scholarly journals Current Status of Forecasting Toxic Harmful Algae for the North-East Atlantic Shellfish Aquaculture Industry

2021 ◽  
Vol 8 ◽  
Author(s):  
Jose A. Fernandes-Salvador ◽  
Keith Davidson ◽  
Marc Sourisseau ◽  
Marta Revilla ◽  
Wiebke Schmidt ◽  
...  
Keyword(s):  
Early Warning ◽  
Harmful Algal Bloom ◽  
Early Warning Systems ◽  
Environmental Data ◽  
Current Status ◽  
Sources Of Information ◽  
Traffic Light ◽  
Shellfish Aquaculture ◽  
North East ◽  
Aquaculture Industry

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.

scholarly journals Community-based early warning systems for flood risk mitigation in Nepal

2017 ◽  
Vol 17 (3) ◽  
pp. 423-437 ◽  
Author(s):  
Paul J. Smith ◽  
Sarah Brown ◽  
Sumit Dugar
Keyword(s):  
Early Warning ◽  
Risk Mitigation ◽  
Early Warning Systems ◽  
Appropriate Technology ◽  
Data Availability ◽  
Current Status ◽  
Lead Times ◽  
Warning Systems ◽  
Community Based ◽  
Probabilistic Forecasts

Abstract. This paper focuses on the use of community-based early warning systems for flood resilience in Nepal. The first part of the work outlines the evolution and current status of these community-based systems, highlighting the limited lead times currently available for early warning. The second part of the paper focuses on the development of a robust operational flood forecasting methodology for use by the Nepal Department of Hydrology and Meteorology (DHM) to enhance early warning lead times. The methodology uses data-based physically interpretable time series models and data assimilation to generate probabilistic forecasts, which are presented in a simple visual tool. The approach is designed to work in situations of limited data availability with an emphasis on sustainability and appropriate technology. The successful application of the forecast methodology to the flood-prone Karnali River basin in western Nepal is outlined, increasing lead times from 2–3 to 7–8 h. The challenges faced in communicating probabilistic forecasts to the last mile of the existing community-based early warning systems across Nepal is discussed. The paper concludes with an assessment of the applicability of this approach in basins and countries beyond Karnali and Nepal and an overview of key lessons learnt from this initiative.

Earthquake Early Warning Systems in Taiwan: Current Status

2021 ◽  
Vol 97 (12) ◽  
pp. 1525-1532
Author(s):  
Yih-Min Wu ◽  
Himanshu Mittal ◽  
Da-Yi Chen ◽  
Ting-Yu Hsu ◽  
Pei-Yang Lin
Keyword(s):  
Early Warning ◽  
Early Warning Systems ◽  
Earthquake Early Warning ◽  
Current Status ◽  
Warning Systems ◽  
Earthquake Early Warning Systems

An Exploratory Study of how to Use RPPs to Build Trust and Support the Use of Early Warning Systems

2020 ◽  
Vol 122 (14) ◽  
pp. 1-28
Author(s):  
Julie R. Kochanek ◽  
Carrie Scholz ◽  
Brianne Monahan ◽  
Max Pardo
Keyword(s):  
Grounded Theory ◽  
New England ◽  
Early Warning ◽  
Early Warning Systems ◽  
Structured Interview ◽  
Interview Data ◽  
Theory Approach ◽  
Research Practice ◽  
Sources Of Information ◽  
Grounded Theory Approach

Background/Context Emerging experiences suggest that research-practice partnerships (RPPs) can benefit both research and practice. As researchers and practitioners become part of the same social network, they also can become trusted sources of information for one another. By modeling the research use process, practitioners can incorporate what they learn into their own research acquisition and interpretation processes and researchers can gain a better understanding of how their work can be designed and conducted so that it is directly relevant to practice. Purpose/Focus of the Study Prior literature on research-practice partnerships has identified common challenges of these partnerships such as turnover, trust, common language, and complex systems. The study follows a grounded theory approach to better understand challenges and dynamics within research-practice partnerships. Setting The study included members of eight research-practice partnerships including two focused primarily on the use of early warning indicators to reduce high school dropout. Partnerships were diverse in their location and maturity. Five partnerships were located in the Midwest, one partnership was located in the South, and two partnerships were located in New England. Half of the partnerships were less than two years old at the time of the interviews, and the oldest partnership was 8 years old. Research Design Using a grounded theory approach to better understand challenges and dynamics within RPPs, we analyzed qualitative interview data inductively to identify common themes discussed by respondents. Data Collection and Analysis The study team conducted telephone interviews with two researchers and two practitioners from eight RPPs, for a total of 31 interviews – one researcher was interviewed for two different partnerships. The team used semi-structured interview protocols aligned to the four research questions. In analyzing the interview data, we identified themes, categories, and theories that emerged from the data and confirmed or refuted our initial impressions.

scholarly journals HABreports: Online Early Warning of Harmful Algal and Biotoxin Risk for the Scottish Shellfish and Finfish Aquaculture Industries

2021 ◽  
Vol 8 ◽  
Author(s):  
Keith Davidson ◽  
Callum Whyte ◽  
Dmitry Aleynik ◽  
Andrew Dale ◽  
Steven Gontarek ◽  
...  
Keyword(s):  
Early Warning ◽  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Warning System ◽  
Environmental Data ◽  
Mitigation Measures ◽  
Traffic Light ◽  
Historical Trends ◽  
Index Approach ◽  
On Line

We present an on-line early warning system that is operational in Scottish coastal waters to minimize the risk to humans and aquaculture businesses in terms of the human health and economic impacts of harmful algal blooms (HABs) and their associated biotoxins. The system includes both map and time-series based visualization tools. A “traffic light” index approach is used to highlight locations at elevated HAB/biotoxin risk. High resolution mathematical modelling of cell advection, in combination with satellite remote sensing, provides early warning of HABs that advect from offshore waters to the coast. Expert interpretation of HAB, biotoxin and environmental data in light of recent and historical trends is used to provide, on a weekly basis, a forecast of the risk from HABs and their biotoxins to allow mitigation measures to be put in place by aquaculture businesses, should a HAB event be imminent.

scholarly journals Community Based Early Warning Systems for flood risk mitigation in Nepal

2016 ◽  
Author(s):  
Paul J. Smith ◽  
Sarah Brown ◽  
Sumit Dugar
Keyword(s):  
Early Warning ◽  
Flood Risk ◽  
Risk Mitigation ◽  
Early Warning Systems ◽  
Current Status ◽  
Lead Times ◽  
Time Series Models ◽  
Warning Systems ◽  
Community Based ◽  
Probabilistic Forecasts

Abstract. This paper focuses on the use of Community Based Early Warning Systems for flood risk mitigation in Nepal. The first part of the work outlines the evolution and current status of these community based systems. A significant ongoing challenge faced by Community Based Early Warning Systems in Nepal is the short lead times available for early warning. The second part of the paper therefore focuses on the development of a robust operational flood forecasting methodology for use by the Department for Hydrology and Meteorology (DHM), Government of Nepal to compliment the community based systems. The resulting methodology uses data based physically interpretable time series models and data assimilation to generate probabilistic forecasts. The paper concludes with an example application to a flood prone catchment (Karnali Basin) in western Nepal.

The CARE Telematics Network for the Surveillance of Influenza in Europe

1995 ◽  
Vol 34 (05) ◽  
pp. 518-522 ◽  
Author(s):  
M. Bensadon ◽  
A. Strauss ◽  
R. Snacken
Keyword(s):  
Public Health ◽  
Early Warning ◽  
Early Warning Systems ◽  
Warning Systems ◽  
Surveillance Networks ◽  
Spanish Flu ◽  
The 1950S ◽  
National Networks ◽  
First Time

Abstract:Since the 1950s, national networks for the surveillance of influenza have been progressively implemented in several countries. New epidemiological arguments have triggered changes in order to increase the sensitivity of existent early warning systems and to strengthen the communications between European networks. The WHO project CARE Telematics, which collects clinical and virological data of nine national networks and sends useful information to public health administrations, is presented. From the results of the 1993-94 season, the benefits of the system are discussed. Though other telematics networks in this field already exist, it is the first time that virological data, absolutely essential for characterizing the type of an outbreak, are timely available by other countries. This argument will be decisive in case of occurrence of a new strain of virus (shift), such as the Spanish flu in 1918. Priorities are now to include other existing European surveillance networks.

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