Connor Graham, Francis Marion University
The approach: In my previous post I talked about using benthic microalgae (BMA) as bioindicators for South Carolina’s coastline. If they are truly the “superheroes” we need, we will be able to use BMA to test water quality that affects commercial and recreational fishing, tourism, and even human health. My job in all of this is to determine whether or not these diatoms are actually present and similar in the sediments of the saltmarshes. If they are similar in similar unimpacted habitats then they can be used as biological signals. The bat-signal illuminates the sky to alert the citizens of Gotham City that there is a problem and in the same way diatoms could potentially be our signal for the environment.
My team and I have traveled to five barrier islands on South Carolina’s coast to gather samples from the mudflat regions. On each island, I had three main sites, 0,10, and 100 meters. From these sites, each had a letter, A, B, C where our samples were collected. At 10 meters, each letter has three sub-sites.
Using BMA as bioindicators will require the community structure to be similar among islands. Previously, I mentioned when concerning microbes we assume they are everywhere because of their incredible abundance, however that is not the case. I will look at the BMA community structure on the various islands and see if there is any correlation between them and geographical distance. If there is a correlation between community variation this relationship is called beta diversity and geographic distance, then is it possible that factors other than environmental one also affects the relationship between regional and local BMA communities (i.e. dispersal limitation).
Some of the environmental factors that were measured at each site at each island are sediment, air and water temperature, amount of light and PAR, humidity, wind speed, pressure and the amount of dissolved oxygen. Current, and water salinity were also measured. If the communities are dissimilar these measurements could be our contributing factors.
The collected samples from the salt marshes will also undergo an array of measurements that are also considered ecological factors. For example, each sample will be measured for the moisture content, organic matter, and chlorophyll. Moisture content data allows me to again compare the different mudflats to identify similarity. The same is for organic matter and chlorophyll. Chlorophyll a measurements, in particular, will allow my team and me to quantify the total mass of diatom species (biomass) of each island.
The idea of microorganisms displaying geographical patterns is debatable. Some believe that patterns are based on ecological factors alone, while others believe that the community diversity geographical patterns are based on ecological factors plus historical factors such as dispersal limitation or competition (Soininen 2012). Either way, we will finally be closer to knowing whether diatoms can be the signals we are looking for. If they are will we be able to see the “Diatom Signal” warning us about the health of our coast and what will we do about it?
I would like to thank my mentors: Dr. Craig Plante and Kristina Hill-Spanik (CofC). Also, I would like to thank my lab partner Max Cook (CofC). This project is supported by the Fort Johnson REU Program, NSF DBI-1757899).
Soininen J. (2012) Macroecology of unicellular organisms – patterns and processes. Environmental Microbiology Reports, 4(1): 10-22.