Dietary composition of black drum Pogonias cromis in a hypersaline estuary reflects water quality and prey availability

• Published in: Journal of Fish Biology
• Main Authors: Rubio, Kathryn S., Ajemian, Matthew, Stunz, Gregory W., Palmer, Terence A., Lebreton, Benoit, Beseres Pollack, Jennifer
• Other Authors: Texas Sea Grant, Texas A and M University, Texas A and M University-Corpus Christi
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2018
• Subjects: Baffin Bay; Baffin
• Online Access: http://dx.doi.org/10.1111/jfb.13654; https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fjfb.13654; https://onlinelibrary.wiley.com/doi/pdf/10.1111/jfb.13654; https://onlinelibrary.wiley.com/doi/full-xml/10.1111/jfb.13654

The Baffin Bay estuary is a hypersaline system in the Gulf of Mexico that supports an important recreational and commercial fishery for black drum Pogonias cromis , a benthic predator. Seasonal measurements of water quality variables, benthic macrofauna densities and biomass, and determination of P. cromis food sources using stomach‐content and stable‐isotope analyses were carried out to determine how P. cromis food sources change with water quality and how this may affect P. cromis diet. Gut‐content analysis indicated P. cromis selectively consumed bivalves Mulinia lateralis and Anomalocardia auberiana . Isotope compositions demonstrated that P. cromis relied on these benthic food resources produced in the Baffin Bay estuary year‐round. Biomass and densities of these bivalves were influenced by changes in water quality variables, particularly salinity and dissolved oxygen. Thus, this paper demonstrates the relationship between water quality variables, benthic macrofauna, and their use as food resources by a carnivorous fish species, and emphasizes the need for integrated assessments when studying the effects of water quality on ecosystem function. Holistic approaches such as these can provide important information for management and conservation of fishery resources and can improve predictions of ecosystem response to climate variability.