TY - JOUR T1 - Crowdsourced geometric morphometrics enable rapid large-scale collection and analysis of phenotypic data JF - bioRxiv DO - 10.1101/023382 SP - 023382 AU - Jonathan Chang AU - Michael E. Alfaro Y1 - 2015/01/01 UR - http://biorxiv.org/content/early/2015/07/28/023382.abstract N2 - Advances in genomics and informatics have enabled the production of large phylogenetic trees. However, the ability to collect large phenotypic datasets has not kept pace.Here, we present a method to quickly and accurately gather morphometric data using crowdsourced image-based landmarking.We find that crowdsourced workers perform similarly to experienced morphologists on the same digitization tasks. We also demonstrate the speed and accuracy of our method on seven families of ray-finned fishes (Actinopterygii).Crowdsourcing will enable the collection of morphological data across vast radiations of organisms, and can facilitate richer inference on the macroevolutionary processes that shape phenotypic diversity across the tree of life. ER -