Crowdsourced geometric morphometrics enable rapid large-scale collection and analysis of phenotypic data

Jonathan Chang, Michael E. Alfaro

Research output: Contribution to journalArticleResearchpeer-review

16 Citations (Scopus)

Abstract

Advances in genomics and informatics have enabled the production of large phylogenetic trees. However, the ability to collect large phenotypic data sets 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.

Original languageEnglish
Pages (from-to)472-482
Number of pages11
JournalMethods in Ecology and Evolution
Volume7
Issue number4
DOIs
Publication statusPublished - 1 Apr 2016
Externally publishedYes

Keywords

  • Actinopterygii
  • Comparative methods
  • Large-scale annotation
  • Macroevolution
  • Mechanical Turk

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