Is color data from citizen science photographs reliable for biodiversity research?

Color research continuously demands better methods and larger sample sizes. Citizen science (CS) projects are producing an ever-growing geo- and time-referenced set of photographs of organisms. These datasets have the potential to make a huge contribution to color research, but the reliability of these data need to be tested before widespread implementation.We compared the difference between color extracted from CS photographs with that of color extracted from controlled lighting conditions (i.e., the current gold standard in spectrometry) for both birds and plants. First, we tested the ability of CS photographs to quantify interspecific variability by assessing > 9,000 CS photographs of 537 Australian bird species with controlled museum spectrometry data. Second, we tested the ability of CS photographs to quantify intraspecific variability by measuring petal color data for two plant species using seven methods/sources with varying levels of control.For interspecific questions, we found that by averaging out variability through a large sample size, CS photographs capture a large proportion of across species variation in plumage color within the visual part of the spectrum (  = 0.68-0.71 for RGB space and 0.72-0.77 for CIE-LAB space). Between 12 and 14 photographs per species are necessary to achieve this averaging effect for interspecific studies. Unsurprisingly, the CS photographs taken with commercial cameras failed to capture information in the UV part of the spectrum. For intraspecific questions, decreasing levels of control increase the color variation but averaging larger sample sizes can partially mitigate this, aside from particular issues related to saturation and irregularities in light capture.CS photographs offer a very large sample size across space and time which offers statistical power for many color research questions. This study shows that CS photographs contain data that lines up closely with controlled measurements within the visual spectrum if the sample size is large enough, highlighting the potential of CS photographs for both interspecific and intraspecific ecological or biological questions. With regard to analyzing color in CS photographs, we suggest, as a starting point, to measure multiple random points within the ROI of each photograph for both patterned and unpatterned patches and approach the recommended sample size of 12-14 photographs per species for interspecific studies. Overall, this study provides groundwork in analyzing the reliability of a novel method, which can propel the field of studying color forward.