Citizen science initiatives document biodiversity baselines at an urban lake.

Changes to biodiversity from urbanization are occurring worldwide, and baseline data is vital to document the magnitude and direction of these alterations. We set out to document the biodiversity of an urban lake in Eastern Iowa that was devoid of baseline data prior to a renovation project that will convert the site into a major area for human recreation. Throughout the course of one year, we studied the biodiversity at Cedar Lake utilizing the citizen-science application iNaturalist coupled with semi-structured BioBlitz events, which we compared to previous opportunistic observations at the site. From a semi-structured approach to document biodiversity with citizen science, our analyses revealed more diverse community metrics over a shorter period compared to more than a decade of prior observations.

Building citizen science intelligence for outbreak preparedness and response: a mixed-method study in nine countries to assess knowledge, readiness and feasibility.

INTRODUCTION: Citizen science (CS) is an emerging approach in public health to harness the collective intelligence of individuals to augment traditional scientific efforts. However, citizens' viewpoint, especially the hard-to-reach population, is lacking in current outbreak-related literature. We aim to understand the awareness, readiness and feasibility of outbreak-related CS, including digitally enabled CS, in low-income and middle-income countries. METHODS: This mixed-method study was conducted in nine countries between October 2022 and June 2023. Recruitment through civil society targeted the general population, marginalised/indigenous groups, youth and community health workers. Participants (aged ≥18 years) completed a quantitative survey, and a subset participated in focus group discussions (FGDs). RESULTS: 2912 participants completed the survey and 4 FGDs were conducted in each country. Incorporating participants' perspectives, CS is defined as the practice of active public participation, collaboration and communication in all aspects of scientific research to increase public knowledge, create awareness, build trust and facilitate information flow between citizens, governments and scientists. In Bangladesh, Indonesia, the Philippines, Cameroon and Kenya, majority were unaware of outbreak-related CS. In India and Uganda, majority were aware but unengaged, while in Nepal and Zimbabwe, majority participated in CS before. Engagement approaches should consider different social and cultural contexts, while addressing incentivisation, attitudes and practicality factors. Overall, 76.0% expressed interest in digital CS but needed training to build skills and confidence. Digital CS was perceived as convenient, safer for outbreak-related activities and producing better quality and quantity of data. However, there were concerns over non-inclusion of certain groups, data security and unclear communication. CONCLUSION: CS interventions need to be relatable and address context-specific factors influencing CS participation. Digital CS has the potential to facilitate collaboration, but capacity and access issues must be considered to ensure inclusive and sustainable engagement.

Beached plastic and other anthropogenic debris in the inner Seychelles islands: Results of a citizen science approach.

Masses of plastic and other anthropogenic debris on beaches of inner Seychelles and derived from 53 organised clean-ups have been analysed. Debris and plastic densities ranged from 0.0011 to 0.1622 kg m-2 and 0.0004 to 0.1179 kg m-2, respectively, and data from successive cleans of the same beach resulted in respective median accumulation rates of 0.0293 and 0.0137 g m-2 d-1. There was no dependence of density or accumulation on beach location/aspect or season, but there were significant inverse relationships with beach area. This effect was attributed to most debris and plastic being trapped on the backshore by rocks and vegetation, and the areal proportion of backshore increasing with decreasing beach size. Plastic is derived from local littering and more distal sources, with polyethylene terephthalate bottles, flip-flops and Styrofoam fragments making important contributions. Without intervention and an increased risk of coastal flooding with climate change, beached debris on Seychelles is predicted to increase.

Decoupling of bird migration from the changing phenology of spring green-up.

The green-up of vegetation in spring brings a pulse of food resources that many animals track during migration. However, green-up phenology is changing with climate change, posing an immense challenge for species that time their migrations to coincide with these resource pulses. We evaluated changes in green-up phenology from 2002 to 2021 in relation to the migrations of 150 Western-Hemisphere bird species using eBird citizen science data. We found that green-up phenology has changed within bird migration routes, and yet the migrations of most species align more closely with long-term averages of green-up than with current conditions. Changing green-up strongly influenced phenological mismatches, especially for longer-distance migrants. These results reveal that bird migration may have limited flexibility to adjust to changing vegetation phenology and emphasize the mounting challenge migratory animals face in following en route resources in a changing climate.

Leveraging citizen science for monitoring urban forageable plants.

Urbanization brings forth social challenges in emerging countries such as Brazil, encompassing food scarcity, health deterioration, air pollution, and biodiversity loss. Despite this, urban areas like the city of São Paulo still boast ample green spaces, offering opportunities for nature appreciation and conservation, enhancing city resilience and livability. Citizen science is a collaborative endeavor between professional scientists and nonprofessional scientists in scientific research that may help to understand the dynamics of urban ecosystems. We believe citizen science has the potential to promote human and nature connection in urban areas and provide useful data on urban biodiversity.

Citizen science and social innovation as citizen empowerment tools to address urban health challenges: The case of the urban health citizen laboratory in Barcelona, Spain.

Urban health faces significant challenges due to the rapid growth of cities and the concentration of population in urban settings that have a strong impact on people's health. The approach to characterize and address these challenges requires increased societal involvement and interdisciplinary solutions to ensure their effectiveness and democratic nature. With this purpose, it is necessary to explore methodologies for citizen participation that foster a critical understanding of the environment and promote their active role in generating scientific knowledge and change. This article describes the creation of a collaborative space for experimentation and learning that, through the intersection of citizen science and social innovation, aims to engage citizens in the research and diagnosis of their local environment, as well as in the design and implementation of local solutions, while raising awareness about the main challenges to urban health. Through a collaborative and participatory framework, the community identified relevant challenges to urban health they wanted to investigate, co-designed and developed the methodology for data collection and analysis, and ultimately, they devised, designed, and implemented innovative solutions based on the scientific evidence obtained. The framework and results of this project hold potential interest for the scientific community, facilities, institutions, and society by offering an innovative and participatory approach to addressing the present and future urban health challenges.

Evaluating the potential of bioacoustics in avian migration research by citizen science and weather radar observations.

The study of nocturnal bird migration brings observational challenges because of reduced visibility and observability of birds at night. Remote sensing tools, especially radars, have long been the preferred choice of scientists to study nocturnal migrations. A major downside of these remote sensing tools is the lack of species-level information. With technological advances in recent decades and with improved accessibility and affordability of acoustic tools, sound recordings have steeply increased in popularity. In Europe, there is no exhaustive qualitative and quantitative evaluation of the content of such acoustic databases and therefore the value for migration science and migration-related applications, such as bird collision hazard assessments, is mostly unknown. In the present work we compared migration schedules estimated from citizen science data with quantitative temporal occurrence of species in four years of acoustic recordings. Furthermore, we contrasted acoustic recordings with citizen science observations and weather radar data from one spring and one autumn season to assess the qualitative and quantitative yield of acoustic recordings for migration-related research and applications. Migration intensity estimated from weather radar data correlated best at low levels with acoustic records including all species in spring while in autumn passerine species showed stronger correlation than the entire species composition. Our findings identify a minor number of species whose call records may be eligible for applications derived from acoustics. Especially the highly vocal species Song thrush and Redwing showed relatively good correlations with radar and citizen science migration schedules. Most long-distance passerine migrants and many other migrants were not captured by acoustics and an estimated seasonal average of about 50% of nocturnally migrating passerine populations remained undetected. Overall, the ability of acoustic records to act as a proxy of overall migration dynamics is highly dependent on the migration period and species involved.

Citizen science shows that small agricultural streams in Germany are in a poor ecological status.

Agricultural pesticides, nutrients, and habitat degradation are major causes of insect declines in lowland streams. To effectively conserve and restore stream habitats, standardized stream monitoring data and societal support for freshwater protection are needed. Here, we sampled 137 small stream monitoring sites across Germany, 83 % of which were located in agricultural catchments, with >900 citizen scientists in 96 monitoring groups. Sampling was carried out according to Water Framework Directive standards as part of the citizen science freshwater monitoring program FLOW in spring and summer 2021, 2022 and 2023. The biological indicator SPEARpesticides was used to assess pesticide exposure and effects based on macroinvertebrate community composition. Overall, 58 % of the agricultural monitoring sites failed to achieve a good ecological status in terms of macroinvertebrate community composition and indicated high pesticide exposure (SPEARpesticides status class: 29 % "moderate", 19 % "poor", 11 % "bad"). The indicated pesticide pressure in streams was related to the proportion of arable land in the catchment areas (R2 = 0.23, p < 0.001). Also with regards to hydromorphology, monitoring results revealed that 65 % of the agricultural monitoring sites failed to reach a good status. The database produced by citizen science groups was characterized by a high degree of accuracy, as results obtained by citizen scientists and professionals were highly correlated for SPEARpesticides index (R2 = 0.79, p < 0.001) and hydromorphology index values (R2 = 0.72, p < 0.001). Such citizen-driven monitoring of the status of watercourses could play a crucial role in monitoring and implementing the objectives of the European Water Framework Directive, thus contributing to restoring and protecting freshwater ecosystems.

Citizen neuroscience: Wearable technology and open software to study the human brain in its natural habitat.

Citizen science allows the public to participate in various stages of scientific research, including study design, data acquisition, and data analysis. Citizen science has a long history in several fields of the natural sciences, and with recent developments in wearable technology, neuroscience has also become more accessible to citizen scientists. This development was largely driven by the influx of minimal sensing systems in the consumer market, allowing more do-it-yourself (DIY) and quantified-self (QS) investigations of the human brain. While most subfields of neuroscience require sophisticated monitoring devices and laboratories, the study of sleep characteristics can be performed at home with relevant noninvasive consumer devices. The strong influence of sleep quality on waking life and the accessibility of devices to measure sleep are two primary reasons citizen scientists have widely embraced sleep research. Their involvement has evolved from solely contributing to data collection to engaging in more collaborative or autonomous approaches, such as instigating ideas, formulating research inquiries, designing research protocols and methodology, acting upon their findings, and disseminating results. In this article, we introduce the emerging field of citizen neuroscience, illustrating examples of such projects in sleep research. We then provide overviews of the wearable technologies for tracking human neurophysiology and various open-source software used to analyse them. Finally, we discuss the opportunities and challenges in citizen neuroscience projects and suggest how to improve the study of the human brain outside the laboratory.

Factors associated with anxiety during the first two years of the COVID-19 pandemic in the United States: An analysis of the COVID-19 Citizen Science study.

COVID-19 increased the prevalence of clinically significant anxiety in the United States. To investigate contributing factors we analyzed anxiety, reported online via monthly Generalized Anxiety Disorders-7 (GAD-7) surveys between April 2020 and May 2022, in association with self-reported worry about the health effects of COVID-19, economic difficulty, personal COVID-19 experience, and subjective social status. 333,292 anxiety surveys from 50,172 participants (82% non-Hispanic white; 73% female; median age 55, IQR 42-66) showed high levels of anxiety, especially early in the pandemic. Anxiety scores showed strong independent associations with worry about the health effects of COVID-19 for oneself or family members (GAD-7 score +3.28 for highest vs. lowest category; 95% confidence interval: 3.24, 3.33; p<0.0001 for trend) and with difficulty paying for basic living expenses (+2.06; 1.97, 2.15, p<0.0001) in multivariable regression models after adjusting for demographic characteristics, COVID-19 case rates and death rates, and personal COVID-19 experience. High levels of COVID-19 health worry and economic stress were each more common among participants reporting lower subjective social status, and median anxiety scores for those experiencing both were in the range considered indicative of moderate to severe clinical anxiety disorders. In summary, health worry and economic difficulty both contributed to high rates of anxiety during the first two years of the COVID-19 pandemic in the US, especially in disadvantaged socioeconomic groups. Programs to address both health concerns and economic insecurity in vulnerable populations could help mitigate pandemic impacts on anxiety and mental health.

Citizen science approach to assessing patient perception of MRI with flexible radiofrequency coils.

Magnetic Resonance Imaging (MRI) is a major medical imaging modality, which is non-invasive and provides unique soft tissue contrast without ionizing radiation. The successful completion of MRI exams critically depends on patient compliance, and, thus patient comfort. The design, appearance and usability of local MRI radiofrequency (RF) coils potentially influences the patients' perception of the exam. However, systematic investigations and empirical evidence for these aspects are missing. A questionnaire specifically evaluating the impact of RF coils on patient comfort in MRI would be a valuable addition to clinical studies comparing the performance of novel flexible RF coils with standard rigid coils. This paper describes the development of such a questionnaire in the scope of a citizen science (CS) initiative conducted with a group of students at the upper secondary school level. In this work, the CS initiative is presented in the format of a case report and its impact on scientific projects and the students' education is outlined. The resulting questionnaire is made available in German and English so as to be directly applicable by researchers working on the clinical evaluation of novel RF coils or the comfort evaluation of specific hardware setups in general.

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.

Citizen science through a recreational underwater diving project supports the collection of large-scale marine litter data: The Oceania case study.

In recent years, a growing body of literature on seafloor macro-litter has been produced worldwide. However, the spatial coverage of these studies is still limited and highly unbalanced, resulting in considerable knowledge gaps in some regions. To address this lack of information in Oceania, we extracted data from the Citizen Science project Dive Against Debris® to characterize marine debris collected by volunteer scuba divers on the coastal seafloor. Overall, the average litter density was 58.22 items/100m2, with plastics accounting for approximately 50 % of the total abundance and Single Use Plastics accounting for nearly 17 %. Notably, 36 % of the total litter abundance consisted of lost Fishing Gear including fishing lines, sinkers, baits and hooks as the most abundant debris items. To reduce lost fishing gear, clean-up initiatives by divers along with management actions such as education programs for fishermen, gear restrictions and the identification of designated fishing sites are recommended.

Large-scale citizen science reveals predictors of sensorimotor adaptation.

Sensorimotor adaptation is essential for keeping our movements well calibrated in response to changes in the body and environment. For over a century, researchers have studied sensorimotor adaptation in laboratory settings that typically involve small sample sizes. While this approach has proved useful for characterizing different learning processes, laboratory studies are not well suited for exploring the myriad of factors that may modulate human performance. Here, using a citizen science website, we collected over 2,000 sessions of data on a visuomotor rotation task. This unique dataset has allowed us to replicate, reconcile and challenge classic findings in the learning and memory literature, as well as discover unappreciated demographic constraints associated with implicit and explicit processes that support sensorimotor adaptation. More generally, this study exemplifies how a large-scale exploratory approach can complement traditional hypothesis-driven laboratory research in advancing sensorimotor neuroscience.

Internet of Things and citizen science as alternative water quality monitoring approaches and the importance of effective water quality communication.

The increasing demand for water and worsening climate change place significant pressure on this vital resource, making its preservation a global priority. Water quality monitoring programs are essential for effectively managing this resource. Current programs rely on traditional monitoring approaches, leading to limitations such as low spatiotemporal resolution and high operational costs. Despite the adoption of novel monitoring approaches that enable better data resolution, the public's comprehension of water quality matters remains low, primarily due to communication process deficiencies. This study explores the advantages and challenges of using Internet of Things (IoT) and citizen science as alternative monitoring approaches, emphasizing the need for enhancing public communication of water quality data. Through a systematic review of studies implemented on-field, we identify and propose strategies to address five key challenges that IoT and citizen science monitoring approaches must overcome to mature into robust sources of water quality information. Additionally, we highlight three fundamental problems affecting the water quality communication process and outline strategies to convey this topic effectively to the public.

Rare Diseases in Citizen Science - Preliminary Experiences in Developing a Personal Health App.

SelEe is a German citizen science project aiming to develop a smartphone app for a patient-managed record. The goal is to study rare diseases with the support of interested citizens and people affected by rare diseases. We established a core research team, including professional researchers (leading the project) and citizens. Citizens have the opportunity to discuss the progress, make suggestions regarding the app's design and data entry and contribute to the dissemination of the project. To gather feedback and experiences from the core research team, we performed an online questionnaire regarding the topics "influence and communication", "improvements and learning effect", and "satisfaction". Finally, 9 citizens of the core research team participated. The results show that the citizens are very satisfied with the design of the app, their participation opportunities and the communication in the project.

Data error propagation in stacked bioclimatic envelope models.

Stacking is the process of overlaying inferred species potential distributions for multiple species based on outputs of bioclimatic envelope models (BEMs). The approach can be used to investigate patterns and processes of species richness. If data limitations on individual species distributions are inevitable, but how do they affect inferences of patterns and processes of species richness? We investigate the influence of different data sources on estimated species richness gradients in China. We fitted BEMs using species distributions data for 334 bird species obtained from (1) global range maps, (2) regional checklists, (3) museum records and surveys, and (4) citizen science data using presence-only (Mahalanobis distance), presence-background (MAXENT), and presence-absence (GAM and BRT) BEMs. Individual species predictions were stacked to generate species richness gradients. Here, we show that different data sources and BEMs can generate spatially varying gradients of species richness. The environmental predictors that best explained species distributions also differed between data sources. Models using citizen-based data had the highest accuracy, whereas those using range data had the lowest accuracy. Potential richness patterns estimated by GAM and BRT models were robust to data uncertainty. When multiple data sets exist for the same region and taxa, we advise that explicit treatments of uncertainty, such as sensitivity analyses of the input data, should be conducted during the process of modeling.