Crassostrea virginica Larval Interactions with Synthetic and Algal Particles Erika Schmitt 1 and Heidi Fuchs 2 1 St. Mary’s College of Maryland, St. Mary’s City, MD 2 Rutgers Univerisity, New Brunswick, NJ Crassostrea virginica (Eastern Oyster) larvae at the veliger stage have the ability to sink or swim. There is evidence that some mollusk larvae are affected by turbulence, causing them to sink, so oysters could have similar reactions. We could observe the larvae’s reaction to turbulence by using particle image velocimetry (PIV), which uses a laser with seeding particles to obtain velocity measurements and determine the flow in fluids. When using live veliger larvae with PIV, they could be affected by the seeding particles, which could change their swimming patterns and reactions. Background Fig 1. C. virginica at veliger stage. The projection is the velum, used for swimming and feeding. Particles can interfere with the velum, affecting their swimming. Thanks to Don Merritt and Stephanie Alexander at Horn Point Laboratories for providing the larvae. Thanks also to Kay Bidle for use of the Coulter counter. Fuchs, H. L., L. S. Mullineaux, and A. R. Solow. (2004). Sinking behavior of gastropod larvae (Ilyanassa obsoleta) in turbulence. Limnology and Oceanography 49 : Raby, D., M. Mingelbier, J. J. Dodson, B. Klein, Y. Lagadeuc, and L. Legendre. (1997). Food-particle size and selection by bivalve larvae in a temperate embayment. Marine Biology 127 : Fig 2. The average length of the C. virginica larvae used was 323 μm. Objectives Results Observe the feeding rates, sinking velocities, and swimming patterns of Crassostrea virginica with different particle types: algae (ρ = 1.07 g/cm 3 ), nylon (ρ = 1.30 g/cm 3 ), hollow glass. (ρ = 1.40 g/cm 3 ), and silver-coated glass (ρ = 1.7 g/cm 3 ). Determine which particles affect them the least so we can improve our observations using PIV. Methods Fig 3. The experiments were conducted in 6L tanks with ppt salinity. Samples were collected at the start and end of an hour period and counted with a Coulter counter to determine feeding rates. Fig 4. We video recorded the swimming patterns of the larvae. After killing the larvae, we video recorded their sinking velocities and analyzed them in MATLAB. Results Conclusions The larvae fed on the algae the most and the nylon the least. The larvae tended to feed on smaller particles (2-10 μm) over the larger ones. The larvae sank faster after feeding on silver-coated and hollow glass particles than after feeding on algae. The larvae that fed on the hollow glass particles were slightly larger than the other larvae. There was no significant correlation between the size of the larvae and the sinking velocity (R 2 = 0.25; p=0.39). The hollow glass seeding particles would be the best choice to use with PIV. The larvae did not seem to be too affected by them and continued normal swimming and feeding patterns. Although algae would be ideal, they are less reflective and therefore harder to see with PIV. Since the synthetic particles are heavier than the algae, this would affect the sinking velocities. The size of the larvae did not seem to have a huge impact. The high feeding rate on algae was expected since that is their food, however there was a surprisingly high feeding rate on the hollow glass particles. These particles stay suspended in the water the best. The silver-coated particles sink and the nylon float, so they may have been more difficult to locate and ingest. References and Acknowledgements Fig 5. Larvae exposed to silver-coated sank the fastest, while the control group (no particles) sank the slowest. There is significant variation among the different particles (ANOVA; p<0.01). Fig 6. Larvae exposed to the hollow glass particles were the largest, and those exposed to the silver-coated and the control (no particles) were the smallest. There is significant variation among the different particles (ANOVA; p<0.01). Fig 7. The highest feeding rate was on the algae, with the lowest on the control (no particles) and nylon. There is significant variance among the different particles (ANOVA; p=0.03).