4.7 Article

Iteratively forecasting biological invasions with PoPS and a little help from our friends

Journal

FRONTIERS IN ECOLOGY AND THE ENVIRONMENT
Volume 19, Issue 7, Pages 411-418

Publisher

WILEY
DOI: 10.1002/fee.2357

Keywords

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Funding

  1. US National Science Foundation (NSF), joint NSF-National Institutes of Health Ecology and Evolution of Infectious Diseases Program [2015-67013-23818]
  2. Google Cloud
  3. NVIDIA

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Ecological forecasting has the potential to support environmental decision making, but is rarely used by resource managers. The PoPS Forecasting Platform, an open-source framework, allows for co-designing short-term iterative forecasts of biological invasions, demonstrating higher forecast skill through iterative calibration.
Ecological forecasting has vast potential to support environmental decision making with repeated, testable predictions across management-relevant timescales and locations. Yet resource managers rarely use co-designed forecasting systems or embed them in decision making. Although prediction of planned management outcomes is particularly important for biological invasions to optimize when and where resources should be allocated, spatial-temporal models of spread typically have not been openly shared, iteratively updated, or interactive to facilitate exploration of management actions. We describe a species-agnostic, open-source framework - called the Pest or Pathogen Spread (PoPS) Forecasting Platform - for co-designing near-term iterative forecasts of biological invasions. Two case studies are presented to demonstrate that iterative calibration yields higher forecast skill than using only the earliest-available data to predict future spread. The PoPS framework is a primary example of an ecological forecasting system that has been both scientifically improved and optimized for real-world decision making through sustained participation and use by management stakeholders.

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