Insect Biodiversity Research Articles

Three steps towards comparability and standardization among molecular methods for characterizing insect communities.

Molecular methods are currently some of the best-suited technologies for implementation in insect monitoring. However, the field is developing rapidly and lacks agreement on methodology or community standards. To apply DNA-based methods in large-scale monitoring, and to gain insight across commensurate data, we need easy-to-implement standards that improve data comparability. Here, we provide three recommendations for how to improve and harmonize efforts in biodiversity assessment and monitoring via metabarcoding: (i) we should adopt the use of synthetic spike-ins, which will act as positive controls and internal standards; (ii) we should consider using several markers through a multiplex polymerase chain reaction (PCR) approach; and (iii) we should commit to the publication and transparency of all protocol-associated metadata in a standardized fashion. For (i), we provide a ready-to-use recipe for synthetic cytochrome c oxidase spike-ins, which enable between-sample comparisons. For (ii), we propose two gene regions for the implementation of multiplex PCR approaches, thereby achieving a more comprehensive community description. For (iii), we offer guidelines for transparent and unified reporting of field, wet-laboratory and dry-laboratory procedures, as a key to making comparisons between studies. Together, we feel that these three advances will result in joint quality and calibration standards rather than the current laboratory-specific proof of concepts. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

Combining environmental DNA and remote sensing for efficient, fine-scale mapping of arthropod biodiversity.

Arthropods contribute importantly to ecosystem functioning but remain understudied. This undermines the validity of conservation decisions. Modern methods are now making arthropods easier to study, since arthropods can be mass-trapped, mass-identified, and semi-mass-quantified into 'many-row (observation), many-column (species)' datasets, with homogeneous error, high resolution, and copious environmental-covariate information. These 'novel community datasets' let us efficiently generate information on arthropod species distributions, conservation values, uncertainty, and the magnitude and direction of human impacts. We use a DNA-based method (barcode mapping) to produce an arthropod-community dataset from 121 Malaise-trap samples, and combine it with 29 remote-imagery layers using a deep neural net in a joint species distribution model. With this approach, we generate distribution maps for 76 arthropod species across a 225 km2 temperate-zone forested landscape. We combine the maps to visualize the fine-scale spatial distributions of species richness, community composition, and site irreplaceability. Old-growth forests show distinct community composition and higher species richness, and stream courses have the highest site-irreplaceability values. With this 'sideways biodiversity modelling' method, we demonstrate the feasibility of biodiversity mapping at sufficient spatial resolution to inform local management choices, while also being efficient enough to scale up to thousands of square kilometres. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

Measuring the state of aquatic environments using eDNA-upscaling spatial resolution of biotic indices.

Aquatic macroinvertebrates, including many aquatic insect orders, are a diverse and ecologically relevant organismal group yet they are strongly affected by anthropogenic activities. As many of these taxa are highly sensitive to environmental change, they offer a particularly good early warning system for human-induced change, thus leading to their intense monitoring. In aquatic ecosystems there is a plethora of biotic monitoring or biomonitoring approaches, with more than 300 assessment methods reported for freshwater taxa alone. Ultimately, monitoring of aquatic macroinvertebrates is used to calculate ecological indices describing the state of aquatic systems. Many of the methods and indices used are not only hard to compare, but especially difficult to scale in time and space. Novel DNA-based approaches to measure the state and change of aquatic environments now offer unprecedented opportunities, also for possible integration towards commonly applicable indices. Here, we first give a perspective on DNA-based approaches in the monitoring of aquatic organisms, with a focus on aquatic insects, and how to move beyond traditional point-based biotic indices. Second, we demonstrate a proof-of-concept for spatially upscaling ecological indices based on environmental DNA, demonstrating how integration of these novel molecular approaches with hydrological models allows an accurate evaluation at the catchment scale. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

Extensive data engineering to the rescue: building a multi-species katydid detector from unbalanced, atypical training datasets.

Passive acoustic monitoring (PAM) is a powerful tool for studying ecosystems. However, its effective application in tropical environments, particularly for insects, poses distinct challenges. Neotropical katydids produce complex species-specific calls, spanning mere milliseconds to seconds and spread across broad audible and ultrasonic frequencies. However, subtle differences in inter-pulse intervals or central frequencies are often the only discriminatory traits. These extremities, coupled with low source levels and susceptibility to masking by ambient noise, challenge species identification in PAM recordings. This study aimed to develop a deep learning-based solution to automate the recognition of 31 katydid species of interest in a biodiverse Panamanian forest with over 80 katydid species. Besides the innate challenges, our efforts were also encumbered by a limited and imbalanced initial training dataset comprising domain-mismatched recordings. To overcome these, we applied rigorous data engineering, improving input variance through controlled playback re-recordings and by employing physics-based data augmentation techniques, and tuning signal-processing, model and training parameters to produce a custom well-fit solution. Methods developed here are incorporated into Koogu, an open-source Python-based toolbox for developing deep learning-based bioacoustic analysis solutions. The parametric implementations offer a valuable resource, enhancing the capabilities of PAM for studying insects in tropical ecosystems. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

Delivering on a promise: futureproofing automated insect monitoring methods.

Due to rapid technological innovations, the automated monitoring of insect assemblages comes within reach. However, this continuous innovation endangers the methodological continuity needed for calculating reliable biodiversity trends in the future. Maintaining methodological continuity over prolonged periods of time is not trivial, since technology improves, reference libraries grow and both the hard- and software used now may no longer be available in the future. Moreover, because data on many species are collected at the same time, there will be no simple way of calibrating the outputs of old and new devices. To ensure that reliable long-term biodiversity trends can be calculated using the collected data, I make four recommendations: (1) Construct devices to last for decades, and have a five-year overlap period when devices are replaced. (2) Construct new devices to resemble the old ones, especially when some kind of attractant (e.g. light) is used. Keep extremely detailed metadata on collection, detection and identification methods, including attractants, to enable this. (3) Store the raw data (sounds, images, DNA extracts, radar/lidar detections) for future reprocessing with updated classification systems. (4) Enable forward and backward compatibility of the processed data, for example by in-silico data 'degradation' to match the older data quality. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

Towards holistic insect monitoring: species discovery, description, identification and traits for all insects.

Holistic insect monitoring needs scalable techniques to overcome taxon biases, determine species abundances, and gather functional traits for all species. This requires that we address taxonomic impediments and the paucity of data on abundance, biomass and functional traits. We here outline how these data deficiencies could be addressed at scale. The workflow starts with large-scale barcoding (megabarcoding) of all specimens from mass samples obtained at biomonitoring sites. The barcodes are then used to group the specimens into molecular operational taxonomic units that are subsequently tested/validated as species with a second data source (e.g. morphology). New species are described using barcodes, images and short diagnoses, and abundance data are collected for both new and described species. The specimen images used for species discovery then become the raw material for training artificial intelligence identification algorithms and collecting trait data such as body size, biomass and feeding modes. Additional trait data can be obtained from vouchers by using genomic tools developed by molecular ecologists. Applying this pipeline to a few samples per site will lead to greatly improved insect monitoring regardless of whether the species composition of a sample is determined with images, metabarcoding or megabarcoding. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

Sharing insect data through GBIF: novel monitoring methods, opportunities and standards.

Technological advancements in biological monitoring have facilitated the study of insect communities at unprecedented spatial scales. The progress allows more comprehensive coverage of the diversity within a given area while minimizing disturbance and reducing the need for extensive human labour. Compared with traditional methods, these novel technologies offer the opportunity to examine biological patterns that were previously beyond our reach. However, to address the pressing scientific inquiries of the future, data must be easily accessible, interoperable and reusable for the global research community. Biodiversity information standards and platforms provide the necessary infrastructure to standardize and share biodiversity data. This paper explores the possibilities and prerequisites of publishing insect data obtained through novel monitoring methods through GBIF, the most comprehensive global biodiversity data infrastructure. We describe the essential components of metadata standards and existing data standards for occurrence data on insects, including data extensions. By addressing the current opportunities, limitations, and future development of GBIF's publishing framework, we hope to encourage researchers to both share data and contribute to the further development of biodiversity data standards and publishing models. Wider commitments to open data initiatives will promote data interoperability and support cross-disciplinary scientific research and key policy indicators. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

PROTAX-GPU: a scalable probabilistic taxonomic classification system for DNA barcodes.

DNA-based identification is vital for classifying biological specimens, yet methods to quantify the uncertainty of sequence-based taxonomic assignments are scarce. Challenges arise from noisy reference databases, including mislabelled entries and missing taxa. PROTAX addresses these issues with a probabilistic approach to taxonomic classification, advancing on methods that rely solely on sequence similarity. It provides calibrated probabilistic assignments to a partially populated taxonomic hierarchy, accounting for taxa that lack references and incorrect taxonomic annotation. While effective on smaller scales, global application of PROTAX necessitates substantially larger reference libraries, a goal previously hindered by computational barriers. We introduce PROTAX-GPU, a scalable algorithm capable of leveraging the global Barcode of Life Data System (>14 million specimens) as a reference database. Using graphics processing units (GPU) to accelerate similarity and nearest-neighbour operations and the JAX library for Python integration, we achieve over a 1000 × speedup compared with the central processing unit (CPU)-based implementation without compromising PROTAX's key benefits. PROTAX-GPU marks a significant stride towards real-time DNA barcoding, enabling quicker and more efficient species identification in environmental assessments. This capability opens up new avenues for real-time monitoring and analysis of biodiversity, advancing our ability to understand and respond to ecological dynamics. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

Towards acoustic monitoring of bees: wingbeat sounds are related to species and individual traits.

Global pollinator decline urgently requires effective methods to assess their trends, distribution and behaviour. Passive acoustics is a non-invasive and cost-efficient monitoring tool increasingly employed for monitoring animal communities. However, insect sounds remain highly unexplored, hindering the application of this technique for pollinators. To overcome this shortfall and support future developments, we recorded and characterized wingbeat sounds of a variety of Iberian domestic and wild bees and tested their relationship with taxonomic, morphological, behavioural and environmental traits at inter- and intra-specific levels. Using directional microphones and machine learning, we shed light on the acoustic signature of bee wingbeat sounds and their potential to be used for species identification and monitoring. Our results revealed that frequency of wingbeat sounds is negatively related with body size and environmental temperature (between-species analysis), while it is positively related with experimentally induced stress conditions (within-individual analysis). We also found a characteristic acoustic signature in the European honeybee that supported automated classification of this bee from a pool of wild bees, paving the way for passive acoustic monitoring of pollinators. Overall, these findings confirm that insect sounds during flight activity can provide insights on individual and species traits, and hence suggest novel and promising applications for this endangered animal group. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

Time and habitat structure shape insect acoustic activity in the Amazon.

Insects are the most diverse animal taxon on Earth and play a key role in ecosystem functioning. However, they are often neglected by ecological surveys owing to the difficulties involved in monitoring this small and hyper-diverse taxon. With technological advances in biomonitoring and analytical methods, these shortcomings may finally be addressed. Here, we performed passive acoustic monitoring at 141 sites (eight habitats) to investigate insect acoustic activity in the Viruá National Park, Brazil. We first describe the frequency range occupied by three soniferous insect groups (cicadas, crickets and katydids) to calculate the acoustic evenness index (AEI). Then, we assess how AEI varies spatially and temporally among habitat types, and finally we investigate the relationship between vegetation structure variables and AEI for each insect category. Overall, crickets occupied lower and narrower frequency bands than cicadas and katydids. AEI values varied among insect categories and across space and time. The highest acoustic activity occurred before sunrise and the lowest acoustic activity was recorded in pastures. Canopy cover was positively associated with cricket acoustic activity but not with katydids. Our findings contribute to a better understanding of the role of time, habitat and vegetation structure in shaping insect activity within diverse Amazonian ecosystems. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

A Taxonomic Checklist of Insect Biodiversity in Loyola College Campus, Chennai, Tamil Nadu, India

A Taxonomic Checklist of Insect Biodiversity in Loyola College Campus, Chennai, Tamil Nadu, India

Pollinator insects on sugar palm (Arenga pinnata Merr.) in South Sumatera, Indonesia

Sugar palm production depends heavily on pollinator insects, including some insects related to A. pinnata. This study aimed to identify pollinating insect species, distribution, and biodiversity in four South Sumatran regions. Sweep nets and yellow sticky traps placed around the flowers of sugar palms were used to catch insects once a week. The trap is set up once every 24 hours. In the Ogan Ilir region, pollinating insect species such as Epuraea aestiva, Mystrops costaricensis, Elaidobius sp., Gabrius sp., and Brachypepluis sp. have been found. Apis meliefera, Apis cerana, Poliba occidentalis, Papilio sp., and Drosophila are found in the Musi Banyuasin of Ogan Komering Ilir (OKI). Drosophila, Graphium agamemnon, Appias libythea, Pothantus lydia, Mycalesis perseus, Vespa affinis, Tetragonula laeviceps, Tabanus sp., Aedes albopictus, Neurothemis fluctuans, Ypthima baldus, Cupha erymanthis, and Apis cerana were found in Muara Enim. Additionally, Muara Enim had the highest pollinator population, while Ogan Ilir had the lowest. Observations showed that the yellow sticky trap technique operated more effectively than the sweep net. The community is anticipated to gain from research by learning more about pollinating insects connected to sugar palms, their role in the surrounding ecosystem, and the bioecology of sugar palms.

Identifying archived insect bulk samples using DNA metabarcoding: A case study using the long‐term Rothamsted Insect Survey

AbstractInsect populations are declining in many parts of the world, but a lack of long‐term monitoring data is impeding our ability to understand and mitigate the causes of insect biodiversity loss. Whilst high‐throughput sequencing (HTS) approaches, such as DNA metabarcoding, have the potential to revolutionize insect biomonitoring through rapid scalable identification, it is unclear to what extent HTS can be applied to long‐term stored insect samples. Archived insect samples could inform forecasting and provide valuable information regarding past changes to biodiversity. Here, we assess the efficacy of DNA metabarcoding to identify archived samples from the longest passive monitoring scheme in the United Kingdom: the Rothamsted Insect Survey (RIS). With a focus on aphids as the target taxa of a national network of suction‐traps, we analyze a 16‐year time‐series of stored samples (2003–2018) using DNA metabarcoding from one of the RIS suction traps as an exemplar. We achieved this by using a non‐destructive DNA extraction protocol, ensuring the integrity of archival samples for further studies. We compared the identities of aphids determined by both metabarcoding (as inferred amplicon sequence variants [ASVs]) and morphological identification and found that metabarcoding detected most genera with varying success (mean > 76%). When comparing the two methods objectively (i.e., including taxa not detected morphologically), however, congruence decreased (51%). We show that minimum sequence copy thresholds can minimize metabarcoding false positives, but at the expense of introducing false negatives, highlighting the need for careful data curation. Detectability of taxa identified morphologically and similarity between the two methods did not significantly vary over time, demonstrating the viability of metabarcoding for screening archival samples. We discuss the advantages and challenges of metabarcoding for insect biomonitoring, particularly from archival samples, including improvements to sample handling, processing, and archiving. We highlight the wider potential of HTS approaches for stored samples from insect monitoring schemes, unlocking the immense potential of global historical time series.

Ground beetle movement is deterred by habitat edges: a mark-release-recapture study on the effectiveness of border crops in an agricultural landscape.

Border crops can increase beneficial insect biodiversity within agricultural fields by supplementing insects with food and nesting resources. However, the effectiveness of border crops relies on insect movement between adjacent habitats and some insects might consider habitat boundaries as barriers. Therefore, understanding insect movement between habitats is needed to determine the effectiveness of border crops for ecosystem services such as pest control within agricultural habitats. Our objective was to compare ground beetle (Coleoptera: Carabidae) movement across soybean plots that were bordered by corn and grassland habitat to determine whether habitat boundaries were considered barriers of movement to predatory beetles. Using a grid of pitfall traps within these habitats, we conducted a mark, release, and recapture experiment to track and evaluate ground beetle movement patterns. We found that ground beetles stayed in the habitat of their release and that movement between habitats, despite the type of bordering habitat or type of edge, was uncommon. We also found that long-distance movement was rare as most beetles moved less than 5 m (regardless of release or recaptured habitat) and movement was perpendicular to habitat edges. These results suggest that any edge habitat, including agricultural-agricultural boundaries and natural-agricultural boundaries, are likely barriers to ground beetle movement. Therefore, in order for border crops to be effective in pest management by ground beetles, making habitat edges more permeable, especially using techniques such as edge softening, could promote cross-habitat movement and ultimately contribute to natural pest control in agricultural systems.

Biodiversity of aquatic insects flourished in the rain water collected from Kosti and Rabak cities, White Nile State, Sudan

Biodiversity including description of status of ecosystems and populations to the best to our knowledge and major threats for better biodiversity conservation. The aim of this study was to evaluate the biodiversity of aquatic insect population in the rain water collected from White Nile State. The samples of the rain water were collected during (March and October 2022) from Kosti and Rabak Cities, White Nile State, Sudan, in clean disposable plastic bottles from random sites. Anopheles, Culex and Aedes mosquito’s larvae were identified and counted, in addition to their aquatic predators (mayfly, dragon fly and water beetles), while algae and snails were just checked for their presence within this sites. The results at Kosti city during March 2022, showed the dominance of Anopheles (37 larvae) over Culex (14 larvae), while mayfly were the more abundant predators (16 naiads), followed by water beetle (6 beetles). In Rabak city, Culex (44 larvae) was the most dominant in addition to water beetles (12 beetles). During October 2022, Anopheles (78 larvae), Culex (34 larvae) and mayfly were the dominant organisms. In Rabak city, Culex (50 larvae) was the most dominant genus, while Aedes larvae were not noticed throughout this study. Mayfly and dragon fly naiads, and water beetles were not noticed in all Rabak site

Integrated parasite management (IPM) and the pasture ecosystem: Optimizing outcomes for cattle, insect biodiversity, and soil health

Concerns over the negative environmental impacts of livestock parasiticide treatments and the widespread development of resistance has precipitated a move towards integrated parasite management (IPM). However, within the pasture ecosystem management strategies are likely to impact multiple processes in complex ways. This study investigates the impacts of IPM strategies on pest flies, gastrointestinal nematode (GIN) parasites, beneficial dung insects, and soil health. Twenty-nine grazing dairy farms participated in the study, representing different chemical and nonchemical parasite management and grazing strategies (continuous, rotational, or management intensive rotational (MIG)). Cattle managed using rotational grazing and MIG had significantly lower FEC than continuously grazed cattle. Farms using chemical parasiticides had significantly fewer pest flies, however farms releasing parasitoid wasps as biological control also had reduced abundances. Dung inhabiting beetle abundance was significantly correlated with reduced pest flies and GIN. Beneficial insects were negatively impacted on farms that used parasiticides. Continuously grazed pastures had higher beneficial insect abundances only on farms that did not use chemical parasiticides. Pastures managed under MIG had lower soil bulk density and higher active carbon compared to continuous grazing. There were positive associations between soil health and tunneling dung insects (Onthophagus spp. dung beetles). Finding optimal strategies will be context dependent, however the results of this study indicate that grazing strategies can control gastrointestinal parasites and improve soil health outcomes, natural enemies such as parasitoid wasps and dung inhabiting beetles can suppress pest fly populations, and the impacts of chemical control strategies may be mitigated through thoughtful implementation.

Diversity pattern of insects from Macao based on an updated species checklist after 25 years.

Insects represent one of the most diverse groups in the organism world with extremely rich species and morphological diversity, playing important roles in natural and city ecosystems. Regional compilation of insect species lists helps to clarify the richness of insect species in a region, enhances our understanding the structure and function of a local ecosystem and promotes the protection and development of insect resources. Moreover, it also serves as a valuable reference for cities with small area, large population and high urbanisation like Macao. Macao (Macau) Special Administrative Region (SAR) is situated at the Pearl River Delta on the southeast coast of mainland China. With urban development accelerating at great rate in a quite restricted area, Macao still has rich fauna, within which the insect diversity is surprisingly high. In this study, we systematically sorted out major references items of manuals or handbooks, monographs, articles, dissertations, official websites and other publicly available information sources about the insects recorded in Macao and, thus, generated a checklist of 15 orders, 166 families, 868 genera, 1,339 species and 118 subspecies. During this process, the preliminarily summarised list was re-examined to eliminate synonyms and invalid species, based on many more extensive literature reviews. Besides, spelling errors of scientific names, authors and years were corrected. Meanwhile, the catalogue revealed a different composition pattern of species diversity between orders from those of the world and China. Even based on the most conservative estimates, the number of insect species in Macao should not be lower than 3,340 species, which hints at the necessity of deeper investigations with adequate collecting in the future to achieve more comprehensive recognition and understanding of Macao's insect biodiversity.

From buzzes to bytes: A systematic review of automated bioacoustics models used to detect, classify and monitor insects

Abstract Insects play vital ecological roles; many provide essential ecosystem services while others are economically devastating pests and disease vectors. Concerns over insect population declines and expansion have generated a pressing need to effectively monitor insects across broad spatial and temporal scales. A promising approach is bioacoustics, which uses sound to study ecological communities. Despite recent increases in machine learning technologies, the status of emerging automated bioacoustics methods for monitoring insects is not well known, limiting potential applications. To address this gap, we systematically review the effectiveness of automated bioacoustics models over the past four decades, analysing 176 studies that met our inclusion criteria. We describe their strengths and limitations compared to traditional methods and propose productive avenues forward. We found automated bioacoustics models for 302 insect species distributed across nine Orders. Studies used intentional calls (e.g. grasshopper stridulation), by‐products of flight (e.g. bee wingbeats) and indirectly produced sounds (e.g. grain movement) for identification. Pests were the most common study focus, driven largely by weevils and borers moving in dried food and wood. All disease vector studies focused on mosquitoes. A quarter of the studies compared multiple insect families. Our review illustrates that machine learning, and deep learning in particular, are becoming the gold standard for bioacoustics automated modelling approaches. We identified models that could classify hundreds of insect species with over 90% accuracy. Bioacoustics models can be useful for reducing lethal sampling, monitoring phenological patterns within and across days and working in locations or conditions where traditional methods are less effective (e.g. shady, shrubby or remote areas). However, it is important to note that not all insect taxa emit easily detectable sounds, and that sound pollution may impede effective recordings in some environmental contexts. Synthesis and applications: Automated bioacoustics methods can be a useful tool for monitoring insects and addressing pressing ecological and societal questions. Successful applications include assessing insect biodiversity, distribution and behaviour, as well as evaluating the effectiveness of restoration and pest control efforts. We recommend collaborations among ecologists and machine learning experts to increase model use by researchers and practitioners.

Becoming Visible

Systematic entomology as the study and ordering of insect biodiversity is a material-based practice that relies on insect bodies as a resource. Especially large amounts of insect specimens were collected and traded globally in the decades surrounding the turn of the twentieth century, often relying on colonial infrastructures. Taking colonial-era Taiwan as a case study, this paper asks under which circumstances specific places became collecting sites. It takes a series of articles on the insect fauna of the island as a point of departure, titled H. Sauter’s Formosa-Ausbeute after the German naturalist who sent the specimens around the world in the early twentieth century. It explores how collecting specimens was entangled with colonial infrastructure projects, insect policies, and forest-based industries. After Taiwan became a Japanese colony in 1895, newly constructed railways, including push car lines and logging trains, gave naturalists access to inner frontiers. Conversely, insects moved into the spotlight by disrupting these same infrastructures. A rush into the mountains was brought on by the island’s abundance in old growth forests, as evergreen trees such as camphor laurels became valuable export resources. The location of insect collecting sites was determined not just by ecological factors but by forest-based industries and colonial policies as well. As ancient trees were felled and aboriginal peoples violently displaced, insect collectors followed colonial infrastructures into the mountains, resulting in what a German entomologist called the “mass fabrication” of articles about Taiwan’s insect fauna.

High temporal resolution data reveal low bat and insect activity over managed meadows in central Europe

Increasing agriculture and pesticide use have led to declines in insect populations and biodiversity worldwide. In addition to insect diversity, it is also important to consider insect abundance, due to the importance of insects as food for species at higher trophic levels such as bats. We monitored spatiotemporal variation in abundance of nocturnal flying insects over meadows, a common open landscape structure in central Europe, and correlated it with bat feeding activity. Our most important result was that insect abundance was almost always extremely low. This was true regardless of management intensity of the different meadows monitored. We also found no correlation of insect abundance or the presence of insect swarms with bat feeding activity. This suggests that insect abundance over meadows was too low and insect swarms too rare for bats to risk expending energy to search for them. Meadows appeared to be poor habitat for nocturnal flying insects, and of low value as a foraging habitat for bats. Our study highlights the importance of long-term monitoring of insect abundance, especially at high temporal scales to identify and protect foraging habitats. This will become increasingly important given the rapid decline of insects.