A Bayesian approach for assessing the boundary between desirable and undesirable environmental status – An example from a coastal fish indicator in the Baltic Sea
Ecological indicator approaches typically compare the prevailing state of an ecosystem component to a reference state reflecting good environmental conditions, i.e. the desirable state. However, defining the reference state is challenging due to a wide range of uncertainties related to natural varia...
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2021
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oai:doaj.org-article:f50715dc82614d8eb9ea3459c755022d2021-12-01T04:31:25ZA Bayesian approach for assessing the boundary between desirable and undesirable environmental status – An example from a coastal fish indicator in the Baltic Sea1470-160X10.1016/j.ecolind.2020.106975https://doaj.org/article/f50715dc82614d8eb9ea3459c755022d2021-01-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X20309146https://doaj.org/toc/1470-160XEcological indicator approaches typically compare the prevailing state of an ecosystem component to a reference state reflecting good environmental conditions, i.e. the desirable state. However, defining the reference state is challenging due to a wide range of uncertainties related to natural variability and measurement error in data, as well as ecological understanding. This study propose a novel probabilistic approach combining historical monitoring data and ecological understanding to estimate the uncertainty associated with the boundary value of an ecological indicator between good and poor environmental states. Bayesian inference is used to estimate the epistemic uncertainty about the true state of an indicator variable during an historical reference period. This approach replaces the traditional boundary value with probability distribution, indicating the uncertainty about the boundary between environmental states providing a transparent safety margin associated with the risk of misclassification of the indicator’s state. The approach is demonstrated by applying it to a time-series of an ecological status indicator, ‘Abundance of coastal key fish species’, included in HELCOM’s Baltic Sea regional status assessment. We suggest that acknowledgement of the uncertainty behind the final classification leads to more transparent and better-informed decision-making processes.Mirka Laurila-PantSamu MäntyniemiÖrjan ÖstmanJens OlssonLaura UusitaloAnnukka LehikoinenElsevierarticleStatus assessmentClassification uncertaintyMSFDPerca fluviatilisGood environmental statusEcologyQH540-549.5ENEcological Indicators, Vol 120, Iss , Pp 106975- (2021) |
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Status assessment Classification uncertainty MSFD Perca fluviatilis Good environmental status Ecology QH540-549.5 |
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Status assessment Classification uncertainty MSFD Perca fluviatilis Good environmental status Ecology QH540-549.5 Mirka Laurila-Pant Samu Mäntyniemi Örjan Östman Jens Olsson Laura Uusitalo Annukka Lehikoinen A Bayesian approach for assessing the boundary between desirable and undesirable environmental status – An example from a coastal fish indicator in the Baltic Sea |
| description |
Ecological indicator approaches typically compare the prevailing state of an ecosystem component to a reference state reflecting good environmental conditions, i.e. the desirable state. However, defining the reference state is challenging due to a wide range of uncertainties related to natural variability and measurement error in data, as well as ecological understanding. This study propose a novel probabilistic approach combining historical monitoring data and ecological understanding to estimate the uncertainty associated with the boundary value of an ecological indicator between good and poor environmental states. Bayesian inference is used to estimate the epistemic uncertainty about the true state of an indicator variable during an historical reference period. This approach replaces the traditional boundary value with probability distribution, indicating the uncertainty about the boundary between environmental states providing a transparent safety margin associated with the risk of misclassification of the indicator’s state. The approach is demonstrated by applying it to a time-series of an ecological status indicator, ‘Abundance of coastal key fish species’, included in HELCOM’s Baltic Sea regional status assessment. We suggest that acknowledgement of the uncertainty behind the final classification leads to more transparent and better-informed decision-making processes. |
| format |
article |
| author |
Mirka Laurila-Pant Samu Mäntyniemi Örjan Östman Jens Olsson Laura Uusitalo Annukka Lehikoinen |
| author_facet |
Mirka Laurila-Pant Samu Mäntyniemi Örjan Östman Jens Olsson Laura Uusitalo Annukka Lehikoinen |
| author_sort |
Mirka Laurila-Pant |
| title |
A Bayesian approach for assessing the boundary between desirable and undesirable environmental status – An example from a coastal fish indicator in the Baltic Sea |
| title_short |
A Bayesian approach for assessing the boundary between desirable and undesirable environmental status – An example from a coastal fish indicator in the Baltic Sea |
| title_full |
A Bayesian approach for assessing the boundary between desirable and undesirable environmental status – An example from a coastal fish indicator in the Baltic Sea |
| title_fullStr |
A Bayesian approach for assessing the boundary between desirable and undesirable environmental status – An example from a coastal fish indicator in the Baltic Sea |
| title_full_unstemmed |
A Bayesian approach for assessing the boundary between desirable and undesirable environmental status – An example from a coastal fish indicator in the Baltic Sea |
| title_sort |
bayesian approach for assessing the boundary between desirable and undesirable environmental status – an example from a coastal fish indicator in the baltic sea |
| publisher |
Elsevier |
| publishDate |
2021 |
| url |
https://doaj.org/article/f50715dc82614d8eb9ea3459c755022d |
| work_keys_str_mv |
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