Complexity of the marine ecosystem in view of the human health factors: role of network science - Capobianco, Enrico; Moretti, Pier Francesco (Frontiers in Marine Science, 2023)
Anthropogenic and natural factors impacting health and well-being in coastal waters, regional seas, and the global ocean have long been recognized by the marine scientists, however not as much by the medical and public health community. Although establishing causal effects that directly or indirectly affect human health-related conditions is problematic and depends on the complex marine ecosystem, significant influences are present at both local and global levels, i.e., specific to coastal areas but also associated with sea activities referred to the ‘ocean health’ status. This offers a good rationale for an assessment of the human-marine environment interaction, evolution and complexity landscape. The health ecosystem as a whole (humans and environment, especially marine in our interests) is a complex bio-entity whose dynamics are largely unknown due to the presence of biodiversity and heterogeneity. In parallel, this complexity translates into various new processes that the stakeholders face to establish possible interventions and preserve the sustainability. A major checkpoint in our discussion refers to how to leverage the consolidated and indeed pervasive role of digital information across multiple fields and disciplines, supported by developments in artificial intelligence, machine learning and network science. This is an urgency, as the scientific marine community and the public health policy makers are struggling to gather big data from multiple sources and/or devices that help reveal the marine environmental status. Improvements in the ability of analyzing efficiently and effectively data are needed, and we suggest to profitably look at knowledge transfer strategies. In particular, considering and valuing how the scientific biomedical community has made use of network inference approaches to better understand complex biosystems in both structural and functional terms, we believe that the existing knowledge base can be further generalized to deal with the marine environmental ecosystem context.