Oceans and Human Health (OHH): a European Perspective from the Marine Board of the European Science Foundation (Marine Board-ESF)

The oceans and coastal seas provide mankind with many benefits including food for around a third of the global population, the air that we breathe and our climate system which enables habitation of much of the planet. However, the converse is that generation of natural events (such as hurricanes, severe storms and tsunamis) can have devastating impacts on coastal populations, while pollution of the seas by pathogens and toxic waste can cause illness and death in humans and animals. Harmful effects from biogenic toxins produced by algal blooms (HABs) and from the pathogens associated with microbial pollution are also a health hazard in seafood and from direct contact with water. The overall global burden of human disease caused by sewage pollution of coastal waters has been estimated at 4 million lost person-years annually. Finally, the impacts of all of these issues will be exacerbated by climate change. A holistic systems approach is needed. It must consider whole ecosystems, and their sustainability, such as integrated coastal zone management, is necessary to address the highly interconnected scientific challenges of increased human population pressure, pollution and over-exploitation of food (and other) resources as drivers of adverse ecological, social and economic impacts. There is also an urgent and critical requirement for effective and integrated public health solutions to be developed through the formulation of politically and environmentally meaningful policies. The research community required to address "Oceans & Human Health" in Europe is currently very fragmented, and recognition by policy makers of some of the problems, outlined in the list of challenges above, is limited. Nevertheless, relevant key policy issues for governments worldwide include the reduction of the burden of disease (including the early detection of emerging pathogens and other threats) and improving the quality of the global environment. Failure to effectively address these issues will impact adversely on efforts to alleviate poverty, sustain the availability of environmental goods and services and improve health and social and economic stability; and thus, will impinge on many policy decisions, both nationally and internationally. Knowledge exchange (KE) will be a key element of any ensuing research. KE will facilitate the integration of biological, medical, epidemiological, social and economic disciplines, as well as the emergence of synergies between seemingly unconnected areas of science and socio-economic issues, and will help to leverage knowledge transfer across the European Union (EU) and beyond. An integrated interdisciplinary systems approach is an effective way to bring together the appropriate groups of scientists, social scientists, economists, industry and other stakeholders with the policy formulators in order to address the complexities of interfacial problems in the area of environment and human health. The Marine Board of the European Science Foundation Working Group on "Oceans and Human Health" has been charged with developing a position paper on this topic with a view to identifying the scientific, social and economic challenges and making recommendations to the EU on policy-relevant research and development activities in this arena. This paper includes the background to health-related issues linked to the coastal environment and highlights the main arguments for an ecosystem-based whole systems approach.

Evaluating machine-learning techniques for recruitment forecasting of seven North East Atlantic fish species

The effect of different factors (spawning biomass, environmental conditions) on recruitment is a subject of great importance in the management of fisheries, recovery plans and scenario exploration. In this study, recently proposed supervised classification techniques, tested by the machine-learning community, are applied to forecast the recruitment of seven fish species of North East Atlantic (anchovy, sardine, mackerel, horse mackerel, hake, blue whiting and albacore), using spawning, environmental and climatic data. In addition, the use of the probabilistic flexible naive Bayes classifier (FNBC) is proposed as modelling approach in order to reduce uncertainty for fisheries management purposes. Those improvements aim is to improve probability estimations of each possible outcome (low, medium and high recruitment) based in kernel density estimation, which is crucial for informed management decision making with high uncertainty. Finally, a comparison between goodness-of-fit and generalization power is provided, in order to assess the reliability of the final forecasting models. It is found that in most cases the proposed methodology provides useful information for management whereas the case of horse mackerel is an example of the limitations of the approach. The proposed improvements allow for a better probabilistic estimation of the different scenarios, i.e. to reduce the uncertainty in the provided forecasts.