Which mammals can be identified from camera traps and crowdsourced photographs?

Roland Kays, Monica Lasky, Maximilian L. Allen, Robert C. Dowler, Melissa T.R. Hawkins, Andrew G. Hope, Brooks A. Kohli, Verity L. Mathis, Bryan McLean, Link E. Olson, Cody W. Thompson, Daniel Thornton, Jane Widness, Michael V. Cove

Research output: Contribution to journalArticlepeer-review

Abstract

While museum voucher specimens continue to be the standard for species identifications, biodiversity data are increasingly represented by photographic records from camera traps and amateur naturalists. Some species are easily recognized in these pictures, others are impossible to distinguish. Here we quantify the extent to which 335 terrestrial nonvolant North American mammals can be identified in typical photographs, with and without considering species range maps. We evaluated all pairwise comparisons of species and judged, based on professional opinion, whether they are visually distinguishable in typical pictures from camera traps or the iNaturalist crowdsourced platform on a 4-point scale: (1) always, (2) usually, (3) rarely, or (4) never. Most (96.5%) of the 55,944 pairwise comparisons were ranked as always or usually distinguishable in a photograph, leaving exactly 2,000 pairs of species that can rarely or never be distinguished from typical pictures, primarily within clades such as shrews and small-bodied rodents. Accounting for a species geographic range eliminates many problematic comparisons, such that the average number of difficult or impossible-to-distinguish species pairs from any location was 7.3 when considering all species, or 0.37 when considering only those typically surveyed with camera traps. The greatest diversity of difficult-to-distinguish species was in Arizona and New Mexico, with 57 difficult pairs of species, suggesting the problem scales with overall species diversity. Our results show which species are most readily differentiated by photographic data and which taxa should be identified only to higher taxonomic levels (e.g., genus). Our results are relevant to ecologists, as well as those using artificial intelligence to identify species in photographs, but also serve as a reminder that continued study of mammals through museum vouchers is critical since it is the only way to accurately identify many smaller species, provides a wealth of data unattainable from photographs, and constrains photographic records via accurate range maps. Ongoing specimen voucher collection, in addition to photographs, will become even more important as species ranges change, and photographic evidence alone will not be sufficient to document these dynamics for many species.

Original languageEnglish (US)
Pages (from-to)767-775
Number of pages9
JournalJournal of Mammalogy
Volume103
Issue number4
DOIs
StatePublished - Aug 1 2022

Keywords

  • artificial intelligence
  • biodiversity
  • camera trap
  • citizen science
  • curation
  • identification
  • iNaturalist
  • photograph
  • range map
  • voucher

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Ecology
  • Animal Science and Zoology
  • Genetics
  • Nature and Landscape Conservation

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