Leveraging Community Science to Measure Bee Body Size From Museum Specimens Article Swipe
Madeleine M. Ostwald
,
Colleen Smith
,
Julie M. Allen
,
Alec Buetow
,
Anika Männer
,
Robert Guralnick
,
Craig Goldsmith
,
Katja C. Seltmann
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1002/ece3.71665
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1002/ece3.71665
Community or volunteer participation in research has the potential to significantly help mobilize the wealth of biodiversity and functional ecological data housed in natural history collections. Many such projects recruit community scientists to transcribe specimen label data from images; a next step is to task community scientists with conducting straightforward morphological measurements (e.g., body size) from specimen images. We investigated whether community science could be an effective approach to generating significant body size datasets from specimen images generated by museum digitization initiatives. Using the community science platform Notes from Nature, we engaged community scientists in a specimen measurement task to estimate body size (i.e., intertegular distance) from images of bee specimens. Community scientists showed high engagement and completion of this task, with each user measuring 43.6 specimens on average and self‐reporting successful measurement of 98.0% of the images. Community scientist measurements were significantly larger than measurements conducted by trained researchers, though the average measurement error was only 2.3%. These results suggest that community science participation could be an effective approach for bee body size measurement, for descriptive studies or for research questions where this degree of expected error is deemed acceptable. For larger‐bodied organisms (e.g., vertebrates), where modest measurement errors represent a smaller proportion of body size, community science approaches may be particularly effective. Methods we present here may serve as a blueprint for future projects aimed at engaging the public in biodiversity and collections‐based research efforts.
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https://doi.org/10.1002/ece3.71665Digital Object Identifier
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Leveraging Community Science to Measure Bee Body Size From Museum SpecimensWork title
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articleOpenAlex work type
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enPrimary language
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2025Year of publication
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2025-06-01Full publication date if available
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Madeleine M. Ostwald, Colleen Smith, Julie M. Allen, Alec Buetow, Anika Männer, Robert Guralnick, Craig Goldsmith, Katja C. SeltmannList of authors in order
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https://doi.org/10.1002/ece3.71665Publisher landing page
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://doi.org/10.1002/ece3.71665Direct OA link when available
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Measure (data warehouse), Honey bee, Citizen science, Biology, Ecology, Computer science, Botany, Data miningTop concepts (fields/topics) attached by OpenAlex
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