Shower thoughts: why scientists should spend more time in the rain

John T. Van Stan, Scott T. Allen, Douglas P. Aubrey, Z. Carter Berry, Matthew Biddick, Miriam A.M.J. Coenders-Gerrits, Paolo Giordani, Sybil G. Gotsch, Ethan D. Gutmann, Yakov Kuzyakov, Donat Magyar, Valentina S.A. Mella, Kevin E. Mueller, Alexandra G. Ponette-Gonzalez, Philipp Porada, Carla E. Rosenfeld, Jack Simmons, Kandikere R. Sridhar, Aron Stubbins, Travis Swanson

Research output: Contribution to journalSystematic reviewpeer-review

5 Scopus citations

Abstract

Stormwater is a vital resource and dynamic driver of terrestrial ecosystem processes. However, processes controlling interactions during and shortly after storms are often poorly seen and poorly sensed when direct observations are substituted with technological ones. We discuss how human observations complement technological ones and the benefits of scientists spending more time in the storm. Human observation can reveal ephemeral storm-related phenomena such as biogeochemical hot moments, organismal responses, and sedimentary processes that can then be explored in greater resolution using sensors and virtual experiments. Storm-related phenomena trigger lasting, oversized impacts on hydrologic and biogeochemical processes, organismal traits or functions, and ecosystem services at all scales. We provide examples of phenomena in forests, across disciplines and scales, that have been overlooked in past research to inspire mindful, holistic observation of ecosystems during storms. We conclude that technological observations alone are insufficient to trace the process complexity and unpredictability of fleeting biogeochemical or ecological events without the shower thoughts produced by scientists' human sensory and cognitive systems during storms.

Original languageEnglish
Pages (from-to)441-452
Number of pages12
JournalBioScience
Volume73
Issue number6
DOIs
StatePublished - Jun 1 2023

Keywords

  • climate change
  • condensation
  • ecosystem functioning
  • extreme event biogeochemistry
  • field and laboratory studies
  • precipitation
  • sampling bias

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