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Iteratively forecasting biological invasions with PoPS and a little help from our friends.
Jones, Chris M; Jones, Shannon; Petrasova, Anna; Petras, Vaclav; Gaydos, Devon; Skrip, Megan M; Takeuchi, Yu; Bigsby, Kevin; Meentemeyer, Ross K.
Afiliação
  • Jones CM; Center for Geospatial Analytics North Carolina State University Raleigh NC.
  • Jones S; Center for Geospatial Analytics North Carolina State University Raleigh NC.
  • Petrasova A; Center for Geospatial Analytics North Carolina State University Raleigh NC.
  • Petras V; Center for Geospatial Analytics North Carolina State University Raleigh NC.
  • Gaydos D; Center for Geospatial Analytics North Carolina State University Raleigh NC.
  • Skrip MM; Animal and Plant Health Inspection Service (APHIS) US Department of Agriculture (USDA) Riverdale MD.
  • Takeuchi Y; Center for Geospatial Analytics North Carolina State University Raleigh NC.
  • Bigsby K; Center for Integrated Pest Management North Carolina State University Raleigh NC.
  • Meentemeyer RK; APHIS USDA Raleigh NC.
Front Ecol Environ ; 19(7): 411-418, 2021 Sep.
Article em En | MEDLINE | ID: mdl-34588928
ABSTRACT
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.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Front Ecol Environ Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Front Ecol Environ Ano de publicação: 2021 Tipo de documento: Article