Syntheses of large-scale biodiversity and health datasets to support evidence-based policy and address key societal challenges

Ecosystems and biodiversity are under intense pressure from multiple cumulative anthropogenic pressures. At the same time, the burden of neglected tropical diseases (NTDs) continues to affect hundreds of millions of people globally. In the face of these current societal challenges, the need to generate, synthesise and utilise high quality biological data for science-based decision-making is more pressing than ever before. Data synthesis allows for the characterisation of ecosystems, monitoring of global change, leading towards evidence-based decision making and development of effective intervention strategies, whether relating to biodiversity and conservation or public health. However, knowledge gaps and barriers preventing the free flow of data can impede the incorporation of scientific findings into policy. These challenges are explored here through the lens of two contrasting fields of research, and drawing on six peer-reviewed publications by the author: 1) the NTDs schistosomiasis and paragonimiasis, addressing spatio-temporal trends in distribution and how findings can shed light on these diseases to support evidence-based interventions; and 2) studies of deep-sea biodiversity and marine genetic resources (MGRs), addressing key knowledge gaps in the context of global ocean governance frameworks. These different research fields provide a basis for exploring common elements (including to achieving effective science-policy integration), including the need for taxonomy and species-level data, the role of biorepositories and archiving, harmonisation efforts for data and sample pipelines, and effective communication and cooperation. Global networks can also act as intermediaries or translators across the science-policy nexus. Such organisations can provide the missing link between data and decision-making, and therefore advance science-policy as a co-produced endeavour. Here, commonalities in seemingly contrasting research fields provide insights for improved science-policy integration.