Leveraging citizen science for monitoring urban forageable plants
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PROVIDER: S-EPMC10914215 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
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Project description:This paper presents two key data sets derived from the Pomar Urbano project. The first data set is a comprehensive catalog of edible fruit-bearing plant species, native or introduced to Brazil. The second data set, sourced from the iNaturalist platform, tracks the distribution and monitoring of these plants within urban landscapes across Brazil. The study includes data from the capitals of all 27 federative units of Brazil, focusing on the ten cities that contributed the most observations as of August 2023. The research emphasizes the significance of citizen science in urban biodiversity monitoring and its potential to contribute to various fields, including food and nutrition, creative industry, study of plant phenology, and machine learning applications. We expect the data sets presented in this paper to serve as resources for further studies in urban foraging, food security, cultural ecosystem services, and environmental sustainability.
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Project description:PurposeWhile technology is a major driver of many of society's comforts, conveniences, and advances, it has been responsible, in a significant way, for engineering regular physical activity and a number of other positive health behaviors out of people's daily lives. A key question concerns how to harness information and communication technologies (ICT) to bring about positive changes in the health promotion field. One such approach involves community-engaged "citizen science," in which local residents leverage the potential of ICT to foster data-driven consensus-building and mobilization efforts that advance physical activity at the individual, social, built environment, and policy levels.MethodThe history of citizen science in the research arena is briefly described and an evidence-based method that embeds citizen science in a multi-level, multi-sectoral community-based participatory research framework for physical activity promotion is presented.ResultsSeveral examples of this citizen science-driven community engagement framework for promoting active lifestyles, called "Our Voice", are discussed, including pilot projects from diverse communities in the U.S. as well as internationally.ConclusionsThe opportunities and challenges involved in leveraging citizen science activities as part of a broader population approach to promoting regular physical activity are explored. The strategic engagement of citizen scientists from socio-demographically diverse communities across the globe as both assessment as well as change agents provides a promising, potentially low-cost and scalable strategy for creating more active, healthful, and equitable neighborhoods and communities worldwide.
| S-EPMC4978140 | biostudies-literature
Project description:Machine learning (ML) and citizen science (CS) are increasingly prevalent and rapidly evolving approaches to studying and managing environmental challenges. Municipal and other governance actors can benefit from technology advances in ML and public engagement benefits of CS but must also address validity and other quality assurance concerns in their application to particular management contexts. In this article, we take up the pervasive challenge of urban litter to demonstrate how ML can support CS by providing quality assurance in the regulatory context of California's stormwater program. We gave quantitative CS-collected data to five ML models to compare their predictions of a qualitative, site-specific, multiclass "Litter Index" score, an important regulatory metric typically only assessed by trained experts. XGBoost had the best outcome, with scores of 0.98 for accuracy, precision, recall and F-1. These strong results show that ML can provide a reliable complement to CS assessments and increase quality assurance in a regulatory context. To date, ML and CS have each contributed to litter management in novel ways and we find that their integration can provide important synergies with additional applications in other environmental management domains.
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Project description:ObjectiveThis systematic review aims to analyze current capabilities, challenges, and impact of self-directed mobile health (mHealth) research applications such as those based on the ResearchKit platform.Materials and methodsA systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. English publications were included if: 1) mobile applications were used in the context of large-scale collection of data for biomedical research, and not as medical or behavioral intervention of any kind, and 2) all activities related to participating in research and data collection methods were executed remotely without any face-to-face interaction between researchers and study participants.ResultsThirty-six unique ResearchKit apps were identified. The majority of the apps were used to conduct observational studies on general citizens and generate large datasets for secondary research. Nearly half of the apps were focused on chronic conditions in adults.DiscussionThe ability to generate large biomedical datasets on diverse populations that can be broadly shared and re-used was identified as a promising feature of mHealth research apps. Common challenges were low participation retention, uncertainty regarding how use patterns influence data quality, need for data validation, and privacy concerns.ConclusionResearchKit and other mHealth-based studies are well positioned to enhance development and validation of novel digital biomarkers as well as generate new biomedical knowledge through retrospective studies. However, in order to capitalize on these benefits, mHealth research studies must strive to improve retention rates, implement rigorous data validation strategies, and address emerging privacy and security challenges.
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Project description:Citizen science approaches are of great interest for their potential to efficiently and sustainably monitor wildlife populations on both public and private lands. Here we present two studies that worked with volunteers to set camera traps for ecological surveys. The photographs recorded by these citizen scientists were archived and verified using the eMammal software platform, providing a professional grade, vouchered database of biodiversity records. Motivated by managers' concern with perceived high bear activity, our first example enlisted the help of homeowners in a short-term study to compare black bear activity inside a National Historic Site with surrounding private land. We found similar levels of bear activity inside and outside the NHS, and regional comparisons suggest the bear population is typical. Participants benefited from knowing their local bear population was normal and managers refocused bear management given this new information. Our second example is a continuous survey of wildlife using the grounds of a nature education center that actively manages habitat to maintain a grassland prairie. Center staff incorporated the camera traps into educational programs, involving visitors with camera setup and picture review. Over two years and 5,968 camera-nights this survey has collected 41,393 detections of 14 wildlife species. Detection rates and occupancy were higher in open habitats compared to forest, suggesting that the maintenance of prairie habitat is beneficial to some species. Over 500 volunteers of all ages participated in this project over two years. Some of the greatest benefits have been to high school students, exemplified by a student with autism who increased his communication and comfort level with others through field work with the cameras. These examples show how, with the right tools, training and survey design protocols, citizen science can be used to answer a variety of applied management questions while connecting participants with their secretive mammal neighbors.
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Project description:Citizen science (CS), as an enabler of open science (OS) practices, is a low-cost and accessible method for data collection in biodiversity monitoring, which can empower and educate the public both on scientific research priorities and on environmental change. Where OS increases research transparency and scientific democratisation; if properly implemented, CS should do the same. Here, we present the findings of a systematic review exploring "openness" of CS in biodiversity monitoring. CS projects were scored between - 1 (closed) and 1 (open) on their adherence to defined OS principles: accessible data, code, software, publication, data management plans, and preregistrations. Openness scores per principle were compared to see where OS is more frequently utilised across the research process. The relationship between interest in CS and openness within the practice was also tested. Overall, CS projects had an average open score of 0.14. There was a significant difference in open scores between OS principles (p = < 0.0001), where "open data" was the most adhered to practice compared to the lowest scores found in relation to preregistrations. The apparent level of interest in CS was not shown to correspond to a significant increase in openness within CS (p = 0.8464). These results reveal CS is not generally "open" despite being an OS approach, with implications for how the public can interact with the research that they play an active role in contributing to. The development of systematic recommendations on where and how OS can be implemented across the research process in citizen science projects is encouraged.
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Project description:Over the past decade, several citizen science projects have been launched, with a smaller subset addressing citizen scientists' involvement in water quality monitoring. Most of these projects were conducted in developed countries and focused on qualitative assessment and measurements of a limited number of water quality parameters. Moreover, data generated by citizen scientists were mainly for monitoring purposes and rarely resulted in remedial measures. In this work, a collaborative citizen science approach involving local citizens and university researchers was applied to assess the groundwater quality in a Lebanese village. Using a mobile laboratory, winter and summer sampling campaigns were conducted and 12 physical, chemical and biological water quality parameters were tested. Results indicated that the data generated by the citizen scientists were comparable with those generated by university researchers for the majority of physical and chemical water quality parameters. However, the bacteriological test results showed a marked difference and may be attributed to the complexity of the testing procedure and quality of testing material. The collaborative and participatory approach resulted in building local capacity and knowledge and in the formation of a locally elected water committee which will be responsible for continuous monitoring of the groundwater resources.
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Project description:Tourism is of growing economical importance to many nations, in particular for developing countries. Although tourism is an important economic vehicle for the host country, its continued growth has led to on-going concerns about its environmental sustainability. Coastal and marine tourism can directly affect the environment through direct and indirect tourist activities. For these reasons tourism sector needs practical actions of sustainability. Several studies have shown how education minimizes the impact on and is proactive for, preserving the natural resources. This paper evaluates the effectiveness of a citizen science program to improve the environmental education of the volunteers, by means of questionnaires provided to participants to a volunteer-based Red Sea coral reef monitoring program (STEproject). Fifteen multiple-choice questions evaluated the level of knowledge on the basic coral reef biology and ecology and the awareness on the impact of human behaviour on the environment. Volunteers filled in questionnaires twice, once at the beginning, before being involved in the project and again at the end of their stay, after several days participation in the program. We found that the participation in STEproject significantly increased both the knowledge of coral reef biology and ecology and the awareness of human behavioural impacts on the environment, but was more effective on the former. We also detected that tourists with a higher education level have a higher initial level of environmental education than less educated people and that the project was more effective on divers than snorkelers. This study has emphasized that citizen science projects have an important and effective educational value and has suggested that tourism and diving stakeholders should increase their commitment and efforts to these programs.
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Project description:The use of citizen science in the collection of surface water marine microplastics (MP) samples with manta trawl was tested in the Baltic Sea, where the collection of surface water samples is often hampered by environmental conditions. Sampling was carried out at 7 locations around the Baltic Sea with a custom-made manta trawl which was operated onboard a sailing boat. The total concentrations of ≥ 0.3 mm MP in the samples ranged from 0.45 to 1.98 MP m-3. Based on the results and experiences from this study, citizen science could be introduced into the toolbox of monitoring large MP. When the common basic constraints of surface water sampling within a regional sea are defined and agreed upon, citizen science could be used for strengthening the power of assessments on the state of the marine environment by increasing the spatial coverage of the monitored area.
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Project description:The skyglow produced by artificial lights at night is one of the most dramatic anthropogenic modifications of Earth's biosphere. The GLOBE at Night citizen science project allows individual observers to quantify skyglow using star maps showing different levels of light pollution. We show that aggregated GLOBE at Night data depend strongly on artificial skyglow, and could be used to track lighting changes worldwide. Naked eye time series can be expected to be very stable, due to the slow pace of human eye evolution. The standard deviation of an individual GLOBE at Night observation is found to be 1.2 stellar magnitudes. Zenith skyglow estimates from the "First World Atlas of Artificial Night Sky Brightness" are tested using a subset of the GLOBE at Night data. Although we find the World Atlas overestimates sky brightness in the very center of large cities, its predictions for Milky Way visibility are accurate.
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