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Modeling Dinophysis in Western Andalucía using an autoregressive hidden Markov model
Dinophysis spp. can produce diarrhetic shellfish toxins (DST) including okadaic acid and dinophysistoxins, and some strains can also produce non-diarrheic pectenotoxins. Although DSTs are of human health concern and have motivated environmental monitoring programs in many locations, these monitoring...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9762684/ https://www.ncbi.nlm.nih.gov/pubmed/36540783 http://dx.doi.org/10.1007/s10651-022-00534-7 |
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author | Aron, Jordan Albert, Paul S. Gribble, Matthew O. |
author_facet | Aron, Jordan Albert, Paul S. Gribble, Matthew O. |
author_sort | Aron, Jordan |
collection | PubMed |
description | Dinophysis spp. can produce diarrhetic shellfish toxins (DST) including okadaic acid and dinophysistoxins, and some strains can also produce non-diarrheic pectenotoxins. Although DSTs are of human health concern and have motivated environmental monitoring programs in many locations, these monitoring programs often have temporal data gaps (e.g., days without measurements). This paper presents a model for the historical time-series, on a daily basis, of DST-producing toxigenic Dinophysis in 8 monitored locations in western Andalucía over 2015–2020, incorporating measurements of algae counts and DST levels. We fitted a bivariate hidden Markov Model (HMM) incorporating an autoregressive correlation among the observed DST measurements to account for environmental persistence of DST. We then reconstruct the maximum-likelihood profile of algae presence in the water column at daily intervals using the Viterbi algorithm. Using historical monitoring data from Andalucía, the model estimated that potentially toxigenic Dinophysis algae is present at greater than or equal to 250 cells/L between < 1% and >10% of the year depending on the site and year. The historical time-series reconstruction enabled by this method may facilitate future investigations into temporal dynamics of toxigenic Dinophysis blooms. |
format | Online Article Text |
id | pubmed-9762684 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
record_format | MEDLINE/PubMed |
spelling | pubmed-97626842022-12-19 Modeling Dinophysis in Western Andalucía using an autoregressive hidden Markov model Aron, Jordan Albert, Paul S. Gribble, Matthew O. Environ Ecol Stat Article Dinophysis spp. can produce diarrhetic shellfish toxins (DST) including okadaic acid and dinophysistoxins, and some strains can also produce non-diarrheic pectenotoxins. Although DSTs are of human health concern and have motivated environmental monitoring programs in many locations, these monitoring programs often have temporal data gaps (e.g., days without measurements). This paper presents a model for the historical time-series, on a daily basis, of DST-producing toxigenic Dinophysis in 8 monitored locations in western Andalucía over 2015–2020, incorporating measurements of algae counts and DST levels. We fitted a bivariate hidden Markov Model (HMM) incorporating an autoregressive correlation among the observed DST measurements to account for environmental persistence of DST. We then reconstruct the maximum-likelihood profile of algae presence in the water column at daily intervals using the Viterbi algorithm. Using historical monitoring data from Andalucía, the model estimated that potentially toxigenic Dinophysis algae is present at greater than or equal to 250 cells/L between < 1% and >10% of the year depending on the site and year. The historical time-series reconstruction enabled by this method may facilitate future investigations into temporal dynamics of toxigenic Dinophysis blooms. 2022-09 2022-05-04 /pmc/articles/PMC9762684/ /pubmed/36540783 http://dx.doi.org/10.1007/s10651-022-00534-7 Text en https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Aron, Jordan Albert, Paul S. Gribble, Matthew O. Modeling Dinophysis in Western Andalucía using an autoregressive hidden Markov model |
title | Modeling Dinophysis in Western Andalucía using an autoregressive hidden Markov model |
title_full | Modeling Dinophysis in Western Andalucía using an autoregressive hidden Markov model |
title_fullStr | Modeling Dinophysis in Western Andalucía using an autoregressive hidden Markov model |
title_full_unstemmed | Modeling Dinophysis in Western Andalucía using an autoregressive hidden Markov model |
title_short | Modeling Dinophysis in Western Andalucía using an autoregressive hidden Markov model |
title_sort | modeling dinophysis in western andalucía using an autoregressive hidden markov model |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9762684/ https://www.ncbi.nlm.nih.gov/pubmed/36540783 http://dx.doi.org/10.1007/s10651-022-00534-7 |
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