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444 results for “Citizen Science”
Citizen science data reveal altitudinal movement and seasonal ecosystem use by hummingbirds in the Andes Mountains
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Improving citizen science data for long-term monitoring of plant species
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Louse flies (Diptera: Hippoboscidae): United Kingdom, Republic of Ireland and Isle of Man: Citizen science data: Part 1, mapping
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Data from: Citizen science can complement professional invasive plant surveys and improve estimates of suitable habitat
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iSCAPE Citizen Science Workshops Data
<p><strong>Dataset Description</strong></p> <p>This dataset contains all the sensor data recorded during the Citizen Science Workshops during the iSCAPE project . Several workshops were held as part of the Citizen Science activities during the project in the cities of Vantaa, Dublin, Bologna, Bottrop, Hasselt and Guildford. Each csv file contains time series data of each experiment, and the yaml files contain the lists of devices used in each site.</p> <p><strong>Sensors</strong></p> <p>The sensors used are herein referred as Citizen Kits or Smart Citizen Kits, and are a set of modular hardware components that feature a selection of low cost sensors for environmental monitoring listed below. The hardware is licensed under <a href="https://www.ohwr.org/licenses/cern-ohl/license_versions/v1.2">CERN Open Hardware License V1.2</a> and is fully described in the HardwareX Open Access publication: <a href="https://doi.org/10.1016/j.ohx.2019.e00070">https://doi.org/10.1016/j.ohx.2019.e00070</a>. The sensor documentation can be found at <a href="https://docs.smartcitizen.me">https://docs.smartcitizen.me</a> and with this DOI at Zenodo: <a href="https://doi.org/10.5281/zenodo.2555029">https://doi.org/10.5281/zenodo.2555029</a>.</p> <p>In the list below, the different sensors for the Citizen Kits are detailed, and their [CHANNELS] in the csv files above linked.</p> <p> </p> <ul> <li>Air temperature (ºC): Sensirion SHT-31 [TEMP]</li> <li>Relative Humidity (%rh): Sensirion SHT-31 [HUM]</li> <li>Noise level (dBA): Invensense ICS-434342 [NOISE_A]</li> <li>Ambient light (lux): Rohm BH1721FVC [LIGHT]</li> <li>Barometric pressure (kPa): NXP MPL3115A26 [PRESS]</li> <li>Particulate Matter PM 1 / 2.5 / 10 (µg/m3) Planttower PMS 5003 [EXT_PM_1,EXT_PM_25,EXT_PM_10]</li> </ul> <p><strong>How to find the data</strong></p> <p>Each yaml file contains the description of a test. Each test is comprised of recordings of several devices in the same location and during the same period. Each yaml file is comprised of the following fields:</p> <ul> <li>author: who has been in charge of performing the test (internal reference - not relevant)</li> <li>comment: describing in general terms what was done in the test, and with what purpose</li> <li>commit: the firmware commit (in the case of Smart Citizen devices) with which the test was performed, for development purposes only</li> <li>devices: a descriptor containing different fields for traceability (below)</li> <li>id: the test name</li> <li>project: within the test was performed, in this case it is always iscape</li> <li>report: if there is any report analysing the test</li> <li>type_test: indoor, oudoor test or other.</li> </ul> <p><strong>Description of devices entry</strong></p> <p>For each device that was used in the test, two generic types are used:</p> <ul> <li>low cost sensors (type: STATION or KIT)</li> <li>high end sensors (type: REFERENCE)</li> </ul> <p>For <strong>low cost Smart Citizen sensors</strong>, the fields are:</p> <ul> <li>alphasense: electrochemical sensors device ids, by pollutant (for manufacturer calibration) and slots in which they were placed</li> <li>device_id: device id in Smartcitizen API</li> <li>fileNameInfo: not used</li> <li>fileNameProc: (only if source = csv is specified) 2019-03_EXT_UCD_URBAN_BACKGROUND_API_CITY_COUNCIL_REF.csv</li> <li>fileNameRaw: (only if source = csv is used) raw file name</li> <li>frequency: original recording frequency</li> <li>location: for timezone correction only, not accurate</li> <li>max_date: last recording date</li> <li>min_date: first recording date</li> <li>name: self-explanatory</li> <li>pm_sensor: if there was a pm sensor connected (all of them are PMS5003 if no sensor is specified)</li> <li>source: api or csv</li> <li>type: STATION (KIT + Alphasense + PM board with two PMS5003) or KIT</li> <li>version: smartcitizen hardware version</li> </ul> <p>For <strong>high end</strong> sensors, the fields are:</p> <ul> <li>channels: which channels the device was recording for internal convertion <ul> <li>names: which are the columns in the csv file</li> <li>pollutants: which pollutants do they respectively refer to</li> <li>units: the units of these pollutants</li> </ul> </li> <li>equipment: the brand of the analyser</li> <li>fileNameProc: same as above</li> <li>fileNameRaw: same as above</li> <li>index: format in which the timeindex is done, for parsing purposes <ul> <li>format: (example '%Y-%m-%d %H:%M:%S')</li> <li>frequency: frequency at which the device was recorded</li> <li>name: column name</li> </ul> </li> <li>location: same as above</li> <li>name: name of the device</li> <li>type: REFERENCE (always for these devices)</li> <li>source: csv</li> </ul> <p><strong>iSCAPE Dataset Reference Numbers</strong></p> <p>The datasets here presented are related to the following iSCAPE dataset reference numbers:</p> <ul> <li>DS_TS_093</li> <li>DS_TS_094</li> <li>DS_TS_095</li> <li>DS_TS_096</li> <li>DS_TS_097</li> <li>DS_TS_098</li> </ul>
Figure 7 in The introduced terrestrial slugs Ambigolimax nyctelius (Bourguignatı 1861) and Ambigolimax valentianus (Férussacı 1821) (Gastropoda: Limacidae) in Californiaı with a discussion of taxonomyı systematicsı and discovery by citizen science
Figure 7. Explanation of the supplementary plates, or 'Exp. Planch. supp. Plate 4A' (Férussac et al. 1820–1851).
Figure 2 in The introduced terrestrial slugs Ambigolimax nyctelius (Bourguignatı 1861) and Ambigolimax valentianus (Férussacı 1821) (Gastropoda: Limacidae) in Californiaı with a discussion of taxonomyı systematicsı and discovery by citizen science
Figure 2. Jaws of A. nyctelius (a–c, h) and A. valentianus (d–g) from sites within Los Angeles County, California imaged using SEM (a–f) and light microscopy (g, h). (a) iNat 4936336, LACM 180543; (b, h) iNat 4936344, LACM 180541; (c) iNat 4936343, LACM 180540; (d, g) iNat 4936341, LACM 180536; (e) iNat 4936340, LACM 180537; (f) iNat 4936346, LACM 180538. Images by Emily Burnett.
Figure 5 in The introduced terrestrial slugs Ambigolimax nyctelius (Bourguignatı 1861) and Ambigolimax valentianus (Férussacı 1821) (Gastropoda: Limacidae) in Californiaı with a discussion of taxonomyı systematicsı and discovery by citizen science
Figure 5. Male genitalia of A. nyctelius (a), iNat 4936338, LACM 180542, and A. valentianus (b), iNat 4936340, LACM 180537 from Los Angeles County, California. bc, bursa copulatrix; ga, genital atrium; p, phallas; pa, phallas appendix; pr, phallas retractor muscle; so, spermoviduct; vd, vas deferens. Photos by Cedric Lee.
The motivation for citizens' involvement in life sciences research is predicted by age and gender
<p>Data for publication <em><strong>The motivation for citizens’ involvement in life sciences research is predicted by age and gender</strong></em></p>
Connecting digital citizen science data quality issue to solution mechanism table
<p>A table explaining how to solve data quality issues in digital citizen science. A total of 35 issues and 64 mechanisms to solve them are proposed</p>
Open database of small-scale solar PV installations: a Citizen Science initiative
<p>Presentation given at the European PV Solar Energy Conference 2020 about the development of a Citizen Science initiative related to PV installations, Generation Solar.</p>
FIGURE 1 in Ontogeny of an arlequin: morphological and colour pattern changes from juvenile to adult in Gnathophyllum elegans (Risso, 1816) (Decapoda: Palaemonidae), traced through citizen science and social media data mining
FIGURE 1. Morphological and colour pattern changes from juvenile to adult in Gnathophyllum elegans (Risso, 1816). A–C. Specimens from Capo Noli (Italy, Mediterranean Sea) (~44.199232N, 8.420455E), 15–16 m, on anthropogenic debris laying on a detritic bottom, 5–13.IX.2020. A. Photo by Walter Bassi. B–C. Photos by Alessandro Raho. D. Specimen from La Laja beach, Gran Canaria (Spain, Atlantic Ocean) (~28.060335N, -15.418428E), 1 m, amidst algae in a tide pool, 29.VIII.2017. Photo by Alberto Navarro. E. Specimen from Bat Galim reef, Haifa (Israel, Mediterranean Sea) (~32.833317N, 34.97431E), 2 m, under a rock on a rocky bottom, ~2017. Photo by Sarah Ohayon. F. Specimen from Capo Caccia, Sardinia (Italy, Mediterranean Sea) (~40.565506N, 8.165579E), 5 m, detritic bottom with rocks, 28.VIII.2015. Photo by Marco Colombo.
Dispatches from the neighborhood watch: using citizen science and field survey data to document color morph frequency in space and time
<p>Heritable color polymorphisms have a long history of study in evolutionary biology, though they are less frequently examined today than in the past. These systems, where multiple discrete, visually identifiable color phenotypes co-occur in the same population, are valuable for tracking evolutionary change and ascertaining the relative importance of different evolutionary mechanisms. Here, we use a combination of citizen science data and field surveys in the Great Lakes region of North America to identify patterns of color morph frequencies in the eastern gray squirrel (<i>Sciurus carolinensis</i>). Using over 68,000 individual squirrel records from both large and small spatial scales, we identify the following patterns: (1) the melanistic (black) phenotype is often localized but nonetheless widespread throughout the Great Lakes region, occurring in all states and provinces sampled. (2) In Ohio, where intensive surveys were performed, there is a weak but significantly positive association between color morph frequency and geographic proximity of populations. Nonetheless, even nearby populations often had radically different frequencies of the melanistic morph, which ranged from 0 to 96%. These patterns were mosaic rather than clinal. (3) In the Wooster, Ohio population, which had over eight years of continuous data on color morph frequency representing nearly 40,000 records, we found that the frequency of the melanistic morph increased gradually over time on some survey routes but decreased or did not change over time on others. These differences were statistically significant and occurred at very small spatial scales (on the order of hundreds of meters). Together, these patterns are suggestive of genetic drift as an important mechanism of evolutionary change in this system. We argue that studies of color polymorphism are still quite valuable in advancing our understanding of fundamental evolutionary processes, especially when coupled with the growing availability of data from citizen science efforts.</p>
Data from: Historical citizen science to understand and predict climate-driven trout decline
Historical species records offer an excellent opportunity to test the predictive ability of range forecasts under climate change, but researchers often consider that historical records are scarce and unreliable, besides the datasets collected by renowned naturalists. Here, we demonstrate the relevance of biodiversity records developed through citizen-science initiatives generated outside the natural sciences academia. We used a Spanish geographical dictionary from the mid-nineteenth century to compile over 10 000 freshwater fish records, including almost 4 000 brown trout (Salmo trutta) citations, and constructed a historical presence–absence dataset covering over 2 000 10 × 10 km cells, which is comparable to present-day data. There has been a clear reduction in trout range in the past 150 years, coinciding with a generalized warming. We show that current trout distribution can be accurately predicted based on historical records and past and present values of three air temperature variables. The models indicate a consistent decline of average suitability of around 25% between 1850s and 2000s, which is expected to surpass 40% by the 2050s. We stress the largely unexplored potential of historical species records from non-academic sources to open new pathways for long-term global change science.
Data from: Non-invasive genetic monitoring involving citizen science enables reconstruction of current pack dynamics in a re-establishing wolf population
Background: Carnivores are re-establishing in many human-populated areas, where their presence is often contentious. Reaching consensus over management decisions is often hampered by a dispute about the size of the local carnivore population. Understanding the reproductive dynamics and individual movements of the carnivores can provide support for management decisions, but individual-level information can be difficult to obtain from elusive, wide-ranging species. Non-invasive genetic sampling can yield such information, but makes subsequent reconstruction of population history challenging due to incomplete population coverage and error-prone data. Here, we combine a collaborative, volunteer-based sampling scheme with Bayesian pedigree reconstruction to describe the pack dynamics of an establishing grey wolf (Canis lupus) population in south-west Finland, where wolf breeding was recorded in 2006 for the first time in over a century. Results: Using DNA extracted mainly from faeces collected since 2008, we identified 81 individual wolves and assigned credible full parentages to 70 of these and partial parentages to a further 9, revealing 7 breeding pairs. Individuals used a range of strategies to obtain breeding opportunities, including dispersal to established or new packs, long-distance migration and inheriting breeding roles. Gene flow occurred between all packs but inbreeding events were rare. Conclusions: These findings demonstrate that characterizing ongoing pack dynamics can provide detailed, locally-relevant insight into the ecology of contentious species such as the wolf. Involving various stakeholders in data collection makes these results more likely to be accepted as unbiased and hence reliable grounds for management decisions.
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.
Citizen science improves our understanding of the impact of soil management on wild pollinator abundance in agroecosystems
<p><span><span><span><span><span><span><span><span><span><span><span>Native bees provide essential pollination services in both natural and managed ecosystems. However, declines in native bee species highlight the need for increased understanding of land management methods that can promote healthy, persistent populations and diverse communities. This can be challenging and costly using traditional scientific methods, but citizen science can overcome many limitations. In this study, we examined the distribution and abundance of an agriculturally important wild bee species, the squash bee (<i>Eucera </i>(<i>Peponapis</i>) <i>pruinosa</i>, Hymenoptera: Apidae). They are ground nesting, specialist bees that depend on cultivated varieties of <i>Cucurbita </i>(squash, pumpkins, gourds). The intimate relationship between squash bees and their host plants suggests that they are likely sensitive to farm management practices, particularly those that disturb the soil. In this study, citizen scientists across Michigan used a smartphone application to submit field management and bee observation data. Survey results indicated that squash bees occupy a wide geographic range and are more abundant in farms with reduced soil disturbance. Citizen science provided a cheap, effective method for examining impacts of farm management practices on squash bees and could be a valuable tool for monitoring and conserving other native pollinators. </span></span></span></span></span></span></span></span></span></span></span></p>
Data from: Survey completeness of a global citizen-science database of bird occurrence
<p>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 <i>ca</i>. 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 <i>ca</i>. 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.</p>
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.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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OpenNeuro
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