An inventory of the marine fish fauna in the extreme northeast of South America was performed, as well as biomass estimates, species richness and environmental variables were collected. Techniques of spatial statistics were used to identify biomass trends and species richness. The main objectives were to generate new information about the specific composition of the fish fauna, allowing the identification of the spatial and temporal distribution of fishing resources, as well as the influence of environmental variables on habitat use, generating information that contributes to establishing measures of management and conservation of the fishing resources of the region. Bottom trawls were conducted on the northern coast of the continental shelf of Rio Grande do Norte (Northeast of Brazil), between May 2002 and November 2004. A total of 20,895 fishes (806.5 kg) distributed within 153 species, 108 genera and 57 families were caught. The number of species identified by trawls ranged from 1 to 46. For species richness, the season of the year, depth, latitude, longitude and distance from the coast were statistically significant. Fish biomass presented values between 0.76 and 6,132 g/km, with highest values occurring between depths of 45 and 65 m during the rainy season, while in dry period higher biomass was found in depths from 35 to 75 m. According to the GLM, season of the year and depth influence the distribution of biomass. Thus, in general terms both models indicated that environmental variables directly influence the occurrence and distribution of the ichthyofauna of the continental shelf of Rio Grande do Norte and therefore should be prioritized in establishing measures for conservation and management of these important resources.
- Bottom trawls
- Continental shelf
- Fish habitat
- Ichthyofauna composition
Nóbrega, M. F., Garcia, J., Rufener, M. C., & Oliveira, J. E. L. (2019). Demersal fishes of the northeast Brazilian continental shelf: Spatial patterns and their temporal variation. Regional Studies in Marine Science, 27, . https://doi.org/10.1016/j.rsma.2019.100534