Cargando…

A quantitative evaluation of a qualitative risk assessment framework: Examining the assumptions and predictions of the Productivity Susceptibility Analysis (PSA)

Qualitative risk assessment frameworks, such as the Productivity Susceptibility Analysis (PSA), have been developed to rapidly evaluate the risks of fishing to marine populations and prioritize management and research among species. Despite being applied to over 1,000 fish populations, and an ongoin...

Descripción completa

Detalles Bibliográficos
Autores principales: Hordyk, Adrian R., Carruthers, Thomas R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5983465/
https://www.ncbi.nlm.nih.gov/pubmed/29856869
http://dx.doi.org/10.1371/journal.pone.0198298
_version_ 1783328422954532864
author Hordyk, Adrian R.
Carruthers, Thomas R.
author_facet Hordyk, Adrian R.
Carruthers, Thomas R.
author_sort Hordyk, Adrian R.
collection PubMed
description Qualitative risk assessment frameworks, such as the Productivity Susceptibility Analysis (PSA), have been developed to rapidly evaluate the risks of fishing to marine populations and prioritize management and research among species. Despite being applied to over 1,000 fish populations, and an ongoing debate about the most appropriate method to convert biological and fishery characteristics into an overall measure of risk, the assumptions and predictive capacity of these approaches have not been evaluated. Several interpretations of the PSA were mapped to a conventional age-structured fisheries dynamics model to evaluate the performance of the approach under a range of assumptions regarding exploitation rates and measures of biological risk. The results demonstrate that the underlying assumptions of these qualitative risk-based approaches are inappropriate, and the expected performance is poor for a wide range of conditions. The information required to score a fishery using a PSA-type approach is comparable to that required to populate an operating model and evaluating the population dynamics within a simulation framework. In addition to providing a more credible characterization of complex system dynamics, the operating model approach is transparent, reproducible and can evaluate alternative management strategies over a range of plausible hypotheses for the system.
format Online
Article
Text
id pubmed-5983465
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-59834652018-06-17 A quantitative evaluation of a qualitative risk assessment framework: Examining the assumptions and predictions of the Productivity Susceptibility Analysis (PSA) Hordyk, Adrian R. Carruthers, Thomas R. PLoS One Research Article Qualitative risk assessment frameworks, such as the Productivity Susceptibility Analysis (PSA), have been developed to rapidly evaluate the risks of fishing to marine populations and prioritize management and research among species. Despite being applied to over 1,000 fish populations, and an ongoing debate about the most appropriate method to convert biological and fishery characteristics into an overall measure of risk, the assumptions and predictive capacity of these approaches have not been evaluated. Several interpretations of the PSA were mapped to a conventional age-structured fisheries dynamics model to evaluate the performance of the approach under a range of assumptions regarding exploitation rates and measures of biological risk. The results demonstrate that the underlying assumptions of these qualitative risk-based approaches are inappropriate, and the expected performance is poor for a wide range of conditions. The information required to score a fishery using a PSA-type approach is comparable to that required to populate an operating model and evaluating the population dynamics within a simulation framework. In addition to providing a more credible characterization of complex system dynamics, the operating model approach is transparent, reproducible and can evaluate alternative management strategies over a range of plausible hypotheses for the system. Public Library of Science 2018-06-01 /pmc/articles/PMC5983465/ /pubmed/29856869 http://dx.doi.org/10.1371/journal.pone.0198298 Text en © 2018 Hordyk, Carruthers http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Hordyk, Adrian R.
Carruthers, Thomas R.
A quantitative evaluation of a qualitative risk assessment framework: Examining the assumptions and predictions of the Productivity Susceptibility Analysis (PSA)
title A quantitative evaluation of a qualitative risk assessment framework: Examining the assumptions and predictions of the Productivity Susceptibility Analysis (PSA)
title_full A quantitative evaluation of a qualitative risk assessment framework: Examining the assumptions and predictions of the Productivity Susceptibility Analysis (PSA)
title_fullStr A quantitative evaluation of a qualitative risk assessment framework: Examining the assumptions and predictions of the Productivity Susceptibility Analysis (PSA)
title_full_unstemmed A quantitative evaluation of a qualitative risk assessment framework: Examining the assumptions and predictions of the Productivity Susceptibility Analysis (PSA)
title_short A quantitative evaluation of a qualitative risk assessment framework: Examining the assumptions and predictions of the Productivity Susceptibility Analysis (PSA)
title_sort quantitative evaluation of a qualitative risk assessment framework: examining the assumptions and predictions of the productivity susceptibility analysis (psa)
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5983465/
https://www.ncbi.nlm.nih.gov/pubmed/29856869
http://dx.doi.org/10.1371/journal.pone.0198298
work_keys_str_mv AT hordykadrianr aquantitativeevaluationofaqualitativeriskassessmentframeworkexaminingtheassumptionsandpredictionsoftheproductivitysusceptibilityanalysispsa
AT carruthersthomasr aquantitativeevaluationofaqualitativeriskassessmentframeworkexaminingtheassumptionsandpredictionsoftheproductivitysusceptibilityanalysispsa
AT hordykadrianr quantitativeevaluationofaqualitativeriskassessmentframeworkexaminingtheassumptionsandpredictionsoftheproductivitysusceptibilityanalysispsa
AT carruthersthomasr quantitativeevaluationofaqualitativeriskassessmentframeworkexaminingtheassumptionsandpredictionsoftheproductivitysusceptibilityanalysispsa