Scientific Foundation for Multi-Parameter Fisheries: Intelligence Oceanographic Basis, Single-Parameter Limitations, and the Case for Integrated Assessment

This research note establishes the scientific foundation for a next-generation fisheries intelligence framework tailored to the unique oceanographic conditions of the Arabian Sea. Focusing on the Ratnagiri coastal region, the study examines how monsoon-driven processes, nutrient dynamics, dissolved oxygen levels, and sea surface temperatures collectively influence fish habitat suitability and fisheries productivity.

The analysis demonstrates that traditional fisheries advisories based on a limited set of environmental parameters are insufficient to capture the complex interactions that govern fish distribution in tropical marine ecosystems. In particular, the study highlights the critical relationship between biological productivity and oxygen availability, showing how highly productive waters may simultaneously impose ecological stress on marine species.

To address these limitations, the research develops a scientifically validated multi-parameter Fishing Suitability Index (FSI) that integrates Net Primary Productivity (NPP), Dissolved Oxygen, Nitrate Gradient, and Sea Surface Temperature into a unified assessment framework. The findings reveal strong alignment between the composite index and observed fisheries outcomes, providing a robust basis for improving fisheries forecasting, resource management, and Blue Economy planning.

The study also identifies emerging climate-related risks, including thermal habitat compression and changing species suitability patterns, underscoring the need for adaptive fisheries management strategies. As the first publication in the MRC Research Note Series on Fisheries Intelligence, this note provides the scientific rationale for transitioning from conventional advisory systems to integrated, data-driven decision-support tools for sustainable marine resource management.

• Single-Parameter Fisheries Advisories Are No Longer Sufficient

Traditional fisheries intelligence systems relying primarily on Sea Surface Temperature (SST) or Chlorophyll fail to capture the complex interactions between productivity, oxygen availability, nutrient dynamics, and habitat suitability in the Arabian Sea. The study establishes the need for a multi-parameter approach to improve fisheries forecasting and decision-making.

• Upwelling Creates a Critical Productivity–Oxygen Paradox

The Southwest Monsoon-driven upwelling that fuels high biological productivity simultaneously introduces oxygen-depleted waters from the Arabian Sea's Oxygen Minimum Zone (OMZ). As a result, periods that appear highly productive may also impose significant ecological stress on commercially important fish species.

• Integrated Fishing Suitability Index (FSI) Provides Superior Fisheries Intelligence

The research develops a scientifically grounded composite Fishing Suitability Index (FSI) integrating Net Primary Productivity (NPP), Dissolved Oxygen, Nitrate Gradient, and Sea Surface Temperature. This multi-parameter framework captures real-world habitat conditions more accurately than conventional single-parameter assessments.

• Climate Change Signals Emerging Risks for Key Commercial Species

Thermal habitat analysis indicates a substantial reduction in suitable habitat for important species such as oil sardine and Indian mackerel in the Ratnagiri region. Rising sea surface temperatures may drive long-term shifts in species distribution, highlighting the need for adaptive fisheries management and climate-resilient Blue Economy strategies.