Kefir4All, a citizen science initiative to raise awareness of the roles that microbes play in food fermentation.

Microorganisms are ubiquitous in nature and are central to human, animal, environmental, and planetary health. They play a particularly important role in the food chain and the production of high-quality, safe, and health-promoting foods, especially fermented foods. This important role is not always apparent to members of the public. Here, we describe Kefir4All, a citizen science project designed to provide the general public with an opportunity to expand their awareness, knowledge, and practical skills relating to microbiology, introduced through the medium of producing fermented food, i.e., milk kefir or water kefir. During the course of Kefir4All, 123 citizen scientists, from second-level school and non-school settings, participated in a study to track changes in the microbial composition of kefirs, by performing and recording details of milk kefir or water kefir fermentations they performed in their homes or schools over the 21-week project. At the start of the study, the citizen scientists were provided with milk or water kefir grains to initiate the fermentations. Both types of kefir grain are semi-solid, gelatinous-like substances, composed of exopolysaccharides and proteins, containing a symbiotic community of bacteria and yeast. The experimental component of the project was complemented by a number of education and outreach events, including career talks and a site visit to our research center (Kefir Day). At the end of the study, a report was provided to each citizen scientist, in which individualized results of their fermenting activities were detailed. A number of approaches were taken to obtain feedback and other insights from the citizen scientists. Evaluations took place before and after the Kefir4All project to gauge the citizen scientist's self-reported awareness, knowledge, and interest in microbiology and fermented foods. Further insights into the level of citizen science participation were gained through assessing the number of samples returned for analysis and the level of participation of the citizen scientists throughout the project. Notably, the survey results revealed a self-reported, increased interest in, and general knowledge of, science among the Kefir4All citizen scientists after undertaking the project and a willingness to take part in further citizen science projects. Ultimately, Kefir4All represents an example of the successful integration of citizen science into existing education and research systems.

Citizen Science Studies in Nursing: A Systematic Review.

BACKGROUND: Citizen science is a research approach wherein citizens actively participate alongside professionals in some or all stages of the research process. The bidirectional benefits it generates, especially in the field of health, including empowerment, new hypotheses, and results, and addressing issues truly important to society, justify the necessity to establish a common framework and address barriers to ensure a fruitful evolution of this new approach within nursing research. The aim was to analyze nursing projects with a citizen science focus that have been conducted. METHODS: PRISMA guidelines were employed to conduct a systematic review. Searches were conducted on PubMed, CINHAL, LILACS, IBECS, and Cochrane. Following the identification and screening process, 13 studies were included. The quality of the articles was assessed using the Joanna Brigg Institute (JBI) critical appraisal checklist and the quality of citizen science research using the Citizen Science Appraisal Tool. RESULTS: Citizen science studies in nursing were notably recent (2017-2023). Five research areas were identified, with environmental health being the most predominant. Multiple tools, both technological and traditional, were utilized, with the "Photovoice" and "Our Voice" methodologies being prominent. Citizen participation was limited to data collection and analysis in 7 out of the 13 studies, with most studies working with small samples. Findings regarding the application of this practice were positive, but no study exceeded 26 points on the CSAT scale to be considered high quality in citizen science. CONCLUSIONS: Citizen science can be a promising approach within the field of nursing. There is a need to increase individual participation to fully realize the potential bidirectional benefits. It is imperative to establish a common theoretical framework and continue working on the development of this methodology within nursing.

Citizen science in environmental health research: A comparison with conventional approaches and creation of a guidance tool issued from the LILAS initiative.

CONTEXT: Public interest for citizen science (CS) in environmental health is growing. The goals of environmental health research projects are diverse, as are the methods used to reach these goals. Opportunities for greater implication of the civil society and related challenges differ at each step of such projects. These methodological aspects need to be widely shared and understood by all stakeholders. The LILAS initiative (acronym for "application of citizen science approaches such as LIving LAbS to research on environmental exposures and chronic risks") aimed to 1) favor a mutual understanding of the main issues and research methods in environmental health, of their stakes for different actors, but also of the requirements, strengths and limitations of these methods and to 2) identify expected benefits and points of attention related to stronger degrees of participation as part of environmental health research projects. METHODS: The LILAS initiative gathered institutional researchers, academics and civil society representatives interested in environmental exposures. Five meetings allowed to collectively identify different types of environmental health research studies and reflect about the benefits, limitations, and methodological issues related to the introduction of growing citizen participation as part of such studies. An analytic table matrix summarizing these aspects was co-created and filled by participants, as a tool devoted to help stakeholders with the definition of future CS research projects in environmental health. RESULTS: For different fields of research (e.g.: studies for assessment of environmental exposures, interventions on these exposures, quantitative risk assessment, epidemiological studies), the matrix lists expected benefits for various stakeholders, the fundamental principles of research methods and related practical constraints, but also advantages and limitations related to the use of CS or conventional research approaches. CONCLUSION: The LILAS initiative allowed to develop a tool which provides consolidated grounds for the co-creation of research projects on environmental exposures involving CS.

New shark in the park: Tiger shark Galeocerdo cuvier observations in the remote South Pacific.

We present the first photographic records of the tiger shark (Galeocerdo cuvier) at the remote Rapa Nui (Easter Island) in the south-east Pacific. Previous anecdotal sightings exist for tiger sharks in this region; however these records have not been reported within the scientific domain. The present sighting occurred in a period of unusually warm sea surface temperature, which has been shown to influence tiger shark range extensions elsewhere. Novel and historic species occurrence records are valuable for determining and predicting species' environmental tolerances, migratory routes, and distributional limits.

Incidence of per- and polyfluoroalkyl substances (PFAS) in private drinking water supplies in Southwest Virginia, USA.

Per- and polyfluoroalkyl substances (PFAS) are a class of man-made contaminants of human health concern due to their resistance to degradation, widespread environmental occurrence, bioaccumulation in living organisms, and potential negative health impacts. Private drinking water supplies may be uniquely vulnerable to PFAS contamination in impacted areas, as these systems are not protected under federal regulations and often include limited treatment or remediation, if contaminated, prior to use. The goal of this study was to determine the incidence of PFAS contamination in private drinking water supplies in two counties in Southwest Virginia, USA (Floyd and Roanoke) that share similar bedrock geologies, are representative of different state Department of Health risk categories, and to examine the potential for reliance on citizen-science based strategies for sample collection in subsequent efforts. Samples for inorganic ions, bacteria, and PFAS analysis were collected on separate occasions by participants and experts at the home drinking water point of use (POU) for comparison. Experts also collected outside tap samples for analysis of 30 PFAS compounds. At least one PFAS was detectable in 95 % of POU samples collected (n = 60), with a mean total PFAS concentration of 23.5 ±â€¯30.8 ppt. PFOA and PFOS, two PFAS compounds which presently have EPA health advisories, were detectable in 13 % and 22 % of POU samples, respectively. On average, each POU sample contained >3 PFAS compounds, and one sample contained as many as 8 compounds, indicating that exposure to a mixture of PFAS in drinking water may be occurring. Although there were significant differences in total PFAS concentrations between expert and participant collected samples (Wilcoxon, alpha = 0.05), collector bias was inconsistent, and may be due to the time of day of sampling (i.e. morning, afternoon) or specific attributes of a given home. Further research is required to resolve sources of intra-sample variability.

Recruitment, Retention, and Training of Citizen Scientists in Translational Medicine Research: A Citizen Science Initiative on Non-Alcoholic Fatty Liver Disease.

Citizen science is a participatory science approach in which members of the public (citizens) collaborate with scientists and professional researchers and become involved in research and innovation activities, resulting in the co-creation of scientific knowledge and innovation. Citizen science has been widely applied in research, particularly in the social sciences, environmental sciences, information and communication technologies, and public health. However, the application of this approach in clinical sciences, particularly in translational medicine research, is still nascent. This exploratory study involved members of the public (citizen scientists) in a translational medicine experiment on non-alcoholic fatty liver disease that incorporated a lifestyle and weight-loss intervention. The aim of this paper is to report successful methods and approaches for the recruitment, retention, and training of citizen scientists. For the citizen scientists' recruitment, online calls placed on the websites of our research project and biomedical research center and targeted emails were the most helpful. Of the 14 members of the public who expressed interest in our study, six were recruited as citizen scientists. Citizen scientists were mostly female (n = 5, 83%), white (n = 3, 50%), over 50 years of age (n = 4, 67%), educated to postgraduate level (n = 5, 83%), and either retired or not in employment (n = 5, 83%). The retention rate was 83% (n = 5), and the dropout rate was 17% (n = 1). We arranged instructor-led interactive online training sessions (an hour-long one-on-one session and two-hour group sessions). Research skills training covered ethics in research and qualitative and quantitative data analysis. Citizen scientists were given several incentives, such as reimbursement of travel and care costs, selection as citizen scientists of the month, publications of their blogs and perspective articles, and co-authorship and acknowledgement in papers and project deliverables. To conclude, members of the public (particularly middle-aged white women with postgraduate education) are interested in becoming citizen scientists in translational medicine research. Their retention rate is higher, and they can contribute to different research activities. However, they need training to develop their research skills and expertise. The training should be simple, comprehensive, and flexible to accommodate the schedules of individual citizen scientists. They deserve incentives as they work on a voluntary basis.

Citizen science mitigates the lack of distributional data on Nigerian birds.

Citizen science projects are expanding globally, with the African continent, particularly Nigeria, registering significant growth. Here, we document and analyse novel operations of the Nigerian Bird Atlas Project (NIBAP), 2015-2022. This project has employed the use of ornithologists, mainly trained at the A. P. Leventis Ornithological Research Institute (APLORI) located in Jos, Nigeria, and its 28 bird clubs established across Nigeria to enlist 827 bird enthusiasts that contribute regular and near real-time data about bird distribution and relative abundance in the country. Interestingly, NiBAP has recorded about 75% of the bird species known from Nigeria in only about 50% of Nigeria's total surface area, including 39 nationally threatened species. The Common Bulbul Pycnonotus barbatus, Laughing Dove Spilopelia senegalensis, and Grey-backed Camaroptera Camaroptera brevicaudata were the most commonly recorded species, while Amurum Forest Reserve, Rennajj Fish Farm, and Obudu Cattle Ranch were the most surveyed sites during the period. Thus, our approach reveals how to increase involvement of nature enthusiasts, ornithologists, and a regional research institute to build local capacity and contribute rich information necessary to alleviate the lack of distributional data about Afrotropical avifauna. We strongly recommend our approach to boost other citizen science projects across Africa and beyond to address the huge lack of biodiversity data, create public awareness, and foster conservation education.

Wildlife-friendly garden practices increase butterfly abundance and species richness in urban and arable landscapes.

Insect declines are being reported worldwide and private, residential gardens could provide refugia for these species under increasing land use change. Interest in wildlife-friendly gardening has increased, but many management recommendations lack a scientific evidence-base. We used a large citizen science scheme, the Garden Butterfly Survey (GBS), with data from over 600 gardens across Great Britain (2016-2021) to determine how the surrounding landscape influences the abundance and species richness of butterflies in gardens and whether wildlife-friendly gardening practices, such as having long grass and providing nectar plants, benefit butterflies. First, we show that GBS provides reliable estimates of species abundances by comparing with results from standardised, long-term monitoring data. Garden size and surrounding land use had significant effects on butterfly abundance and richness in gardens, including positive relationships with garden size, woodland and arable farmland and negative relationships with urbanisation. Both the presence and area of long grass in gardens were positively related to higher butterfly richness and abundance, with the latter being driven by butterflies that use grasses as larval host plants. These effects differed depending on the surrounding landscape, such that long grass resulted in higher garden butterfly abundance in landscapes dominated by arable farming, and higher abundance and richness in highly urbanised areas. The presence of flowering ivy (Hedera spp.) in gardens resulted in higher abundance of Celastrina argiolus holly blue which uses ivy as a larval host, and of Vanessa atalanta red admiral and Polygonia c-album comma, which favour it as a nectar source. Our work provides evidence that undertaking simple wildlife-friendly garden practices can be beneficial for attracting butterflies, particularly in heavily modified areas. With over 728,000 ha of gardens in Great Britain, the cumulative effect of leaving areas of lawn uncut and providing nectar and larval host plants could be key for helping biodiversity.

Exploring fungal diversity in Vietnam: A citizen science initiative.

Invasive fungal diseases are increasing globally, causing a large burden of disease in vulnerable populations. At the same time, antifungal resistance is rapidly emerging. Affordable nationwide and regional surveillance of fungal pathogens is needed. We have adapted a citizen-science methodology developed by a United Kingdom research group to study six key fungi in Vietnam, where there is no existing formal surveillance. These pathogens were ranked as high or critical in the World Health Organization fungal priority pathogens list and recognized as major disease-causing agents in Vietnam. Secondary school students (n = 90) in Hanoi were our citizen scientists, collecting soil (n = 90) and air (n = 90) samples for fungal identification and characterisation of drug-susceptibility in the laboratory. Pilot studies confirmed the effectiveness of our revised isolation procedure, which used selective culture media to improve the isolation of target fungi. Through active school and student involvement, optimized protocols, and our cost-effective sampling, the study could be scaled across Vietnam. We demonstrate an approach to fungal surveillance which also enhances science education, and awareness of fungal diseases. It addresses critical healthcare and education challenges in Vietnam while combating the growing issues of invasive fungal diseases and antifungal resistance.

On the Search for Potentially Anomalous Traces of Cosmic Ray Particles in Images Acquired by Cmos Detectors for a Continuous Stream of Emerging Observational Data.

In this paper we propose the method for detecting potential anomalous cosmic ray particle tracks in big data image dataset acquired by Complementary Metal-Oxide-Semiconductors (CMOS). Those sensors are part of scientific infrastructure of Cosmic Ray Extremely Distributed Observatory (CREDO). The use of Incremental PCA (Principal Components Analysis) allowed approximation of loadings which might be updated at runtime. Incremental PCA with Sequential Karhunen-Loeve Transform results with almost identical embedding as basic PCA. Depending on image preprocessing method the weighted distance between coordinate frame and its approximation was at the level from 0.01 to 0.02 radian for batches with size of 10,000 images. This significantly reduces the necessary calculations in terms of memory complexity so that our method can be used for big data. The use of intuitive parameters of the potential anomalies detection algorithm based on object density in embedding space makes our method intuitive to use. The sets of anomalies returned by our proposed algorithm do not contain any typical morphologies of particle tracks shapes. Thus, one can conclude that our proposed method effectively filter-off typical (in terms of analysis of variance) shapes of particle tracks by searching for those that can be treated as significantly different from the others in the dataset. We also proposed method that can be used to find similar objects, which gives it the potential, for example, to be used in minimal distance-based classification and CREDO image database querying. The proposed algorithm was tested on more than half a million (570,000+) images that contains various morphologies of cosmic particle tracks. To our knowledge, this is the first study of this kind based on data collected using a distributed network of CMOS sensors embedded in the cell phones of participants collaborating within the citizen science paradigm.

Wildlife Conservation on Private Land: A Social-Ecological Systems Study.

As human activity accelerates the global crisis facing wildlife populations, private land conservation provides an example of wildlife management challenges in social-ecological systems. This study reports on the research phase of 'WildTracker' - a co-created citizen science project, involving 160 landholders across three Tasmanian regions. This was a transdisciplinary collaboration between an environmental organisation, university researchers, and local landholders. Focusing on mammal and bird species, the project integrated diverse data types and technologies: social surveys, quantitative ecology, motion sensor cameras, acoustic recorders, and advanced machine-learning analytics. An iterative analytical methodology encompassed Pearson and point-biserial correlation for interrelationships, Non-Metric Multidimensional Scaling (NMDS) for clustering, and Random Forest machine learning for variable importance and prediction. Taken together, these analyses revealed complex relationships between wildlife populations and a suite of ecological, socio-economic, and land management variables. Both site-scale habitat characteristics and landscape-scale vegetation patterns were useful predictors of mammal and bird activity, but these relationships were different for mammals and birds. Four focal mammal species showed variation in their response to ecological and land management drivers. Unexpectedly, threatened species, such as the eastern quoll (Dasyurus viverrinus), favoured locations where habitat was substantially modified by human activities. The research provides actionable insights for landowners, and highlights the importance of 'messy,' ecologically heterogeneous, mixed agricultural landscapes for wildlife conservation. The identification of thresholds in habitat fragmentation reinforced the importance of collaboration across private landscapes. Participatory research models such as WildTracker can complement efforts to address the wicked problem of wildlife conservation in the Anthropocene.

Modelling heterogeneity in the classification process in multi-species distribution models can improve predictive performance.

Species distribution models and maps from large-scale biodiversity data are necessary for conservation management. One current issue is that biodiversity data are prone to taxonomic misclassifications. Methods to account for these misclassifications in multi-species distribution models have assumed that the classification probabilities are constant throughout the study. In reality, classification probabilities are likely to vary with several covariates. Failure to account for such heterogeneity can lead to biased prediction of species distributions. Here, we present a general multi-species distribution model that accounts for heterogeneity in the classification process. The proposed model assumes a multinomial generalised linear model for the classification confusion matrix. We compare the performance of the heterogeneous classification model to that of the homogeneous classification model by assessing how well they estimate the parameters in the model and their predictive performance on hold-out samples. We applied the model to gull data from Norway, Denmark and Finland, obtained from the Global Biodiversity Information Facility. Our simulation study showed that accounting for heterogeneity in the classification process increased the precision of true species' identity predictions by 30% and accuracy and recall by 6%. Since all the models in this study accounted for misclassification of some sort, there was no significant effect of accounting for heterogeneity in the classification process on the inference about the ecological process. Applying the model framework to the gull dataset did not improve the predictive performance between the homogeneous and heterogeneous models (with parametric distributions) due to the smaller misclassified sample sizes. However, when machine learning predictive scores were used as weights to inform the species distribution models about the classification process, the precision increased by 70%. We recommend multiple multinomial regression to be used to model the variation in the classification process when the data contains relatively larger misclassified samples. Machine learning prediction scores should be used when the data contains relatively smaller misclassified samples.

Developmental psychologists should adopt citizen science to improve generalization and reproducibility.

Widespread failures of replication and generalization are, ironically, a scientific triumph, in that they confirm the fundamental metascientific theory that underlies our field. Generalizable and replicable findings require testing large numbers of subjects from a wide range of demographics with a large, randomly-sampled stimulus set, and using a variety of experimental parameters. Because few studies accomplish any of this, meta-scientists predict that findings will frequently fail to replicate or generalize. We argue that to be more robust and replicable, developmental psychology needs to find a mechanism for collecting data at greater scale and from more diverse populations. Luckily, this mechanism already exists: Citizen science, in which large numbers of uncompensated volunteers provide data. While best-known for its contributions to astronomy and ecology, citizen science has also produced major findings in neuroscience and psychology, and increasingly in developmental psychology. We provide examples, address practical challenges, discuss limitations, and compare to other methods of obtaining large datasets. Ultimately, we argue that the range of studies where it makes sense *not* to use citizen science is steadily dwindling.

Integrated distance sampling models for simple point counts.

Point counts (PCs) are widely used in biodiversity surveys but, despite numerous advantages, simple PCs suffer from several problems: detectability, and therefore abundance, is unknown; systematic spatiotemporal variation in detectability yields biased inferences, and unknown survey area prevents formal density estimation and scaling-up to the landscape level. We introduce integrated distance sampling (IDS) models that combine distance sampling (DS) with simple PC or detection/nondetection (DND) data to capitalize on the strengths and mitigate the weaknesses of each data type. Key to IDS models is the view of simple PC and DND data as aggregations of latent DS surveys that observe the same underlying density process. This enables the estimation of separate detection functions, along with distinct covariate effects, for all data types. Additional information from repeat or time-removal surveys, or variable survey duration, enables the separate estimation of the availability and perceptibility components of detectability with DS and PC data. IDS models reconcile spatial and temporal mismatches among data sets and solve the above-mentioned problems of simple PC and DND data. To fit IDS models, we provide JAGS code and the new "IDS()" function in the R package unmarked. Extant citizen-science data generally lack the information necessary to adjust for detection biases, but IDS models address this shortcoming, thus greatly extending the utility and reach of these data. In addition, they enable formal density estimation in hybrid designs, which efficiently combine DS with distance-free, point-based PC or DND surveys. We believe that IDS models have considerable scope in ecology, management, and monitoring.

A protocol for harvesting biodiversity data from Facebook.

The expanding use of community science platforms has led to an exponential increase in biodiversity data in global repositories. Yet, understanding of species distributions remains patchy. Biodiversity data from social media can potentially reduce the global biodiversity knowledge gap. However, practical guidelines and standardized methods for harvesting such data are nonexistent. Following data privacy and protection safeguards, we devised a standardized method for extracting species distribution records from Facebook groups that allow access to their data. It involves 3 steps: group selection, data extraction, and georeferencing the record location. We present how to structure keywords, search for species photographs, and georeference localities for such records. We further highlight some challenges users might face when extracting species distribution data from Facebook and suggest solutions. Following our proposed framework, we present a case study on Bangladesh's biodiversity-a tropical megadiverse South Asian country. We scraped nearly 45,000 unique georeferenced records across 967 species and found a median of 27 records per species. About 12% of the distribution data were for threatened species, representing 27% of all species. We also obtained data for 56 DataDeficient species for Bangladesh. If carefully harvested, social media data can significantly reduce global biodiversity knowledge gaps. Consequently, developing an automated tool to extract and interpret social media biodiversity data is a research priority.

Un protocolo para recolectar datos sobre biodiversidad en Facebook Resumen El uso creciente de plataformas de ciencia comunitaria ha causado un incremento exponencial de los datos sobre biodiversidad en los repositorios mundiales. Sin embargo, el conocimiento sobre la distribución de las especies todavía está incompleto. Los datos sobre biodiversidad obtenidos de las redes sociales tienen el potencial para disminuir el vacío de conocimiento sobre la biodiversidad mundial. No obstante, no existe una guía práctica o un método estandarizado para recolectar dichos datos. Seguimos los protocolos de privacidad y protección de datos para diseñar un método estandarizado para extraer registros de la distribución de especies de grupos en Facebook que permiten el acceso a sus datos. El método consta de tres pasos: selección del grupo, extracción de datos y georreferenciación de la localidad registrada. También planteamos cómo estructurar las palabras clave, buscar fotografías de especies y georreferenciar las localidades de dichos registros. Además, resaltamos algunos retos que los usuarios pueden enfrentar al extraer los datos de distribución de Facebook y sugerimos algunas soluciones. Aplicamos nuestro marco de trabajo propuesto a un estudio de caso de la biodiversidad en Bangladesh, un país tropical megadiverso en el sureste de Asia. Reunimos casi 45,000 registros georreferenciados únicos para 967 especies y encontramos una media de 27 registros por especie. Casi el 12% de los datos de distribución correspondió a especies amenazadas, que representaban el 27% de todas las especies. También obtuvimos datos para 56 especies deficientes de datos en Bangladesh. Si los datos de las redes sociales se recolectan con cuidado, éstos pueden reducir de forma significativa el vacío de conocimiento para la biodiversidad mundial. Como consecuencia, es una prioridad para la investigación el desarrollo de una herramienta automatizada para extraer e interpretar los datos sobre biodiversidad de las redes sociales.

A new, unusually large, Clavicornaltica Scherer, 1974 flea beetle from Borneo, described and sequenced in the field by citizen scientists (Coleoptera, Chrysomelidae, Galerucinae).

Background: The genus Clavicornaltica Scherer 1974 consists of very small, soil-dwelling flea beetles in South, Southeast and East Asia. Due to their diminutive size and morphological similarities, very little is known about their ecology and taxonomical diversity. It is likely that further studies will reveal this genus to be much more speciose than the 30 species currently recognised. New information: A new species of Clavicornaltica from Brunei Darussalam is described, C.mataikanensis Otani et al., sp. nov. This is the second species of this genus recorded from Ulu Temburong National Park.

Monitoring jellyfish outbreaks along Israel's Mediterranean coast using digital footprints.

With mounting global concerns about jellyfish outbreaks, monitoring their occurrence remains challenging. Tapping into the wealth of digital data that internet users share online, which includes reports of jellyfish sightings, may provide an alternative or complement to more conventional expert-based or citizen science monitoring. Here, we explore digital footprints as a data source to monitor jellyfish outbreaks along the Israeli Mediterranean coast. We compiled jellyfish sighting data for the period 2011-2022 from multiple platforms, including leading social media platforms, searches in the Google search engine, and Wikipedia page views. Employing time series analysis, cross-correlation, and various evaluation metrics for presence/absence data, we compared weekly data from three sources: digital footprints, citizen science, and traditional expert-based field monitoring. Consistent seasonal patterns emerge across datasets, with notable correlations, particularly in jellyfish abundance. The cross-correlation between digital footprint and citizen science data exceeds >0.7, with Twitter and Instagram showing the highest correlation. Citizen science data often precedes digital footprints by up to one week. Correlation with traditional, expert-based field monitoring is limited as a result of limited data availability. Digital footprints demonstrate substantial agreement with the other data sources regarding jellyfish presence/absence and major outbreaks, especially for data from Wikipedia, Twitter, and Instagram. Overall, we highlight digital footprint data as a reliable, cost-effective tool for passive monitoring of jellyfish outbreaks, which can aid characterization in data-scarce coastal regions, including retrospective assessment. Transferring and scaling up the proposed approach should consider data accessibility as well as platform relative popularity and usage in the regions under investigation.

Exploring the abundance and characteristics of litter in Lithuanian riversides: a citizen science approach.

To gain a better understanding of the sources and ecological effects of plastic contamination in Lithuanian rivers, as well as to provide guidance for mitigation, monitoring is necessary. This is a logistically and financially demanding endeavor, particularly in the case of microplastics. Citizen science provides a viable option for sampling sites that are accessible, thus enabling the monitoring of wide areas. In Lithuania, a citizen science approach was employed, with schoolchildren examining litter at riversides and identifying potential sources at 24 sampling sites in Autumn 2022 and 32 in Spring 2023, covering both large and small rivers. The maximum amount of 220 items per location was registered in Autumn 2022, whereas 111 items per location were registered in Spring 2023. The two main types of microlitter discovered were plastic (34-42%) and cigarette butts (17-22%), with glass, paper, and metal also present, which suggests that recreational visitors are the main source of litter. By K-means clustering analysis, all locations were divided into four clusters according to litter composition. To sum up, the findings of this study illustrate the importance of citizen science in providing insight into the contamination of Lithuanian rivers, which can be used to inform the development of conservation strategies.

An evolutionary innovation for mating facilitates ecological niche expansion and buffers species against climate change.

One of the drivers of life's diversification has been the emergence of "evolutionary innovations": The evolution of traits that grant access to underused ecological niches. Since ecological interactions can occur separately from mating, mating-related traits have not traditionally been considered factors in niche evolution. However, in order to persist in their environment, animals need to successfully mate just as much as they need to survive. Innovations that facilitate mating activity may therefore be an overlooked determinant of species' ecological limits. Here, we show that species' historical niches and responses to contemporary climate change are shaped by an innovation involved in mating-a waxy, ultra-violet-reflective pruinescence produced by male dragonflies. Physiological experiments in two species demonstrate that pruinescence reduces heating and water loss. Phylogenetic analyses show that pruinescence is gained after taxa begin adopting a thermohydrically stressful mating behavior. Further comparative analyses reveal that pruinose species are more likely to breed in exposed, open-canopy microhabitats. Biogeographic analyses uncover that pruinose species occupy warmer and drier regions in North America. Citizen-science observations of Pachydiplax longipennis suggest that the extent of pruinescence can be optimized to match the local conditions. Finally, temporal analyses indicate that pruinose species have been buffered against contemporary climate change. Overall, these historical and contemporary patterns show that successful mating can shape species' niche limits in the same way as growth and survival.