Ranking ecosystem impacts on Chesapeake Bay blue crab ( Callinectes sapidus ) using empirical Gaussian Graphical Models

• Published in: Canadian Journal of Fisheries and Aquatic Sciences
• Main Authors: Liang, Dong, Nesslage, Geneviève M., Wilberg, Michael J., Miller, Thomas J.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Canadian Science Publishing 2021
• Subjects: Aquatic Science; Ecology, Evolution, Behavior and Systematics; North Atlantic; North Atlantic oscillation
• Online Access: http://dx.doi.org/10.1139/cjfas-2019-0439; https://cdnsciencepub.com/doi/full-xml/10.1139/cjfas-2019-0439; https://cdnsciencepub.com/doi/pdf/10.1139/cjfas-2019-0439

Moving toward ecosystem-based fisheries management requires integration of biotic and abiotic factors into our understanding of population dynamics. Using blue crab (Callinectes sapidus) in the Chesapeake Bay as a model system, we applied Gaussian Graphical Models (GGMs) to understand the influence of climatic, water quality, and biotic variables on estimates of key indices of blue crab recruitment for 1990–2017. Variables included the North Atlantic Oscillation (NAO), Susquehanna River discharge, wind forcing, hypoxic volume, submerged aquatic vegetation, and the catch per unit effort of striped bass (Morone saxatilis). Direct effects of age‐1+ crabs and summer salinity on recruitment were significant. Phase of the NAO in summer and spring, summer and winter discharge, and hypoxic volume indirectly affected the recruitment. A simulation study showed that GGM model selection achieved nominal coverage and outperformed structural equation modeling (SEM) and Multivariate Adaptive Regression Splines (MARS). GGMs have the potential to improve ecosystem-based management of blue crabs in Chesapeake Bay. Specifically, the approach can be used to examine ecosystem impacts on blue crab productivity and to improve forecasts of blue crab recruitment.