Cargando…

A structured elicitation method to identify key direct risk factors for the management of natural resources

The high level of uncertainty inherent in natural resource management requires planners to apply comprehensive risk analyses, often in situations where there are few resources. In this paper, we demonstrate a broadly applicable, novel and structured elicitation approach to identify important direct...

Descripción completa

Detalles Bibliográficos
Autores principales: Smith, Michael, Wallace, Ken, Lewis, Loretta, Wagner, Christian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4945618/
https://www.ncbi.nlm.nih.gov/pubmed/27441228
http://dx.doi.org/10.1016/j.heliyon.2015.e00043
_version_ 1782442896421552128
author Smith, Michael
Wallace, Ken
Lewis, Loretta
Wagner, Christian
author_facet Smith, Michael
Wallace, Ken
Lewis, Loretta
Wagner, Christian
author_sort Smith, Michael
collection PubMed
description The high level of uncertainty inherent in natural resource management requires planners to apply comprehensive risk analyses, often in situations where there are few resources. In this paper, we demonstrate a broadly applicable, novel and structured elicitation approach to identify important direct risk factors. This new approach combines expert calibration and fuzzy based mathematics to capture and aggregate subjective expert estimates of the likelihood that a set of direct risk factors will cause management failure. A specific case study is used to demonstrate the approach; however, the described methods are widely applicable in risk analysis. For the case study, the management target was to retain all species that characterise a set of natural biological elements. The analysis was bounded by the spatial distribution of the biological elements under consideration and a 20-year time frame. Fourteen biological elements were expected to be at risk. Eleven important direct risk factors were identified that related to surrounding land use practices, climate change, problem species (e.g., feral predators), fire and hydrological change. In terms of their overall influence, the two most important risk factors were salinisation and a lack of water which together pose a considerable threat to the survival of nine biological elements. The described approach successfully overcame two concerns arising from previous risk analysis work: (1) the lack of an intuitive, yet comprehensive scoring method enabling the detection and clarification of expert agreement and associated levels of uncertainty; and (2) the ease with which results can be interpreted and communicated while preserving a rich level of detail essential for informed decision making.
format Online
Article
Text
id pubmed-4945618
institution National Center for Biotechnology Information
language English
publishDate 2015
publisher Elsevier
record_format MEDLINE/PubMed
spelling pubmed-49456182016-07-20 A structured elicitation method to identify key direct risk factors for the management of natural resources Smith, Michael Wallace, Ken Lewis, Loretta Wagner, Christian Heliyon Article The high level of uncertainty inherent in natural resource management requires planners to apply comprehensive risk analyses, often in situations where there are few resources. In this paper, we demonstrate a broadly applicable, novel and structured elicitation approach to identify important direct risk factors. This new approach combines expert calibration and fuzzy based mathematics to capture and aggregate subjective expert estimates of the likelihood that a set of direct risk factors will cause management failure. A specific case study is used to demonstrate the approach; however, the described methods are widely applicable in risk analysis. For the case study, the management target was to retain all species that characterise a set of natural biological elements. The analysis was bounded by the spatial distribution of the biological elements under consideration and a 20-year time frame. Fourteen biological elements were expected to be at risk. Eleven important direct risk factors were identified that related to surrounding land use practices, climate change, problem species (e.g., feral predators), fire and hydrological change. In terms of their overall influence, the two most important risk factors were salinisation and a lack of water which together pose a considerable threat to the survival of nine biological elements. The described approach successfully overcame two concerns arising from previous risk analysis work: (1) the lack of an intuitive, yet comprehensive scoring method enabling the detection and clarification of expert agreement and associated levels of uncertainty; and (2) the ease with which results can be interpreted and communicated while preserving a rich level of detail essential for informed decision making. Elsevier 2015-11-24 /pmc/articles/PMC4945618/ /pubmed/27441228 http://dx.doi.org/10.1016/j.heliyon.2015.e00043 Text en © 2015 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Smith, Michael
Wallace, Ken
Lewis, Loretta
Wagner, Christian
A structured elicitation method to identify key direct risk factors for the management of natural resources
title A structured elicitation method to identify key direct risk factors for the management of natural resources
title_full A structured elicitation method to identify key direct risk factors for the management of natural resources
title_fullStr A structured elicitation method to identify key direct risk factors for the management of natural resources
title_full_unstemmed A structured elicitation method to identify key direct risk factors for the management of natural resources
title_short A structured elicitation method to identify key direct risk factors for the management of natural resources
title_sort structured elicitation method to identify key direct risk factors for the management of natural resources
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4945618/
https://www.ncbi.nlm.nih.gov/pubmed/27441228
http://dx.doi.org/10.1016/j.heliyon.2015.e00043
work_keys_str_mv AT smithmichael astructuredelicitationmethodtoidentifykeydirectriskfactorsforthemanagementofnaturalresources
AT wallaceken astructuredelicitationmethodtoidentifykeydirectriskfactorsforthemanagementofnaturalresources
AT lewisloretta astructuredelicitationmethodtoidentifykeydirectriskfactorsforthemanagementofnaturalresources
AT wagnerchristian astructuredelicitationmethodtoidentifykeydirectriskfactorsforthemanagementofnaturalresources
AT smithmichael structuredelicitationmethodtoidentifykeydirectriskfactorsforthemanagementofnaturalresources
AT wallaceken structuredelicitationmethodtoidentifykeydirectriskfactorsforthemanagementofnaturalresources
AT lewisloretta structuredelicitationmethodtoidentifykeydirectriskfactorsforthemanagementofnaturalresources
AT wagnerchristian structuredelicitationmethodtoidentifykeydirectriskfactorsforthemanagementofnaturalresources