Advances in the Early Warning of Shellfish Toxification by Dinophysis acuminata
In Western Europe, the incidence of DST is likely the highest globally, posing a significant threat with prolonged bans on shellfish harvesting, mainly caused by species of the dinoflagellate genus Dinophysis. Using a time series from 2014 to 2020, our study aimed (i) to determine the concentration...
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| Vydáno v: | Toxins Ročník 16; číslo 5; s. 204 |
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| Abstract | In Western Europe, the incidence of DST is likely the highest globally, posing a significant threat with prolonged bans on shellfish harvesting, mainly caused by species of the dinoflagellate genus Dinophysis. Using a time series from 2014 to 2020, our study aimed (i) to determine the concentration of D. acuminata in water at which shellfish toxin levels could surpass the regulatory limit (160 µg OA equiv kg−1) and (ii) to assess the predictability of toxic events for timely mitigation actions, especially concerning potential harvesting bans. The analysis considered factors such as (i) overdispersion in the data, (ii) distinct periods of presence and absence, (iii) the persistence of cells, and (iv) the temporal lag between cells in the water and toxins in shellfish. Four generalized additive models were tested, with the Tweedie (TW-GAM) model showing superior performance (>85%) and lower complexity. The results suggest existing thresholds currently employed (200 and 500 cells L−1) are well-suited for the Portuguese coast, supported by empirical evidence (54–79% accuracy). The developed algorithm allows for thresholds to be tailored on a case-by-case basis, offering flexibility for regional variations. |
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| AbstractList | In Western Europe, the incidence of DST is likely the highest globally, posing a significant threat with prolonged bans on shellfish harvesting, mainly caused by species of the dinoflagellate genus Dinophysis. Using a time series from 2014 to 2020, our study aimed (i) to determine the concentration of D. acuminata in water at which shellfish toxin levels could surpass the regulatory limit (160 µg OA equiv kg−1) and (ii) to assess the predictability of toxic events for timely mitigation actions, especially concerning potential harvesting bans. The analysis considered factors such as (i) overdispersion in the data, (ii) distinct periods of presence and absence, (iii) the persistence of cells, and (iv) the temporal lag between cells in the water and toxins in shellfish. Four generalized additive models were tested, with the Tweedie (TW-GAM) model showing superior performance (>85%) and lower complexity. The results suggest existing thresholds currently employed (200 and 500 cells L−1) are well-suited for the Portuguese coast, supported by empirical evidence (54–79% accuracy). The developed algorithm allows for thresholds to be tailored on a case-by-case basis, offering flexibility for regional variations. In Western Europe, the incidence of DST is likely the highest globally, posing a significant threat with prolonged bans on shellfish harvesting, mainly caused by species of the dinoflagellate genus Dinophysis. Using a time series from 2014 to 2020, our study aimed (i) to determine the concentration of D. acuminata in water at which shellfish toxin levels could surpass the regulatory limit (160 µg OA equiv kg-1) and (ii) to assess the predictability of toxic events for timely mitigation actions, especially concerning potential harvesting bans. The analysis considered factors such as (i) overdispersion in the data, (ii) distinct periods of presence and absence, (iii) the persistence of cells, and (iv) the temporal lag between cells in the water and toxins in shellfish. Four generalized additive models were tested, with the Tweedie (TW-GAM) model showing superior performance (>85%) and lower complexity. The results suggest existing thresholds currently employed (200 and 500 cells L-1) are well-suited for the Portuguese coast, supported by empirical evidence (54-79% accuracy). The developed algorithm allows for thresholds to be tailored on a case-by-case basis, offering flexibility for regional variations.In Western Europe, the incidence of DST is likely the highest globally, posing a significant threat with prolonged bans on shellfish harvesting, mainly caused by species of the dinoflagellate genus Dinophysis. Using a time series from 2014 to 2020, our study aimed (i) to determine the concentration of D. acuminata in water at which shellfish toxin levels could surpass the regulatory limit (160 µg OA equiv kg-1) and (ii) to assess the predictability of toxic events for timely mitigation actions, especially concerning potential harvesting bans. The analysis considered factors such as (i) overdispersion in the data, (ii) distinct periods of presence and absence, (iii) the persistence of cells, and (iv) the temporal lag between cells in the water and toxins in shellfish. Four generalized additive models were tested, with the Tweedie (TW-GAM) model showing superior performance (>85%) and lower complexity. The results suggest existing thresholds currently employed (200 and 500 cells L-1) are well-suited for the Portuguese coast, supported by empirical evidence (54-79% accuracy). The developed algorithm allows for thresholds to be tailored on a case-by-case basis, offering flexibility for regional variations. In Western Europe, the incidence of DST is likely the highest globally, posing a significant threat with prolonged bans on shellfish harvesting, mainly caused by species of the dinoflagellate genus . Using a time series from 2014 to 2020, our study aimed (i) to determine the concentration of in water at which shellfish toxin levels could surpass the regulatory limit (160 µg OA equiv kg ) and (ii) to assess the predictability of toxic events for timely mitigation actions, especially concerning potential harvesting bans. The analysis considered factors such as (i) overdispersion in the data, (ii) distinct periods of presence and absence, (iii) the persistence of cells, and (iv) the temporal lag between cells in the water and toxins in shellfish. Four generalized additive models were tested, with the Tweedie (TW-GAM) model showing superior performance (>85%) and lower complexity. The results suggest existing thresholds currently employed (200 and 500 cells L ) are well-suited for the Portuguese coast, supported by empirical evidence (54-79% accuracy). The developed algorithm allows for thresholds to be tailored on a case-by-case basis, offering flexibility for regional variations. |
| Author | Duarte Silva, Alexandra Rodrigues, Susana Margarida Godinho, Lia |
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| Keywords | diarrhetic shellfish toxins food safety Tweedie distribution generalized additive models early warning time series Dinophysis HABs monitoring okadaic acid |
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| SubjectTerms | Algorithms Animals Aquaculture Bans Coasts Consumption diarrhetic shellfish toxins Dinoflagellates Dinoflagellida Dinophysis Empirical analysis Environmental Monitoring - methods Food Contamination - analysis generalized additive models Laboratories Marine Toxins - analysis Marine Toxins - toxicity Mollusks okadaic acid Plankton Portugal Public health Seafood Shellfish Shellfish Poisoning - prevention & control Thresholds time series Toxicity Toxins Tweedie distribution Water quality |
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| Title | Advances in the Early Warning of Shellfish Toxification by Dinophysis acuminata |
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