Hey guys, this summer I am studying two species of freshwater mussels native to Texas, Q. petrina and Q. aurea. The significance of studying these species is that both are considered threatened species in Texas, and little is known about the environments that they live in throughout the course of their lives. I have made significant headway on my project since my last blog post. I have micromilled 130 samples along the prismatic growth layer of the mussel species Q. petrina. Approximately half of these samples have already been analyzed in the mass spectrometer, which will provide us with the oxygen isotope ratios (oxygen 18, in particular) and carbon isotope ratios (carbon 13) for each sample.
My next task is to use these shell isotope ratios to reconstruct the environmental conditions that the mussels experienced during their lifetimes. The shells oxygen isotope values can be used to estimate the water temperatures that these mussels experienced using methods in previous studies. Additionally, the isotope ratios can be compared to a time series of the mussel using growth increment chronology in order to show seasonal oscillations in the isotope values, hopefully illustrating temperature fluctuation and other events such as flooding.
The below picture is a cross section of Q. petrina. Each cross section of this species contains three different layers. The periostracum is the very outer layer, contains no growth increments and under the microscope it is the darkest of the three layers. The second is the prismatic layer, which is the colored middle layer, and contains the growth increments that we want for the experiment. The third layer is the nacreous layer, which contains many growth increments, but cannot be used because there are too many growth increments in each area, and therefore cannot serve as proxy for any period of time in particular. One of my jobs is to use the computer operated Micromill to drill out samples in the shape of raster’s (basically rectangles) into the prismatic layer. By lining the raster’s one after another, it allows us to then use the shell isotope values from the samples to compare with their respective raster areas, combined with measuring the distance between the midpoints of each raster to the next, to create a time series with a growth-climate relationship. More to come soon!