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Harnessing the power of digitized natural history collections to visualize spatiotemporal patterns in native and non-native bee flight phenology

  • Author(s): Wood, Zoe
  • Thrift, Charles
  • Hobson, Evan
  • Seltmann, Katja C
  • et al.
The data associated with this publication are available at:
https://doi.org/10.5281/zenodo.4282990
Abstract

What time of year are bees flying, where are they flying, and how do biogeographical factors, sex, and native status affect flight phenology? Consistent monitoring along with creating spatially and temporally explicit visualizations using large openly available data sets enhance our understanding of trends in flight time phenology and shape our understanding of bee-plant interactions, including shifts in the phenology of bee pollinators.

Species occurrence data from digitized collection networks (iNaturalist, Global Biodiversity Information Faculty (GBIF), Integrated Digitized Biocollections (iDigBio), Symbiota Collections of Arthropods Network (SCAN), and UC Santa Barbara Collection Network) are part of an effort to improve our understanding of bees in coastal Santa Barbara County, including the California Channel Islands. New inventory collections combined with historical data from over 11 natural history museums and 2 observation networks are used in an effort to examine patterns and changes in phenology of native and non-native bee species, and create updated species inventories.

Synthesizing species observation data from digitized natural history collections makes use of a wealth of existing data and multiplies the analytical power of isolated observations, but it is not without limitations and challenges. By exploring novel techniques to generate clear and accurate visualizations to communicate bee flight time, we present our key initial findings and identify geographic, temporal, and taxonomic gaps, which will lead to further focused inventory projects of coastal Santa Barbara County, improved data quality for phenological analyses, and reusable methods for visualizing insect phenology data across taxa or geography. 

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