Observations from the USA National Phenology Network can be leveraged to model airborne pollen

Daniel S.W. Katz, Elizabeth Vogt, Arie Manangan, Claudia L. Brown, Dan Dalan, Kai Zhu, Yiluan Song, Theresa M. Crimmins

Research output: Contribution to journalArticlepeer-review

Abstract

The USA National Phenology Network (USA-NPN) hosts the largest volunteer-contributed collection of plant phenology observations in the USA. The potential contributions of these spatially and temporally explicit observations of flowers and pollen cones to the field of aerobiology remain largely unexplored. Here, we introduce this freely available dataset and demonstrate its prospective applications for modeling airborne pollen in a case study. Specifically, we compare the timing of 4265 observations of flowering for oak (Quercus) trees in the eastern USA to winter–spring temperatures. We then use this relationship to predict the day of peak flowering at 15 pollen monitoring stations in 15 years and compare the predicted day of peak flowering to the peak day of measured pollen (n = 111 station-years). There was a strong association between winter–spring temperature and the presence of open flowers (r2 = 0.66, p < 0.0001) and the predicted peak flowering was strongly correlated with peak airborne pollen concentrations (r2 = 0.81, p < 0.0001). These results demonstrate the potential for the USA-NPN’s phenological observations to underpin source-based models of airborne pollen. We also highlight opportunities for leveraging and enhancing this near real-time dataset for aerobiological applications.

Original languageEnglish (US)
Pages (from-to)169-174
Number of pages6
JournalAerobiologia
Volume39
Issue number1
DOIs
StatePublished - Mar 2023

Keywords

  • Citizen science
  • Flowers
  • Open data
  • Phenological models
  • Pollen cones

ASJC Scopus subject areas

  • Immunology and Allergy
  • Immunology
  • Plant Science

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