A Review of Standardization in Mississippi’s Multidecadal Inland Fisheries Monitoring Program

Abstract

Standardizing data collection, management, and analysis processes can improve the reliability and efficiency of fisheries monitoring programs, yet few studies have examined the operationalization of these tasks within agency settings. We reviewed the Mississippi Department of Wildlife, Fisheries, and Parks, Fisheries Bureau’s inland recreational fisheries monitoring program—a 30+-year effort to standardize field protocols, data handling procedures, and automated analyses through a custom-built computer application, the Fisheries Resources Analysis System (FRAS). Drawing on quantitative summaries of sampling trends and qualitative interviews with fisheries managers, we identified key benefits, challenges, and opportunities associated with the Bureau’s standardization efforts. Standardized procedures improved sampling consistency, data reliability, and operational efficiency, enabling the long-term tracking of fish population and angler metrics across more than 270 managed waterbodies. However, challenges related to analytical transparency and spatiotemporal comparisons persist. Simulations indicated that under current conditions, 5.8, 22.9, and 37.1 years would be required to sample (boat electrofishing) 50%, 75%, and 95% of the Bureau’s waterbodies at least once, respectively; these figures should translate to other agencies, assuming similar resource availability per waterbody. The monitoring program has reduced manual processing effort and enhanced staff capacity for waterbody-specific management, yet several opportunities remain to improve efficiency and utility. These include expanding FRAS functionalities for trend visualization, integrating mobile field data entry to reduce transcription errors, linking monitoring results with management objectives, and enhancing automated report generation for management support. Strengthening these elements could not only streamline workflows but better position agencies to apply standardized data in adaptive management embedded into the monitoring program.