emergence and 16:32 for flight, and the two peaks differed significantly, separated by an estimated phase gap of about 2.83 hours. The amplitudes of both rhythms were significantly greater than zero, and flight activity showed a lower amplitude than emergence, indicating that while both behaviors are strongly rhythmic, the emergence pulse is more sharply concentrated. In ecological terms, the sequence is elegant: beetles exit the bamboo in the early afternoon, then launch into flight roughly three hours later, allowing a brief interval for cuticular hardening and orientation before committing to dispersal.

Laboratory assays corroborated the field pattern. Thirty newly emerged adults were individually observed in Petri dishes at 10:00 and 16:00, with each 30-minute session recorded on video and analyzed using EthoVision tracking software. Beetles observed at 16:00 made significantly more flight attempts, were significantly more likely to actually take off, moved faster, and covered greater distances than their morning counterparts. The probability of flight initiation was markedly higher in the afternoon, and both mean velocity and total distance traveled differed significantly between the two time points, confirming that the afternoon surge in activity is a robust feature of the beetle’s behavior rather than an artifact of field conditions.

The authors are careful about what these patterns do and do not prove. Because the laboratory assay compared only two time points within a single light-dark cycle, it demonstrates a time-of-day difference rather than free-running rhythmicity, and the field experiments, though conducted under natural conditions, cannot by themselves assign causation to any specific environmental cue. Demonstrating true endogenous circadian control would require continuous observations over multiple cycles under constant conditions, the gold standard for clock research. The cues that synchronize emergence inside the bamboo remain unresolved: light entering through exit holes or thin regions of the culm wall could provide a photic signal, and daily temperature waves propagating through the culm could contribute, but neither variable was measured, and the study site’s microclimates were not instrumented, so the relative roles of light, temperature, and their interaction cannot yet be distinguished.

What the study does establish is a pattern with deep evolutionary echoes. Similar mid-afternoon activity peaks have been documented across a surprising range of insects: the Asian citrus psyllid disperses most actively in the afternoon, black flies and the Asian gypsy moth show flight peaks near 16:00, and a recent year-long automated multispecies survey found that beetles in particular exhibit pronounced activity maxima around that hour. Most intriguingly, the coffee berry borer, another concealed boring beetle, shows late-afternoon sexual activity in the laboratory and a marked mid-afternoon dispersal peak in the field. The parallels suggest that synchronized afternoon dispersal may be a shared adaptive strategy among wood- and seed-boring beetles, one that concentrates mate finding and host colonization into a window when flight conditions are favorable and when suitable, recently damaged host material is most likely to be encountered.

For D. minutus, a host specialist that colonizes primarily injured culms of a limited number of bamboo genera and responds to specific aldehyde blends emitted by damaged plants, timing may be everything. Suitable host substrates are available only in narrow spatial and temporal windows, and concentrating dispersal in the mid-afternoon could simultaneously optimize mate encounter, host location, and avoidance of unfavorable conditions, while potentially reducing competition with other bamboo-associated insects. The applied implications are equally clear. Monitoring programs, semiochemical-baited trapping systems, and the protection of freshly injured culms can all be concentrated into the afternoon activity window, raising detection probability while cutting labor costs. For a pest that spends half its life hidden inside bamboo, the brief daily moment when it faces the open air is now a predictable, exploitable target.

Subject of Research: Diel rhythms of emergence and dispersal flight in the bamboo borer beetle Dinoderus minutus

Article Title: Diel emergence and dispersal rhythms in the bamboo borer Dinoderus minutus (Coleoptera: Bostrichidae)

Article References: Gonçalves, F. G., Rainho, H. L., de Azevedo, K. E. X., de Lara, I. A. R., de Andrade Moral, R., & Bento, J. M. S. (2026). Diel emergence and dispersal rhythms in the bamboo borer Dinoderus minutus (Coleoptera: Bostrichidae). The Science of Nature, 113(6), Article 127. https://doi.org/10.1007/s00114-026-02181-5

Image Credits: AI Generated

DOI: 10.1007/s00114-026-02181-5

Keywords: bamboo borer, Dinoderus minutus, chronobiology, diel rhythm, insect dispersal, emergence, circadian rhythm, pest management, semiochemicals, Bostrichidae, flight activity, entomology

The research, led by Pietro Pollo and Michael Kasumovic of the University of New South Wales, represents the most comprehensive assessment of taxonomic bias ever conducted in the field. Previous studies relied on small samples of journals and manual classification of papers, leaving open the question of whether the patterns documented in the early 2000s had persisted. To overcome these limitations, the team analyzed 1,383,803 papers from 612 journals, spanning literature published as far back as 1877, and tracked how the representation of different animal groups changed between 2001 and 2025.

Classifying papers by hand at this scale would have been impossible, so the researchers built a keyword-based algorithm trained on nearly 5,000 manually classified papers. The algorithm drew on the GBIF Backbone Taxonomy and a customized vocabulary of taxonomic terms to identify the animal focus of each paper from its title, abstract, and keywords. When tested against 1,815 papers the researchers had classified independently, the algorithm achieved at least 97.2 percent accuracy for every animal group, with an F1-score of 91.2 percent. The team also verified that the algorithm rarely produced impossible labels, such as identifying a paper in a mammalogy journal as being about something other than mammals.

The scale of the bias is striking. Of the 991,894 papers involving animals, 46.1 percent focused exclusively on invertebrates and 45.1 percent exclusively on vertebrates, figures that appear roughly balanced until one considers that invertebrates account for approximately 95 percent of animal species. When the researchers compared the observed proportion of papers on each group with what would be expected if research effort were distributed in proportion to species richness, insects emerged as the most underrepresented group relative to their diversity, while mammals and fish were the most overrepresented.

The study also documented how bias is embedded in the structure of the field itself. Nearly 40 percent of the 612 journals analyzed had explicit taxonomic restrictions, and a striking 42 percent of these specialized journals focused on arthropods. The researchers found that species-rich invertebrate groups such as insects and arachnids are often relegated to these specialized outlets, which likely reach narrower audiences than general ecology and evolution journals. This means the true extent of vertebrate favoritism may be even more pronounced from the perspective of an average researcher scanning the broader literature.

Perhaps most disappointingly, the overall pattern has shown no improvement since taxonomic bias was first formally discussed in 2002. The proportion of papers on vertebrates across the literature as a whole remained stable over the 25-year study period, and in some subfields it actually increased. In aquatic journals, for example, fish rose from 35.8 percent of papers in 2001 to 49.7 percent in 2025. In behaviour, conservation, and general ecology and evolution journals, mammals and birds remained particularly dominant. The only subfield where invertebrate research increased was zoology journals, likely because these outlets publish much of the work describing new species, the vast majority of which are invertebrates.

The researchers also examined whether journal prestige metrics were linked to taxonomic focus. Papers published between 2021 and 2025 in journals with higher impact factors and citation indicators were more likely to focus on vertebrates, although the relationship was not uniform across subfields. Interestingly, birds were equally likely to appear in high-impact and lower-impact journals, suggesting that the prestige advantage accrues to vertebrates as a broad category rather than to any single charismatic group.

The attention gap proved even more consequential than the publication gap. Compared with papers on invertebrates in the same journal, papers on vertebrates received on average 10.2 percent more citations, 43.1 percent more mentions in online documents such as news outlets and social media, 24.2 percent more readers on the reference manager Mendeley, and 45.1 percent higher Altmetric scores, a weighted measure of overall online attention. These findings align with previous research showing that vertebrates attract more attention on platforms like Instagram and Wikipedia, and even on government-curated imagery such as postage stamps. Within the attention metrics, birds often attracted the greatest online buzz but received the fewest citations, revealing that public appeal and academic influence do not always coincide.

The authors caution that their within-journal attention analyses are correlational and cannot fully rule out confounding factors such as paper topic. Still, they argue that the patterns likely reflect deeper societal biases, since surveys consistently show that people value vertebrates more than invertebrates, a perception that editors, reviewers, and funding committees may unconsciously apply when judging research appeal. The consequences extend beyond academic vanity: taxonomic bias can stifle medical and engineering innovation by limiting biomimetic inspiration from understudied organisms, and it undermines the theoretical generality that ecology and evolution depend upon.

To break the cycle, the researchers propose concrete interventions within academia. They urge journals and funding bodies to systematically collect and publicly report the taxa studied in submitted manuscripts and funded projects, to incorporate taxonomic diversity into guidelines for awards, hiring, and publication decisions, and to establish targeted financial and publishing incentives for research on neglected organisms. They also emphasize the need to revive descriptive disciplines such as taxonomy and natural history, since hypotheses cannot be tested about organisms that have never been described. While such measures may seem ambitious, the authors note that similar skepticism once greeted diversity initiatives that are now widely accepted, and they hope their findings will prompt institutions to extend their commitments to equity to the tree of life itself.

Subject of Research: Taxonomic bias in ecology and evolution research literature

Article Title: Taxonomic Bias Persists in Ecology and Evolution Research Despite Decades of Concern

Article References: Pollo, P., & Kasumovic, M. M. (2026). Taxonomic Bias Persists in Ecology and Evolution Research Despite Decades of Concern. Ecology and Evolution, 16(10), Article e74450. https://doi.org/10.1002/ece3.74450

Image Credits: AI Generated

DOI: 10.1002/ece3.74450

Keywords: taxonomic bias, ecology, evolutionary biology, vertebrates, invertebrates, journal impact factor, Altmetric, biodiversity, conservation, entomology, scientific publishing, citation bias

The evidence assembled by the team ranges from the charming to the downright bizarre. Consider the Hoffmann’s two-toed sloth, whose shaggy coat hosts a miniature ecosystem. Sloth moths live out their lives in the animal’s fur, and their activities help cultivate algae that grow in the sloth’s hair — algae the sloth then eats, supplementing its otherwise meadow-sparse diet of leaves. In this sense, the sloth is not merely tolerating its insect tenants; it is actively farming them, or at least farming the garden they fertilize. Remove the moths, and the sloth loses both a nutrient source and a living camouflage that helps it vanish into the canopy.

Other examples reveal insects serving as tools, infrastructure, and even medicine. Chimpanzees have been observed applying insects to open wounds, a behavior that appears to help sterilize injuries and may represent a form of self-medication. Herons, meanwhile, have turned insects into fishing equipment, using them as bait to lure fish within striking distance. Birds and reptiles lay their eggs inside termite mounds, exploiting the structures’ remarkably stable internal temperatures as natural incubators. In arid environments, some desert frogs take refuge inside ant nests, where the humidity offers a buffer against desiccation in landscapes where water is the scarcest resource of all.

“Insects are sometimes called the ‘little things that run the world’ because they are so important to life on Earth,” said Grames, the paper’s co-lead author. “We often hear about their importance as pollinators, or decomposers, or food for insectivores like birds and bats, but we forget about all the other things they do for us and for other species.” That observation captures the review’s core ambition: to move beyond the well-worn categories of pollination and predation and catalog the full breadth of insect-vertebrate relationships, many of which fall through the cracks of conventional ecological research.

The project was a genuinely international undertaking, with authors drawn from eight countries. Alongside Grames, the review was co-led by Rob Cooke, an ecological modeler at the UK Centre for Ecology and Hydrology, and Chris Elphick, professor of ecology and evolutionary biology at the University of Connecticut. Additional Binghamton contributors included Lindsey Swierk, assistant professor of biological sciences, and biological sciences alumni Julianna Yager and Suyeon Jang. In a fitting touch, Jang — an undergraduate with a painting minor — created the paper’s main illustration as an independent study project, translating the review’s scientific breadth into a single visual statement.

The effort traces its origins to 2022, when researchers established the Status of Insects: An International Research Coordination Network, an initiative funded by the National Science Foundation. The network emerged directly from Grames’ doctoral work in Elphick’s laboratory, and it was designed to confront a persistent problem in entomology and ecology more broadly: the literature on insect-vertebrate interactions is scattered across hundreds of individual studies, each examining a narrow slice of the picture. By consolidating that dispersed evidence into a single synthesis, the review offers the most comprehensive account yet of how deeply vertebrate life is woven into the fabric of insect diversity.

The scale of that dependence is difficult to overstate. There are an estimated 14 to 30 million species of insects on Earth, and they underpin the health and function of ecosystems on nearly every continent. They feed species ranging from hummingbirds, whose metabolisms demand near-constant refueling, to grizzly bears, which gorge on moths and other insects during critical seasons. Insects also enable other food sources indirectly through pollination, and they produce substances — honeydew, honey, and wax among them — that are themselves consumed by other species. For many vertebrates, insect abundance is not a background condition but a calendar: a variety of species time their breeding seasons to coincide with seasonal pulses of insect availability, synchronizing reproduction with the brief windows when their young can be fed.

The review also documents subtler forms of dependence that border on engineering. Birds incorporate spider and insect silk into their nests, taking advantage of materials with tensile properties that few natural substances can match. Some birds go further, deliberately situating their nests near stinging insects such as wasps, recruiting the colony’s venomous defenses as a security system against predators. More than 200 bird species use crushed ants for grooming — a behavior known as anting, in which the birds rub ants over their plumage, likely benefiting from the insects’ chemical secretions. And the relationship between insects and nesting vertebrates stretches deep into the past: insects once lived inside dinosaur nests, cleaning them out, and according to Grames, they still perform that sanitation service today in the nests of some owls and kingfishers.

Yet for all this richness, the scientific literature has a conspicuous blind spot. Few studies consider how insect population declines affect vertebrate species beyond the most obvious channel — a shrinking food supply. That narrow framing, the authors argue, dramatically understates the risk. If insects disappear, vertebrates lose not only calories but nesting materials, incubators, medicines, sanitation services, climate refuges, and the ecological timing cues that structure their reproductive cycles. Some insect populations have experienced alarming declines in recent decades, and those losses will ultimately propagate through the vertebrate communities that depend on them in ways that current research has barely begun to measure.

The numbers behind that warning are stark. “We’re losing insects at a rate of about 1-2% per year,” Grames said. “When you scale that up across a few decades, we’re talking about a major change to ecosystems. Insect conservation should be a top priority for anyone worried about the future of biodiversity.” A decline of even one to two percent annually, compounded over half a century, translates into a transformation of insect communities on a scale that has no precedent in recent ecological memory. Elphick, an ornithologist by training, framed the implication as a call for scientific bridge-building: he hopes the review will foster increased collaboration between scientists who study vertebrates and those who study insects. “If you want to have vertebrates, then you’ve got to be thinking about insect conservation, and we don’t do that nearly enough,” he said. In an era when conservation planning is often organized around charismatic vertebrates and their habitats, the review’s synthesis delivers a pointed reminder that the fates of sloths, songbirds, chimpanzees, and frogs are entangled with creatures small enough to escape notice — and that protecting the little things that run the world may be the surest way to protect everything that runs on them.

Subject of Research: The diverse roles of insect biodiversity in supporting vertebrate species

Article Title: Insects are essential to vertebrate life — as food, shelter and medicine

Article References: Insects are essential to vertebrate life — as food, shelter and medicine. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: insects, vertebrates, biodiversity, conservation, sloths, entomology, ecology, insect decline, termite mounds, chimpanzees, Nature Reviews Biodiversity, ecosystems

The significance of the work extends well beyond Arkansas, though the stakes in the Natural State are considerable. Rice is a major crop in Arkansas, which ranks among the leading rice-producing regions of the United States, and the rice stink bug ranks among the most significant threats to the crop. The insect’s feeding damages developing rice grains, reducing both yield and quality, and the economic toll is well documented: the pest cost Arkansas rice growers more than $16 million in 2017 alone, with similar losses estimated in 2018 and 2019, according to figures cited in the research team’s earlier population-genetic study. A reference genome does not eliminate those losses overnight, but it transforms the questions scientists can ask about the insect’s biology.

Rich Adams, an assistant professor of agricultural statistics for the Arkansas Agricultural Experiment Station and corresponding author of the study, described the assembly as a landmark for the field. “This gives us our first chromosome-scale view of the rice stink bug genome,” Adams said. “We were able to assemble much of the nuclear genome, identify more than 13,000 genes and uncover genetic features involved in the insect’s biology and interactions with agricultural systems. It creates a foundation and hypothesis for future studies of rice stink bug biology and management.” Adams is also a teaching faculty member in the department of entomology and plant pathology in the Dale Bumpers College of Agricultural, Food and Life Sciences at the University of Arkansas and a member of the experiment station’s Center for Agricultural Data Analytics.

Technically, the assembly is a substantial feat. Using modern sequencing approaches, the team reconstructed a genome of roughly 826 million base pairs with unprecedented resolution for this species, organizing much of the nuclear genome onto predicted chromosomes and annotating their gene content. Beyond the protein-coding genes, the analysis revealed evidence of approximately 21,000 non-coding RNAs, the regulatory molecules that increasingly are recognized as central players in how genomes orchestrate development and environmental response. The result is the most detailed genomic analysis to date of the rice stink bug and, more broadly, a valuable comparative resource for understanding genome structure and gene family evolution across the stink bug family Pentatomidae, a group that includes many of agriculture’s most notorious plant-feeding pests.

What excites agricultural scientists most, however, is not the raw sequence itself but what the gene content reveals about how this insect makes its living. The analysis identified genes with predicted roles in plant digestion, including carbohydrate-active enzymes, a class of proteins that allows herbivorous insects to break down the complex carbohydrates found in plant tissues. The researchers also uncovered expansions and contractions in gene families associated with key life history traits and agricultural impact, including families linked to feeding, host adaptation and detoxification. Detoxification genes, in particular, are of intense interest because they can underpin a pest’s ability to tolerate the chemical defenses of host plants and, in some cases, the synthetic insecticides deployed against it.

That last point carries real urgency. The rice stink bug feeds on more than 15 host plant species, including grain sorghum, an ecological breadth that reflects a remarkable capacity to adapt to different plant hosts. More troubling still, some populations of the insect have shown resistance to pyrethroid insecticides, the chemical class most commonly relied upon by growers to manage stink bug outbreaks. The new genome identifies genes that may play roles in insecticide resistance, giving researchers a concrete set of molecular targets to monitor. Rather than waiting for control failures to appear in the field, scientists can now look for the genetic signatures of resistance as they emerge, potentially years before they become a widespread management crisis.

Allen Szalanski, a professor of entomology and plant pathology for the experiment station and a co-author of the study, emphasized the breadth of the resource. “This genome provides a foundation for studying genome structure, gene family evolution, plant feeding, host adaptation, detoxification and potential insecticide resistance,” Szalanski said. The new research builds directly on findings from a previous study by Szalanski, Adams and colleagues with the University of Arkansas Division of Agriculture and Florida A&M University, which examined genetic variation among rice stink bug populations across Arkansas, Mississippi, Florida and Cuba. That earlier work, published in Florida Entomologist, analyzed a mitochondrial DNA marker and found high genetic diversity within O. pugnax populations, results that pointed to movement of rice stink bugs among southeastern states and suggested that two invasive Oebalus species found in Florida may have originated in Cuba.

The relationship between the two studies illustrates how modern pest science proceeds in layers. “The first study helped us understand how rice stink bug populations vary genetically and move across regions,” Szalanski said. “This new genome gives us the tools to investigate the biological mechanisms behind those differences and how this pest adapts to rice production systems.” In other words, the population genetics established where the insect goes and how its populations are connected; the genome now provides the mechanistic vocabulary to explain why. If bugs moving among states carry different feeding capacities or resistance profiles, researchers can begin to trace those differences to specific genes and gene families rather than inferring them from field observations alone.

Adams was careful to frame the assembly as a scientific starting point rather than a finished product. Genome assemblies are living resources: as additional data become available, from improved sequencing of wild populations to functional studies of individual genes, researchers can refine the assembly and use it to test new hypotheses about the evolution, behavior and management of rice stink bugs. This iterative model has already transformed the management of other agricultural pests worldwide, where reference genomes have enabled everything from pheromone-based monitoring to the identification of resistance mutations before they spread. The rice stink bug genome places this pest squarely within that modern framework, and the funding support from the Arkansas Biosciences Institute that made the work possible reflects a strategic bet on the value of such foundational resources.

For rice producers, the practical payoff may take years to fully materialize, but the trajectory is clear. “Knowing more about the genetic basis of these traits can ultimately help researchers develop better monitoring and management strategies for rice producers,” Szalanski said. Better monitoring could mean molecular surveillance of resistance alleles across the mid-South; better management could mean control strategies informed by a precise understanding of how the bug digests its host plants and adapts to new ones. The research team included first author Rokeya Akter, a graduate student in the department of entomology and plant pathology, along with co-authors Mahamad Sayab Miya, a senior research assistant, and Duane D. McKenna, the William Hill Professor of Biology and founding director of the Center for Biodiversity Research at the University of Memphis. Together, they have turned one of Arkansas agriculture’s costliest adversaries into one of its most genetically well-characterized insects, and in doing so they have given growers and scientists alike something they have never had before: a complete, chromosome-scale map of the enemy.

Subject of Research: Chromosome-scale genome assembly of the rice stink bug Oebalus pugnax

Article Title: Genome assembly of rice stink bug offers new data-informed tool in fight against costly pest

Article References: Genome assembly of rice stink bug offers new data-informed tool in fight against costly pest. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: rice stink bug, genome assembly, Oebalus pugnax, entomology, insecticide resistance, rice production, gene family evolution, host adaptation, detoxification, Pentatomidae, agricultural pest management, Arkansas

The research team, led by Qiuyu Li and Zhijie Xu of Xi’an Jiaotong-Liverpool University together with colleagues at the University of Liverpool and Zhengzhou University of Light Industry, framed the problem around five recurring obstacles: cluttered backgrounds, life-stage variation, subtle inter-class differences, long-tailed category distributions, and unsupported taxa that the model has never seen during training. Each of these obstacles can derail a conventional classifier. Life-stage variation means that the larva of one species may resemble the adult of another; long-tailed distributions mean that a handful of pest categories dominate the training data while dozens of rare species are represented by only a few images. Unsupported taxa pose an even deeper problem, because a closed-set classifier will confidently assign a label even when the insect in front of it belongs to a species entirely absent from its training set.

CLARiF’s first line of attack is structured diagnostic captioning. Rather than treating an image as an undifferentiated bundle of pixels, the framework generates textual descriptions that follow the logic an entomologist would use at a diagnostic key: body shape, coloration, markings, wing structure, and other morphological clues. This converts the recognition task into something closer to a cross-modal reasoning problem, in which the visual evidence and the verbal description of diagnostic traits must be brought into alignment. The approach draws on the recent wave of vision–language models, including architectures descended from CLIP, Flamingo, BLIP-2, LLaVA, and Qwen-VL, which have demonstrated that pairing images with natural language can dramatically improve generalization on tasks that require fine distinctions.

The second component, mask-guided part extraction, addresses the clutter problem directly. Using segmentation techniques in the lineage of the Segment Anything Model family, the framework isolates the insect from its surroundings before deeper analysis begins. This matters because a classifier that must simultaneously learn what the insect looks like and what the background looks like wastes capacity on irrelevant variation. By constraining attention to the segmented organism, and further to meaningful body parts within it, CLARiF ensures that the features driving a decision correspond to the anatomy of the pest rather than to the texture of a leaf or the angle of the sunlight.

The third element, bidirectional part–attribute fusion, is where the framework earns the alignment half of its name. Visual features extracted from specific body parts are fused with the attribute terms in the diagnostic captions in both directions: parts inform which attributes are present, and attributes guide which parts deserve scrutiny. This bidirectional flow allows the model to reason, in effect, that a particular spot pattern on the forewing supports one species hypothesis while the segment count on the antenna supports another. Such structured reasoning is precisely what separates fine-grained recognition from ordinary object classification, where a single holistic impression of the image is often sufficient.

The fourth component, exemplar-informed re-ranking, borrows an idea from retrieval-augmented systems. After the model produces an initial ranking of candidate species, the framework consults a gallery of reference exemplars and adjusts the ranking in light of the closest matches. This retrieval-informed fusion gives the system a form of case-based memory: even if the learned representations are imperfect, comparison against curated reference images can correct the final decision. The authors report that under comparable data-processing and fine-tuning settings, CLARiF outperformed independently reproduced vision–language baselines while retaining each model’s native language backbone, suggesting that the gains come from the framework rather than from any single underlying model.

The headline numbers are striking. On the official test split of IP102, the large-scale benchmark for insect pest recognition introduced by Wu and colleagues in 2019, CLARiF achieves an accuracy of 77.81 percent with a standard deviation of 0.18 across runs, and a macro-F1 score of 77.07 percent with a standard deviation of 0.21. The macro-F1 figure is particularly meaningful in this domain because it weights all classes equally, refusing to let abundant categories mask poor performance on rare ones. In a long-tailed setting where many species have few training examples, a high macro-F1 indicates that the framework is genuinely learning to distinguish the scarce and difficult categories, not merely riding the statistics of the common ones.

Perhaps the most consequential result concerns the open-set problem. Under a fixed held-out-species protocol, in which certain species were deliberately excluded from training and then presented to the model at test time, CLARiF achieved an area under the receiver operating characteristic curve of 88.62 percent for rejecting unsupported inputs. In practical terms, this means the system can often tell when it does not know, flagging an insect as outside its competence rather than fabricating a confident but wrong identification. For agricultural deployment, this property may matter more than raw accuracy: a misidentification of a quarantine pest as a harmless lookalike, or vice versa, can trigger unnecessary pesticide applications or allow an invasive species to spread undetected. A model that abstains when uncertain is a far safer instrument than one that always answers.

The evaluation was not confined to a single dataset. Alongside IP102, the study drew on the Forestry Pest Dataset and a curated control set referred to as IP102-Control, and the authors report that the data-processing pipeline, prompt templates, random seeds, held-out-species split files, gallery-construction scripts, and rejection-threshold configurations are documented in detail, with source code and processed exemplar metadata available from the corresponding author on reasonable request. This level of procedural transparency addresses a persistent weakness in the applied machine-learning literature, where comparisons between methods are often confounded by undisclosed differences in preprocessing, augmentation, or evaluation protocol. By reproducing the baselines themselves under identical settings, the team strengthened the claim that the observed improvements are attributable to the CLARiF design.

The broader significance of the work lies in what it suggests about the future of agricultural AI. Pest management is a cornerstone of global food security, and deep learning has already transformed tasks from disease detection on leaves to automated insect monitoring in greenhouses and pheromone traps. Yet most deployed systems remain brittle at the species level, where the decisions that matter are actually made. CLARiF demonstrates that the combination of language-grounded diagnostic reasoning, precise visual localization, and retrieval-based verification can push fine-grained recognition to a level of reliability that begins to approach expert practice, while the open-set rejection capability provides a guardrail against the overconfident errors that have historically undermined trust in automated identification. As vision–language models continue to improve, frameworks of this kind could become the analytical backbone of smartphone-based field diagnostics, extension services in regions without resident entomologists, and early-warning networks for invasive pests. The study, published in volume 56 of Applied Intelligence as article number 474, was supported by the SIP Leadership Talent Program, the Jiangsu Provincial Double Initiative Plan, and a Xi’an Jiaotong-Liverpool University research development grant, and the authors declare no competing interests.

Subject of Research: Vision–language-based fine-grained recognition of agricultural insect pests

Article Title: CLARiF: clue alignment and retrieval-informed fusion for fine-grained pest recognition

Article References: Li, Q., Pan, Y., Xiang, N., Zhang, H., Li, Z., Huang, X., & Xu, Z. (2026). CLARiF: clue alignment and retrieval-informed fusion for fine-grained pest recognition. Applied Intelligence, 56(15), Article 474. https://doi.org/10.1007/s10489-026-07522-5

Image Credits: AI Generated

DOI: 10.1007/s10489-026-07522-5

Keywords: pest recognition, vision-language model, fine-grained classification, IP102 benchmark, agricultural AI, open-set recognition, retrieval-augmented learning, image segmentation, macro-F1, entomology, deep learning, crop protection

The significance of the advance lies partly in the mosquito genus involved. Culex species have received far less attention from spectroscopy-based methods than Anopheles mosquitoes, which dominate malaria research, despite the fact that Culex vectors are increasingly important players in the transmission of orthoflaviviruses and filarial parasites. Because these pathogens typically infect multiple host species, including birds, mammals and humans, mapping the feeding patterns of Culex mosquitoes is essential for predicting where and when spillover into human populations is likely to occur. Traditional blood meal identification relies on techniques such as PCR-based assays or sequencing, which are accurate but costly, time-consuming and progressively less reliable as the blood meal is digested inside the mosquito. A method that is rapid, inexpensive and robust to digestion time could transform the scale at which blood meal surveillance is feasible, particularly in the low-resource settings where mosquito-borne disease burdens are often highest.

The experimental design was straightforward but rigorous. The team reared Culex quinquefasciatus mosquitoes in the laboratory and fed them blood from six different host species: human, pig, chicken, cattle, dog and horse. This panel deliberately spans the range of hosts that matter most for multi-host pathogens in many endemic regions, from domestic animals that amplify viruses to humans who suffer the consequences. At four time points after feeding, namely 6, 12, 24 and 30 hours, the researchers rolled the abdominal contents of the mosquitoes onto filter paper to create dried bloodspots, a simple and field-friendly way of preserving samples without refrigeration or elaborate cold chains. Each bloodspot was then scanned using a Bruker ALPHA Fourier-transform infrared spectrometer, an instrument that measures how the sample absorbs mid-infrared light across a spectrum of wavelengths.

The underlying physics is what gives the method its power. Mid-infrared light interacts with the vibrational modes of chemical bonds in proteins, lipids, carbohydrates and nucleic acids, producing a complex absorption spectrum that acts as a molecular fingerprint of the sample. Because the blood of different host species differs subtly in its biochemical composition, those fingerprints carry enough information to distinguish a chicken blood meal from a dog blood meal, or a human meal from a horse meal. The raw spectra, however, are far too intricate for visual interpretation, which is where machine learning enters. The researchers trained a multilayer perceptron, a type of artificial neural network, on the spectra from laboratory mosquitoes with known blood meal origins, allowing the algorithm to learn the spectral patterns that discriminate between host species and then apply that learned knowledge to unknown samples.

The results were striking. On laboratory-reared mosquitoes, the trained model predicted host species with 93.6 percent accuracy, a dramatic improvement over the 16.7 percent expected from random classification among six host species. Even more importantly for real-world application, accuracy declined only modestly with digestion time, falling by just 6 percent at the 30-hour mark. This resilience matters because mosquitoes caught in surveillance traps are rarely fresh; they may have fed a day or more earlier, and conventional molecular methods lose accuracy as digestive enzymes break down the host DNA they rely on. A technique that remains reliable across a full day of digestion therefore captures a much larger and more representative fraction of the blood meals collected in the field, reducing the bias that plagues traditional approaches.

The true test came with field-collected mosquitoes. When the laboratory-trained model was applied to bloodspots from wild-caught Culex mosquitoes, accuracy dropped to 67.9 percent. The authors attribute this gap to differences between laboratory and field conditions rather than any fundamental flaw in the approach. Wild mosquitoes feed directly on living hosts, whereas the laboratory mosquitoes were fed through artificial feeders, and the blood used in the laboratory was treated with anticoagulants that wild blood meals naturally lack. Wild blood meals also reflect the true biochemical diversity of free-ranging animals, whose diet, health and physiology vary far more than those of the standardized blood sources used in the laboratory. In other words, the model was trained on a simplified version of the world and then asked to interpret a messier one, and the performance drop is an expected consequence of that mismatch.

Crucially, the team found a practical way to manage this uncertainty. By applying a probability threshold to the model’s predictions, accepting only classifications in which the algorithm expressed high confidence, accuracy on field samples rose to 78 percent, at the cost of discarding 21 percent of samples that the model could not confidently assign. This trade-off is a familiar one in applied machine learning, and for surveillance purposes it is often the right one. A public health programme that needs to know which hosts are driving transmission can afford to leave a fifth of samples unclassified if the remaining classifications are substantially more trustworthy. The threshold approach effectively lets users dial between coverage and confidence depending on the question at hand, a flexibility that rigid molecular assays do not offer.

The economic and logistical implications are considerable. Once the spectrometer is in place, the marginal cost of scanning a bloodspot is minimal, and the analysis requires no reagents, no cold chain and no highly specialized molecular biology laboratory. Filter paper bloodspots can be collected in remote villages, shipped at ambient temperature and analysed centrally, which makes the method particularly attractive for large-scale surveillance programmes in low-resource settings. The study’s field collections in the Philippines, supported by the Department of Health and local partners, alongside work in Australia’s Northern Peninsula Area, demonstrate that the sampling workflow is feasible in exactly the kinds of environments where Culex-borne pathogens impose their greatest burden. The work was funded by the Wellcome Trust, the European Research Council and several university and institutional grants, reflecting a collaboration spanning the University of Glasgow, the University of Sydney, NSW Health Pathology and the Ifakara Health Institute.

There are, of course, limits to what the current model can do. The laboratory training set covered only six host species, whereas real mosquitoes bite a far wider menagerie, including wild birds, rodents, bats and marsupials, and the model cannot classify hosts it was never taught to recognize. Expanding the library of host species, incorporating spectra from wild-fed mosquitoes into the training data, and refining the preprocessing of spectra to correct for the chemical differences introduced by anticoagulants and artificial feeders are all obvious next steps. The authors note that further development using samples from field-collected mosquitoes could enhance classification accuracy and broaden the range of identifiable hosts, and the open-access publication of the work should accelerate those efforts across the research community.

Even in its present form, however, the study marks a meaningful shift in how blood meal analysis could be conducted. By demonstrating that a benchtop infrared spectrometer and a neural network can recover host identities from a day-old blood meal with near-laboratory accuracy, the researchers have opened a path toward blood meal surveillance at a scale that PCR-based methods could never economically achieve. For diseases that move between animals and humans along cryptic transmission chains, that scale is precisely what has been missing. If subsequent studies confirm and extend these results across more host species and more field settings, the humble dried bloodspot, read by a beam of infrared light, may become one of the standard tools of vector-borne disease intelligence, helping health authorities see not just which mosquitoes are present, but whose blood they are carrying and which transmission pathways need to be interrupted first.

Subject of Research: Mid-infrared spectroscopy and machine learning for identifying host species of Culex mosquito blood meals

Article Title: Rapid host species identification from dried bloodspots of Culex mosquito blood meals using mid-infrared spectroscopy

Article References: Rapid host species identification from dried bloodspots of Culex mosquito blood meals using mid-infrared spectroscopy. (n.d.). https://doi.org/10.1186/s13071-026-07703-8

Image Credits: AI Generated

DOI: 10.1186/s13071-026-07703-8

Keywords: Culex mosquitoes, blood meal analysis, mid-infrared spectroscopy, machine learning, multilayer perceptron, vector-borne disease, orthoflaviviruses, lymphatic filariasis, dried bloodspots, disease surveillance, one health, entomology

Sand flies are small, hairy flies of the subfamily Phlebotominae whose blood-feeding females transmit a range of pathogens, most notably Leishmania parasites, as well as phleboviruses such as those causing sand fly fever. More than one billion people live in areas where they are exposed to sand fly-borne infections, and with no effective human vaccines available for most of these diseases, vector control remains the principal line of defense. Traditional measures such as insecticide spraying face growing challenges from resistance and environmental concerns, prompting researchers to explore alternative strategies. Among the most promising of these is the use of Wolbachia, an intracellular bacterium that infects an enormous range of arthropods and can be deployed to suppress mosquito populations or reduce their ability to transmit pathogens such as dengue and Zika viruses.

Despite the success of Wolbachia-based approaches in mosquitoes, surprisingly little is known about the bacterium’s natural presence in sand flies. This gap in knowledge motivated a team of researchers at the Istituto Zooprofilattico Sperimentale della Lombardia e dell’Emilia-Romagna in Brescia, led by Maya Carrera and colleagues, to undertake a systematic survey of Wolbachia infections in wild-caught sand flies across Northern Italy. The study, conducted between 2023 and 2025, set out to determine not only how common the bacterium is in these populations but also which genetic types of Wolbachia are circulating, information that is essential for judging whether the endosymbiont is already interacting with local vector populations in ways that could be exploited.

The fieldwork covered 24 collection sites distributed across Northern Italy, a region where sand fly activity is seasonal and where Phlebotomus perniciosus dominates the vector community. The researchers deployed two complementary trapping methods: CO2-baited traps, which mimic the breath of vertebrate hosts and attract host-seeking females, and CDC light traps, a standard tool for sampling nocturnal flying insects. Captured specimens were pooled according to sex, collection site, and date, a pooling strategy that balances the practical constraints of molecular screening with the need to estimate infection prevalence across a large sample. Male sand flies, which can be identified by examining morphological features of their genitalia and other structures, were identified to species under the microscope, while females, which are harder to distinguish morphologically, were screened directly for Wolbachia DNA using polymerase chain reaction, or PCR.

The scale of the sampling effort was considerable. In total, 1,158 male sand flies were morphologically identified, revealing seven species in the region. Phlebotomus perniciosus was by far the most abundant, accounting for 751 specimens, followed by P. perfiliewi, P. neglectus, P. ariasi, Sergentomyia minuta, P. mascittii, and P. papatasi. For the molecular screening, 1,937 sand flies were divided into 124 pools, including 10 male pools that could not be assigned to a species morphologically. When these pools were tested for Wolbachia, the results were striking: the overall prevalence of infection was 38.7 percent, a remarkably high figure for a vector group in which Wolbachia had been considered rare or poorly documented.

Prevalence was not static across the study period. In 2023, 44.9 percent of the screened pools tested positive for the bacterium. The following year, the figure dropped to 21.3 percent, less than half the initial rate, before rebounding sharply to 57.1 percent in 2025. This year-to-year variation suggests that Wolbachia infection dynamics in sand fly populations are influenced by fluctuating ecological conditions, whether climatic, related to host population structure, or driven by other factors that the study was not designed to disentangle. Understanding what drives these swings will be important for any future attempt to model or manipulate the bacterium’s spread through wild populations.

To characterize the Wolbachia strains genetically, the team amplified five housekeeping genes used in the standard multi-locus sequence typing scheme for the bacterium: coxA, fbpA, ftsZ, gatB, and hcpA. Because Wolbachia is classified into supergroups based on such sequence data, this approach allows precise assignment of strains to evolutionary lineages. In addition, the researchers amplified the cytochrome oxidase I gene, or COI, a widely used DNA barcoding marker, to confirm the identity of the host sand flies, and for four samples they also sequenced a partial fragment of the wsp gene, which encodes a Wolbachia surface protein. Samples for which all target genes were successfully amplified were then subjected to nanopore sequencing, a long-read technology that enables rapid and relatively inexpensive generation of sequence data.

The genetic results were unambiguous and, in one respect, quite unexpected. Complete MLST profiles were obtained for 11 samples, and every one of them belonged to Wolbachia Supergroup B, one of the major divisions of the bacterium. COI barcoding confirmed that all 11 infected hosts were Phlebotomus perniciosus. More remarkable still, all 11 sequenced Wolbachia shared an identical sequence type, despite having been collected across different years and from different habitats within the study region. This genetic uniformity points to a single, well-established strain circulating in P. perniciosus populations across Northern Italy, rather than a diverse community of unrelated infections. When the researchers compared this profile against public sequence databases, they found no exact match; the closest known profile came from the confused flour beetle, Tribolium confusum, hinting at possible evolutionary links between the sand fly strain and Wolbachia found in other insect hosts.

The significance of these findings extends beyond basic microbiology. Wolbachia’s appeal as a control agent rests on two well-documented phenomena. The first is cytoplasmic incompatibility, a reproductive manipulation in which males carrying certain Wolbachia strains can only successfully breed with females carrying the same or a compatible strain, a mechanism that can be exploited to suppress populations or to drive desirable traits through a population. The second is the ability of some strains to reduce vector competence, meaning the infected insect becomes less able to support and transmit pathogens. Both mechanisms have been deployed successfully against Aedes mosquitoes in programs targeting dengue. Whether the Supergroup B strain found in P. perniciosus exhibits similar properties is not yet known, but the new study provides the essential baseline: researchers now know which strain is present, how common it is, and that it persists stably across years and habitats.

The authors emphasize that this work is a foundation rather than a conclusion. Future studies will need to examine the effects of the identified Wolbachia strain on sand fly reproduction, survival, and, crucially, vector competence for Leishmania parasites and phleboviruses. The demonstration that a single, genetically uniform strain infects a large fraction of the most important sand fly vector in Northern Italy raises the possibility that natural Wolbachia infections could already be influencing transmission dynamics in the region, or that they could be augmented through release strategies similar to those used against mosquitoes. As climate change and land-use shifts continue to expand the range of sand flies and the diseases they carry, tools that can complement or replace chemical insecticides will only grow in importance. This survey of Italian sand flies offers a detailed genetic portrait of a candidate ally hiding within the insects themselves, and it opens a concrete path toward testing whether that ally can be turned against the pathogens the flies transmit.

Subject of Research: Wolbachia endosymbiont infections in wild sand fly populations in Northern Italy

Article Title: Phylogenetic insights into Wolbachia natural infections in sand flies of Northern Italy

Article References: Carrera, M., Bertasio, C., Carta, V., Marelli, A., Muratore, R., Tolini, C., Lelli, D., Sozzi, E., Moreno, A., & Defilippo, F. (2026). Phylogenetic insights into Wolbachia natural infections in sand flies of Northern Italy. Parasites & Vectors. https://doi.org/10.1186/s13071-026-07578-9

Image Credits: AI Generated

DOI: 10.1186/s13071-026-07578-9

Keywords: Wolbachia, sand flies, Phlebotomus perniciosus, leishmaniasis, vector control, MLST, nanopore sequencing, Italy, endosymbiont, biological control, Parasites & Vectors, entomology

Chemosensation is the invisible language of insect life. From locating a host plant across a forest clearing to recognizing a potential mate by pheromone, nearly every critical decision an insect makes depends on its ability to detect, bind, and transduce chemical signals. These functions are carried out by families of proteins expressed in sensory organs, chiefly the antennae. Odorant-binding proteins, or OBPs, and chemosensory proteins, or CSPs, capture volatile molecules in the fluid-filled pores of sensory hairs and shuttle them to receptors embedded in nerve cell membranes. Odorant receptors, or ORs, ionotropic receptors, or IRs, and gustatory receptors, or GRs, then convert chemical binding events into electrical signals the brain can interpret. Sensory neuron membrane proteins, or SNMPs, assist in the detection of fatty acid-derived compounds such as pheromones, while Niemann-Pick type C2 proteins, or NPC2s, contribute to the transport of hydrophobic molecules. Until this study, not a single one of these gene families had been reported for R. cyatheae, leaving researchers with no molecular handle on how the wasp tracks its unusual fern host.

To build that handle, the team assembled a transcriptome database from male and female adult wasps, sequencing the complete set of messenger RNA molecules being expressed in their bodies. The effort yielded 30,296 unigenes, the distinct assembled sequences representing the insect’s active genes, with an N50 length of 3,286 base pairs, a measure indicating that half of the assembled sequences were longer than that threshold and reflecting a high-quality assembly. The researchers then compared these sequences against six major public annotation databases: NR, Swiss-Prot, Pfam, eggNOG, GO, and KEGG. In total, 11,109 unigenes, or 36.67 percent of the full set, could be functionally annotated. The NR database proved the most productive, matching 10,774 unigenes, while the KEGG pathway database annotated the fewest, 6,300. This annotation step is essential because it allows researchers to distinguish genuine chemosensory genes from the thousands of other sequences involved in basic cellular housekeeping.

Screening the annotated transcriptome against known insect chemosensory gene families revealed 90 candidate chemosensory genes in R. cyatheae. The inventory includes 11 OBPs, 10 CSPs, 6 NPC2s, 24 ORs, 20 IRs, 15 GRs, and 4 SNMPs. Within the OR family, the researchers distinguished 23 typical odorant receptor genes and a single Orco gene, the highly conserved co-receptor that partners with typical ORs across virtually all insect species and is essential for odor detection. The numbers themselves tell an evolutionary story. Compared with insects that rely heavily on chemical communication, such as moths with dozens or hundreds of ORs, the wasp’s relatively compact receptor repertoire may reflect its narrow ecological niche, though the authors present the counts as a baseline for future comparison rather than drawing firm ecological conclusions.

To place these genes in evolutionary context, the team constructed phylogenetic trees relating the chemosensory genes of R. cyatheae to their counterparts in other insect species. Phylogenetic analysis groups genes by sequence similarity, allowing researchers to infer which genes are orthologs, descended from a common ancestor, and which may have expanded or contracted in particular lineages. Such trees also help flag genes that cluster with well-characterized relatives in other insects, providing hypotheses about function that can later be tested experimentally. For a species whose chemosensory biology had never been examined at the molecular level, this comparative framework is the first map connecting the wasp’s sensory genes to the broader landscape of insect olfaction research.

One of the most intriguing findings emerged when the researchers compared gene expression between male and female adults. Thirteen of the candidate chemosensory genes were differentially expressed between the sexes, meaning their activity levels differed significantly. Sex-biased expression in chemosensory genes often points to roles in behaviors that differ between males and females, such as mate location through pheromone detection in males or host plant selection for oviposition in females. Because R. cyatheae infestations coincide with the sprouting period of its host fern, understanding which sex drives host finding, and which molecular sensors are involved, could reveal weak points in the infestation cycle that might be targeted by behavioral interventions or attractant-based monitoring tools.

To confirm that the transcriptome data accurately reflected biology rather than sequencing artifacts, the team verified the tissue expression profiles of the differentially expressed genes using reverse transcription quantitative polymerase chain reaction, or RT-qPCR. This laboratory technique measures the abundance of specific messenger RNA molecules with high sensitivity and is the standard method for validating transcriptome-wide expression patterns. The RT-qPCR results corroborated the expression differences observed in the sequencing data, strengthening confidence that the 13 sex-biased genes are genuinely regulated differently in males and females. This kind of validation is a critical quality checkpoint in genomics studies, where computational identification of candidate genes must be backed by independent experimental evidence before functional work can proceed.

The significance of the study extends beyond a single pest species. Tree ferns of the genus Alsophila are living fossils, and A. spinulosa is protected within the Chishui Alsophila National Nature Reserve, whose administration supported the fieldwork. Conservation of an endangered fern depends on managing the insects that attack it, and effective management in turn depends on understanding the chemical ecology of the pest. The gene catalogue now makes it possible to pursue questions that were previously unanswerable: which odorant receptors respond to fern volatiles, whether males detect female-produced pheromones, and whether synthetic lures could be designed to monitor or disrupt mating. Similar transcriptome-based approaches have enabled the development of semiochemical-based control tools for other forest pests, and the new data provide the raw material for analogous efforts against R. cyatheae.

The work also fills a taxonomic gap. Hymenoptera, the order that includes wasps, bees, and ants, is enormously diverse, yet chemosensory gene repertoires have been characterized for only a fraction of its members, and herbivorous hymenopterans that attack ferns are especially poorly studied. By documenting OBPs, CSPs, NPC2s, ORs, IRs, GRs, and SNMPs in a fern-feeding sawfly relative, the study offers comparative data that will help researchers trace how chemosensory gene families evolve as insects shift onto unusual host plants. The authors note that their findings lay a solid molecular foundation for future investigations of gene function and the mechanisms of olfactory perception in R. cyatheae.

From a technical standpoint, the study demonstrates a now-standard but powerful pipeline for working with non-model insects: assemble a transcriptome, annotate it against multiple databases, mine it for gene families of interest, place the candidates in phylogenetic context, and validate expression patterns experimentally. The resulting catalogue of 90 chemosensory genes, anchored by a high-quality assembly of 30,296 unigenes and confirmed sex-specific expression patterns, transforms R. cyatheae from a molecularly unknown pest into a tractable research system. For the endangered tree fern it threatens, that transformation may ultimately matter most: every gene identified is a potential target for understanding, predicting, and eventually managing the outbreaks that strike when the fern’s tender new fronds emerge. The research was funded by a project on pest resistance mechanisms of different Cyathea species based on multi-generation transcriptomes and protein metabolomes, and by a Science and Technology Innovation Talent Team project of Guizhou Province, reflecting sustained regional investment in protecting this unique fragment of prehistoric flora.

Subject of Research: Identification of chemosensory genes in the adult transcriptome of the tree fern pest wasp Rhoptroceros cyatheae

Article Title: Analysis and identification of chemosensory genes in the transcriptome of adult Rhoptroceros cyatheae

Article References: Analysis and identification of chemosensory genes in the transcriptome of adult Rhoptroceros cyatheae. (n.d.). https://doi.org/10.1186/s12864-026-13393-4

Image Credits: AI Generated

DOI: 10.1186/s12864-026-13393-4

Keywords: Rhoptroceros cyatheae, chemosensory genes, transcriptome, odorant-binding proteins, odorant receptors, Alsophila spinulosa, tree fern, olfaction, RT-qPCR, phylogenetic analysis, BMC Genomics, entomology

The research, conducted at the research farm of ICAR-Central Institute for Cotton Research’s Regional Station in Sirsa, Haryana, in the semi-arid north Indian cotton zone, spanned the kharif seasons of 2018-19 and 2019-20. The site sits at roughly 202 meters above sea level, receives about 335 millimeters of annual rainfall concentrated in the July-to-September monsoon, and is underlain by sandy loam soils of Gangetic alluvium origin with a mildly alkaline pH of 8.2. In this setting, the team led by Rishi Kumar, Amarpreet Singh and Debashis Paul set out to answer a question that has long nagged agronomists: how do sowing date, genotype and nitrogen rate interact to drive whitefly dynamics and productivity in Gossypium hirsutum cotton?

The experimental design was deliberately ambitious. Using a split-split plot layout replicated three times, the researchers compared four planting dates—early, optimum, late and very late—across two genotypes, a Bt-II hybrid (NCS 9013) and a local American cotton variety (CSH 3129), each grown under both protected conditions, where recommended insecticides were sprayed, and unprotected conditions, where no chemical sprays were applied. Layered onto this were three nitrogen regimes: a dose below the recommended rate, the recommended dose itself, and a dose exceeding it, applied in two splits. Weekly monitoring of adult whiteflies began in early July, around the 27th Standard Meteorological Week, and continued until populations receded in early October. Counts were taken from the upper, middle and lower canopy of tagged plants before 10 a.m. to avoid disturbing the adults, with nymphs tallied using a hand lens.

The headline finding concerns timing. Cotton sown very late carried mean adult whitefly populations 9.2 to 14 percent higher than crops planted at the optimum time, with the gap widening precisely during the pest’s peak activity window around the 38th Standard Meteorological Week, when counts reached 15.82 and 21.67 whiteflies per three leaves in the two seasons respectively. In 2018-19, seasonal means per three leaves ranged from 12.24 whiteflies on optimum-sown cotton to 13.96 on very late plantings; in 2019-20 the corresponding figures were 14.08 and 15.68. Statistical tests confirmed that late and very late sowings supported significantly higher populations than optimum sowing during the peak weeks of both years.

The nymphal data tell an equally revealing story about how the pest tracks the crop’s phenology. Early in the season, at the 27th Standard Meteorological Week, very late-sown cotton—still spindly and poorly developed—actually hosted fewer nymphs, averaging 8.01 and 8.59 per three leaves across the two years. But as delayed crops put on vigorous growth and tender foliage, the pattern flipped: by the 33rd week, very late plots carried 13.36 and 10.96 nymphs per three leaves, overtaking their earlier-sown counterparts. Whiteflies, in other words, follow the freshest plant tissue. In the fragmented smallholder landscapes of north India, where early and late fields sit side by side without isolation, this creates a relay: adults abandon aging canopies and colonize younger, lusher crops as the season progresses, a dynamic the authors warn makes staggered sowing windows genuinely risky.

Genotype, by contrast, proved far less influential. The hybrid and the local variety supported statistically indistinguishable whitefly numbers, likely because both developed similar canopy architectures. Protected and unprotected plots also differed only numerically, not significantly—though populations hovered near the economic threshold of six adults per leaf, prompting two insecticide sprays in each season, using neem-based products and diafenthiuron, which knocked counts down immediately after application. The moderate overall pressure meant that chemical protection, while helpful, was not the decisive variable in this study.

Nitrogen, however, was. Plots fertilized above the recommended dose consistently hosted more whiteflies throughout the season, with seasonal means of 14.21 and 15.60 adults per three leaves in the high-nitrogen treatments during 2018-19 and 2019-20, compared with lows of 11.87 and 13.36 in plots receiving less than the recommended rate. Nymphal counts followed the same trajectory, with significantly higher numbers on high-nitrogen cotton during specific weeks in both years. The mechanism is well grounded in plant physiology: nitrogen fertilization raises the concentration of amino-nitrogen compounds in phloem sap, improving the nutritional quality of the diet for phloem-feeding insects and boosting their feeding preference, survival, growth, reproduction and population density. This is consistent with a long line of studies showing that excess nitrogen fuels outbreaks of homopteran pests such as aphids, scales and whiteflies, and it matters enormously in north India, where farmers habitually apply nitrogen well beyond recommended rates across a broad sowing window.

The yield consequences were stark. Early-sown cotton produced 32.00 and 32.75 quintals of seed cotton per hectare across the two years, and optimum-timed sowings delivered 30.94 and 32.50 quintals per hectare—both significantly outperforming late sowings at 27.77 and 27.85 quintals and very late sowings at just 19.66 and 21.63 quintals per hectare. Nitrogen rate showed no significant effect on yield in the first year but a significant one in the second, with higher doses lifting yields while simultaneously carrying a heavier whitefly burden. The yield advantage of early planting likely reflects greater translocation of photosynthates and earlier canopy establishment, giving the crop a head start before pest pressure peaks.

The findings resonate with a painful recent history. Delayed sowing was identified as a major contributor to the devastating whitefly outbreak of 2015-16 in north India, when poorly established crops succumbed rapidly to infestation. Ambient temperature, natural enemies and host plant condition are known to govern pest dynamics, and the new study shows how ordinary agronomic choices tip those balances. Interestingly, the picture is not universally simple: research from dryland cotton in Texas found higher banded-winged whitefly numbers on early plantings, a reminder that local climate and cropping systems shape the outcome. But in the irrigated north Indian system, where roughly 1.6 million hectares are sown between April and June depending on canal water availability, the evidence points firmly toward early, uniform sowing.

The practical message is refreshingly actionable. Timely planting of cotton genotypes, combined with nitrogen applied strictly at recommended doses, delivers both better yields and lower whitefly pressure—no additional cost, no additional sprays, just disciplined agronomy. Avoiding late sowing and resisting the temptation to over-fertilize could spare farmers the yield penalties of up to a third of the crop seen in very late plantings, while reducing the pesticide load and the risk of the kind of regional outbreaks that have twice convulsed the north Indian cotton economy within a decade. In the ongoing arms race against Bemisia tabaci, it turns out that the calendar and the fertilizer bag may be a farmer’s most underrated weapons.

Subject of Research: Effects of planting date and nitrogen fertilization on whitefly population dynamics and yield in cotton

Article Title: Planting dates and rate of nitrogen fertilization influences whitefly population dynamics and incidence in cotton (Gossypium hirsutum L.)

Article References: Kumar, R., Singh, A., & Paul, D. (2025). Planting dates and rate of nitrogen fertilization influences whitefly population dynamics and incidence in cotton (Gossypium hirsutum L.). Discover Ecology, 1(1), Article 11. https://doi.org/10.1007/s44396-025-00011-y

Image Credits: AI Generated

DOI: 10.1007/s44396-025-00011-y

Keywords: whitefly, Bemisia tabaci, cotton, planting date, nitrogen fertilization, pest management, seed cotton yield, Gossypium hirsutum, agronomy, entomology, India, sucking pests

The experiment took its inspiration from a celebrated 2013 study in which researchers showed that the African ball-rolling dung beetle Scarabaeus satyrus uses the Milky Way to keep its dung ball rolling in a straight line. That finding, made famous partly because African beetles roll their prized balls directly away from the dung pile in a race against competitors, raised an obvious evolutionary question: is celestial orientation a special adaptation of exposed, ball-rolling beetles in open habitats, or a far more ancient capacity shared across the scarab beetle family? Vera Kaunath, Tony Werner, Christopher Kyba and Jana Eccard decided to test a species with a very different lifestyle. The European dung beetle does not roll balls to unknown destinations. Instead, it flies from dung pile to dung pile, locates its resource largely by smell, and digs its breeding tunnels directly beneath the find. Yet even a beetle that stays put once it has found food must still travel efficiently between resources, and for that, a compass could help.

During October 2015, the team captured beetles with cheese-baited pitfall traps in dense forest around the lake Teufelssee, roughly 36 kilometres southwest of Berlin. The site is genuinely dark by human standards, with no detectable surface glow in satellite imagery, although scattered light from Potsdam and Berlin brightens the zenith sky to roughly four times its natural brightness on clear nights. The beetles were housed in semi-opaque boxes filled with soil, leaves and horse dung, and each animal was used only once before being released near its point of capture. The stage for the actual experiment was provided by the URANIA Planetarium in Potsdam, whose dome can project up to 6,000 stars, allowing the researchers to assemble night skies of precisely controlled brightness and content, something no field site can offer.

The design was elegantly simple. A one-metre wooden arena, painted black with a white starting circle and grid, was placed on the planetarium floor. Each beetle was acclimatised for ten minutes in a glass tube, then released at the centre of the arena facing north. The test ended when the animal crossed a circle 50 centimetres from the release point, or after five minutes if it never got that far. A night-shot video camera with infrared illumination filmed every run from above, and the arena was cleaned with ethanol between trials. The beetles faced four treatments: complete darkness, a projection of roughly 2,500 stars, stars together with the Milky Way projected in a north-south orientation, and finally a single artificial lamp positioned three metres away, standing in for a real-world point source of light pollution. Light levels were measured with a Sky Quality Meter, confirming that the stars treatment matched a realistic starry sky with airglow, while the stars-and-Milky-Way projection was about 50 percent brighter than a natural sky.

Of 181 beetles tested, 77 produced analysable paths, with between 12 and 25 animals per treatment. Some beetles simply stopped moving, and some tracking attempts failed because the infrared footage did not provide enough contrast. Importantly, the proportion of excluded animals did not differ significantly across treatments, so the exclusions were unlikely to bias the comparison. The recorded paths were converted into coordinate sequences, one location every two seconds, and characterised by total walking distance, time to the arena edge and mean turning angle, a standard measure of how tortuous a route is. Direction of exit was analysed with circular statistics, including Rayleigh tests for non-random heading and Watson’s large-sample test for comparisons among treatments, and the movement variables were evaluated together with a multivariate analysis of variance.

The results were striking. Under the lamp, beetles walked the shortest distances, took the straightest routes and reached the arena edge faster than under any other condition. In complete darkness and under stars alone, their paths were the longest, slowest and most winding, with no statistical difference between the two dark treatments. The stars-and-Milky-Way treatment fell in between: total distance was shorter than in the darker conditions, and time and turning angle were intermediate. Because all three measures come from the same path, the team used a multivariate framework, which showed a highly significant overall difference among treatments, and follow-up analyses pinned the differences down for each individual variable. In plain terms, the more the beetles had to look at, the better they seemed to move, and that was as true for a projected galaxy as for an ordinary electric lamp.

Direction added a further puzzle. Across all treatments, roughly 74 percent of beetles left the arena heading west, a concentration that held even in the dark treatment, where it appeared only as a tendency. Rayleigh tests confirmed non-random, westward movement in the three illuminated treatments. Intriguingly, in the two brightest treatments, stars-and-Milky-Way and lamp, about 30 percent of the remaining animals exited in the exact opposite direction, and the median exit direction did not differ significantly among treatments. Because the Milky Way and the lamp sat roughly 90 degrees apart from the beetle’s perspective, yet the beetles’ exits clustered in a common direction regardless of treatment, the authors argue that the animals were probably not using the experimental light cues to set their heading. Instead, the shared direction may have come from some other feature of the hall, such as the silhouette of equipment, an olfactory cue or a draft near the door. Alternatively, the researchers speculate, beetles released facing north may follow self-referenced, idiothetic spiralling paths; a consistent leftward spiral would carry most animals across the perimeter at a similar spot, while a rightward spiral would produce the opposite exit, and brighter conditions might simply allow more precise execution of these stereotyped movements.

The conservation implications are deliberately cautious. On the one hand, the findings support the hypothesis that celestial bodies help optimise movement, an ability that may be ancestral among insects and that persists even in a species adapted to dark forest interiors and partly subterranean life. On the other hand, the authors explicitly note that this species’ navigation may not be disrupted by artificial light at night, because the beetles moved most efficiently under the lamp. That efficiency could, however, come at a hidden cost. African dung beetles have been shown to accept artificial light sources as substitute celestial cues when no natural ones are present, and the researchers suggest the European beetles may have misinterpreted the lamp as the moon. Whether such attraction escalates into the fatal attraction documented for flying insects, in which the dorsal light response causes moths and other aerial species to circle lamps until they die of exhaustion or predation, remains untested here.

What is not in doubt is the ecological weight these beetles carry. By burying dung and carrion, they accelerate the decomposition of organic matter and reduce the spread of flies and parasites, a service that could erode if artificial lighting chronically alters their activity. Insects exposed to constant light can show stress and exhaustion that steal time from foraging, dung transfer and mate searching. The authors conclude that pairing the avoidance of artificial lighting in natural and semi-natural areas with carefully tailored lighting concepts offers a practical window to limit the impact of light pollution before its effects become drastic. For now, the image that lingers is a small forest beetle, descendants of animals that have crawled through leaf litter for millions of years, apparently still reading the sky, and perhaps mistaking a streetlamp for the Milky Way when the real one fades from view.

Subject of Research: Celestial and artificial light cue use in the movement behaviour of the European dung beetle Anoplotrupes stercorosus

Article Title: Do dung beetles use the Milky Way to optimise their movement?

Article References: Kaunath, V., Werner, T., Kyba, C. C. M., & Eccard, J. A. (2025). Do dung beetles use the Milky Way to optimise their movement?. BMC Environmental Science, 2(1), Article 25. https://doi.org/10.1186/s44329-025-00039-1

Image Credits: AI Generated

DOI: 10.1186/s44329-025-00039-1

Keywords: dung beetle, celestial navigation, Milky Way, light pollution, artificial light at night, insect orientation, planetarium experiment, movement ecology, entomology, conservation, scarab beetles, night sky