The research topic explores an integrated approach to studying physiological and behavioral adaptive responses of aquatic and terrestrial vertebrates in human-influenced environments. It aims to develop robust animal-based measures (ABMs) for affective states by identifying behavioral, endocrine, molecular, and metabolic indicators of stress and welfare, particularly in fish species. The study focuses on various conditions, including discomfort, chronic low arousal states, social stress, transport, responses to both impoverished and enriched environments, and end-of-life phases. The research proposes to utilize artificial intelligence and, potentially, automated physiological signal detection tools (for heart rate, respiratory rate, and neural activity) to complement traditional methodologies, creating a comprehensive understanding of adaptive processes in animals. This field of study is crucial for understanding how fish cope with various conditions, as well as how they adapt to changes in their natural habitats. It aims to enhance the understanding of these animals' adaptation mechanisms and provide valuable insights to ensure positive environments for them.

Five publications related to the Research topic for the candidate interview:

• Alvarado M. V.,  Cerdá-Reverter J. M.,  Espigares F.; A functional framework for a comprehensive study of welfare in fishes. Proc Biol Sci 1 October 2025; 292 (2056): 20251833. https://doi.org/10.1098/rspb.2025.1833
• Yuan, M.; Fang, Q.; Lu, W.; Wang, X.; Hao, T.; Chong, C.-M.; Chen, S. Stress in Fish: Neuroendocrine and Neurotransmitter Responses. Fishes 2025, 10, 307. https://doi.org/10.3390/fishes10070307
• Oppedal F., Barrett L.T., Fraser T.W.K., Vågseth T., Zhang G., Andersen OG., Jacson L., Dieng MA., Vindas M.A. The Behavioral and Neurobiological Response to Sound Stress in Salmon. Brain Behav Evol. 2025;100(1):11-28. doi: 10.1159/000539329. Epub 2024 May 16. PMID: 38754387.
• Arechavala-Lopez P., Cabrera-Álvarez M.J., Maia C.M., Saraiva J.L. Environmental enrichment in fish aquaculture: A review of fundamental and practical aspects. Rev Aquac. 2022; 14: 704–728. https://doi.org/10.1111/raq.12620
• Iqbal, U.; Li, D.; Akhter, M. Intelligent Diagnosis of Fish Behavior Using Deep Learning Method. Fishes 2022, 7, 201. https://doi.org/10.3390/fishes7040201

Tutor: Prof. Daniela Bertotto
e-mail address: daniela.bertotto@unipd.it