FN Archimer Export Format
PT J
TI Current Status of Forecasting Toxic Harmful Algae for the North-East Atlantic Shellfish Aquaculture Industry
BT 
AF Fernandes-Salvador, Jose A
   Davidson, Keith
   SOURISSEAU, Marc
   Revilla, Marta
   Schmidt, Wiebke
   Clarke, Dave
   Miller, Peter I
   Arce, Paola
   Fernandez, Raul
   Maman, Luz
   Silva, Alexandra
   Whyte, Callum
   Mateo, Maria
   Neira, Patricia
   Mateus, Marcos
   Ruiz-Villarreal, Manuel
   FERRERA, Luis
   Silke, Joe
AS 1:1;2:2;3:3;4:1;5:4,5;6:4;7:6;8:2;9:7;10:7;11:8;12:2;13:1;14:4;15:9;16:10;17:1;18:4;
FF 1:;2:;3:PDG-ODE-DYNECO-PELAGOS;4:;5:;6:;7:;8:;9:;10:;11:;12:;13:;14:;15:;16:;17:;18:;
C1 AZTI, Marine Research, Basque Research and Technology Alliance, Pasaia, Spain
   Scottish Association for Marine Science, Scottish Marine Institute, Oban, United Kingdom
   French Research Institute for Exploitation of the Sea, Ifremer DYNECO PELAGOS, Plouzané, France
   Marine Institute, Galway, Ireland
   Environment Agency, Chief Scientist’s Group, Bristol, United Kingdom
   Plymouth Marine Laboratory, Plymouth, United Kingdom
   Laboratorio de Control de Calidad de los Recursos Pesqueros, Agencia de Gestión Agraria y Pesquera de Andalucía, Consejería de Agricultura, Ganadería, Pesca y Desarrollo Sostenible, Junta de Andalucía, Cartaya, Spain
   Phytoplankton Laboratory, Division of Oceanography and Marine Environment, Instituto Português do Mar e da Atmosfera, Lisbon, Portugal
   MARETEC – Marine, Environment and Technology Centre, LARSyS, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
   Centro Oceanográfico de A Coruña, Instituto Español de Oceanografía (IEO,CSIC), A Coruña, Spain
C2 AZTI, SPAIN
   SAMS SCOTLAND, UK
   IFREMER, FRANCE
   MARINE INST GALWAY, IRELAND
   ENVIRONMENT AGENCY, UK
   PML, UK
   CONSEJ AGRIC GANADERIA PESCA DESRALLO SOSTENIBLE, SPAIN
   IPMA, PORTUGAL
   UNIV LISBON, PORTUGAL
   IEO, SPAIN
SI BREST
SE PDG-ODE-DYNECO-PELAGOS
IN WOS Ifremer UPR
   DOAJ
   copubli-europe
IF 5.247
TC 32
UR https://archimer.ifremer.fr/doc/00698/80981/85013.pdf
   https://archimer.ifremer.fr/doc/00698/80981/85014.docx
LA English
DT Article
DE ;modeling;machine learning;toxins;phytoplankton;food production;short-term;regulation;early warning systems
AB Across the European Atlantic Arc (Scotland, Ireland, England, France, Spain, and Portugal) the shellfish aquaculture industry is dominated by the production of mussels, followed by oysters and clams. A range of spatially and temporally variable harmful algal bloom species (HABs) impact the industry through their production of biotoxins that accumulate and concentrate in shellfish flesh, which negatively impact the health of consumers through consumption. Regulatory monitoring of harmful cells in the water column and toxin concentrations within shellfish flesh are currently the main means of warning of elevated toxin events in bivalves, with harvesting being suspended when toxicity is elevated above EU regulatory limits. However, while such an approach is generally successful in safeguarding human health, it does not provide the early warning that is needed to support business planning and harvesting by the aquaculture industry. To address this issue, a proliferation of web portals have been developed to make monitoring data widely accessible. These systems are now transitioning from “nowcasts” to operational Early Warning Systems (EWS) to better mitigate against HAB-generated harmful effects. To achieve this, EWS are incorporating a range of environmental data parameters and developing varied forecasting approaches. For example, EWS are increasingly utilizing satellite data and the results of oceanographic modeling to identify and predict the behavior of HABs. Modeling demonstrates that some HABs can be advected significant distances before impacting aquaculture sites. Traffic light indices are being developed to provide users with an easily interpreted assessment of HAB and biotoxin risk, and expert interpretation of these multiple data streams is being used to assess risk into the future. Proof-of-concept EWS are being developed to combine model information with in situ data, in some cases using machine learning-based approaches. This article: (1) reviews HAB and biotoxin issues relevant to shellfish aquaculture in the European Atlantic Arc (Scotland, Ireland, England, France, Spain, and Portugal; (2) evaluates the current status of HAB events and EWS in the region; and (3) evaluates the potential of further improving these EWS though multi-disciplinary approaches combining heterogeneous sources of information. 
PY 2021
PD JUL
SO Frontiers In Marine Science
SN 2296-7745
PU Frontiers Media
VL 8
UT 000663425600001
DI 10.3389/fmars.2021.666583
ID 80981
ER

EF