Find research datasets worth reusing

opencc-zeroDec 2010View details →

Data from: Citizen science reveals unexpected continental-scale evolutionary change in a model organism

Organisms provide some of the most sensitive indicators of climate change and evolutionary responses are becoming apparent in species with short generation times. Large datasets on genetic polymorphism that can provide an historical benchmark against which to test for recent evolutionary responses are very rare, but an exception is found in the brown-lipped banded snail (Cepaea nemoralis). This species is sensitive to its thermal environment and exhibits several polymorphisms of shell colour and banding pattern affecting shell albedo in the majority of populations within its native range in Europe. We tested for evolutionary changes in shell albedo that might have been driven by the warming of the climate in Europe over the last half century by compiling an historical dataset for 6,515 native populations of C. nemoralis and comparing this with new data on nearly 3,000 populations. The new data were sampled mainly in 2009 through the Evolution MegaLab, a citizen science project that engaged thousands of volunteers in 15 countries throughout Europe in the biggest such exercise ever undertaken. A known geographic cline in the frequency of the colour phenotype with the highest albedo (yellow) was shown to have persisted and a difference in colour frequency between woodland and more open habitats was confirmed, but there was no general increase in the frequency of yellow shells. This may have been because snails adapted to a warming climate through behavioural thermoregulation. By contrast, we detected an unexpected decrease in the frequency of Unbanded shells and an increase in the Mid-banded morph. Neither of these evolutionary changes appears to be a direct response to climate change, indicating that the influence of other selective agents, possibly related to changing predation pressure and habitat change with effects on micro-climate.

opencc-zeroOct 2019View details →

Data from: Survey completeness of a global citizen-science database of bird occurrence

Measuring the completeness of survey inventories created by citizen-science initiatives can identify the strengths and shortfalls in our knowledge of where species occur geographically. Here, we use occurrence information from eBird to measure the survey completeness of the world's birds in this database at three temporal resolutions and four spatial resolutions across the annual cycle during the period 2002 to 2018. Approximately 84% of the earth's terrestrial surface contained bird occurrence information with the greatest concentrations occurring in North America, Europe, India, Australia, and New Zealand. The largest regions with low levels of survey completeness were located in central South America, northern and central Africa, and northern Asia. Across spatial and temporal resolutions, survey completeness in regions with occurrence information was 55–74% on average, with the highest values occurring at coarser temporal and coarser spatial resolutions and during spring migration within temperate and boreal regions. Across spatial and temporal resolutions, survey completeness exceeded 90% within ca. 4–14% of the earth's terrestrial surface. Survey completeness increased globally from 2002 to 2018 across all months of the year at a rate of ca. 3% per year. The slowest gains occurred in Africa and in montane regions, and the most rapid gains occurred in India and in tropical forests after 2012. Thus, occurrence information from a global citizen-science program for a charismatic and well-studied taxon was geographically broad but contained heterogeneous patterns of survey completeness that were strongly influenced by temporal and especially spatial resolution. Our results identify regions where the application of additional effort would address current knowledge shortfalls, and regions where the maintenance of existing effort would benefit long-term monitoring efforts. Our findings highlight the potential of citizen science initiatives to further our knowledge of where species occur across space and time, information whose applications under global change will likely increase.

Data from: DIY meteorology: use of citizen science to monitor snow dynamics in a data-sparse city

Cities are under pressure to operate their services effectively and project costs of operations across various timeframes. In high-latitude and high-altitude urban centers, snow management is one of the larger unknowns and has both operational and budgetary limitations. Snowfall and snow depth observations within urban environments are important to plan snow clearing and prepare for the effects of spring runoff on cities' drainage systems. In-house research functions are expensive, but one way to overcome that expense and still produce effective data is through citizen science. In this paper, we examine the potential to use citizen science for snowfall data collection in urban environments. A group of volunteers measured daily snowfall and snow depth at an urban site in Saskatoon (Canada) during two winters. Reliability was assessed with a statistical consistency analysis and a comparison with other data sets collected around Saskatoon. We found that citizen-science-derived data were more reliable and relevant for many urban management stakeholders. Feedback from the participants demonstrated reflexivity about social learning and a renewed sense of community built around generating reliable and useful data. We conclude that citizen science holds great potential to improve data provision for effective and sustainable city planning and greater social learning benefits overall.

Data from: Estimates of observer expertise improve species distributions from citizen science data

1. Citizen science data are increasingly making valuable contributions to ecological studies. However, many citizen science surveys are also designed to encourage wide participation and therefore the participants have a range of natural history expertise, leading to variation and potentially bias in the data. 2. We assessed a recently proposed measure of observer expertise, calculated based on the average numbers of species recorded by observers. We investigated if this observer expertise score is associated with how often an observer records any individual species. Species reporting rates increased monotonically with the observer's expertise score for 197 of 200 species, suggesting that this expertise score describes inter-observer variation in the detectability of individual species. 3. Expertise scores were incorporated into single-species occupancy models as a covariate, to explain inter-observer variation in detectability. Including expertise as a detectability covariate led to improved model fit and improved predictive performance on validation data. The expertise score had a large effect on the estimated detectability, comparable in magnitude to the effect of the duration of the observation period. 4. Expertise scores were also included into single-species occupancy models that estimated seasonal patterns in species occupancy and seasonal expertise effects. The addition of a seasonal effect of expertise led to improved model fit and increased predictive performance on validation data. The seasonal expertise variables accounted for bias that may be introduced by seasonal differences in the effect of expertise, caused by changes in the environment or species behaviour. 5. Measures of observer expertise included in models as a covariate can account for heterogeneity and bias introduced by variable expertise, although in this example the differences in estimated occupancy were small. This method of incorporating observer expertise can be used in any regression model of species occurrence, occupancy, abundance, or density to produce more reliable ecological inference and may be most important where citizen science schemes encourage wide participation. Overall, the results highlight the value of recording observer identity and other detectability covariates, to control for sources of bias associated with the observation process.

opencc-zeroDec 2015View details →

Data from: Using citizen-collected wildlife sightings to predict traffic strike hotspots for threatened species: a case study on the southern cassowary

Assessing the causal factors underpinning the distribution and abundance of wildlife road-induced mortality can be challenging. This is particularly ubiquitous for rare or elusive species, because traffic strikes occur infrequently for these populations and information about localized abundance, distribution, and movements are generally lacking. Here we assessed if citizen-collected sightings data may serve as a low cost and efficient means of gathering long-term animal road-side presence and road crossing information, which could then be used to assess the causative factors and direct mitigation actions aimed at reducing wildlife traffic strike frequency. We explored this principle using two decades of traffic strike records and citizen-collected sightings of the southern cassowary Casuarius casuarius johnsonii. Roads have bisected the cassowaries' rainforest habitat and despite considerable investment into mitigation strategies for this species, road-induced mortality is considered one of the primary threatening processes affecting the population. Using a Bayesian approach and controlling for spatial autocorrelation with conditional autoregressive (CAR) models, we demonstrate that traffic strikes are primarily a density-dependent process in the southern cassowary. That is, traffic strike clusters occurred along stretches of road where cassowaries were most frequently sighted. There were, however, road stretches where traffic strike frequency was greater than predicted by the number of road-side sightings, illustrating when and where density-independent processes increased the mortality potential for a road-crossing cassowary. Synthesis and applications. This is the first time that citizen-collected sightings data have been used to systematically inform upon the abundance and distribution of wildlife traffic strike. The technique not only predicts where incidents are likely to occur but also helps us to understand the factors responsible for strike clustering. While not a replacement for systematic surveys, we highlight citizen-collected sightings data as a low-cost option when assessing contributing factors to vehicle-induced mortality. Accounting for density-dependent and independent processes will ensure the most effective allocation of resources when implementing wildlife traffic strike mitigation.

Data from: Using citizen science monitoring data in species distribution models to inform isotopic assignment of migratory connectivity in wetland birds

Stable isotopes have been used to estimate migratory connectivity in many species. Estimates are often greatly improved when coupled with species distribution models (SDMs), which temper estimates in relation to occurrence. SDMs can be constructed using from point locality data from a variety of sources including extensive monitoring data typically collected by citizen scientists. However, one potential issue with SDM is that these data oven have sampling bias. To avoid this potential bias, an approach using SDMs based on marsh bird monitoring program data collected by citizen scientists and other participants following protocols specifically designed to maximize detections of species of interest at locations representative of the species range. We then used the SDMs to refine isotopic assignments of breeding areas of autumn-migrating and wintering Sora (Porzana carolina), Virginia Rails (Rallus limicola), and Yellow Rails (Coturnicops noveboracensis) based on feathers collected from individuals caught at various locations in the United States from Minnesota south to Louisiana and South Carolina. Sora were assigned to an area that included much of the western U.S. and prairie Canada, covering parts of the Pacific, Central, and Mississippi Flyways. Yellow Rails were assigned to a broad area along Hudson and James Bay in northern Manitoba and Ontario, as well as smaller parts of Quebec, Minnesota, Wisconsin, and Michigan, including parts of the Mississippi and Atlantic Flyways. Virginia Rails were from several discrete areas, including parts of Colorado, New Mexico, the central valley of California, and southern Saskatchewan and Manitoba in the Pacific and Central Flyways. Our study demonstrates extensive data from organized citizen science monitoring programs are especially useful for improving isotopic assignments of migratory connectivity in birds, which can ultimately lead to better informed management decisions and conservation actions.

opencc-by-4.0Dec 2023View details →

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Supplementary material from "Utilising citizen science data to rapidly assess changing associations between wild birds and avian influenza outbreaks in poultry."

Stephen H. Vickers, Jayna Raghwani, Ashley C. Banyard, Ian H. Brown, Guillaume Fournie and Sarah C. Hill

opencc-by-4.0Feb 2024View details →

Data from: Mapping wing morphs of Tetrix subulata using citizen science data: flightless groundhoppers are more prevalent in grasslands near water

To analyse the correlation between groundhopper wing morph and landscape characteristics, we collected the following data. GBIF observations of Tetrix subulata (Linnaeus, 1758) in the Netherlands were annotated with wing morph and sex (based on the images), and weather and landscape information (based on the location). The weather information is based on an interpolation of data from the Royal Netherlands Meteorological Institute (KNMI). Landscape and habitat information was characterised by determining the area of different area types, from the Basisregistratie Topografie (BRT) TOP10NL dataset, in a radius around the observation. The landscape information also includes Dutch physical-geographical regions. To check for possible effects of seasonality, the event date of the observation is included. To check for the effect of the landscape radius on the analysis, those analyses were repeated for different radiuses. Depending on the precision of the coordinate location, some radiuses could not be tested for some observations.  The file "data.csv" contains one row per observation-radius combination, with the following columns (* repeated for each radius): <table> <tbody> <tr> <td>Columns</td> <td>Description</td> </tr> <tr> <td>gbifID*</td> <td>ID of the observation on GBIF</td> </tr> <tr> <td>eventDate*</td> <td>Date of observation (YYYY-MM-DD)</td> </tr> <tr> <td>wing_morph*</td> <td>Wing morph annotation (long; short)</td> </tr> <tr> <td>sex*</td> <td>Sex annotation (female; male; obscured; multiple; reevaluate i.e. unknown)</td> </tr> <tr> <td>region*</td> <td>Physical-geographical region in which the observation was made</td> </tr> <tr> <td>temperature*</td> <td>Predicted temperature (average over 1991-2020; degrees Celsius)</td> </tr> <tr> <td>windspeed*</td> <td>Predicted windspeed (average over 1991-2020; meters per second)</td> </tr> <tr> <td>precipitation*</td> <td>Predicted precipitation (average over 1991-2020; millimeters)</td> </tr> <tr> <td>landscape_radius</td> <td>Landscape radius (50, 100, 200, 500, or 1000 meters)</td> </tr> <tr> <td>deciduous forest, grass, mixed forest, ...</td> <td>Total surface area of given area type in given radius around observation (square meters)</td> </tr> </tbody> </table>

opencc-by-4.0Apr 2024View details →

Data for "Citizen Science for Health: an international survey on its characteristics and enabling factors"

Data and data analysis code for manuscript "Citizen Science for Health: an international survey on its characteristics and enabling factors"

opencc-by-4.0Oct 2021View details →

2021 DATA SET OF TRAFFIC COUNTES BASED ON CITIZEN SENSORS TO MONITOR DAILY TRAFFIC SOUTHERN INNER BYPASS RING IN LJUBLJANA

Traffic counters for Southern inner bypass ring in Ljubljana, Slovenia. Corresponding roads: A&scaron;kerčeva road, Zoisova road, Karlov&scaron;ka road and Ro&scaron;ka road.

opencc-zeroJan 2022View details →

Data supporting: Assessment of the performance of nonfouling polymer hydrogels utilizing citizen scientists

This dataset contains all data collected by citizen scientists in support of the publication: "Hansen N, Bryant A, McCormack R, Johnson H, Lindsay T, Stelck K, et al. (2021) Assessment of the performance of nonfouling polymer hydrogels utilizing citizen scientists. PLoS ONE 16(12): e0261817. https://doi.org/10.1371/journal.pone.0261817". This study evaluates the performance of several commercially available nonfouling polymers using citizen science, to identify the best performing chemistry for future applications as bacteria resistant coatings. The specific polymer chemistries tested were zwitterionic sulfobetaine methacrylate (SBMA), and polyampholytes composed of [2-(acryloyloxy)ethyl] trimethylammonium chloride and 2-carboxyethyl acrylate (TMA:CAA) or TMA and 3-sulfopropyl methacrylate (TMA:SA). Each polymer chemistry is known to exhibit bacteria resistance, and this study utilizes a citizen science approach to compare the performance of these chemistries.

opencc-by-4.0Feb 2022View details →

Data for: Impacts of urbanization on chloride and stream invertebrates: a 10-year citizen science field study of road salt in stormwater runoff

Abstract: The use of deicing agents during the winter months is one of many stressors that impact stream ecosystems in urban and urbanizing watersheds. In this study, a long-term dataset collected by citizen scientists with the Missouri Stream Team was used to evaluate the relationships between watershed urbanization metrics and chloride metrics. Further, these data were used to explore effects of elevated chloride concentrations on stream invertebrate communities using quantile regression. While the amount of road surface in a watershed was a dominant factor in predicting the maximum chloride measurement, the median chloride concentration was also strongly related to the amount of medium-to-high density development in the watershed, suggesting that non-municipal salt use is an important contributor to increases in baseflow chloride concentrations. Additionally, chloride concentration appears to be one of the many factors that impact invertebrate density and diversity measurements, with decreases in invertebrate diversity corresponding with the U.S. EPA water quality criteria. Our findings suggest that the use of chloride-based road salt on municipal roads as well as in non-municipal settings is contributing to a loss of diversity and density of aquatic invertebrate communities in urban regions.

opencc-zeroMay 2022View details →

Data from: Identifying conservation priorities for gorgonian forests in Italian coastal waters with multiple methods including citizen science and social media content analysis

<div> <div> <div> <div> Gorgonian forests are among the most complex of subtidal habitats in the Mediterranean Sea, supporting high biodiversity and providing diverse ecosystem services. Despite their iconic status, the geographical distribution and condition of gorgonian species is poorly known. Using multiple online data sources, our primary aims were to compile, map and analyse observations of gorgonian forests in Italian coastal waters to assess the biological complexity of gorgonian forests; evaluate impacts and vulnerable species, and identify areas of special interest inside and outside of existing MPAs to help prioritise conservation strategies and actions. </div> </div> </div> </div>

opencc-by-4.0May 2022View details →

[Suplemental Materials] Accuracy of bird identifications in citizen science data: a quantification of errors using photographic records

Supporting Information Appendix S1. The full dataset used in this study with a reproducible R code to perform data quality and network analyses.  Appendix S2. All species ranking of identification accuracy of photo reports submitted to eBird in Argentina. The ranking is first ordered by the minimum value found for either precision and recall scores, and second by the number of samples analyzed for each species. Species that were tagged as difficult to identify are indicated as ‘TRUE’ in column D named ‘hard_to_id’. Appendix S3. High-resolution network (Html file).

opencc-by-4.0May 2022View details →

Accuracy of bird identifications in citizen science data: a quantification of errors using photographic records [R code]

Appendix S1. The full dataset used in this study with a reproducible R code to perform data quality and network analyses. R code archived to Zenodo for publication.

opencc-zeroDec 2015View details →

Data from: Combining citizen science species distribution models and stable isotopes reveals migratory connectivity in the secretive Virginia rail

Stable hydrogen isotope (δD) methods for tracking animal movement are widely used yet often produce low resolution assignments. Incorporating prior knowledge of abundance, distribution or movement patterns can ameliorate this limitation, but data are lacking for most species. We demonstrate how observations reported by citizen scientists can be used to develop robust estimates of species distributions and to constrain δD assignments. We developed a Bayesian framework to refine isotopic estimates of migrant animal origins conditional on species distribution models constructed from citizen scientist observations. To illustrate this approach, we analysed the migratory connectivity of the Virginia rail Rallus limicola, a secretive and declining migratory game bird in North America. Citizen science observations enabled both estimation of sampling bias and construction of bias-corrected species distribution models. Conditioning δD assignments on these species distribution models yielded comparably high-resolution assignments. Most Virginia rails wintering across five Gulf Coast sites spent the previous summer near the Great Lakes, although a considerable minority originated from the Chesapeake Bay watershed or Prairie Pothole region of North Dakota. Conversely, the majority of migrating Virginia rails from a site in the Great Lakes most likely spent the previous winter on the Gulf Coast between Texas and Louisiana. Synthesis and applications. In this analysis, Virginia rail migratory connectivity does not fully correspond to the administrative flyways used to manage migratory birds. This example demonstrates that with the increasing availability of citizen science data to create species distribution models, our framework can produce high-resolution estimates of migratory connectivity for many animals, including cryptic species. Empirical evidence of links between seasonal habitats will help enable effective habitat management, hunting quotas and population monitoring and also highlight critical knowledge gaps.

Supplementary material 2 from: Runnel V, Wetzel F, Groom Q, Koch W, Pe'er I, Valland N, Panteri E, Kõljalg U (2016) Summary report and strategy recommendations for EU citizen science gateway for biodiversity data. Research Ideas and Outcomes 2: e11563. https://doi.org/10.3897/rio.2.e11563

EU BON conducted a survey to assess how willing are researchers to recruit volunteers in their work, what are the main effects, motivators and hindrances.

Supplementary material 3 from: Runnel V, Wetzel F, Groom Q, Koch W, Pe'er I, Valland N, Panteri E, Kõljalg U (2016) Summary report and strategy recommendations for EU citizen science gateway for biodiversity data. Research Ideas and Outcomes 2: e11563. https://doi.org/10.3897/rio.2.e11563

Citizen science and biodiversity observations – EU BON best practice cases of initiatives, systems and tools.

opencc-by-4.0Feb 2024View details →

Assessing and Correcting Neighborhood Socioeconomic Spatial Sampling Biases in Citizen Science Mosquito Data Collection

Reporting data from the Mosquito Alert citizen science system, active catch basin surveillance, and mosquito trap surveillance used in "Assessing and Correcting Neighborhood Socioeconomic Spatial Sampling Biases in Citizen Science Mosquito Data Collection." The file named mosquito_alert_adult_bite_reports_Barcelona_2014_2023.Rds includes all adult mosquito and mosquito bite reports received from Barcelona Municipality from the start of the Mosqiuto Alert project in 2014 through the end of 2023. The file named mosquito_alert_validated_albopictus_reports_Barcelona_2014_23.Rds includes all expert-validated Ae. albopictus reports received from Barcelona Municipality during the same time period. The data is stored as RDS files and contain the following fields: <ul> <li>year - the year in which the report was made. Class = dbl.</li> <li>date - the date om which the report was made. Class = date.</li> <li>type - the report type, either adult mosquito ("adult") or mosquito breeding site ("site"). Class = chr.</li> <li>lon - the longitude of the report location. Class = dbl.</li> <li>lat - the latitude of the report location. Class = dbl.</li> <li>validation_score - Entolab validation score. Either 1 (possible Ae. albopictus) or 2 (probable Ae. albopictus). This field is present only in the validated reports data. </li> </ul> The file named active_catch_basin_drain_data.Rds includes information about all catch basin drains in Barcelona Municipality in which the Barcelona Public Health Agency (ASPB) detected mosquito activity as part of its continuous monitoring and control of mosquitoes from 2019 through 2023. The data is stored in an RDS file with the following fields: <ul> <li>any_reports - dummy variable indicating whether any Mosquito Alert adult mosquito or mosquito bite reports were sent through Mosquito Alert from within 200 m of the catch basin drain during the year in which the ASPB detected mosquito activity in hte catch basin drain. Class = lgl.</li> <li>se_expected - sampling effort for the 0.025 degree lon/lat sampling cell in which the catch basin drain lies during the year in which the ASPB detected mosquito activity in the drain. This value is taken from the SE_expected variable in the sampling_effort_daily_cellres_025.csv.gz file available at https://zenodo.org/records/12602985. Sampling effort is estimated as the expected number of participants sending at least one report from the cell during the day in question given the the number of participants recorded in the cell that day and the amount of time elapsed since each one began participating in the project. Class = dbl.</li> <li>p_singlehh - proportion of single-member households in the population of the census tract in which the catch basin drain is located. Class = dbl.</li> <li>mean_age - mean age of the population of the census tract in which the catch basin drain is located. Class = dbl.</li> <li>mean_rent_consumption_unit - mean income per consumption unit in the census tract in which the catch basin drain is located. Class = dbl.</li> <li>popd - population density of the census tract in which the catch basin drain is located. Class = dbl.</li> <li>id_item - unique identifier given to the catch basin drain. Drain itentifiers appear multiple times in the data when the ASPB detected activity in the drain in multiple years. Class = dbl.</li> </ul> The file named trap_data.Rds includes information on the adult mosquito trap surveillance analyzed in this article. The data is stored in an RDS file with the following fields: <ul> <li>females - number of Ae. albopictus females found in the trap. Class = dbl.</li> <li>trap_name - unique identifier for the trap. Class = chr.</li> <li>trapping_effort - number of days from when the trap was set to when it was checked. Class = dbl.</li> <li>date - date on which the trap was checked. Class = date.</li> <li>mean_tm30 - mean temperature for the 30 days leading up to the date on which the trap was checked. Class = dbl.</li> <li>mean_rent_consumption_unit - mean income per consumption unit for the census tract in which the trap was located. Class = dbl.</li> </ul>