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<p>Population dynamics modeling represents a fundamental pillar of sustainable fisheries management. However, the intellectual development, methodological diversification, and thematic trajectory of this field have not previously been synthesized through a comprehensive global assessment. In this study, a large-scale bibliometric analysis was performed to evaluate the historical evolution, structural knowledge networks, and emerging research directions in fisheries population-dynamics research. A total of 2269 publications indexed in the Web of Science database were analyzed using performance metrics, co-citation mapping, and collaboration network analyses. The results indicate a substantial expansion in scientific output beginning in the late 1990s, followed by accelerated growth after 2010 and a pronounced publication peak in 2025, suggesting a phase of rapid methodological consolidation and technological integration. Network analyses identify key intellectual nodes shaping the discipline, with Andre E. Punt emerging as a central scholarly contributor and institutions such as NOAA and ICES functioning as dominant organizational hubs. Thematic evolution patterns reveal a transition from traditional single-species analytical frameworks toward integrative approaches, including Ecosystem-Based Fisheries Management (EBFM) and Management Strategy Evaluation (MSE). Despite this progress, a marked geographical imbalance persists, with research activity strongly concentrated in the United States, Canada, and Australia, whereas small-scale fisheries and data-limited regions remain underrepresented within the global literature. Emerging research trends indicate a convergence of classical population models with advanced monitoring technologies such as environmental DNA, and artificial intelligence in response to climate-driven variability. The findings suggest that future fisheries management will depend on integrative frameworks combining biologically based models with high-resolution data to support resilient and sustainable governance.</p>

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Fisheries Population Dynamics Revisited: Global Trends, Intellectual Landscapes, and Future Frontiers Based on Web of Science Publications (1989–2026)

  • 期刊论文

  • 发表日期：

    2026年7月7日

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  • Erkan Uğurlu,
  • Emrah Şimşek,
  • Mehmet Fatih Can,
  • Aydın Demirci

摘要

Population dynamics modeling represents a fundamental pillar of sustainable fisheries management. However, the intellectual development, methodological diversification, and thematic trajectory of this field have not previously been synthesized through a comprehensive global assessment. In this study, a large-scale bibliometric analysis was performed to evaluate the historical evolution, structural knowledge networks, and emerging research directions in fisheries population-dynamics research. A total of 2269 publications indexed in the Web of Science database were analyzed using performance metrics, co-citation mapping, and collaboration network analyses. The results indicate a substantial expansion in scientific output beginning in the late 1990s, followed by accelerated growth after 2010 and a pronounced publication peak in 2025, suggesting a phase of rapid methodological consolidation and technological integration. Network analyses identify key intellectual nodes shaping the discipline, with Andre E. Punt emerging as a central scholarly contributor and institutions such as NOAA and ICES functioning as dominant organizational hubs. Thematic evolution patterns reveal a transition from traditional single-species analytical frameworks toward integrative approaches, including Ecosystem-Based Fisheries Management (EBFM) and Management Strategy Evaluation (MSE). Despite this progress, a marked geographical imbalance persists, with research activity strongly concentrated in the United States, Canada, and Australia, whereas small-scale fisheries and data-limited regions remain underrepresented within the global literature. Emerging research trends indicate a convergence of classical population models with advanced monitoring technologies such as environmental DNA, and artificial intelligence in response to climate-driven variability. The findings suggest that future fisheries management will depend on integrative frameworks combining biologically based models with high-resolution data to support resilient and sustainable governance.