Empirical Indicators for Characterising a Multi-Species, Data-Poor Fishery: The Case of Tela Bay, Honduras

Student: 
Saeesh Sunil Mangwani

Small-Scale Fishery (SSF) management is a pressing challenge for coastal communities worldwide. Typically characterised by multiple gears and species, SSFs are poorly served by traditional stock assessment models that target singular species. In this study, we characterise the data-limited SSFs of Tela Bay, Honduras using empirical indicators. By focusing on the fishing pattern, we demonstrate that an indicator approach can characterise dynamics for both a single commercially important species (the Lane Snapper, Lutjanus synagris) as well the entire multispecies fishery. Our results show that the state of fishing in Tela, although historically showing intensive exploitation, has improved since the introduction of co-management in 2018. Improvements are observed for both single and multi-species objectives, as increases in the targeted catch size and higher estimated yields for the Lane Snapper occur alongside an improved balance of pressure across species and sizes. The study thus provides important baseline information regarding the state of fishing in Tela and highlights the impact of co-management in inducing a more optimal fishing pattern. Moreover, in viewing single and multi-species indicators in combination, our results draw attention to the potential for synergy between single-species management and the maintenance of ecosystem structure under balanced harvest.

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