Riska Fatmawati, Fuad, Romie Jhonnerie, Dhita Widhiastika, Nofrizal, Lisa Nur Hidayah, Kristina Marsela, Fahresa Nugraheni Supadminingsih, Arisya Fitri Nugraha
Fish behavior research has emerged as a strategically applied scientific domain, yet its global knowledge structure, thematic evolution, and interdisciplinary integration remain insufficiently characterized through systematic bibliometric analysis, particularly for the post-2019 period defined by rapid technological innovation and intensifying environmental pressures. This study employed a bibliometric approach using the Bibliometrix R package and VOSviewer, drawing on metadata extracted from the Scopus database via a two-stage Boolean search strategy and a PRISMA-adapted screening protocol, yielding a final analytical dataset of 857 peer-reviewed documents published between 2019 and 2024. Publication output increased progressively from 154 documents in 2019 to a peak of 185 in 2023 (CAGR = 4.7%), with research concentrated in 27 Q1-and Q2-ranked journals led by Science of the Total Environment (n= 28; IF= 8.0), Fisheries Research (n= 22), and Aquaculture (n= 20), meanwhile 2024 is incompletely indexed, reflecting the structural migration of behavioral science toward environmental, fisheries, and aquaculture-oriented outlets rather than specialist ethological venues. Global output is dominated by China (n= 159; 18.6%), the United States (n= 98; 11.4%), and Canada (n= 44; 5.1%), while institutional analysis identifies China Agricultural University (n= 148 cumulative publications) and the Institute of Marine Research, Norway (n= 105) as the primary centres of excellence, collectively representing 55.4% of the total dataset (n= 475). Keyword co-occurrence analysis constructed via VOSviewer (minimum threshold= 5; Leiden algorithm; resolution= 1.0) reveals two strongly interconnected thematic clusters ecological–environmental behavior and experimental–toxicological behavior bridged by terms including fish, behavior, and physiology, indicating progressive convergence between laboratory-derived mechanistic evidence and field-based applied science. Citation analysis identifies computer vision-based behavioral classification (Wang et al., 2022; NTC = 13.37) as the highest normalised-impact contribution, followed by studies on pollution-induced behavioral responses, aquaculture welfare, and technology-enabled monitoring. © 2026, Egyptian Society for the Development of Fisheries and Human Health. All rights reserved.
Department of Fisheries Resources Utilization, Faculty of Fisheries and Marine Science, Universitas Riau, Riau, Pekanbaru, Indonesia; Ruaya Institute, Riau, Pekanbaru, Indonesia; Department of Fisheries Resources Utilization, Faculty of Fisheries and Marine Science, Universitas Brawijaya, East Java, Malang, Indonesia; Department of Fisheries, Faculty of Agriculture, University of Sultan Ageng Tirtayasa, Banten, Indonesia; Department of Aquatic Resources Management, Faculty of Fisheries and Marine Science, Lambung Mangkurat University, South Kalimantan, Indonesia
