Differences in extreme low salinity timing and duration differentially affect eastern oyster (Crassostrea virginica) size class growth and mortality in Breton Sound, LA

Understanding how different life history stages are impacted by extreme or stochastic environmental variation is critical for predicting and modeling organism population dynamics. This project examined recruitment, growth, and mortality of seed (25–75 mm) and market (>75 mm) sized oysters along a salinity gradient over two years in Breton Sound, LA. In April 2010, management responses to the Deepwater Horizon oil spill resulted in extreme low salinity (<5) at all sites through August 2010; in 2011, a 100-year Mississippi River flood event resulted in low salinity in late spring. Extended low salinity (<5) during hot summer months (>25 °C) significantly and negatively impacted oyster recruitment, survival and growth in 2010, while low salinity (<5) for a shorter period that did not extend into July (<25 °C) in 2011 had minimal impacts on oyster growth and mortality. In 2011, recruitment was limited, which may be due to a combination of low spring time salinities, high 2010 oyster mortality, minimal 2010 recruitment, cumulative effects from 10 years of declining oyster stock in the area, and poor cultch quality. In both 2010 and 2011, Perkinsus marinusinfection prevalence remained low throughout the year at all sites and almost all infection intensities were light. Oyster plasma osmolality failed to match surrounding low salinity waters in 2010, while oysters appeared to osmoconform throughout 2011 indicating that the high mortality in 2010 may be due to extended valve closing and resulting starvation or asphyxiation in response to the combination of low salinity during high temperatures (>25 °C). With increasing management of our freshwater inputs to estuaries combined with predicted climate changes, how extreme events affect different life history stages is key to understanding variation in population demographics of commercially important species and predicting future populations.