1
|
Gould J, Taylor J, Davies B, Donelly R, Schmahl K, Bugir CK, Beranek CT, McGregor J, Mahony SV, Seeto R, Upton R, McHenry C, Callen A. Tadpole fingerprinting: Using tail venation patterns to photo‐identify tadpole individuals of a threatened frog. AUSTRAL ECOL 2023. [DOI: 10.1111/aec.13286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Affiliation(s)
- John Gould
- Conservation Science Research Group, School of Environmental and Life Sciences University of Newcastle Callaghan New South Wales Australia
| | - James Taylor
- Conservation Science Research Group, School of Environmental and Life Sciences University of Newcastle Callaghan New South Wales Australia
| | - Bryce Davies
- Conservation Science Research Group, School of Environmental and Life Sciences University of Newcastle Callaghan New South Wales Australia
| | - Rachael Donelly
- Conservation Science Research Group, School of Environmental and Life Sciences University of Newcastle Callaghan New South Wales Australia
| | - Kate Schmahl
- Conservation Science Research Group, School of Environmental and Life Sciences University of Newcastle Callaghan New South Wales Australia
| | - Cassandra K. Bugir
- Conservation Science Research Group, School of Environmental and Life Sciences University of Newcastle Callaghan New South Wales Australia
| | - Chad T. Beranek
- Conservation Science Research Group, School of Environmental and Life Sciences University of Newcastle Callaghan New South Wales Australia
- FAUNA Research Alliance Kahibah New South Wales Australia
| | - Jess McGregor
- Conservation Science Research Group, School of Environmental and Life Sciences University of Newcastle Callaghan New South Wales Australia
| | - Stephen V. Mahony
- Conservation Science Research Group, School of Environmental and Life Sciences University of Newcastle Callaghan New South Wales Australia
| | - Rebecca Seeto
- Conservation Science Research Group, School of Environmental and Life Sciences University of Newcastle Callaghan New South Wales Australia
| | - Rose Upton
- Conservation Science Research Group, School of Environmental and Life Sciences University of Newcastle Callaghan New South Wales Australia
| | - Colin McHenry
- Conservation Science Research Group, School of Environmental and Life Sciences University of Newcastle Callaghan New South Wales Australia
| | - Alex Callen
- Conservation Science Research Group, School of Environmental and Life Sciences University of Newcastle Callaghan New South Wales Australia
| |
Collapse
|
2
|
Peeters ETHM, Gerritsen AAM, Seelen LMS, Begheyn M, Rienks F, Teurlincx S. Monitoring biological water quality by volunteers complements professional assessments. PLoS One 2022; 17:e0263899. [PMID: 35213583 PMCID: PMC8880917 DOI: 10.1371/journal.pone.0263899] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Accepted: 01/30/2022] [Indexed: 11/18/2022] Open
Abstract
Progressively more community initiatives have been undertaken over last decades to monitor water quality. Biological data collected by volunteers has been used for biodiversity and water quality studies. Despite the many citizen science projects collecting and using macroinvertebrates, the number of scientific peer-reviewed publications that use this data, remains limited. In 2018, a citizen science project on biological water quality assessment was launched in the Netherlands. In this project, volunteers collect macroinvertebrates from a nearby waterbody, identify and count the number of specimens, and register the catch through a web portal to instantaneously receive a water quality score based on their data. Water quality monitoring in the Netherlands is traditionally the field of professionals working at water authorities. Here, we compare the data from the citizen science project with the data gathered by professionals. We evaluate information regarding type and distribution of sampled waterbodies and sampling period, and compare general patterns in both datasets with respect to collected animals and calculated water quality scores. The results show that volunteers and professionals seldomly sample the same waterbody, that there is some overlap in sampling period, and that volunteers more frequently sampled urban waters and smaller waterbodies. The citizen science project is thus yielding data about understudied waters and this spatial and temporal complementarity is useful. The character and thoroughness of the assessments by volunteers and professionals are likely to differentiate. Volunteers collected significantly lower numbers of animals per sample and fewer animals from soft sediments like worms and more mobile individuals from the open water column such as boatsmen and beetles. Due to the lack of simultaneous observations at various locations by volunteers and professionals, a direct comparison of water quality scores is impossible. However, the obtained patterns from both datasets show that the water quality scores between volunteers and professionals are dissimilar for the different water types. To bridge these differences, new tools and processes need to be further developed to increase the value of monitoring biological water quality by volunteers for professionals.
Collapse
Affiliation(s)
- Edwin T. H. M. Peeters
- Chairgroup Aquatic Ecology and Water Quality Management, Wageningen University, Wageningen, The Netherlands
- * E-mail:
| | | | - Laura M. S. Seelen
- Department of Planning and Monitoring, Regional Water Authority Brabantse Delta, Breda, The Netherlands
| | - Matthijs Begheyn
- Global Learning and Observations to Benefit the Environment (GLOBE) Netherlands, Utrecht, The Netherlands
| | - Froukje Rienks
- Section Public Relations & Science Communication, Netherlands Institute of Ecology (NIOO-KNAW), Wageningen, The Netherlands
| | - Sven Teurlincx
- Department of Aquatic Ecology, Netherlands Institute of Ecology (NIOO-KNAW), Wageningen, The Netherlands
| |
Collapse
|
3
|
Ramírez-Andreotta MD, Walls R, Youens-Clark K, Blumberg K, Isaacs KE, Kaufmann D, Maier RM. Alleviating Environmental Health Disparities Through Community Science and Data Integration. FRONTIERS IN SUSTAINABLE FOOD SYSTEMS 2021; 5. [PMID: 35664667 PMCID: PMC9165534 DOI: 10.3389/fsufs.2021.620470] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Environmental contamination is a fundamental determinant of health and well-being, and when the environment is compromised, vulnerabilities are generated. The complex challenges associated with environmental health and food security are influenced by current and emerging political, social, economic, and environmental contexts. To solve these “wicked” dilemmas, disparate public health surveillance efforts are conducted by local, state, and federal agencies. More recently, citizen/community science (CS) monitoring efforts are providing site-specific data. One of the biggest challenges in using these government datasets, let alone incorporating CS data, for a holistic assessment of environmental exposure is data management and interoperability. To facilitate a more holistic perspective and approach to solution generation, we have developed a method to provide a common data model that will allow environmental health researchers working at different scales and research domains to exchange data and ask new questions. We anticipate that this method will help to address environmental health disparities, which are unjust and avoidable, while ensuring CS datasets are ethically integrated to achieve environmental justice. Specifically, we used a transdisciplinary research framework to develop a methodology to integrate CS data with existing governmental environmental monitoring and social attribute data (vulnerability and resilience variables) that span across 10 different federal and state agencies. A key challenge in integrating such different datasets is the lack of widely adopted ontologies for vulnerability and resiliency factors. In addition to following the best practice of submitting new term requests to existing ontologies to fill gaps, we have also created an application ontology, the Superfund Research Project Data Interface Ontology (SRPDIO).
Collapse
Affiliation(s)
- Mónica D. Ramírez-Andreotta
- Department of Environmental Science, University of Arizona, Tucson, AZ, United States
- Mel and Enid Zuckerman College of Public Health’s Division of Community, Environment and Policy, University of Arizona, Tucson, AZ, United States
- Correspondence: Mónica D. Ramírez-Andreotta
| | - Ramona Walls
- BIO5 Institute, University of Arizona, Tucson, AZ, United States
| | - Ken Youens-Clark
- Department of Biosystems Engineering, University of Arizona, Tucson, AZ, United States
| | - Kai Blumberg
- Department of Biosystems Engineering, University of Arizona, Tucson, AZ, United States
| | - Katherine E. Isaacs
- Department of Computer Science, University of Arizona, Tucson, AZ, United States
| | - Dorsey Kaufmann
- Department of Environmental Science, University of Arizona, Tucson, AZ, United States
| | - Raina M. Maier
- Department of Environmental Science, University of Arizona, Tucson, AZ, United States
| |
Collapse
|
4
|
Hall MJ, Martin JM, Burns AL, Hochuli DF. Ecological insights into a charismatic bird using different citizen science approaches. AUSTRAL ECOL 2021. [DOI: 10.1111/aec.13062] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Affiliation(s)
- Matthew J. Hall
- School of Life and Environmental Sciences The University of Sydney Camperdown New South Wales 2006Australia
| | - John M. Martin
- School of Life and Environmental Sciences The University of Sydney Camperdown New South Wales 2006Australia
- Institute of Science and Learning Taronga Conservation Society Australia Mosman New South Wales Australia
| | - Alicia L. Burns
- School of Life and Environmental Sciences The University of Sydney Camperdown New South Wales 2006Australia
- Institute of Science and Learning Taronga Conservation Society Australia Mosman New South Wales Australia
| | - Dieter F. Hochuli
- School of Life and Environmental Sciences The University of Sydney Camperdown New South Wales 2006Australia
| |
Collapse
|
5
|
McCarthy MS, Stephens C, Dieguez P, Samuni L, Després‐Einspenner M, Harder B, Landsmann A, Lynn LK, Maldonado N, Ročkaiová Z, Widness J, Wittig RM, Boesch C, Kühl HS, Arandjelovic M. Chimpanzee identification and social network construction through an online citizen science platform. Ecol Evol 2021; 11:1598-1608. [PMID: 33613992 PMCID: PMC7882979 DOI: 10.1002/ece3.7128] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Revised: 11/08/2020] [Accepted: 11/13/2020] [Indexed: 11/10/2022] Open
Abstract
Citizen science has grown rapidly in popularity in recent years due to its potential to educate and engage the public while providing a means to address a myriad of scientific questions. However, the rise in popularity of citizen science has also been accompanied by concerns about the quality of data emerging from citizen science research projects. We assessed data quality in the online citizen scientist platform Chimp&See, which hosts camera trap videos of chimpanzees (Pan troglodytes) and other species across Equatorial Africa. In particular, we compared detection and identification of individual chimpanzees by citizen scientists with that of experts with years of experience studying those chimpanzees. We found that citizen scientists typically detected the same number of individual chimpanzees as experts, but assigned far fewer identifications (IDs) to those individuals. Those IDs assigned, however, were nearly always in agreement with the IDs provided by experts. We applied the data sets of citizen scientists and experts by constructing social networks from each. We found that both social networks were relatively robust and shared a similar structure, as well as having positively correlated individual network positions. Our findings demonstrate that, although citizen scientists produced a smaller data set based on fewer confirmed IDs, the data strongly reflect expert classifications and can be used for meaningful assessments of group structure and dynamics. This approach expands opportunities for social research and conservation monitoring in great apes and many other individually identifiable species.
Collapse
Affiliation(s)
| | - Colleen Stephens
- Max Planck Institute for Evolutionary AnthropologyLeipzigGermany
| | - Paula Dieguez
- Max Planck Institute for Evolutionary AnthropologyLeipzigGermany
| | - Liran Samuni
- Department of Human Evolutionary BiologyHarvard UniversityCambridgeMassachusettsUSA
- Taï Chimpanzee ProjectCentre Suisse de Recherches ScientifiquesAbidjanIvory Coast
| | | | - Briana Harder
- Zooniverse Citizen Scientistc/o Max Planck Institute for Evolutionary AnthropologyLeipzigGermany
| | - Anja Landsmann
- Zooniverse Citizen Scientistc/o Max Planck Institute for Evolutionary AnthropologyLeipzigGermany
- Faculty of MedicineInstitute for Drug DiscoveryLeipzig UniversityLeipzigGermany
| | - Laura K. Lynn
- Zooniverse Citizen Scientistc/o Max Planck Institute for Evolutionary AnthropologyLeipzigGermany
| | - Nuria Maldonado
- Max Planck Institute for Evolutionary AnthropologyLeipzigGermany
- iScapesValenciaSpain
| | - Zuzana Ročkaiová
- Zooniverse Citizen Scientistc/o Max Planck Institute for Evolutionary AnthropologyLeipzigGermany
| | - Jane Widness
- Zooniverse Citizen Scientistc/o Max Planck Institute for Evolutionary AnthropologyLeipzigGermany
- Department of AnthropologyYale UniversityNew HavenConnecticutUSA
| | - Roman M. Wittig
- Max Planck Institute for Evolutionary AnthropologyLeipzigGermany
- Taï Chimpanzee ProjectCentre Suisse de Recherches ScientifiquesAbidjanIvory Coast
| | | | - Hjalmar S. Kühl
- Max Planck Institute for Evolutionary AnthropologyLeipzigGermany
- German Centre for Integrative Biodiversity Research (iDiv)Halle‐Leipzig‐JenaGermany
| | | |
Collapse
|
6
|
Callaghan CT, Martin JM, Major RE, Kingsford RT. Avian monitoring – comparing structured and unstructured citizen science. WILDLIFE RESEARCH 2018. [DOI: 10.1071/wr17141] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Context Citizen science is increasingly used to collect biodiversity data to inform conservation management, but its validity within urban greenspaces remains largely unresolved. Aims To assess the validity of eBird data for generating biodiversity estimates within an urban greenspace. Methods We compared data from structured avian surveys with eBird data at an urban greenspace in Sydney during 2012–16, using species richness and Shannon diversity indices. We also compared community composition, using non-metric multidimensional scaling (NMDS) and dissimilarities using non-parametric MANOVA. Key results Structured surveys had a lower overall species richness (80 versus 116) and Shannon diversity (3.64 versus 3.94) than eBird data, but we found no significant differences when using years as replicates. After standardising the richness and diversity indices by time spent surveying in a given year, structured surveys produced significantly higher biodiversity estimates. Further, when grouped into species occupying different broad habitats, there were no significant differences in waterbird or landbird species richness, or in Shannon diversity between data sources. Conclusions The most likely explanation for the larger magnitudes of the biodiversity indices from the eBird data is the increase in effort manifested in the number of observers, time spent surveying and spatial coverage. This resulted in increased detection of uncommon species, which in turn accounted for a significant difference (R2 = 0.21, P = 0.015) in overall community composition measured by the two methods. Implications Our results highlight the opportunities provided by eBird data as a useful tool for land managers for monitoring avian communities in urban areas.
Collapse
|
7
|
Tredick CA, Lewison RL, Deutschman DH, Hunt TANN, Gordon KL, Von Hendy P. A Rubric to Evaluate Citizen-Science Programs for Long-Term Ecological Monitoring. Bioscience 2017. [DOI: 10.1093/biosci/bix090] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
|
8
|
Quality of non-expert citizen science data collected for habitat type conservation status assessment in Natura 2000 protected areas. Sci Rep 2017; 7:8873. [PMID: 28827770 PMCID: PMC5567195 DOI: 10.1038/s41598-017-09316-9] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2016] [Accepted: 07/26/2017] [Indexed: 11/11/2022] Open
Abstract
EU biodiversity conservation policy is based on the Habitats Directive (92/43/EC), which aims that habitat types and species of Community interest should reach ‘favourable conservation status’. To this end, Member States are obliged to perform periodic assessment of species and habitat conservation status through biodiversity monitoring, which, in almost all cases, was performed by experts implementing standardized field protocols. Here, we examine the quality of data collected in the field by non-experts (citizen scientists) for the conservation status assessment of habitat types, and specifically for the criteria ‘typical species’, ‘specific structures and functions’, and ‘pressures and threats’. This task is complicated and demands different types of field data. We visited two Natura 2000 sites and investigated four habitat types (two in each site) with non-experts and compared their data to the data collected by experts for accuracy, completeness and spatial arrangement. The majority of the non-expert data were accurate (i.e. non-experts recorded information they observed in the field), but they were incomplete (i.e. non-experts detected less information than the experts). Also, non-experts chose their sampling locations closer to the edge of the habitat, i.e. in more marginal conditions and thus in potentially more degraded conditions, than experts.
Collapse
|
9
|
Runnel V, Wetzel F, Groom Q, Koch W, Pe’er I, Valland N, Panteri E, Kõljalg U. Summary report and strategy recommendations for EU citizen science gateway for biodiversity data. RESEARCH IDEAS AND OUTCOMES 2016. [DOI: 10.3897/rio.2.e11563] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
|
10
|
Citizen surveillance for environmental monitoring: combining the efforts of citizen science and crowdsourcing in a quantitative data framework. SPRINGERPLUS 2016; 5:1890. [PMID: 27843747 PMCID: PMC5084151 DOI: 10.1186/s40064-016-3583-5] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/24/2015] [Accepted: 10/19/2016] [Indexed: 11/25/2022]
Abstract
Citizen science and crowdsourcing have been emerging as methods to collect data for surveillance and/or monitoring activities. They could be gathered under the overarching term citizen surveillance. The discipline, however, still struggles to be widely accepted in the scientific community, mainly because these activities are not embedded in a quantitative framework. This results in an ongoing discussion on how to analyze and make useful inference from these data. When considering the data collection process, we illustrate how citizen surveillance can be classified according to the nature of the underlying observation process measured in two dimensions—the degree of observer reporting intention and the control in observer detection effort. By classifying the observation process in these dimensions we distinguish between crowdsourcing, unstructured citizen science and structured citizen science. This classification helps the determine data processing and statistical treatment of these data for making inference. Using our framework, it is apparent that published studies are overwhelmingly associated with structured citizen science, and there are well developed statistical methods for the resulting data. In contrast, methods for making useful inference from purely crowd-sourced data remain under development, with the challenges of accounting for the unknown observation process considerable. Our quantitative framework for citizen surveillance calls for an integration of citizen science and crowdsourcing and provides a way forward to solve the statistical challenges inherent to citizen-sourced data.
Collapse
|
11
|
Ratnieks FLW, Schrell F, Sheppard RC, Brown E, Bristow OE, Garbuzov M. Data reliability in citizen science: learning curve and the effects of training method, volunteer background and experience on identification accuracy of insects visiting ivy flowers. Methods Ecol Evol 2016. [DOI: 10.1111/2041-210x.12581] [Citation(s) in RCA: 57] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Francis L. W. Ratnieks
- Laboratory of Apiculture & Social Insects School of Life Sciences University of Sussex Falmer Brighton BN1 9QG UK
| | - Felix Schrell
- Laboratory of Apiculture & Social Insects School of Life Sciences University of Sussex Falmer Brighton BN1 9QG UK
| | - Rebecca C. Sheppard
- Laboratory of Apiculture & Social Insects School of Life Sciences University of Sussex Falmer Brighton BN1 9QG UK
| | - Emmeline Brown
- Laboratory of Apiculture & Social Insects School of Life Sciences University of Sussex Falmer Brighton BN1 9QG UK
| | - Oliver E. Bristow
- Laboratory of Apiculture & Social Insects School of Life Sciences University of Sussex Falmer Brighton BN1 9QG UK
| | - Mihail Garbuzov
- Laboratory of Apiculture & Social Insects School of Life Sciences University of Sussex Falmer Brighton BN1 9QG UK
| |
Collapse
|
12
|
Lewandowski E, Specht H. Influence of volunteer and project characteristics on data quality of biological surveys. CONSERVATION BIOLOGY : THE JOURNAL OF THE SOCIETY FOR CONSERVATION BIOLOGY 2015; 29:713-723. [PMID: 25800171 DOI: 10.1111/cobi.12481] [Citation(s) in RCA: 63] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/14/2014] [Accepted: 12/07/2014] [Indexed: 06/04/2023]
Abstract
Volunteer involvement in biological surveys is becoming common in conservation and ecology, prompting questions on the quality of data collected in such surveys. In a systematic review of the peer-reviewed literature on the quality of data collected by volunteers, we examined the characteristics of volunteers (e.g., age, prior knowledge) and projects (e.g., systematic vs. opportunistic monitoring schemes) that affect data quality with regards to standardization of sampling, accuracy and precision of data collection, spatial and temporal representation of data, and sample size. Most studies (70%, n = 71) focused on the act of data collection. The majority of assessments of volunteer characteristics (58%, n = 93) examined the effect of prior knowledge and experience on quality of the data collected, often by comparing volunteers with experts or professionals, who were usually assumed to collect higher quality data. However, when both groups' data were compared with the same accuracy standard, professional data were more accurate in only 4 of 7 cases. The few studies that measured precision of volunteer and professional data did not conclusively show that professional data were less variable than volunteer data. To improve data quality, studies recommended changes to survey protocols, volunteer training, statistical analyses, and project structure (e.g., volunteer recruitment and retention).
Collapse
Affiliation(s)
- Eva Lewandowski
- Conservation Biology Graduate Program, Department of Fisheries, Wildlife and Conservation Biology, University of Minnesota, 135 Skok Hall, 2003 Upper Buford Circle, Saint Paul, MN, 55108, U.S.A..
| | - Hannah Specht
- Conservation Biology Graduate Program, Department of Fisheries, Wildlife and Conservation Biology, University of Minnesota, 135 Skok Hall, 2003 Upper Buford Circle, Saint Paul, MN, 55108, U.S.A
| |
Collapse
|
13
|
Forrester G, Baily P, Conetta D, Forrester L, Kintzing E, Jarecki L. Comparing monitoring data collected by volunteers and professionals shows that citizen scientists can detect long-term change on coral reefs. J Nat Conserv 2015. [DOI: 10.1016/j.jnc.2015.01.002] [Citation(s) in RCA: 43] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
|
14
|
Thorson JT, Scheuerell MD, Semmens BX, Pattengill-Semmens CV. Demographic modeling of citizen science data informs habitat preferences and population dynamics of recovering fishes. Ecology 2014. [DOI: 10.1890/13-2223.1] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
|
15
|
The invisible prevalence of citizen science in global research: migratory birds and climate change. PLoS One 2014. [PMID: 25184755 DOI: 10.1371/journal.pone.0106508.] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Citizen science is a research practice that relies on public contributions of data. The strong recognition of its educational value combined with the need for novel methods to handle subsequent large and complex data sets raises the question: Is citizen science effective at science? A quantitative assessment of the contributions of citizen science for its core purpose--scientific research--is lacking. We examined the contribution of citizen science to a review paper by ornithologists in which they formulated ten central claims about the impact of climate change on avian migration. Citizen science was never explicitly mentioned in the review article. For each of the claims, these ornithologists scored their opinions about the amount of research effort invested in each claim and how strongly the claim was supported by evidence. This allowed us to also determine whether their trust in claims was, unwittingly or not, related to the degree to which the claims relied primarily on data generated by citizen scientists. We found that papers based on citizen science constituted between 24 and 77% of the references backing each claim, with no evidence of a mistrust of claims that relied heavily on citizen-science data. We reveal that many of these papers may not easily be recognized as drawing upon volunteer contributions, as the search terms "citizen science" and "volunteer" would have overlooked the majority of the studies that back the ten claims about birds and climate change. Our results suggest that the significance of citizen science to global research, an endeavor that is reliant on long-term information at large spatial scales, might be far greater than is readily perceived. To better understand and track the contributions of citizen science in the future, we urge researchers to use the keyword "citizen science" in papers that draw on efforts of non-professionals.
Collapse
|
16
|
Cooper CB, Shirk J, Zuckerberg B. The invisible prevalence of citizen science in global research: migratory birds and climate change. PLoS One 2014; 9:e106508. [PMID: 25184755 PMCID: PMC4153593 DOI: 10.1371/journal.pone.0106508] [Citation(s) in RCA: 63] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2014] [Accepted: 08/01/2014] [Indexed: 11/28/2022] Open
Abstract
Citizen science is a research practice that relies on public contributions of data. The strong recognition of its educational value combined with the need for novel methods to handle subsequent large and complex data sets raises the question: Is citizen science effective at science? A quantitative assessment of the contributions of citizen science for its core purpose – scientific research – is lacking. We examined the contribution of citizen science to a review paper by ornithologists in which they formulated ten central claims about the impact of climate change on avian migration. Citizen science was never explicitly mentioned in the review article. For each of the claims, these ornithologists scored their opinions about the amount of research effort invested in each claim and how strongly the claim was supported by evidence. This allowed us to also determine whether their trust in claims was, unwittingly or not, related to the degree to which the claims relied primarily on data generated by citizen scientists. We found that papers based on citizen science constituted between 24 and 77% of the references backing each claim, with no evidence of a mistrust of claims that relied heavily on citizen-science data. We reveal that many of these papers may not easily be recognized as drawing upon volunteer contributions, as the search terms “citizen science” and “volunteer” would have overlooked the majority of the studies that back the ten claims about birds and climate change. Our results suggest that the significance of citizen science to global research, an endeavor that is reliant on long-term information at large spatial scales, might be far greater than is readily perceived. To better understand and track the contributions of citizen science in the future, we urge researchers to use the keyword “citizen science” in papers that draw on efforts of non-professionals.
Collapse
Affiliation(s)
- Caren B. Cooper
- Cornell Lab of Ornithology, Ithaca, New York, United States of America
- * E-mail:
| | - Jennifer Shirk
- Cornell Lab of Ornithology, Ithaca, New York, United States of America
| | | |
Collapse
|
17
|
Ashcroft MB, Gollan JR, Ramp D. Creating vegetation density profiles for a diverse range of ecological habitats using terrestrial laser scanning. Methods Ecol Evol 2014. [DOI: 10.1111/2041-210x.12157] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Affiliation(s)
- Michael B. Ashcroft
- Australian Museum; Sydney NSW 2010 Australia
- School of Biological, Earth and Environmental Sciences; Australian Wetlands, Rivers and Landscapes Centre; The University of New South Wales; Sydney NSW 2052 Australia
| | - John R. Gollan
- Australian Museum; Sydney NSW 2010 Australia
- School of the Environment; University of Technology; Sydney NSW 2007 Australia
| | - Daniel Ramp
- School of the Environment; University of Technology; Sydney NSW 2007 Australia
| |
Collapse
|