A fish’s ear stone and eye lens record its entire life history, and researchers are now reading those chemical diaries to track where fish go and what harms them. Current methods for monitoring fish movements rely on expensive electronic tags that only work on large adults, leaving huge gaps in knowledge about juveniles and the nursery habitats that sustain commercial fisheries. This programme combines chemical tracers from fish tissues with archival tag data and machine learning to reconstruct the full life story of individual fish—where they were born, what they ate, what pollutants they absorbed, and how oxygen levels or temperature affected their growth. If successful, the work will give fisheries managers a practical, scalable way to map critical habitats and predict how fish populations will respond to climate change, pollution, and overfishing. The North Sea serves as the test bed, but the methods are designed to transfer to any aquatic ecosystem. The researchers are also founding an international consortium to push these chemical records into routine resource management, moving beyond the current piecemeal use of tags and tracers toward an integrated monitoring system.
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Aquatic ecosystems provide a variety of critical goods and services, including fisheries, energy and coastal protection. However, these fragile ecosystems are increasingly threatened by interacting stressors such as climate change, pollutants and overfishing. To protect key ecosystem services and ensure food security in an increasingly unpredictable climate, there is a pressing need to improve our understanding of fish habitat requirements and their vulnerability to different stressors. In this programme, we are using an integrated systems approach to address these knowledge gaps, providing novel solutions for the sustainable management of aquatic ecosystems in the 21st Century. To deliver sustainable fisheries management we need to understand fish connectivity patterns across species and life stages. Our knowledge of fish movements and habitat use has been significantly enhanced by the advent of electronic archival tags, but sample sizes can be limited by high costs, and the tags are typically restricted to larger-bodied species and life stages. Accordingly, we often know very little about juvenile life stages and the nursery habitats supporting our commercial fisheries. Luckily, all animals are equipped with their own intrinsic 'sensors' that record a wealth of information about the internal and external environment as they grow. By interrogating biogeochemical tracers in incrementally-grown tissues such as fish ear stones and eye lenses, we will read their 'life stories' and gain unique insights into their past health and habitat use. These tissues often exhibit growth bands ('biochronologies'), analogous to tree rings, which allow us to look back in time to reconstruct the fish's age, growth and movement timings, providing exciting opportunities to explore latent and cumulative effects of stressors on their physiology and health. Despite clear opportunities for archival tags, chemical tracers and biochronologies to cross-validate and augment each other, they are rarely used in combination. This programme aims to demonstrate how to integrate and scale these tools to support effective ecosystem management. This global programme involves a series of case studies that integrate emerging technologies (e.g. electronic archival tags and machine learning), novel chemical tracers and modelling to quantify and predict the movements and fitness of key fish species over a broad range of global change scenarios. We are using the North Sea as a model system to explore how integrated fish health and connectivity monitoring could enhance marine spatial planning. By pairing otolith chemistry and archival tag data from the same fish, we will determine optimal methods for reconstructing individual movement patterns using otolith tracers. To shed light on the mechanisms driving interannual variability in fisheries performance, we will develop and validate new tools for reconstructing fish health and contaminant exposure history. To reveal the critical habitats, dietary sources and fine-scale movement patterns of vulnerable salmonids we will use isotopic maps ('isoscapes') and tracers combined with novel machine learning methods. To quantify the latent and cumulative effects of hypoxia on fish size and fitness we will combine archival tag records and chemical tracers, then predict the impact of this growing environmental issue on fisheries productivity and stability. The overall synthesis of these case studies will provide new insights into fish habitat needs and their vulnerabilities to interacting stressors, improving our ability to predict fishery responses to differing global change and management scenarios. Finally, to promote multidisciplinary innovation and the integration of these emerging tools into mainstream resource management, we will establish an International Consortium dedicated to the EXploration, TRanslation and Application of Chemical records in fish Tissues (EXTRACT).
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