Distribution of Mysid species in Relation to Environmental factors in Maryland Coastal Bays

The distributions of two mysid species, Neomysis americana and Americamysis bahia, were investigated in the coastal lagoons of Maryland using macrobenthic sled survey data collected from 2012-2013. Specifically, we compared mysid abundances between the northern and southern bays that differ with respect to the biomass of phytoplankton, macroalgae and fish, and examined the relationships between mysid abundance and abiotic factors and fish abundance. Generally, Neomysis was more abundant in the northern bays than in the southern bays in 2012 (Mann-Whitney U = 1.90; P = 0.05) and 2013 (Mann-Whitney U = 2.75; P = 0.01) as was noted for Americamysis in 2012 (U = 2.35, P = 0.02). Americamysis was more abundant on the western parts of the estuary where muddy-silty sediments dominate than on the eastern part with predominantly sandy substrate, but no such distinct distribution pattern was observed for Neomysis. Spearman’s rank correlation analyses indicated that Neomysis americana abundance was inversely correlated with temperature in 2012 (r_s = -0.49; p < 0.001, n = 89) and 2013 (r_s = -0.28; p < 0.001, n =130), salinity in 2013 (r_s = -0.23, p<0.01, n = 130), but positively correlated with water depth in 2012 (r_s = 0.33, p<0.01, n = 76). However, no such correlations were observed for A. bahia. There was an inverse relationship (r_s = -0.45, p = 0.03, n = 24) between the abundance of mysids and fish predators such that mysid mean catch per unit effort was comparatively higher in winter (13.3 ± 5.73) and spring (7.9 ± 5.7), when the densities of fish predators were relatively low (9.92 ± 9.92), than during summer (0.85 ± 0.45) and fall (3.95 ± 2.09) when fish densities were relatively high (65.76 ± 10.86). This suggests that mysid abundance is controlled by fish predation. Knowledge of the population dynamics of keystone species such as N. americana and A. bahia is important for understanding estuarine food web dynamics and developing ecosystem models.