Category: OSCAR

Plastic material is a ubiquitous component of nearly every ecological niche on the planet. Once broken down to pieces less than 5mm in diameter, these plastics are considered “microplastics”. Microplastics act as a substrate for bacterial and viral organisms which can lead to transmission of potentially dangerous pathogens. One organism that may negatively impact the health of animals is cyanobacteria through the production of cyanotoxins that can be harmful to many aquatic animals that might attempt to ingest microplastic. Research into the colonization and succession of cyanobacteria on microplastic has intensified over the years, with various strategies being employed to measure the volume of organic material found on microplastic. To investigate these succession dynamics in the Potomac River, three different types of plastic were sampled across 8 weeks. Samples were preserved for visualization with fluorescence microscopy, so that total cell counts and counts of cyanobacteria can be collected. While cell counts are still ongoing, a protocol was developed to visualize cyanobacteria. Each plastic piece was stained with DAPI and visualized using a light microscope, with two UV filters to capture various wavelengths. This research will be valuable in determining how cyanobacteria colonize different types of microplastics in a eutrophic aquatic environment.

Hello, my name is Victor Cregger. Today I will be going over my presentation on succession in microplastics, or simp for short, if you want to call it that. I want to thank everyone for joining me today, let’s not waste time and get right onto the presentation. I will be going over what microplastics are, the field work done, and the data extrapolated from that field work, and then future research and final remarks. On the left you’ll see I have cut up milk jugs and plastic bags, they were used during the experiment and will be covered in more detail shortly. First, what are microplastics? Microplastics are any plastic particulate less than 5mm in diameter. They are found in every corner of the world from the deepest part of the ocean to the most remote deserts on the planet. Microplastics are dangerous as they can act as a substrate for dangerous pathogens. Current research is being done to see if the pathogens can cross into the animal barrier and if we can contract diseases from that. Microplastics then serve as a potential health hazard. One phylum of bacteria that I am studying is cyanobacteria, because they produce cyanotoxin that is very dangerous to any organism that tries to ingest it. The goal of this experiment was to see if, when, and how these cyanobacteria populate microplastics over the course of 8 weeks. For the field work and data, I would like to first give thanks to Tom Hutchinson, as he provided much of the material used for the experiment as well as assisted in creating the experimental design. Without him this would have been very difficult so thank you Tom for the help. What we did is tie a rope to two anchored buoys and tied knots 2-3 feet apart from each other, the line itself was about 25 feet in length and this was taken right outside the Potomac science center dock. What I did was tie a mesh bag to each individual knot, each mesh bag contained different types of microplastic such as milk jugs, yogurt containers, and plastic bags. I had two sets of three different microplastic in case I ran out in one set, I would still have more material. Then I put the plastic into whirl Pak bags and placed them into 4% formalin tubes to be z fixed. This freezes cells in place so that I can look at the pieces under a microscope later on. Any sort of microplastic I had remaining was frozen in the -80 freezer for future study. Now that every sample is ready for microscopy, I can now conduct cell counts in the fall. I also collected water characteristics using a YSI and filter machine. The YSI tells me temperature, salinity, and just about every water characteristic that I need. This is to see if there is any correlation between cyano growth and the property of the water at that time. The filter again was to see what exactly was going on, so I have a pretty good snapshot of the river every Monday that I went to go sampling over 8 weeks. This is what I got from the YSI. The bottom table shows the water properties, there is a big difference in water property over the course of 8 weeks, and the top shows the identifier on what my plastic looks like. You’ll see I have polyethylene and polypropylene bags, and this again is to test to see if there is preferential treatment of cyano growth on plastic type. Unfortunately, I could not conduct cell counts at this time, the microscope I have does not have the filter I need to see cyanobacteria. They auto fluoresce at a specific wavelength, and I can not cover this wavelength with the filter I have. However, I do have a filtered microscope now that can hopefully see cyanobacteria, which will allow me to finish the experiment in the fall. This will help any future research, especially with the frozen material I have, this will allow us to see bacterial succession and other topics that may be picked up at a later date. Again, research into cyano growth in a eutrophic aquatic environment is always helpful. Thank you so much for watching my video.

A project to find and culture a local strain of the pathogenic fungus Ophidiomyces ophidiicola, which is responsible for sickening and killing large amounts of wild snakes. Swabs were collected from wild snakes around the Northern Virginia area, for the purpose of growing the fungus in pure culture, extracting its genetic material, and sequencing its genome using Long Read/Oxford Nanopore sequencing technology, a new and higher fidelity method of sequencing entire genomes.

Welcome to the presentation on genetically sequencing Ophidiomyces ophidiicola. This is a Summer 2023 George Mason University Undergraduate Research Scholar Project. My name is Joshua Walton. I’m a senior in the biology program here at GMU and today I will be showing you my science.

To start I’ll tell you what Ophidiomyces ophidiicola is. It’s a pathogenic fungus that resides in the soil across the United States and it was first discovered in 2009 on the skin of a black rat snake. Since then, further study has revealed that the fungus causes a disease known as Ophidiomycosis, which results in severe illness and even death in wild snakes of all species. Because of the great importance of wild snakes in controlling populations of animals that cause human diseases like ticks and rodents, the fungus has been of great concern to herpetologists since it was first detected. This concern is mainly due to its rapid spread, which climate change and environmental destruction is suspected to play a part in.

The goal of my project was to capture and culture a sample of local Ophidiomyces ophidiicola from a wild snake and sequence its genome using a newer genetic sequencing technology called long read/Oxford Nanopore sequencing. However I was unable to grow enough of the pure fungus to perform this type of genetic sequencing, so that hasn’t happened yet. In the meantime, let me take you through the process that this kind of science requires. This is a unique project that encompasses all levels of biology from sample collection in the woods to data analysis with computer code in the lab. The first step in the process is to go out into nature and grab a wild snake with your bare hands. The majority of wild snakes are not venomous, so this is a perfectly safe activity as long as you know how to spot the venomous species like Copperheads. Once the snake is caught, the snake’s face and body are brushed with sample collection swabs, which are just giant Q-tips. Further data about the snake is collected such as length, temperature, sex, and number of skin defects visible. If a snake has a skin defect, also known as a lesion, it is swabbed specifically and that swab is rubbed into a specially formulated agar gel plate to attempt to grow a sample culture of any fungus that may be infecting the snake.

Back at the lab, DNA is extracted directly from the sample swabs or from fungal tissue cut from the agar plates by placing them into test tubes containing tiny plastic beads. These tubes are then placed into a machine that shakes them with Incredible violence. The beads pulverize and liquefy the samples, breaking the cell walls of the material and allowing the DNA to float freely in the liquid. This is a messy process that there is no instruction manual for, and you have to make the directions for yourself by reading a bunch of technical specification sheets and journal papers published by other scientists working on similar projects, and then putting all the useful bits together for yourself. It took me in my mentor Lauren many tries and many days to produce a reliably working extraction process, but we finally did it.

After extraction comes analysis, and the sky’s the limit for this part. Typically samples will be run through an awesome machine called PCR, which is literally a copy machine for DNA. A specific DNA sequence of interest can be copied and then analyzed through things like gel electrophoresis to confirm if a specific species of fungus is present. A sample can also be run through a different type of PCR called Quantitative PCR, which can tell you how much of a specific fungus is present. These are the same tools that doctors use to measure things like COVID infections in humans. With Quantitative PCR you can also perform limited genetic sequencing to separate one strain of fungus from another variant of the same species of fungus, by looking at very small single letter changes in the DNA of both fungi. Since I was unable to grow enough fungus to perform a whole genome genetic sequence, this process is now the focus of my project because much information about Ophidiomyces ophidiicola can still be gleaned from it. This project has been incredibly fun and rewarding for me. I’ve gotten to see and experience how science works in the real world, in addition to gaining enormous amounts of practical skills in the laboratory. Despite the fact that I couldn’t get a whole genome sequence of the fungus like I wanted, I’ve gained many priceless lessons along the way. I’d like to thank my mentor Lauren Fuchs for her invaluable help with this project and beyond, and everyone else who has provided help and advice to me throughout the course of this project, all of whom are listed on this slide. I plan to continue working on this project for the foreseeable future, and hope that it eventually produces some valuable results. Thank you.

For this research project, I focused on Alzheimer’s Disease. Which is the most common dementia related diagnosis given to the elderly in America. Alzheimer’s is diagnosed post-mortem, because only through brain dissections can doctors be 100% sure that the patient had Alzheimer’s. From these post-mortem dissections it is known that Alzheimer’s is caused by a buildup of amyloid plaques and tau tangles. The most well known symptom of Alzheimer’s is memory loss and there is no known cure that targets Alzheimer’s t the root, but rather medicine that reduces AD symptoms. Researcher like Dissel and her team, have found that sleep can help reduce the memory loss symptoms of Alzheimer’s. In her paper they mechanically induced sleep in fly models through rocking them to sleep.
For this project, I used Drosophila models that exhibited human amyloid precursor protein and Beta-secretase (APP:BACE) and amyloid precursor protein microtubule-associated protein tau (APP + MAPT) , to see how mechanically induced sleep effects short term memory retention.
Overall, due to technical errors, not a lot of sleep data could be collected. However from the Pilot 1 study, the results show that mechanically induced sleep may not overall significantly increase day sleep, it does significantly increase day sleep hour-by-hour
The short term memory tests did relay that the procedure was properly working, but the results were not conclusive enough to determine if rocking flies to sleep increases their STM.

Hello My name is Saba Shaukat and my OSCAR research is on The Effects of Rocking on Short Term Memory in APP:BACE and APP+MAPT Drosophila Melanogaster.
For this research project, I focused on Alzheimer’s Disease. Which is the most common dementia related diagnosis given to the elderly in America. Alzheimer’s is diagnosed post-mortem, because only through brain dissections can doctors be 100% sure that the patient had Alzheimer’s. From these post-mortem dissections it is known that Alzheimer’s is caused by a buildup of amyloid plaques and tau tangles. The most well known symptom of Alzheimer’s is memory loss and there is no known cure that targets Alzheimer’s t the root, but rather medicine that reduces AD symptoms. Researcher like Dissel and her team, have found that sleep can help reduce the memory loss symptoms of Alzheimer’s. In her paper they mechanically induced sleep in fly models through rocking them to sleep.
For this project, I used Drosophila models that exhibited human amyloid precursor protein and Beta-secretase (APP:BACE) and amyloid precursor protein microtubule-associated protein tau (APP + MAPT) , to see how mechanically induced sleep effects short term memory retention.
My methodology consisted of many parts. I first conducted a Pilot study with my parent flies. During this time collected baseline sleep data, that did not include rocking and then I collected rocking sleep data. For sleep data I placed the flies onto a Drosophila Activity Monitoring System, or DAM2 monitors. And For the rocking I placed the DAM2 monitors onto a shaker from 7 am to 7 pm,, and had the speed set to 2. I then crossed my parent flies with GAL4 drivers and collected the F1 progeny flies. I then conducted pre- rocking short term memory phototoxic tests and post-rocking short term memory tests. This was done by placing the flies in the center of two tubes, one was covered in aluminum foil to mimic the dark and the other one had a kiwi wipe soaked in a sour quinine solution. The tests were done in blocks of 4 trials for 16 trials for each fly. Due to technical difficulties sleep data could not be collected for the F1 generation.
The key results of this project were determined using the Pilot 1 sleep data and the accumulation of pre-and post-rocking data for short term memory. The results showed that there was no significant increase in day sleep for the APP:BACE and APP+MAPT flies when comparing the results for the baseline sleep and the mechanically induced sleep.
The graphs shown depict day bout and night bout for each group of fly. The graphs that depict short term memory show that there is learned behavior as the trials went one, comparing the results from the firs block to the last block. The first four trials and the last four trials
This graph showcase, pilot 1 data for day bout a day before rocking, when compared to the graph showcasing the day of rocking data, (change to next slide) The data does showcase slightly increased amount of day bout sleep and looking at the data on a hour-by-hour case, there is significant increase in sleep during the day after the sixth hour but when looking at the whole 24 hours there is no significance for either the APP:BACE nor the APP:MAPT
The next two graphs show night bout sleep for the day before rocking and the day after. A similar pattern is seen, the day of rocking has a slight increase of sleep, maxing at 720, but not enough to be significant.
This graph showcases the results for the Short term memory, for both the males and females pre-rocking and post-rocking. The orange line is depicts the last 4 trials, and it is notable that for both graphs the flies showcase learned behavior where they have an increase in movement towards the dark tube, avoiding the light and the tube that has the aversive substance. In this case the quinine.
This graph depicts the learned behaviors of the male APP:MAPT flies pre- and post-rocking. They demonstrate similar behaviors where the last block, scene in orange is mainly higher after the rocking. This could mean that rocking the flies to sleep may have helped with their memory retention, but without sleep data to compare with, this results are not significant enough.
The last two graphs depict the female APP+MAPT flies, they also demonstrate positive learned behavior regarding the short term memory procedure, but without sleep data, the results can not be considered significant and no correlation between mechanically induced sleep and increased memory retention can be made.
Overall, due to technical errors, not a lot of sleep data could be collected. However from the Pilot 1 study, the results show that mechanically induced sleep may not overall significantly increase day sleep, it does significantly increase day sleep hour-by-hour
The short term memory tests did relay that the procedure was properly working, but the results were not conclusive enough to determine if rocking flies to sleep increases their STM.
For future research that looks at alternative ways to reduce memory loss symptoms in Alzheimer patients, more sleep data needs to be collected with a larger sample size. It would also be interesting to see how different modes of rocking effect the condition of sleep and o be able to draw better comparison between rocking and sleep improvement. Also, it examining brain dissections of flies with memory impairment pre- and post-rocking would be beneficial to understanding microscopic differences in the memory control centers.
And that is all for my OSCAR project, thank you.

In the recent 2023 report from the Intergovernmental Panel on Climate Change, concerns were raised over the rising global temperatures and relative humidity, particularly in tropical regions. These factors are critical in humans’ effectiveness of sweating and avoiding hyperthermia. Wet bulb globe temperature (WBGT) is a newer, more effective heat index used to measure heat stress on the human body depending on air temperature, relative humidity, wind speed, and solar radiation. It provides a more accurate “feels like” temperature. This study to calculates WBGTs and their associated variables for St. Thomas, Water Island, and St. John, USVI using seven Tempest Weatherflow Stations across the three islands. This creates a recent historical basis for WGBT in the region as well as provide a foundation for predicting how future climate change will affect risk to human health in the Virgin Islands.

Hello, my name is Katie Russell and I am an undergraduate Biology major at George Mason University. I participated in the 2023 summer URSP to conduct research on wet bulb globe temperature across the islands of St. Thomas, Water Island and St. John, USVI.
According to the recent report from the Intergovernmental Panel on Climate Change, globally increasing temperatures and relative humidity put communities at elevated risk of hyperthermia, or overheating. Our bodies are able to combat this to a certain extent by sweating. Sweating is vital for thermoregulation. When the body temperature begins to rise, sweat glands are activated. As the sweat evaporates, the body temperature is lowered, and we can maintain our delicate internal homeostasis.
This mechanism is threatened in areas of elevated humidity. For sweating to cool you down, the air must absorb the water evaporating from your sweat. However, when humidity is high, the air is already saturated and the sweat on your skin will not readily evaporate, making it much more difficult to cool down. Extreme heat is the leading cause of weather fatalities across the U.S. with increasing frequency. For every day of extreme heat, there is an additional 0.07 deaths per 100,000 adults.
There are several indexes used to assess this relationship between temperature and humidity. The one you are most likely familiar with is the heat index. The heat index tells you the “feels like” temperature, or how the temperature feels to the average human while standing in the shade. The issue is that humans do not feel all heat the same, so this parameter is often considered subjective and not an indicator of heat stress on the body.
The other, newer method is wet bulb temperature and wet bulb globe temperature. These two terms are often used interchangeably, however, wet bulb temperature is a measure of the lowest temperature to which the air can be cooled by evaporation. Wet bulb globe temperature is a measure of the heat stress on the human body in direct sunlight. These measurements were traditionally taken using a thermometer covered by a wet cloth and assessing how much the thermometer cooled as the water on the cloth evaporates. In this way, wet bulb and wet bulb globe temperature can be used as a proxy for climate change influence on temperature and relative humidity and as a predictor for habitability, especially for tropical environments.
In this study I collaborated with Mr. Jay Titlow, senior meteorologist and co-founder of WeatherFlow, to access data from Tempest weather stations across the Virgin Islands. Tempest weather stations are a mixture of privately owned and installed weather stations and those established by the University of the Virgin Islands. Their prime directive is to monitor wind speeds and direction for hurricanes, however they collect data on most relevant weather parameters.
Of the 18 active stations on St. Thomas, St. John, and Water Island, only seven of them had been operational for at least a year. Two on St. Thomas, one on Water Island, and four on St. John. For each of these seven stations, air temperature, relative humidity, sea level pressure, wind speed, and solar radiation averages were collected for every week since the station began reliably recording. There are several instances of gaps within the historical data for which their were no values. These are colored red.
As the Tempest stations are not equipped with a wet bulb thermometer, the wet bulb temperature and wet bulb globe temperature are derived values that are calculated in real-time using a coding algorithm and are not saved in the historical databases. Although wet bulb temperature and wet bulb globe temperature are different, wet bulb temperature is a variable in the calculation for wet bulb globe temperatures. Calculation of wet bulb temperature was done for individual data points using the National Weather Service’s online calculator for “Dewpoint and wet-bulb from relative humidity” created by Tim Brice and Todd Hall. This calculator requires only the air temperature, relative humidity, and station pressure – which in this case is sea level pressure.
Differences in readings from the sites are a result of different positioning, and location. Wind speed is particularly variable based on wind shadowing and altitude of the station. Outlier data due to incorrect calibration or system malfunctions were removed from the final data sets.
At this point in the research, I have just completed producing the graphs for wet bulb temperature, dewpoint, and the observed parameters. The wet bulb and dewpoints show consistent seasonality, with the highest values beginning in April and declining in November. Lower wet bulb temperatures in the cooler months indicate that there is less moisture in the air and water vapor, or sweat, can readily evaporate and cool the air.
Dewpoint and wet bulb values follow each other reliably, with dewpoint always falling slightly below. I also observed from the data that sea level pressure has a negligible impact on wet bulb temperature, but lower pressure will produce a higher dewpoint.
According to a 2010 study by Massachusetts Institute of Technology, the critical wet bulb temperature is 35 degrees Celsius at which a human can no longer metabolically dissipate heat. Another lab study conducted by Penn State, indicated that the critical environmental limit at which an individual’s internal temperature begins to exponentially rise is a wet bulb temperature of 31 degrees Celsius. This presents significant concern as the maximum wet bulb value found in my datasets was a staggering 26.9 degrees Celsius for the week of 6/5/2023 at the Water Island Station. Maximums datapoints for all stations fall above 25 degrees Celsius.
Wet bulb globe temperature has yet to be calculated for this data using the equations shown. Wet bulb globe temperature will provide a better predictor of heat stress on an individual in these conditions. It is expected that wet bulb globe temperatures will result in higher values than wet bulb temperature.
The original goal for this data was to use it to make model predictions of future wet bulb globe temperatures and human habitability using climate models from the IPCC report. However, none of the Tempest data stations have records going back further than three years which is insufficient historical data for model building. Despite this setback, this project will produce the first recorded database for wet bulb and wet bulb globe temperatures in the Virgin Islands. As time progresses, more data can be added to the set and a larger sample size will make modeling, predictions, and the establishment of climate trends possible.
That being said, once wet bulb globe temperatures have been calculated, they will be graphed against air temperature to extrapolate values under warming scenarios put forth by the 2023 IPCC report. This will either loosely support or counter the hypothesis that under severe warming conditions the Virgin Islands wet bulb globe temperatures will exceed habitable levels.

The goal of this project was to measure trace metal concentrations along a salinity gradient in the Potomac River for future use in studies using otolith chemistry to remap the life history of economically valuable sportfish like red drum and river herring. Two sampling sessions were made taking triplicate water samples at 5 PSU intervals (0-15) starting from the mouth of the river and working upstream. ICP-AES Mass Spectrophotometer analyzed diluted samples according to the salinity in which they were obtained. Targeted elements of interest were Calcium (Ca), Strontium (Sr), Barium (Ba), and Magnesium (Mg) as well as the last three’s ratio to Calcium specifically (ex. Sr : Ca). Analysis revealed the observed concentrations of all targeted elements to be remarkably similar to what was expected, indicating that the proper biogeochemical cycling mechanisms in the Potomac River remain intact. Observed values for Sr, Ca, and Mg increased linearly with salinity while Ba exhibited a non-linear gradual decrease in line with its multi-faceted cycling in and out of estuarine environments. Ratios of Sr:Ca and Mg:Ca displayed the expected exponential increase while Ba:Ca declined exponentially. Using elements as salinity proxies relies on the difference in elemental concentrations between marine and estuarine environments to remap a fish’s location history based on the amount of the aforementioned elemental ratios in a given growth ring in an otolith. This study fulfilled the first out of three ‘need to know’ aspects for using element concentrations in otolith to remap life history: knowing what elements are in the environment and how they vary with salinity, what elements end up in the fish otolith, and the proportion of water elemental concentrations that make it into a fish otolith at a given salinity.

Hello, my name is Riley Robinson and today I’ll be presenting my Summer 2023 research project that I conducted under the mentorship of Dr. Thomas Reid Nelson. This summer our project was quantifying trace metal concentrations along a salinity gradient in the Potomac River and in these next few slides, I’ll just give you some more details into what we did. So the goal of this research was to establish the relationships between elemental concentrations of barium, strontium, calcium, and magnesium across a salinity gradient in the Potomac River for use in future otolith analysis of common migratory fish species like river or blueback herring, striped bass, and alewife. This research is of particular importance because the Potomac River has a lot of economic and environmental value for the state of Virginia and its neighbors. It holds a lot of sought-after sport fish that are targeted by anglers and is a large resource of revenue for crabbing and many other industries. As for the specific applications of this research, many might ask, how do you use otolith chemistry to reconstruct fish migration patterns? Well, remapping the life history of the fish requires a lot of steps, but three main need-to-know aspects. And the first one is knowing what elements are in the environment and how they vary with salinity. Second, knowing what elements end up in the fish otolith. In the figure below, you can see an extracted otolith from a red drumfish. And third, knowing the proportion of elemental concentrations that make it into a fish otolith at a given salinity. So, this research project is limited in scope to the first one only. The main application of using salinity proxies to reconstruct fish migration patterns is that it relies on the freshwater and the marine water that are mixing in estuaries. It relies on them having different elemental concentrations. to be able to determine a specific location along a salinity scale. As for our methodology, since this was a trace metal study, we had to be very careful about cross-contamination for our samples with anything else that had metal on it specifically. So for that reason, we had to acid clean our sample bottles and syringes and then fix the bottle specifically with one-to-one nitric acid to preserve the integrity of the trace metals. Then what we did is we worked our way from the mouth of the river all the way back at five PSU intervals and at each site we took three water samples through a syringe with a 45-micron filter. This was used specifically to remove the particulate matter that’s found in these very muddy brackish estuarine waters. We found this specific salinity using the device in the top right called the YSI Sonone and that specifically just tells you the salinity and many other parameters. But once we found that we got to sampling. And then once we finally brought our samples back, and put them on ice, we finally got around to diluting them. And we do this because the instrument that we use to analyze them, the mass spectrometer, it’s not very good with impurities. So obviously we want to make our sample as pure as possible. So we use the syringe filter and then we dilute it even further because the excess salt that’s found and mixed in the estuarine waters is really not good for the machine. So we diluted it based on the PSU that it was taken from. So the less than one PSU was diluted 10 times, one to seven, 20 times, and then any higher than that was 50 times. As for the mass spectrometer itself, we had to make custom standards since it was just cheaper than buying this specific one. And our goal in doing this was to sort of mimic the environment that the sample is found in. So what we do is we tell the machine what to look for and then we give it our sample and it looks for how much of that is in our sample. As for the historical trends of these elements in estuaries, usually, concentrations of calcium, strontium, and magnesium are conservative with salinity, displaying a linear increase in estuarine environments. Concentrations of these elements are usually a consequence of riverbed weathering upstream, which affects their concentration downstream. The ratios of strontium to calcium and magnesium to calcium both increase non-linearly with salinity. As for barium, it’s far less predictable since it enters and exits estuaries in really complex manners. Addition usually occurs through desorption from suspended particulate matter, benthic release from the very soil on the riverbed, and addition through submarine groundwater discharge which, all in all, is also affected by river flows, which thus further complicates things. We see a conservative decrease with barium, which is shown in this expected graph in the bottom middle. And as for the ratios of barium to calcium, these also decline exponentially, which is that bottom curve you see. As for the results, I’m going to go through the individual elements first, and we’ll get back to the ratios later. So to start with calcium, which is probably the most important, since it makes up a good portion of the calcium carbonate matrix that we find in the fish otoliths. So we expected this linear increase, and this is really what we saw. It wasn’t anything unusual. Moving on with Strontium, we also expected this linear increase, and to no surprise, it’s also what we saw. As for Strontium though, the levels were a teensy tiny bit lower than what we expected, but it really wasn’t anything of note. As for magnesium, we also expected this linear increase, and to no surprise, we also got it, which is a good indicator that there isn’t really anything wrong with the river itself since we are seeing these normal linear trends. As for Barium, it’s also exactly what we expected. It had this conservative decrease, but it’s certainly not linear. It’s really just all over the place. You see all these data points. They’re not really in a specific fashion, other than gradually going downwards. Like I mentioned previously, since Barium is highly variable in estuarine environments from the complex ways that it enters and exits, this is really normal for Barium in an Estuarine environment. As for the elemental ratio results, starting with strontium to calcium, we expected this nonlinear increase with salinity, and that’s what we got. As for barium to calcium, we expected it to decline exponentially, and once again, that is also what we found. The same goes for magnesium to calcium, which was again an expected nonlinear increase. I just wanted to mention, take note at the units of these concentrations. Strontium and calcium are in millimoles to moles, and this is because the concentrations that these are found in, vary far greatly. Since calcium is more profound, it has the moles, since strontium is less profound, it has the millimoles. We can’t really put them on the same mole-to-mole or millimole-to-millimole scale because it just doesn’t really work. You can’t really do that in good faith. We were trying to make an accurate graph. So the same goes for a lot of these other ones. Magnesium to calcium is sort of an exception. You can do the mole-to-mole ratio, but it’s a little different. As for the analysis and application of our data, the primary use for our dataset was to fulfill only one of the three need-to-know aspects to use otolith chemistry to study fish migration. This need-to-know aspect is knowing which elements are in the environment and how they vary with salinity. By doing this and doing the other two in turn, you can correlate the concentrations of metabolized trace metals in an otolith, which grows during the fish’s lifespan, sort of like tree rings, to the trace metal concentrations along a salinity gradient. which allows for somebody to remap the life history of a fish and see where they were at a given point in its lifespan. The way that this is possible is through the chemical makeup of otoliths. They’re normally made up of calcium carbonate, to which similar elements were also studied, calcium, magnesium, strontium, and barium. These all take the place of calcium within an otolith once it’s metabolized. and it’s why the ratios of similar elements to calcium are of extreme relevance. So what’s next? I mean, we only have one part of our data set, but future researchers looking to study migratory fish via otolith chemistry in the Potomac River can use this data set in one of two ways, as A, a reference set to determine if extensive otolith studies should be done, or B, a procedural replicate of trace metal concentrations in the Potomac River for studies conducted in the near future. but future speaking, five-plus years later, since the elemental concentrations can also vary over time. It’s my recommendation that this data set be a procedural replicate only and then supplemented with its own replication of our methods in a future study in order to ensure a proper coherent data set. And that’s all I have for you guys today. If you have any questions, please feel free to comment or ask down below. And here are my references and I hope you guys all have a good day.