Periodic Reporting for period 2 - FISHEARS (Enigmatic fish ears: solving a sensory biology riddle with bioengineering and Artificial Intelligence)
Periodo di rendicontazione: 2024-06-01 al 2025-05-31
The project aimed to:
- Generate high-resolution 3D models of elasmobranch hearing structures
- Develop the first Finite Element Model (FEM) for elasmobranch hearing.
- Use artificial intelligence to unravel the factors that shape the hearing systems of elasmobranch fishes.
The project has successfully made significant strides toward these goals. High-resolution imaging methodologies were refined, enabling the creation of detailed 3D models of elasmobranch inner ear structures. Over 40 high-resolution 3D images of elasmobranch heads have been produced from preserved specimens, representing a unique and comprehensive collection of inner ear structures for any fish taxa. The segmentation of these scans provides an impressive representation of the structural diversity across more than 10 species of sharks and rays. The FEM approach was initiated, with essential groundwork laid for computational modeling of elasmobranch hearing mechanisms. Furthermore, the application of artificial intelligence has opened pathways to better understand the evolutionary and functional drivers of hearing diversity in these species.
Although the project ended earlier than planned due to a career transition, its outputs have already contributed meaningfully to the field. The project resulted in several high-impact publications, with more in preparation, and generated outreach tools, including 3D-printed inner ear models, enhancing public and academic engagement.
Overall, the project has had a transformative impact on the researcher’s career, providing advanced technical skills, fostering international collaborations, and securing a tenure-track position. These accomplishments ensure the continuation of this research and its integration into future initiatives, strengthening the foundation for further exploration of elasmobranch sensory biology and its implications for conservation.
The project also laid the groundwork for the first Finite Element Model (FEM) of elasmobranch hearing. This included extensive training in FEM techniques, preparation of 3D meshes, and collaborative efforts to measure material properties from fresh specimens. These activities ensured a solid foundation for future experimental validation of the FEM. Additionally, artificial intelligence and multivariate analytical frameworks were developed to explore evolutionary and functional drivers of hearing diversity. These frameworks incorporated phylogenetic relationships and standardised pipelines, ensuring scalability and applicability to broader datasets. Due to the early termination of the project, the FEM and the final multivariate analysis has not been completed. However, the researcher is planning to continue this research and build on the solid base that has been constructed.
The project resulted in three peer-reviewed publications and six oral presentations at international conferences (included one keynote presentation), significantly contributing to the scientific understanding of elasmobranch sensory biology. Outreach initiatives included educational materials for public engagement, such as displays at the Goat Island Discovery Centre (New Zealand).
Although the project concluded earlier than planned due to the researcher’s transition to a tenure-track position, the foundational work has ensured the continuation of its objectives. The outcomes have not only advanced the scientific field but also catalysed the researcher’s career progression, securing grants and fostering international collaborations.
The project also introduced the first steps toward a Finite Element Model (FEM) of elasmobranch hearing, a groundbreaking approach for understanding functional mechanics in these species. Additionally, artificial intelligence techniques have been applied to streamline segmentation and identify the evolutionary and ecological drivers shaping hearing diversity in elasmobranchs. This interdisciplinary approach—melding biology, engineering, and machine learning—has broadened the scope of sensory biology and its applications.
The outcomes include a dataset of high-resolution 3D models across multiple elasmobranch species, complete with volumetric and structural analyses. The FEM will be refined further with experimentally validated material properties, offering a predictive framework for understanding hearing mechanics in sharks and rays. The AI-driven analytical pipeline will enable broader-scale investigations into the relationships between hearing morphology, ecology, and phylogeny. These results are expected to culminate in multiple high-impact publications and accessible outreach tools, including 3D-printed models and educational resources.
Scientifically, FISHEARS has advanced the understanding of elasmobranch sensory systems, critical for informing biodiversity conservation strategies. By providing insights into how these species interact with their environments, the project contributes to mitigating human impacts such as noise pollution, a growing concern in marine ecosystems. Educational impacts are evident through public engagement initiatives, such as exhibits at the Goat Island Discovery Centre, and outreach materials fostering greater awareness of elasmobranch biology. At a societal level, the project has raised awareness of the importance of preserving marine biodiversity and understanding the effects of anthropogenic pressures on vulnerable species. Furthermore, the interdisciplinary nature of the research underscores the value of integrating advanced technologies to address ecological challenges, inspiring innovation and cross-sector collaboration.
 
           
        