Title: Fisheries data management, extraction, and visualisation in St. Kitts and Nevis to foster sustainable management.

This study examined the fisheries departments of St. Kitts and Nevis and revealed comprehensive efforts to retrieve and standardise historical catch and effort sample data, ensuring its integration into the current database system (TFM) for future fisheries and stock assessment analyses. The research aimed to establish efficient methods for data collection and management, ensuring that stakeholders and policymakers have access to accurate information to make decisions about resource allocation and conservation measures. Accordingly, a thorough characterisation of target species, gear types, and seasonality in St. Kitts fisheries was conducted. There has been a general increase in sampling across the five major sites from 2014 to 2022, as there has been a consistent upward trend in the number of vessels sampled. With the use of historical data of sample records from 2014 to 2023 obtained from the Department of Marine Resources in St. Kitts and Nevis, data files were imported into R Studio and Excel, and selected variable names were standardised. The data illustrated varied trends in fishing gear usage across different methods, with the three most common being spearguns, traps, and handlines. The data also highlighted the distribution of fishing efforts across different sites, with some sites serving as focal points for fishing activities while others exhibited lower levels of engagement in fisheries. The findings revealed that a specific species, namely Queen Conch (Strombus gigas) and Spiny Lobster (Panulirus argus) possessed greater commercial value. Queen Conch and Spiny Lobster are the subjects of species-specific analyses, which emphasize their commercial importance and the varying trends in CPUE that occur when employing different fishing techniques. However, more research is needed to fully understand the trends. The development of a systematic approach for extracting data from the Fisheries Manager database, along with reporting templates, will facilitate efficient data handling and the presentation of key management metrics and trends.