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Data from: Continent‐scale phenotype mapping using citizen scientists’ photographs

Cite this dataset

Drury, Jonathan P. et al. (2019). Data from: Continent‐scale phenotype mapping using citizen scientists’ photographs [Dataset]. Dryad.


Field investigations of phenotypic variation in free‐living organisms are often limited in scope owing to time and funding constraints. By collaborating with online communities of amateur naturalists, investigators can greatly increase the amount and diversity of phenotypic data in their analyses while simultaneously engaging with a public audience. Here, we present a method for quantifying phenotypes of individual organisms in citizen scientists’ photographs. We then show that our protocol for measuring wing phenotypes from photographs yields accurate measurements in two species of Calopterygid damselflies. Next, we show that, while most observations of our target species were made by members of the large and established community of amateur naturalists at, our efforts to increase recruitment through various outreach initiatives were successful. Finally, we present results from two case studies: (1) an analysis of wing pigmentation in male smoky rubyspots (Hetaerina titia) showing previously undocumented geographical variation in a seasonal polyphenism, and (2) an analysis of variation in the relative size of the wing spots of male banded demoiselles (Calopteryx splendens) in Great Britain questioning previously documented evidence for character displacement. Our results demonstrate that our protocol can be used to create high quality phenotypic datasets using citizen scientists’ photographs, and, when combined with metadata (e.g., date and location), can greatly broaden the scope of studies of geographical and temporal variation in phenotypes. Our analyses of the recruitment and engagement process also demonstrate that collaborating with an online community of amateur naturalists can be a powerful way to conduct hypothesis‐driven research aiming to elucidate the processes that impact trait evolution at landscape scales.

Usage notes


National Science Foundation, Award: DEB-1457844, DEB-1213348


Great Britain
United States
Costa Rica