bluuebunny/crossref_metadata_2025 huggingface dataset:
Towards global insect biomonitoring with frugal methods
Authors: Brydegaard Mikkel , Pedales Ronniel D. , Feng Vivian , Yamoa Assoumou saint-doria , Kouakou Benoit , Månefjord Hampus , Wührl Lorenz , Pylatiuk Christian , Amorim Dalton de Souza , Meier Rudolf
Published: May 2024

None of the global targets for protecting nature are currently met, although humanity is critically dependent on biodiversity. A significant issue is the lack of data for most biodiverse regions of the planet where the use of frugal methods for biomonitoring would be particularly important because the available funding for monitoring is insufficient, especially in low-income countries. We here discuss how three approaches to insect biomonitoring (computer vision, lidar, DNA sequences) could be made more frugal and urge that all biomonitoring techniques should be evaluated for global suitability before becoming the default in high-income countries. This requires that techniques popular in high-income countries should undergo a phase of ‘innovation through simplification’ before they are implemented more broadly. We predict that techniques that acquire raw data at low cost and are suitable for analysis with AI (e.g. images, lidar-signals) will be particularly suitable for global biomonitoring, while techniques that rely heavily on patented technologies may be less promising (e.g. DNA sequences). We conclude the opinion piece by pointing out that the widespread use of AI for data analysis will require a global strategy for providing the necessary computational resources and training.

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
Authors: Svenningsen Cecilie S. , Schigel Dmitry
Published: May 2024

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’.
Delivering on a promise: futureproofing automated insect monitoring methods
Authors: van Klink Roel
Published: May 2024

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’.
Emerging technologies in citizen science and potential for insect monitoring
Authors: Sheard Julie Koch , Adriaens Tim , Bowler Diana E. , Büermann Andrea , Callaghan Corey T. , Camprasse Elodie C. M. , Chowdhury Shawan , Engel Thore , Finch Elizabeth A. , von Gönner Julia , Hsing Pen-Yuan , Mikula Peter , Rachel Oh Rui Ying , Peters Birte , Phartyal Shyam S. , Pocock Michael J. O. , Wäldchen Jana , Bonn Aletta
Published: May 2024

Emerging technologies are increasingly employed in environmental citizen science projects. This integration offers benefits and opportunities for scientists and participants alike. Citizen science can support large-scale, long-term monitoring of species occurrences, behaviour and interactions. At the same time, technologies can foster participant engagement, regardless of pre-existing taxonomic expertise or experience, and permit new types of data to be collected. Yet, technologies may also create challenges by potentially increasing financial costs, necessitating technological expertise or demanding training of participants. Technology could also reduce people's direct involvement and engagement with nature. In this perspective, we discuss how current technologies have spurred an increase in citizen science projects and how the implementation of emerging technologies in citizen science may enhance scientific impact and public engagement. We show how technology can act as (i) a facilitator of current citizen science and monitoring efforts, (ii) an enabler of new research opportunities, and (iii) a transformer of science, policy and public participation, but could also become (iv) an inhibitor of participation, equity and scientific rigour. Technology is developing fast and promises to provide many exciting opportunities for citizen science and insect monitoring, but while we seize these opportunities, we must remain vigilant against potential risks.

This article is part of the theme issue ‘Towards a toolkit for global insect biodiversity monitoring’.
Towards a standardized framework for AI-assisted, image-based monitoring of nocturnal insects
Authors: Roy D. B. , Alison J. , August T. A. , Bélisle M. , Bjerge K. , Bowden J. J. , Bunsen M. J. , Cunha F. , Geissmann Q. , Goldmann K. , Gomez-Segura A. , Jain A. , Huijbers C. , Larrivée M. , Lawson J. L. , Mann H. M. , Mazerolle M. J. , McFarland K. P. , Pasi L. , Peters S. , Pinoy N. , Rolnick D. , Skinner G. L. , Strickson O. T. , Svenning A. , Teagle S. , Høye T. T.
Published: May 2024

Automated sensors have potential to standardize and expand the monitoring of insects across the globe. As one of the most scalable and fastest developing sensor technologies, we describe a framework for automated, image-based monitoring of nocturnal insects—from sensor development and field deployment to workflows for data processing and publishing. Sensors comprise a light to attract insects, a camera for collecting images and a computer for scheduling, data storage and processing. Metadata is important to describe sampling schedules that balance the capture of relevant ecological information against power and data storage limitations. Large data volumes of images from automated systems necessitate scalable and effective data processing. We describe computer vision approaches for the detection, tracking and classification of insects, including models built from existing aggregations of labelled insect images. Data from automated camera systems necessitate approaches that account for inherent biases. We advocate models that explicitly correct for bias in species occurrence or abundance estimates resulting from the imperfect detection of species or individuals present during sampling occasions. We propose ten priorities towards a step-change in automated monitoring of nocturnal insects, a vital task in the face of rapid biodiversity loss from global threats.

This article is part of the theme issue ‘Towards a toolkit for global insect biodiversity monitoring’.
The potential of acoustic monitoring of aquatic insects for freshwater assessment
Authors: Desjonquères Camille , Linke Simon , Greenhalgh Jack , Rybak Fanny , Sueur Jérôme
Published: May 2024

Aquatic insects are a major indicator used to assess ecological condition in freshwater environments. However, current methods to collect and identify aquatic insects require advanced taxonomic expertise and rely on invasive techniques that lack spatio-temporal replication. Passive acoustic monitoring (PAM) is emerging as a non-invasive complementary sampling method allowing broad spatio-temporal and taxonomic coverage. The application of PAM in freshwater ecosystems has already proved useful, revealing unexpected acoustic diversity produced by fishes, amphibians, submerged aquatic plants, and aquatic insects. However, the identity of species producing sounds remains largely unknown. Among them, aquatic insects appear to be the major contributor to freshwater soundscapes. Here, we estimate the potential number of soniferous aquatic insects worldwide using data from the Global Biodiversity Information Facility. We found that four aquatic insect orders produce sounds totalling over 7000 species. This number is probably underestimated owing to poor knowledge of aquatic insects bioacoustics. We then assess the value of sound producing aquatic insects to evaluate ecological condition and find that they might be useful despite having similar responses in pristine and degraded environments in some cases. Both expert and automated identifications will be necessary to build international reference libraries and to conduct acoustic bioassessment in freshwaters.

This article is part of the theme issue ‘Towards a toolkit for global insect biodiversity monitoring’.
Multi-year soundscape recordings and automated call detection reveals varied impact of moonlight on calling activity of neotropical forest katydids
Authors: Symes Laurel B. , Madhusudhana Shyam , Martinson Sharon J. , Geipel Inga , ter Hofstede Hannah M.
Published: May 2024

Night-time light can have profound ecological effects, even when the source is natural moonlight. The impacts of light can, however, vary substantially by taxon, habitat and geographical region. We used a custom machine learning model built with the Python package
Koogu
to investigate the
in situ
effects of moonlight on the calling activity of neotropical forest katydids over multiple years. We prioritised species with calls that were commonly detected in human annotated data, enabling us to evaluate model performance. We focused on eight species of katydids that the model identified with high precision (generally greater than 0.90) and moderate-to-high recall (minimum 0.35), ensuring that detections were generally correct and that many calls were detected. These results suggest that moonlight has modest effects on the amount of calling, with the magnitude and direction of effect varying by species: half of the species showed positive effects of light and half showed negative. These findings emphasize the importance of understanding natural history for anticipating how biological communities respond to moonlight. The methods applied in this project highlight the emerging opportunities for evaluating large quantities of data with machine learning models to address ecological questions over space and time.

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
Authors: Rodríguez Ballesteros Alberto , Desjonquères Camille , Hevia Violeta , García Llorente Marina , Ulloa Juan S. , Llusia Diego
Published: May 2024

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
Authors: Do Nascimento Leandro A. , Pérez-Granados Cristian , Alencar Janderson B. Rodrigues , Beard Karen H.
Published: May 2024

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’.
Monitoring aerial insect biodiversity: a radar perspective
Authors: Bauer Silke , Tielens Elske K. , Haest Birgen
Published: May 2024

In the current biodiversity crisis, populations of many species have alarmingly declined, and insects are no exception to this general trend. Biodiversity monitoring has become an essential asset to detect biodiversity change but remains patchy and challenging for organisms that are small, inconspicuous or make (nocturnal) long-distance movements. Radars are powerful remote-sensing tools that can provide detailed information on intensity, timing, altitude and spatial scale of aerial movements and might therefore be particularly suited for monitoring aerial insects and their movements. Importantly, they can contribute to several essential biodiversity variables (EBVs) within a harmonized observation system. We review existing research using small-scale biological and weather surveillance radars for insect monitoring and outline how the derived measures and quantities can contribute to the EBVs ‘species population’, ‘species traits’, ‘community composition’ and ‘ecosystem function’. Furthermore, we synthesize how ongoing and future methodological, analytical and technological advancements will greatly expand the use of radar for insect biodiversity monitoring and beyond. Owing to their long-term and regional-to-large-scale deployment, radar-based approaches can be a powerful asset in the biodiversity monitoring toolbox whose potential has yet to be fully tapped.

This article is part of the theme issue ‘Towards a toolkit for global insect biodiversity monitoring’.
Temperature, not net primary productivity, drives continental-scale variation in insect flight activity
Authors: Tielens Elske K , Kelly Jeff
Published: May 2024

The amount of energy available in a system constrains large-scale patterns of abundance. Here, we test the role of temperature and net primary productivity as drivers of flying insect abundance using a novel continental-scale data source: weather surveillance radar. We use the United States NEXRAD weather radar network to generate a near-daily dataset of insect flight activity across a gradient of temperature and productivity. Insect flight activity was positively correlated with mean annual temperature, explaining 38% of variation across sites. By contrast, net primary productivity did not explain additional variation. Grassland, forest and arid-xeric shrubland biomes differed in their insect flight activity, with the greatest abundance in subtropical and temperate grasslands. The relationship between insect flight abundance and temperature varied across biome types. In arid-xeric shrublands and in forest biomes the temperature–abundance relationship was indirectly (through net primary productivity) or directly (in the form of precipitation) mediated by water availability. These results suggest that temperature constraints on metabolism, development, or flight activity shape macroecological patterns in ectotherm abundance. Assessing the drivers of continental-scale patterns in insect abundance and their variation across biomes is particularly important to predict insect community response to warming conditions.

This article is part of the theme issue ‘Towards a toolkit for global insect biodiversity monitoring’.
Effects of nocturnal celestial illumination on high-flying migrant insects
Authors: Gao Boya , Hu Gao , Chapman Jason W.
Published: May 2024

Radar networks hold great promise for monitoring population trends of migrating insects. However, it is important to elucidate the nature of responses to environmental cues. We use data from a mini-network of vertical-looking entomological radars in the southern UK to investigate changes in nightly abundance, flight altitude and behaviour of insect migrants, in relation to meteorological and celestial conditions. Abundance of migrants showed positive relationships with air temperature, indicating that this is the single most important variable influencing the decision to initiate migration. In addition, there was a small but significant effect of moonlight illumination, with more insects migrating on full moon nights. While the effect of nocturnal illumination levels on abundance was relatively minor, there was a stronger effect on the insects' ability to orientate close to downwind: flight headings were more tightly clustered on nights when the moon was bright and when cloud cover was sparse. This indicates that nocturnal illumination is important for the navigational mechanisms used by nocturnal insect migrants. Further, our results clearly show that environmental conditions such as air temperature and light levels must be considered if long-term radar datasets are to be used to assess changing population trends of migrants.

This article is part of the theme issue ‘Towards a toolkit for global insect biodiversity monitoring’.
Continental-scale patterns in diel flight timing of high-altitude migratory insects
Authors: Haest Birgen , Liechti Felix , Hawkes Will L. , Chapman Jason , Åkesson Susanne , Shamoun-Baranes Judy , Nesterova Anna P. , Comor Vincent , Preatoni Damiano , Bauer Silke
Published: May 2024

Many insects depend on high-altitude, migratory movements during part of their life cycle. The daily timing of these migratory movements is not random, e.g. many insect species show peak migratory flight activity at dawn, noon or dusk. These insects provide essential ecosystem services such as pollination but also contribute to crop damage. Quantifying the diel timing of their migratory flight and its geographical and seasonal variation, are hence key towards effective conservation and pest management. Vertical-looking radars provide continuous and automated measurements of insect migration, but large-scale application has not been possible because of limited availability of suitable devices. Here, we quantify patterns in diel flight periodicity of migratory insects between 50 and 500 m above ground level during March-October 2021 using a network of 17 vertical-looking radars across Europe. Independent of the overall daily migratory movements and location, peak migratory movements occur around noon, during crepuscular evening and occasionally the morning. Relative daily proportions of insect migration intensity and traffic during the diel phases of crepuscular-morning, day, crepuscular-evening and night remain largely equal throughout May-September and across Europe. These findings highlight, extend, and generalize previous regional-scale findings on diel migratory insect movement patterns to the whole of temperate Europe.

This article is part of the theme issue ‘Towards a toolkit for global insect biodiversity monitoring’.
Monitoring insect numbers and biodiversity with a vertical-beam entomological radar
Authors: Drake V. Alistair , Hao Zhenhua , Wang Haikou
Published: May 2024

Concerns about perceived widespread declines in insect numbers have led to recognition of a requirement for long-term monitoring of insect biodiversity. Here we examine whether an existing, radar-based, insect monitoring system developed for research on insect migration could be adapted to this role. The radar detects individual larger (greater than 10 mg) insects flying at heights of 150–2550 m and estimates their size and mass. It operates automatically and almost continuously through both day and night. Accumulation of data over a ‘half-month’ (approx. 15 days) averages out weather effects and broadens the source area of the wind-borne observation sample. Insect counts are scaled or interpolated to compensate for missed observations; adjustment for variation of detectability with range and insect size is also possible. Size distributions for individual days and nights exhibit distinct peaks, representing different insect types, and Simpson and Shannon–Wiener indices of biodiversity are calculated from these. Half-month count, biomass and index statistics exhibit variations associated with the annual cycle and year to year changes that can be attributed to drought and periods of high rainfall. While species-based biodiversity measures cannot be provided, the radar's capacity to estimate insect biomass over a wide area indicates utility for tracking insect population sizes.

This article is part of the theme issue ‘Towards a toolkit for global insect biodiversity monitoring’.
Three steps towards comparability and standardization among molecular methods for characterizing insect communities
Authors: Iwaszkiewicz-Eggebrecht Ela , Zizka Vera , Lynggaard Christina
Published: May 2024

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 cytochromecoxidase 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’.
Towards holistic insect monitoring: species discovery, description, identification and traits for all insects
Authors: Meier Rudolf , Hartop Emily , Pylatiuk Christian , Srivathsan Amrita
Published: May 2024

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’.
Measuring the state of aquatic environments using eDNA—upscaling spatial resolution of biotic indices
Authors: Blackman Rosetta C. , Carraro Luca , Keck François , Altermatt Florian
Published: May 2024

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’.
With a little help from my friends: the roles of microbial symbionts in insect populations and communities
Authors: Łukasik Piotr , Kolasa Michał R.
Published: May 2024

To understand insect abundance, distribution and dynamics, we need to understand the relevant drivers of their populations and communities. While microbial symbionts are known to strongly affect many aspects of insect biology, we lack data on their effects on populations or community processes, or on insects' evolutionary responses at different timescales. How these effects change as the anthropogenic effects on ecosystems intensify is an area of intense research. Recent developments in sequencing and bioinformatics permit cost-effective microbial diversity surveys, tracking symbiont transmission, and identification of functions across insect populations and multi-species communities. In this review, we explore how different functional categories of symbionts can influence insect life-history traits, how these effects could affect insect populations and their interactions with other species, and how they may affect processes and patterns at the level of entire communities. We argue that insect-associated microbes should be considered important drivers of insect response and adaptation to environmental challenges and opportunities. We also outline the emerging approaches for surveying and characterizing insect-associated microbiota at population and community scales.

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
Authors: Li Roy , Ratnasingham Sujeevan , Zarubiieva Iuliia , Somervuo Panu , Taylor Graham W.
Published: May 2024

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’.
Extensive data engineering to the rescue: building a multi-species katydid detector from unbalanced, atypical training datasets
Authors: Madhusudhana Shyam , Klinck Holger , Symes Laurel B.
Published: May 2024

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’.
Genotypic and phenotypic consequences of domestication in dogs
Authors: Sweetalana  , Nataneli Shirin , Huang Shengmiao , Mooney Jazlyn A , Szpiech Zachary A
Published: May 2024

Runs of homozygosity (ROH) are genomic regions that arise when two copies of identical haplotypes are inherited from a shared common ancestor. In this study, we leverage ROH to identify associations between genetic diversity and non-disease phenotypes inCanis lupus familiaris(dogs). We find significant association between the ROH inbreeding coefficient (FROH) and several phenotypic traits. These traits include height, weight, lifespan, muscled, white coloring of the head and chest, furnishings, and fur length. After correcting for population structure, we identified more than 45 genes across the examined quantitative traits that exceed the threshold for suggestive significance. We observe distinct distributions of inbreeding and elevated levels of long ROH in modern breed dogs compared to more ancient breeds, which aligns with breeding practices during Victorian era breed establishment. Our results highlight the impact of non-additive variation and of polygenicity on complex quantitative phenotypes in dogs due to domestication and the breed formation bottleneck.
Study demands and health status among medical students in two German universities
Authors: Voss Amanda , Dettmer Susanne , Tschorn Mira , Zoellick Jan C.
Published: May 2024

Background and objectives

Medical students regularly report high study demands and low mental health. We thus studied medical students in two different curricula in Germany investigating their study demands, study and life satisfaction, and overall and mental health with emphasis on contrasting beginners and advanced students.

Design and methods

We used online surveys with convenience samples through university mailing lists and student union channels. Uni1 participants (N=357; 70% female,M=24.83 years) were older than Uni2 participants (N=126; 79% female;M=23.39 years), but the cohorts did not differ further regarding sociodemographic variables. For analyses, we usedt-tests for comparisons and correlations for associations.

Results

Students of both universities reported good mental and overall health as well as high satisfaction with their studies and lives, yet sleep difficulties were prevalent. Study demands were low to medium with the highest demands being learning activities (M=5.31;SD=2.19, scale 0-10), self-structuring (M=4.61;SD=2.01), and performance pressure (M=4.45;SD=2.27). The students in the reformed degree programme reported fewer issues with integrating theory and practice compared to those in the regular degree programme (MUni1=3.38;SDUni1=2.05;MUni2=4.17;SDUni2=2.06;t(430)=-3.53,p<.001).

Discussion and conclusions

Our sample was rather resilient regarding mental health and coping with study demands. The two universities showed little to no differences. With relative increased demands regarding learning activities, self-structuring, and performance pressure we suggest to focus on learning strategies for beginners and strategies for stress reduction to address, among other things, the reported sleep difficulties.
Using explainable artificial intelligence to identify linguistic biomarkers of amyloid pathology in primary progressive aphasia
Authors: Robertson Cole , Rezaii Neguine , Hochberg Daisy , Quimby Megan , Wolff Phillip , Dickerson Bradford C.
Published: May 2024

Introduction

Recent success has been achieved in Alzheimer’s disease (AD) clinical trials targeting amyloid beta (β), demonstrating a reduction in the rate of cognitive decline. However, testing methods for amyloid-β positivity are currently costly or invasive, motivating the development of accessible screening approaches to steer patients toward appropriate diagnostic tests. Here, we employ a pre-trained language model (Distil-RoBERTa) to identify amyloid-β positivity from a short, connected speech sample. We further use explainable AI (XAI) methods to extract interpretable linguistic features that can be employed in clinical practice.

Methods

We obtained language samples from 74 patients with primary progressive aphasia (PPA) across its three variants. Amyloid-β positivity was established through the analysis of cerebrospinal fluid, amyloid PET, or autopsy. 51% of the sample was amyloid-positive. We trained Distil-RoBERTa for 16 epochs with a batch size of 6 and a learning rate of 5e−5, and used the LIME algorithm to train interpretation models to interpret the trained classifier’s inference conditions.

Results

Over ten runs of 10-fold cross-validation, the classifier achieved a mean accuracy of 92%, SD = 0.01. Interpretation models were able to capture the classifier’s behavior well, achieving an accuracy of 97% against classifier predictions, and uncovering several novel speech patterns that may characterize amyloid-β positivity.

Discussion

Our work improves previous research which indicates connected speech is a useful diagnostic input for prediction of the presence of amyloid-β in patients with PPA. Further, we leverage XAI techniques to reveal novel linguistic features that can be tested in clinical practice in the appropriate subspecialty setting. Computational linguistic analysis of connected speech shows great promise as a novel assessment method in patients with AD and related disorders.
Time-course analysis of the transcriptome ofArabidopsis thalianaleaves under high-concentration ammonium sulfate treatment
Authors: Iwanaga Hiroko , Arai Yuki , Nezuo Maiko , Doi Akiko , Takei Takahito , Fujiwara Masayuki , Hachiya Takushi , Hamada Takahiro
Published: May 2024

Nitrogen is essential for plant growth and is sourced primarily from nitrate and ammonium in the soil. Even though plants can take ammonium up for nutrition, it often results in toxic effects such as growth suppression and chlorosis. To elucidate the mechanism of ammonium toxicity, a time-course analysis of the transcriptome was performed onA. thalianaleaves treated with high concentrations of ammonium sulfate in the presence of sufficient nitrate. The expression of nitrate-inducible genes tended to be downregulated by the treatment. The expression of genes relating to abscisic acid, jasmonic acid (JA), salicylic acid (SA), and membrane trafficking was upregulated, whereas that of photosynthesis-, auxin-, and cytokinin-related genes involved in growth and development was downregulated. The induction of many osmotic stress-responsive genes suggests the involvement of osmotic stress in ammonium toxicity. Furthermore, the upregulation of nitric oxide (NO)-inducible genes and the simultaneous upregulation of genes involved in JA biosynthesis, glutathione metabolism, and SA response suggested the involvement of endogenous NO and protein S-nitrosylation in response to high concentrations of ammonium sulfate. This study provides a novel and comprehensive overview of transcriptional changes occurring in response to high ammonium sulfate concentrations and proposes possible mechanisms of ammonium toxicity that can be explored in future research.
Modification of xylan in secondary walls alters cell wall biosynthesis and wood formation programs
Authors: Sivan Pramod , Urbancsok János , Donev Evgeniy N. , Derba-Maceluch Marta , Barbut Félix R. , Yassin Zakiya , Gandla Madhavi L. , Mitra Madhusree , Heinonen Saara E. , Šimura Jan , Cermanová Kateřina , Karady Michal , Scheepers Gerhard , Jönsson Leif J. , Master Emma R. , Vilaplana Francisco , Mellerowicz Ewa J.
Published: May 2024

Wood of broad-leaf tree species is a valued source of renewable biomass for biorefinery and a target for genetic improvement efforts to reduce its recalcitrance. Glucuronoxylan (GX) plays a key role in recalcitrance through its interactions with cellulose and lignin. To reduce recalcitrance, we modified wood GX by expressing GH10 and GH11 endoxylanases fromAspergillus nidulansin hybrid aspen (Populus tremulaL. xtremuloidesMichx.) and targeting the enzymes to cell wall. The xylanases reduced tree height, modified cambial activity by increasing phloem and reducing xylem production, and reduced secondary wall deposition. Xylan molecular weight was decreased, and the spacing between acetyl and MeGlcA side chains was reduced in transgenic lines. The transgenic trees produced hypolignified xylem having thin secondary walls and deformed vessels. Glucose yields of enzymatic saccharification without pretreatment almost doubled indicating decreased recalcitrance. The transcriptomics, hormonomics and metabolomics data provided evidence for activation of cytokinin and ethylene signaling pathways, decrease in ABA levels, transcriptional suppression of lignification and a subset of secondary wall biosynthetic program, including xylan glucuronidation and acetylation machinery. Several candidate genes for perception of impairment in xylan integrity were detected. These candidates could provide a new target for uncoupling negative growth effects from reduced recalcitrance. In conclusion, our study supports the hypothesis that xylan modification generates intrinsic signals and evokes novel pathways regulating tree growth and secondary wall biosynthesis.
Advancing thermostability of the key photorespiratory enzyme glycerate 3-kinase by structure-based recombination
Authors: Roze Ludmila V. , Antoniak Anna , Sarkar Daipayan , Liepman Aaron H. , Tejera-Nieves Mauricio , Vermaas Josh V. , Walker Berkley J.
Published: May 2024

As global temperatures rise, maintaining and improving crop yields will require enhancing the thermotolerance of crops. One approach for improving thermotolerance is using bioengineering to increase the thermostability of enzymes catalyzing essential biological processes. Photorespiration is an essential recycling process in plants that is integral to photosynthesis and crop growth. The enzymes of photorespiration are targets for enhancing plant thermotolerance as this pathway limits carbon fixation at elevated temperatures. Exploring inter-specific variation of the key photorespiratory enzyme glycerate kinase (GLYK) from various photosynthetic organisms, we found that the homolog from the thermophilic algaCyanidioschyzon merolaewas more thermotolerant than those from mesophilic plants, includingArabidopsis thaliana. To understand factors influencing thermotolerance ofC. merolaeGLYK (CmGLYK), we performed molecular dynamics simulations using AlphaFold-predicted structures, which revealed greater movement of loop regions of mesophilic plant GLYKs at higher temperatures compared to CmGLYK. Based on these simulations, a series of hybrid proteins were produced and analyzed. These hybrid enzymes contained selected loop regions from CmGLYK replacing the most highly mobile corresponding loops of AtGLYK. Two of these hybrid enzymes had enhanced thermostability, with melting temperatures increased by 6 °C. One hybrid with three grafted loops maintained higher activity at elevated temperatures. While this hybrid enzyme exhibited enhanced thermostability and a similar Kmfor ATP compared to AtGLYK, its Kmfor glycerate increased threefold. This study demonstrates that molecular dynamics simulation-guided structure-based recombination offers a promising strategy for enhancing thermostability of other plant enzymes.
Multiomic analysis of genes related to oil traits in legumes provide insights into lipid metabolism and oil richness in soybean
Authors: Turquetti-Moraes Dayana K. , Cardoso-Silva Cláudio Benício , Almeida-Silva Fabricio , Venancio Thiago M.
Published: May 2024

Soybean (Glycine max) and common bean (Phaseolus vulgaris) diverged approximately 19 million years ago. While these species share a whole-genome duplication (WGD), theGlycinelineage experienced a second, independent WGD. Despite the significance of these WGDs, their impact on gene families related to oil-traits remains poorly understood. Here, we report an in-depth investigation of oil-related gene families in soybean, common bean, and twenty-eight other legume species. We adopted a systematic approach that included transcriptome and co-expression analysis, identification of orthologous groups, gene duplication modes and evolutionary rates, and family expansions and contractions. We curated a list of oil candidate genes and found that 91.5% of the families containing these genes expanded in soybean in comparison to common bean. Notably, we observed an expansion of triacylglycerol (TAG) biosynthesis (∼3:1) and an erosion of TAG degradation (∼1.4:1) families in soybean in comparison to common bean. In addition, TAG degradation genes were two-fold more expressed in common bean than in soybean, suggesting that oil degradation is also important for the sharply contrasting seed oil contents in these species. We found 17 transcription factor hub genes that are likely regulators of lipid metabolism. Finally, we inferred expanded and contracted families and correlated these patterns with oil content found in different legume species. In summary, our results do not only shed light on the evolution of oil metabolism genes in soybean, but also present multifactorial evidence supporting the prioritization of candidates for crop improvement.