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

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 planne...

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Autores principales: Jones, Chris M, Jones, Shannon, Petrasova, Anna, Petras, Vaclav, Gaydos, Devon, Skrip, Megan M, Takeuchi, Yu, Bigsby, Kevin, Meentemeyer, Ross K
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8453564/
https://www.ncbi.nlm.nih.gov/pubmed/34588928
http://dx.doi.org/10.1002/fee.2357
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author Jones, Chris M
Jones, Shannon
Petrasova, Anna
Petras, Vaclav
Gaydos, Devon
Skrip, Megan M
Takeuchi, Yu
Bigsby, Kevin
Meentemeyer, Ross K
author_facet Jones, Chris M
Jones, Shannon
Petrasova, Anna
Petras, Vaclav
Gaydos, Devon
Skrip, Megan M
Takeuchi, Yu
Bigsby, Kevin
Meentemeyer, Ross K
author_sort Jones, Chris M
collection PubMed
description 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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spelling pubmed-84535642021-09-27 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 Front Ecol Environ Concepts and Questions 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. John Wiley and Sons Inc. 2021-06-03 2021-09 /pmc/articles/PMC8453564/ /pubmed/34588928 http://dx.doi.org/10.1002/fee.2357 Text en © 2021 The Authors. Frontiers in Ecology and the Environment published by Wiley Periodicals LLC on behalf of the Ecological Society of America. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Concepts and Questions
Jones, Chris M
Jones, Shannon
Petrasova, Anna
Petras, Vaclav
Gaydos, Devon
Skrip, Megan M
Takeuchi, Yu
Bigsby, Kevin
Meentemeyer, Ross K
Iteratively forecasting biological invasions with PoPS and a little help from our friends
title Iteratively forecasting biological invasions with PoPS and a little help from our friends
title_full Iteratively forecasting biological invasions with PoPS and a little help from our friends
title_fullStr Iteratively forecasting biological invasions with PoPS and a little help from our friends
title_full_unstemmed Iteratively forecasting biological invasions with PoPS and a little help from our friends
title_short Iteratively forecasting biological invasions with PoPS and a little help from our friends
title_sort iteratively forecasting biological invasions with pops and a little help from our friends
topic Concepts and Questions
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8453564/
https://www.ncbi.nlm.nih.gov/pubmed/34588928
http://dx.doi.org/10.1002/fee.2357
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