Understanding the main factors that regulate species composition in fisheries is of utmost importance for developing efficient management strategies, particularly under the scope of ecosystem-based conservation approaches. This study used multivariate statistics to analyze catch data collected during a ~10-year, fishery-independent, standardized longline survey conducted in coastal waters (<20-m isobaths) off Recife, northeastern Brazil. A redundancy analysis (RDA) was performed to assess the influence of spatiotemporal, environmental, and bioecological variables on the variability in longline catch composition and to identify similarly distributed groups of species. Additionally, an analysis of similarities (ANOSIM) was conducted to investigate the likeness among the multispecific groups and identify the most influential variables. A total of 1,295 specimens representing 29 species of teleosts, elasmobranchs, and sea turtles were caught, but most species (62.0%) were little represented (<1%) in the catch composition. The RDA model indicated that the catch composition was significantly influenced by habitat type, behavior, trophic level, year, site, water transparency, month, and sea surface temperature; bioecological variables provided the greatest contribution to explain the variability in catch composition. The ANOSIM revealed that marine catfishes, moray eels, and Nurse Shark Ginglymostoma cirratum were the most similar in their relation to several spatiotemporal and environmental variables. The patterns reported herein might be useful to improve coastal fisheries management because they present the species that are influenced by similar drivers and the main factors underlying their respective catch rates. Therefore, this approach could be a potentially useful tool for lessening the number of biological dimensions, which frequently limit the capacity to implement effective management strategies in multispecies fisheries.