An assessment of the larval fish diversity within a coastal marine reserve: Larval fish diversity within a marine reserve

Abstract

Knowledge of ichthyoplankton diversity and distribution is important in the management of a fishery for increased productivity and to ensure sustainability. In the Discovery Bay Special Fishery Conservation Area (DBSFCA) and other marine protected areas in Jamaica, there is a paucity of information on larval fish communities and the factors affecting their diversity and distribution. Therefore, we compared the efficiencies of light traps and plankton nets to assess the richness and composition of ichthyoplankton species in Jamaica’s oldest fish sanctuary, the DBSFCA. Min/Max Auto-correlation Factor Analysis (MAFA) and the Dynamic Factor Analysis (DFA) were then used to compare biotic and abiotic factors that influenced larval fish diversity and distribution. A total of 41 species belonging to 39 families of predominantly reef-associated species were identified during the sampling period of February to November 2014. The plankton net proved to be more efficient, catching 2202 individuals from 36 species, while light traps caught 590 individuals from 15 larval fish species. The plankton nets and light traps collected 27 and seven mutually exclusive species, respectively. From February to July, Clupeidae and Pomacentridae dominated the larvae community and throughout the study period Clupeidae was the most abundant family in the light traps. Blennidae, Gobiidae, Labridae, Labrisomidae, Pomacentridae and Sparidae frequently accounted for less than 50% of the relative abundance. Commercially important families such as Lutjanidae and Haemulidae were rarely caught with both gears. Additionally, temporal changes in the abundance and richness of fish larvae, indicating peak abundance during July and August, were detected with both DFA and MAFA. A DFA model with two common trends and three explanatory variables (mean day-length, mean zooplankton richness and mean monthly sea temperature) was the optimal model for characterizing ichthyoplankton abundance. The study highlights the importance of incorporating ichthyoplankton surveys in marine reserves especially with the threat of climate change and overfishing.