The risks and rewards of community science for threatened species monitoring

Soroye, Peter; Edwards, Brandon P.M.; Buxton, Rachel T.; Ethier, Jeffrey P.; Frempong‐Manso, Acacia; Keefe, Hannah E.; Berberi, Albana; Roach‐Krajewski, Maisy; Binley, Allison D.; Vincent, Jaimie G.; Lin, Hsien‐Yung; Cooke, Steven J.; Bennett, Joseph

doi:10.1111/csp2.12788

Cited by 17 publications

(26 citation statements)

References 59 publications

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“…Community science is inherently open and sharing the location of these species may put them at greater risk (Tulloch et al, 2018). Safeguards that protect the location of at-risk species and the well-being of wildlife populations, as well as the safety of the people observing these species, can be put in place for monitoring sensitive species with community science initiatives (Soroye et al, 2022).…”

Section: Discussionmentioning

confidence: 99%

“…The spatial and temporal scale of a community science project, along with scientific rigour and data availability, are major factors in predicting whether the data from a community science project are used in peer-reviewed literature (Theobald et al 2015). Most data are concentrated around populous cities and accessible areas such as parks and near roads (Geldmann et al, 2016;Soroye et al, 2022) and are biased towards more charismatic species such as butterflies and birds . CC-BY-NC-ND 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.…”

Section: Introductionmentioning

confidence: 99%

“…The copyright holder for this preprint this version posted October 21, 2022. ; https://doi.org/10.1101/2022.10.17.512636 doi: bioRxiv preprint (Theobald et al, 2015). Community science is often regarded only as a source of baseline surveillance data (Dickinson et al, 2010), and enlisting the public to help monitor sensitive species can pose significant risks (Soroye et al, 2022). These patterns could be perpetuated into the literature, compounding similar existing research biases (Donaldson et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

“…The spatial and temporal scale of a community science project, along with scientific rigour and data availability, are major factors in predicting whether the data from a community science project are used in peer-reviewed literature (Theobald et al 2015). Most data are concentrated around populous cities and accessible areas such as parks and near roads (Geldmann et al, 2016; Soroye et al, 2022) and are biased towards more charismatic species such as butterflies and birds (Theobald et al, 2015). Community science is often regarded only as a source of baseline surveillance data (Dickinson et al, 2010), and enlisting the public to help monitor sensitive species can pose significant risks (Soroye et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

“…Most data are concentrated around populous cities and accessible areas such as parks and near roads (Geldmann et al, 2016; Soroye et al, 2022) and are biased towards more charismatic species such as butterflies and birds (Theobald et al, 2015). Community science is often regarded only as a source of baseline surveillance data (Dickinson et al, 2010), and enlisting the public to help monitor sensitive species can pose significant risks (Soroye et al, 2022). These patterns could be perpetuated into the literature, compounding similar existing research biases (Donaldson et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

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Patterns of community science data use in peer-reviewed research on biodiversity

Binley

Vincent

Rytwinski

et al. 2022

Preprint

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Community science (“citizen science”) represent a potentially abundant and inexpensive source of information for biodiversity research. However, analyzing such data has inherent challenges. To explore where and how community science data are translated into scientific knowledge, we conducted a literature review in a sample of 334 peer-reviewed scientific articles. Specifically, we investigated how the use of community science data varied among taxonomic groups and geographic regions, and what threats to biodiversity, if any, were examined. Community science data were used mostly for research on birds and invertebrates, and the data used were mainly from the United States and the United Kingdom. Literature in certain countries used a wider breadth of projects, while others made repeated use of comparably fewer datasets. Community science efforts were largely used to measure abundance, trends, distributions, and range shifts. However, few articles linked these metrics to any particular threats to biodiversity. Furthermore, community science data were used infrequently for research on threatened species and limited mostly to count data rather than collecting more specific information such as life history, phenological or genetic data, suggesting that community science may be underutilized for these key aspects of biodiversity conservation. We conclude that even with the rise of community science data use in research, there remains tremendous potential to better use these existing datasets for biodiversity research.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…The spatial and temporal scale of a community science project, along with scientific rigour and data availability, are major factors in predicting whether the data from a community science project are used in peer-reviewed literature (Theobald et al 2015). Most data are concentrated around populous cities and accessible areas such as parks and near roads (Geldmann et al, 2016; Soroye et al, 2022) and are biased towards more charismatic species such as butterflies and birds (Theobald et al, 2015). Community science is often regarded only as a source of baseline surveillance data (Dickinson et al, 2010), and enlisting the public to help monitor sensitive species can pose significant risks (Soroye et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Patterns of community science data use in peer-reviewed research on biodiversity

Binley

Vincent

Rytwinski

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

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Minimizing Data Waste: Conservation in the Big Data Era

Binley

Edwards

Dansereau

et al. 2023

Bulletin Ecologic Soc America

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Session motivation and objectivesAdvances in computing, statistics, and technology over the past few decades has resulted in the accumulation of massive amounts of biodiversity data, as well as novel methods for using and integrating them (Miller et al. 2019). Data that have been collected for decades or even centuries can now be analyzed and applied in brand new ways. These data include alternative sources of information such as citizen science (also called community science) programs (Butcher et al. 1990, Sullivan et al. 2014, Hudson et al. 2017). In the midst of a global biodiversity crisis, these databases may hold the key to detecting important obstacles and threats to conservation, as well as determining the best interventions before it is too late. The ecological processes in question frequently occur across broad spatial and temporal scales; migratory species' ranges can span thousands of kilometers, and the impacts of threats such as climate change cannot necessarily be assessed on a local scale. Conventional methods of biodiversity monitoring may therefore be inadequate in the face of broad scale change. The individual researcher can generally only collect data on a localized scale, yet with the proper data practices, this information can contribute to a better understanding of the bigger picture (Sutherland et al. 2009).

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