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444 results for “Citizen Science”
Bird strikes at commercial airports explained by citizen science and weather radar data
<p>1. Aircraft collisions with birds span the entire history of human aviation, including fatal collisions during some of the first powered human flights. Much effort has been expended to reduce such collisions, but increased knowledge about bird movements and species occurrence could dramatically improve decision support and proactive measures to reduce them. Migratory movements of birds pose a unique, often overlooked, threat to aviation that is particularly difficult for individual airports to monitor and predict: the occurrence of birds vary extensively in space and time at the local scales of airport responses.</p> <p>2. We use two publicly available datasets, radar data from the US NEXRAD network characterizing migration movements and eBird data collected by citizen scientists to map bird movements and species composition with low human effort expenditures but high temporal and spatial resolution relative to other large scale bird survey methods. As a test case we compare these results from weather radar distributions and eBird species composition with detailed bird strike records from three major New York airports.</p> <p>3. We show that weather radar based estimates of migration intensity can accurately predict probability of bird strikes, with 80% of the variation in bird strikes across the year explained by the average amount of migratory movements captured on weather radar. We also show that eBird based estimates of species occurrence can, using species' body mass and flocking propensity, accurately predict when most damaging strikes occur.</p> <p>4. Synthesis and applications: Our results highlight the power of federating datasets with movement and distribution data for developing better and more taxonomically and ecologically tuned models of likelihood of strikes occurring and severity of strikes. By better understanding when, and where, different species occur, airports across the world can predict seasonal periods of collision risks with greater temporal and spatial resolution; such predictions include potential to predict when the most severe and damaging strikes may occur.</p>
Cannot see the diversity for all the species: evaluating inclusion criteria for local species lists when using abundant citizen science data
Abundant citizen science data on species occurrences is becoming increasingly available and enables identifying composition of communities occurring at multiple sites with high temporal resolution. However, for species displaying temporary patterns of local occurrences, i.e. that are transient to some sites, biodiversity measures are clearly dependent on the criteria used to include species into local species lists. Using abundant opportunistic citizen science data from frequently visited wetlands we investigated the sensitivity of α- and β-diversity estimates to the use raw vs. detection-corrected data and to the use of inclusion criteria for species presence reflecting alternative site use. We tested 7 inclusion criteria (with varying number of days required to be present) on time series of daily occurrence status during a breeding season of 90 days for 77 wetland bird species. We show that even when opportunistic presence-only observation data is abundant, raw data may not produce reliable local species richness estimates and rank sites very differently in terms of species richness. Furthermore, occupancy model based - and - diversity estimates were sensitive to the inclusion criteria used. Total species lists (all species observed at least once during a season) may therefore mask diversity differences among sites in local communities of species, by e.g. including vagrant species on potentially breeding communities and change the relative rank order of sites in terms of species richness. Very high sampling effort does not necessarily free opportunistic data from its inherent bias and can produce a pattern in which many species are observed at least once almost everywhere, thus leading to a possible paradox: the large amount of biological information may hinder its usefulness. Therefore, when prioritizing among sites to manage or preserve species diversity estimates need to be carefully related to relevant inclusion criteria depending on the diversity estimate in focus.
Adopt a Pixel 3 km: A Multiscale Data Set Linking Remotely Sensed Land Cover Imagery with Field Based Citizen Science Observation
<p>These datasets were used in an article submitted to the journal Frontiers in Climate in 2021: <a href="https://www.frontiersin.org/articles/10.3389/fclim.2021.658063/full">https://www.frontiersin.org/articles/10.3389/fclim.2021.658063/full</a></p> <p>Further supplemental links (including general information about GLOBE data) can be accessed at <a href="https://observer.globe.gov/get-data/mosquito-habitat-data">https://observer.globe.gov/get-data/mosquito-habitat-data</a>.</p>
FIGURE 2 in Insecta non gratae: New Distribution Records of Eight Alien Bug (Hemiptera) Species in Turkey with Contributions of Citizen Science
FIGURE 2. Corythucha arcuata (Say, 1832): A. Male specimen on an oak (Quercus sp.) leaf from İstanbul, B. Nymphs on an oak (Quercus sp.) leaf from the same locality.
FIGURE 1. Zelus renardii Kolenati, 1856 in Insecta non gratae: New Distribution Records of Eight Alien Bug (Hemiptera) Species in Turkey with Contributions of Citizen Science
FIGURE 1. Zelus renardii Kolenati, 1856: A. Adult male from İstanbul, B. Mating specimens from İzmir, C. Nymphe from İzmir. D. Egg pile from İstanbul.
Workshop recording: Towards Implementation of the UNESCO Recommendation on Open Science – How to integrate citizen science into (open) science policy
<p>Recording of the workshop: Towards Implementation of the UNESCO Recommendation on Open Science – How to integrate citizen science into (open) science policy. If you have any questions or comments, please contact the workshop organisers Uta Wehn (<a href="mailto:u.wehn@un-ihe.org">u.wehn@un-ihe.org</a>) and Libby Hepburn (<a href="mailto:libby@atlasoflife.org.au">libby@atlasoflife.org.au</a>).</p>
Video related to the study "Spatial variability of Saharan dust deposition revealed through a citizen science campaign"
<p>This video is related to the manuscript "Spatial variability of Saharan dust deposition revealed through a citizen science campaign", by Dumont et al., submitted in December 2022 to the journal "Earth System Science Data".</p> <p>It illustrates the timeline of dust deposition, simulated by the atmospheric transport model MOCAGE.</p> <p> </p>
Survey dataset - Environmental Citizen Science: practices and scientists' attitudes at ILTER
<p>The dataset contains survey outcomes from ILTER scientists about their attitudes and actions with regard to Environmental Citizen Science.</p>
FIG. 2 in The Utility of Acoustic Citizen Science Data in Understanding Geographic Distributions of Morphologically Conserved Species: Frogs in the Litoria phyllochroa Species Group
FIG. 2. Map of eastern Australia including the states of Queensland (QLD), New South Wales (NSW), Australian Capital Territory (ACT), and Victoria (VIC) showing the mapped ranges of known extant species in the Litoria phyllochroa group as informed by data from FrogID and the Atlas of Living Australia, including areas where species' ranges may overlap.
FIG. 1 in The Utility of Acoustic Citizen Science Data in Understanding Geographic Distributions of Morphologically Conserved Species: Frogs in the Litoria phyllochroa Species Group
FIG. 1. Map of eastern Australia including the states of Queensland (QLD), New South Wales (NSW), Australian Capital Territory (ACT), and Victoria (VIC) showing records of known extant species of the Litoria phyllochroa group from the Atlas of Living Australia (ALA; A), FrogID (B), and a combined dataset containing both FrogID records and those deemed spatially and taxonomically reliable from ALA (C).
Supplementary material 2 from: Colombari F, Battisti A (2023) Citizen science at school increases awareness of biological invasions and contributes to the detection of exotic ambrosia beetles. In: Jactel H, Orazio C, Robinet C, Douma JC, Santini A, Battisti A, Branco M, Seehausen L, Kenis M (Eds) Conceptual and technical innovations to better manage invasions of alien pests and pathogens in forests. NeoBiota 84: 211-229. https://doi.org/10.3897/neobiota.84.95177
Slides of the lecture on 'Monitoring of insect species harmful to trees and forests' and link to educational videos
An annotated list of horizon scanned technologies with potential for application in alien species citizen science projects
<p><strong>Context</strong></p> <p>The contribution of volunteers in recording invasive alien species (IAS) has been fostered by technological developments such as social media, apps, low-cost sensors, search engines and predictive analytics. These technology developments, an increased attention to citizen science and a cultural change towards collaboration and openness in research within the policy agenda should increase the contribution of volunteer recording. Within the framework of the COST Action CA17122 <a href="https://www.ceh.ac.uk/our-science/projects/alien-csi"><em>Increasing Understanding of Alien Species through Citizen Science</em></a> (<a href="https://doi.org/10.3897/rio.4.e31412">Roy et al. 2018</a>) a group of researchers explored the value of emerging technologies for citizen science in the context of alien species, recognizing the contribution of volunteers and reviewing their potential to engage broad audiences, motivate volunteers, improve data collection, increase data quality etc.</p> <p><strong>Survey</strong></p> <p>The following criteria were then used to evaluate the potential of these technologies for alien species citizen science through a dedicated <a href="https://forms.gle/9GQJctnAbPLKyxDE7">survey</a>:</p> <p>● <em><strong>Audience</strong></em>: the technology can attract new target audiences for IAS citizen science and/or support more inclusivity in IAS citizen science (can overcome inequalities in participation, attract under-privileged audiences/those underrepresented in the scientific enterprise, allow participation of sensory/cognitive/otherwise impaired...)<br> ● <em><strong>Engagement </strong></em>with others: the technology supports better connections with other participants, helpful in building a community<br> ● <em><strong>Engagement via feedback</strong></em>: the technology increases the quality, amount or rate of feedback (including supporting learning) to participants<br> ● <strong><em>Application</em></strong>: the technology can be embedded in everyday life and therefore has the potential for wide, generic application</p> <p>● <em><strong>New data</strong></em>: the technology yields new types of data that would not be available without the technology (improved the detectability of IAS, new types of data, species interactions, new information sources)<br> ● <strong><em>Extends data</em></strong>: the technology expands the scope of data collection or analysis (e.g. better coverage spatially, temporally)<br> ● <strong><em>Improves data quality</em></strong>: the technology improves species ID, reduces uncertainty, improves validation<br> ● <strong><em>Improves the flow of data</em></strong>: the technology increases the speed of record transmission (e.g. for early warning)<br> ● <strong><em>Improves the curation of data</em></strong>: the technology itself allows for improved data curation (better metadata, sustainability and long term preservation data, open data, tracked provenance of data, FAIR data management, enable to better credit citizen scientists for their data contributions)</p> <p><strong>Dataset description</strong></p> <p>This dataset represents the list of technologies (in the broadest sense, including approaches) that were identified collectively by the experts as being relevant technologies in the framework of (alien species) citizen science. The dataset includes the following fields:</p> <ul> <li><em>Name</em>: name of the approach/technology</li> <li><em>Category</em>: broad categorisation of the approach/technology (Hardware and infrastructure, data collection and analysis tools, tools to improve user experience). If some approaches are combinations this is mentioned in description.</li> <li><em>Description</em>: a definition and/or description of the approach/technology</li> <li><em>Reference</em>: a reference on the approach/technology (e.g. paper, online reference), mostly with a doi</li> <li><em>Example</em>: an example of the approach/technology, mostly with reference to an (alien species) citizen science project that applied it</li> <li><em>Notes: </em>any further remarks</li> </ul>
Dataset related to the study "Spatial variability of Saharan dust deposition revealed through a citizen science campaign"
<p>This dataset contains the data and the measurements related to the manuscript "Spatial variability of Saharan dust deposition revealed through a citizen science campaign", by Dumont et al., submitted in December 2022 to the journal "Earth System Science Data".</p> <p> </p>
FIGURES 11–16 in An annotated checklist of terrestrial flatworms (Platyhelminthes: Tricladida: Geoplanidae) from Mexico, with new records of invasive species from a citizen science platform and a new nomen dubium
FIGURES 11–16. Illustrations of invasive species of Caenoplanini found in Mexico: dorsal (11) and ventral (12) aspect of Caenoplana coerulea; dorsal (13) and ventral (14) aspect of Endeavouria septemlineata; dorsal (15) and ventral (16) aspect of Parakontikia ventrolineata.
FIGURES 5–6 in An annotated checklist of terrestrial flatworms (Platyhelminthes: Tricladida: Geoplanidae) from Mexico, with new records of invasive species from a citizen science platform and a new nomen dubium
FIGURES 5–6. External aspect of Geoplana multipunctata: photograph of the dorsal (5) and ventral (6) sides of G. multipunctata sensu Fuhrmann (1914) (fig. 25 of plate XVI of Fuhrman [1914]; (7) lateral aspect of G. multipunctata sensu Hyman (1938) showing distribution of the eyes and aspect of a monolobate (bottom left) and trilobate eye (bottom center) (fig. 1 of Hyman [1938], redrawn). Scales not available.
FIGURES 17–25 in An annotated checklist of terrestrial flatworms (Platyhelminthes: Tricladida: Geoplanidae) from Mexico, with new records of invasive species from a citizen science platform and a new nomen dubium
FIGURES 17–25. Illustrations of invasive species of Rhynchodemini found in Mexico: (17) dorsal aspect of Dolichoplana carvalhoi with a dorsal pattern of five stripes; (18) dorsal aspect of D. carvalhoi and Dolichoplana striata with a dorsal pattern of six stripes; (19) detail of the dorsal aspect with six stripes; (20) detail of the dorsal aspect with a pattern of four stripes found in some specimens of D. striata; (21) detail of the dorsal aspect with five stripes; (22) detail of the ventral aspect of D. striata and D. carvalhoi with six dorsal stripes; (23) detail of the ventral aspect of D. carvalhoi with five dorsal stripes; dorsal (24) and ventral (25) aspect of Rhynchodemus sylvaticus. Scale bars: 5 mm.
FIGURES 1–4 in An annotated checklist of terrestrial flatworms (Platyhelminthes: Tricladida: Geoplanidae) from Mexico, with new records of invasive species from a citizen science platform and a new nomen dubium
FIGURES 1–4. Illustrations of invasive species of Bipaliinae found in Mexico: dorsal (1) and ventral (2) aspect of Bipalium kewense; dorsal (3) and ventral (3) aspect of Bipalium vagum. Scale bars: 5 mm.
FIGURE 10 in An annotated checklist of terrestrial flatworms (Platyhelminthes: Tricladida: Geoplanidae) from Mexico, with new records of invasive species from a citizen science platform and a new nomen dubium
FIGURE 10. Diporodemus yucatani. Redrawn from Hyman (1938), dorsal aspect of specimen. Scales not available.
FIGURES 8–9 in An annotated checklist of terrestrial flatworms (Platyhelminthes: Tricladida: Geoplanidae) from Mexico, with new records of invasive species from a citizen science platform and a new nomen dubium
FIGURES 8–9. Pseudogeoplana nigrofusca sensu von Graff (1899a, 1899b): (8) illustration of the dorsal aspect of a living specimen (fig. 1 of plate II of von Graff [1899b]); (9) illustration of the dorsal aspect of a fixed specimen missing a piece of integument (fig. 2 of plate II of von Graff [1899b]). Scales not available.
FIGURE 26 in An annotated checklist of terrestrial flatworms (Platyhelminthes: Tricladida: Geoplanidae) from Mexico, with new records of invasive species from a citizen science platform and a new nomen dubium
FIGURE 26. Map of Mexico pointing the iNaturalist records of the invasive terrestrial flatworms, excluding hammerhead flatworms (for those see de Luna et al. 2022): Caenoplana coerulea (blue circle), Dolichoplana carvalhoi (red hexagon), Dolichoplana striata (yellow hexagons), Endevouria septemlineata (orange squares), Parakontikia ventrolineata (green triangles), and Rhynchodemus sylvaticus (pink hexagon).
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.