This week, I worked on initial results from one of our spatiotemporal models, which we are using to understand how Mississippi River management scenarios affect the health of fish, shellfish, and fisheries in the northern Gulf of Mexico. The results from these model runs come in multiple forms, including yearly biomass data, yearly fisheries landings data, some economic data regarding fisheries landings, and spatiotemporal distributions data. This last option, like a species distribution model, provides insight to how mobile species respond to changes in the environment and how sessile, non-mobile organisms respond in terms of biomass loss. While I cannot show results from this work since it is ongoing, I created a figure here using artificial values that helps explain how these models work and how we interpret the model results.










​From the model, we get a month by month distribution of organisms across the entire model domain, and the model gives us these distributions in a column and row format. From these column and row data, we can create a map of our model domain and plot the biomass of each individual across the entire geographic space. We can then follow a single species across the entire model run by plotting its biomass for every month and we can interpret month-to-month differences in the biomasses but also the locations of the biomass within the model. In the first panel here, model group A is only present in the upper left portion of the figure, which is Lake Borgne. In the second panel here, model group A has moved eastward and the individuals are no longer living within the lake. These distributional changes for mobile species indicate that something about the environment caused a fleeing response in the model group; perhaps the temperature in that area got too high, or the salinity dropped. A predator may have been successful in that original area or the model group may be following their own prey somewhere else. When we see distributional changes, we note which months these changes occurred between and then we can investigate what environmental factors changed during this time step. 

We can also create figures called difference plots, which frequently help us visualize the differences between the time steps. We subtract one plot from another to show shifts in distributions or loss of biomass, which can also identify model areas that became unsuitable to the model group during a time step. When researchers are using spatial models to evaluate differences between management scenarios, the researchers frequently use a baseline model or a model that evaluates a future without action and then compares scenarios to that baseline to show how much a management action improves the distribution or biomass of a key model group or how much a management action harms the model group. 

For this work, our next steps will be to investigate the key model groups and identify which time steps showed the largest differences between the different scenarios. Then, we will investigate which factors likely influenced the distributions and how ongoing Mississippi River management scenarios can shape the health of the fish, shellfish, and fisheries in the northern Gulf.

Happy New Year everyone. While I took time off from work for our winter vacation, I returned this week to finish putting together data from our December field excursions. Across 4 days in the field, we collected data for 10+ hours, all of which start as an organized mess of numbers. Our nitrate sensor and water quality sensor aboard the BlueBoat collect data every minute and each sensor records their collection time, which is really useful. When we deployed the BlueBoat for its missions, we had a team member record the start of the mission and end of the missions so that we could match the data. If we hadn't recorded these time stamps, we might struggle to determine which data are worth keeping and which data were from non-target locations, since both the nitrate sensor and water quality sensor collect data as soon as we turn them on, meaning they collect data before we put them in the water and after we retrieve them. 

Unfortunately, the BlueBoat adds a layer of mess to the data cleaning process. The BlueBoat at the time of writing records data every 0.1 seconds, but the BlueBoat does not have a real time clock. Instead, it logs the data as time since the boat was booted up. Aligning the BlueBoat GPS data with the water quality data, therefore, means finding the time stamp for the start of the mission and moving in 1 minute intervals to align these coordinates with the water quality data. If you're doing the math, that means filtering out 599 rows of data times the length of the excursion. Now, to find the start of the mission, I can upload the mission log to the UAV (unmanned aquatic/aerial vehicle) log viewer, which generates an image like the one you see here. I can trace along the graph and the BlueBoat icon will move along the path, and the system has the path color coded based on the driving mode. For our December missions, we piloted mostly using Auto mode (marked here by the yellow graph sections), so I can easily find the starting point and hover over the area of the graph to get the time stamp. In this process, though, I learned that if we are not thoughtful about how we work with the BlueBoat in the field, our data processing steps get longer, as the BlueBoat will record data whether its in the water or not. As long as it is on, the BlueBoat extends the log, which means more rows of data to sort through. Moving forward, we will hopefully remember to only turn the BlueBoat on when we are ready to deploy and that we will turn the BlueBoat off before we get it back onboard. 

We are planning our next set of missions for February and I'm hoping that everything we've learned from this first trip will lead to more success in the coming months. I'm especially interested in getting our BlueBoat super user-friendly, so that more members can participate in the various aspects of deployments. Stay tuned for more adventures!

This week we took one additional field sampling trip since we had to stop our final sampling trip early last week due to boat issues. Across these four trips, however, we learned a lot about how all the marine technology works, ways that we can improve the sampling process, and some alternative strategies for our next trips, which we will make in a few months. Tomorrow I will be bringing all of our processed samples to our collaborator who will work to analyze the water and sediment we collected. Our USM-based colleagues will then use these data to inform their biogeochemical and sediment transport models, which inform the ecosystem model on which Kim and I work. My next steps, likely starting Monday, are to process the data. Here, I need to work across three different types of data we collected in the field and my goal is to create an end product that links the three data components together. When we pilot the BlueBoat, we have a time that the boat starts moving, a fixed path it takes through the water with an end point, and a time the boat stops its path. We also have a set travel speed for every deployment. What I do not know is whether the boat logs its GPS coordinates and time stamps them so that I can track its exact position every minute it is moving. With the start time, end time, and the speed, however, I can determine the approximate location of the boat at every minute of its path, which is useful for the other data points. The water quality sampler and the nitrate sensor both record time-stamped data every minute they are receiving power. Therefore, if I know the location of the boat, I can plot the water quality and nitrate data points in geographic space, which further helps our physical modeling team. Perhaps one side of the river channel gets more flow than the other or there are higher nutrient loads in the middle than on the sides. These are valuable pieces of information for our team, and I will spend a few days starting to put these items together. 

Now, regarding the title of today's blog, there's one piece of data that the BlueBoat collects that I have not talked about. We outfitted the BlueBoat with a ping echosounder, which is a device that sends out ultrasonic pulses or pings and listens for the echo to bounce back. From these pings and echos, the BlueBoat generates an image of the seafloor and determines the depth of the water column. In today's picture you can see that the water column was 1.99 m or approximately 6.5 feet at the point of the ping. Even from this data set that looks rough, a scientist can take some additional information and make a three-dimensional image of the seafloor, and what I really like is that the BlueBoat and this echosounder are not outlandishly expensive items, making some aspects of this research feasible on a tight budget. I am not sure if we will use the echosounder data yet, except to possibly answer questions about the water quality data set if there are trends that may be supported by differences in depth, but I enjoy seeing the variety of information we can collect by putting our boat in the water, connecting it to the computer and software, and piloting it across a small body of water.

That's all for this week. There will not be blogs for the next two weeks, as I will be away, so stay tuned for the next blog scheduled for January 8th. Happy Holidays, everyone.

This week we embarked on two (soon to be three) field expeditions to start our water quality sampling project. We spent Tuesday and Wednesday sampling across Mobile Bay, Alabama, and the Pascagoula River and Biloxi Bay in Mississippi. Tomorrow we set sail for portions of the western Mississippi Sound and expect to sample in four distinct locations. The purpose of these field excursions is to collect water quality data through a horizontal transect and a vertical profile. The BlueBoat automatically cruises on site to collect nitrate, salinity, temperature, dissolved oxygen, and some additional parameters from the surface water. Then, we sail to the center of the horizontal transect and use our water quality sensor to collect similar measurements starting at the water surface and moving slowly toward the seafloor. Along with the vertical water quality sensor deployments, we collect water samples during the vertical profile for nutrient analysis. The nutrient analysis process involves filtering the water samples to collect any suspended sediments, then filtering the water through a very fine filter to remove as much bacteria and microscopic organisms as possible to prevent ongoing decomposition of the nutrients in the water. We freeze the samples and then ship them to a colleague's lab where he will conduct the rest of the nutrient analysis processing. 

We encounter a few challenges during the first field day, as the boat ran out of power because the batteries had drained over the weekend and I didn't realize. Day two, however, went much smoother and the BlueBoat even managed to avoid an array of crab traps during its longer transect route. We also successfully collected nitrate data from the transects, which is a big win since this was our first time testing out the capabilities of the nitrate sensor.

Tomorrow, we set out on our final sampling day for our December trips, where we will sample four locations-one large bay mouth and three smaller river mouths. While we will need approximately one hour to complete the bay transect, we will only need ten to fifteen minutes per river. However, these times are nothing compared to the four hour transect in Mobile Bay. Additionally, tomorrow we expect the best weather we have had all week, with temperatures in the low 70s. This compared to the 40 degree weather during the four hour transect. A big thank you to the teams who have assisted with this field work and to those who have contributed their pictures. Since I haven't found time to train others on programming and using the automatic functions of the BlueBoat, I need to sit in front of the computer controls during the field work and don't have much time to snap pictures.

​Stay tuned next week for more updates from the De Mutsert lab and our field adventures.

This week I worked at one of the other USM campuses to work with our engineering and hydrography team to upgrade the boat. We collaboratively designed, constructed, and affixed components to house the two sensors we will attach to the boat during field deployments: the nitrate sensor and the water quality sensor. The housing, seen in the picture here, is a PVC pipe with holes to allow water flow, and it is attached to the boat frame with an a-frame. Additionally, we added extra supports at the bottom to prevent the sensors from falling through if there is a catastrophic failure and carabiners at the top to create additional holds or handles. After putting these additional pieces on the boat, we took the boat to the small pool pictured here for weight, float, and maneuvering tests, since the only times we've piloted the boat were without additional weight. I'm pleased to say the boat performed well even with the two sensors and I can't wait to take the boat out into the field for our first true deployment. We were going to set sail tomorrow but the weather is not favorable so we will plan three trips next week. For each trip, we will let the boat drive on auto-pilot to make a slow transect (straight line path) across the rivers and bays we are sampling. While the boat is moving, the sensors will collect and store data on the water temperature, nutrient levels, and other parameters at the water's surface. We will also conduct a vertical profile at the mid-point of each transect so that we can get measurements for the surface, mid-depth, and seafloor to help inform the biogeochemical model for our projects.

Stay tuned next week for an update on the first two of these field experiences!

Last week, Kim and I attended the Coastal and Estuarine Research Federation 2025 Conference, which was a wonderful opportunity to network with professionals, speak to undergraduate and graduate students about research and career opportunities, and to connect with friends old and new. I got to catch up with people I haven't seen in more than a year and perhaps slightly more excitingly, I got to present on my postdoc research. For those who have been following my marine science journey, you may realize this is the first time I've given a research talk or presentation that did not focus on microplastics or nematodes, but it certainly won't be the last. As you can see from this first picture, I was working hard to remember to not explain that oysters can also filter microplastics out of the water column. I really enjoyed the microplastics and marine debris sessions, though, as I got to learn some new techniques for microplastic separation, interesting ways that researchers are evaluating microplastics as viral vectors, and see some new microplastic removal robotics that take inspiration from marine animals.

This week, as promised, I want to talk about oyster research in North America as a precursor to my conference talk. There are more than 200 species of oysters across the world, but only five that are commercially grown and harvested within the United States: the Pacific oyster, the eastern oyster, the Kumamoto oyster, the Olympia oyster (although really two species), and the European flat oyster. While many value the oyster because of its taste, these bivalves perform really important functions in coastal ecosystems. They absorb wave energy and protect shorelines, the serve as habitats for a variety of marine life, they play important roles in cycling nutrients and as food for larger predators, and they are exceptional filter feeders. The eastern oyster, Crassostrea virginica, is native from southeastern Canada all the way to the southern Gulf of Mexico and the earliest commercial eastern oyster fishery was established in the early 1800s within the United States. However, long before settlers established oyster fisheries, indigenous people fished and cultivated oysters across what is now the United States, and there are a lot of great studies that have evaluated the history of the oyster industry and how changes in oyster cultivation practices may be threatening this marine resource.

Oysters face a lot of environmental challenges but are particularly threatened by warming waters and by direct anthropogenic influences like overfishing and reef damage. Warming waters make the oysters susceptible to disease and predation and one of their main predators in the Gulf, the oyster drill (a marine snail), does well in warmer waters. Unfortunately, due to the increased ocean temperatures and other stressors, oyster reefs have decreased in spatial coverage and productivity, especially in the Gulf of Mexico. Across multiple parts of the northern Gulf, the oyster fishery has collapsed, and you may be aware of major news stories about the unexpected collapse of the oyster industry in Apalachicola, Florida or even in Mississippi.

As part of my work, I am evaluating how the collapse of oyster resources in the Mississippi Sound--a portion of the northern Gulf between the Mississippi River and Mobile Bay, Alabama--compares to reports across North America. I have had the opportunity to read about oyster research in Canada, much of the US east coast, the US Gulf coast, and even Mexico and Cuba. Some researchers were interested in harvesting methods to make oysters more delicious, others were interested in harvesting methods to reduce oyster disease that could be transmitted to consumers, and many were interested in how genetic research on oysters can be used to promote oysters that are tolerant of really low salinity levels. I will be presenting my work at a conference next week, and this will be the first time I've given a conference talk that focused on topics other than microplastics and nematodes. It is certainly a different preparation process when you realize that your focal organism is well-known and when you don't have to spend a lot of time explaining why the research is important.

Since I will be at the conference next week, I will not be posting a blog. Stay tuned, though, for the next blog which will be out on Thursday, November 20th!

As promised during last week's blog, I am going to focus this week on describing a challenge associated with making spatial models. This is a great week for this topic, as we have been busy preparing for upcoming events, like our conference and field work, so it hasn't been a week of new tasks. 

If you've been reading the blog for the past few months, you will remember that the project we recently finished used a temporal modeling framework-that is, we modeled everything at one place but evaluated changes across time. The temporal framework involves a researcher providing spreadsheets of forcing data (environmental characteristics like temperature, salinity) that inform how organisms survive in their environment. Our models are forecast models, which means that we train our model on existing biological data--how many of each type of marine organism we have per year, how many of those animals are removed by fishing pressure, how many animals get accidentally removed by fishing and then die before they can make it back to the environment--and then we let the model evaluate what the future looks like given model scenarios. These model scenarios for our project involved various Bonnet Carré Spillway operations. 

Now that we are creating a spatiotemporal framework, we need to consider how the organisms use the physical space of the Mississippi Sound and Bight, which creates some challenges. For the previous project I made response curves for temperature and salinity for all our animals, where were based on a combination of laboratory studies, literature searches, and data from field monitoring efforts for the organisms in our model. The field monitoring efforts are almost always reports from state agencies that record data on the number of marine species caught during fishing efforts and the environmental data from where the fishing occurred. While the field monitoring data are quite useful for evaluations of salinity and temperature tolerances, we are now working to incorporate depth as a factor in the model. The fishing efforts are highly biased regarding depth because while the depth of the seafloor is not the same every time they go fishing because they are fishing in different locations, they are deploying an otter trawl, which samples at the sea floor. Even if the fish is slightly above the sea floor, if it gets caught in the net, the team will record the depth of the sea floor because that's the depth of the trawl. Additionally, since the state agencies are not fishing in the rivers or in close proximity to the shore, there are model groups that may not be represented by these fishing efforts (like largemouth bass, sunfishes, many juvenile fishes that frequent rivers or nearshore environments). One solution is to evaluate local knowledge including local fishing histories, perhaps reported sightings of organisms, to narrow in on an appropriate depth range for these organisms. I will note that the depth responses for some of our animals gets quite difficult because while we may know the minimum and maximum depths that an observer has seen an animal, we may struggle to determine its optimum depth range.

As an alternative, I have seen some teams use distance to shore as a qualifier, rather than depth, though this metric is also based on field sightings and fishing efforts, which doesn't necessarily eliminate the potential bias. One solution that does help is relying on depth when necessary but finding alternative geographic or spatial features that may help explain distributions. For instance, if you are modeling a coastline that has mangroves, you could include a mangrove proximity variable to reflect the refuge mangroves provide for juvenile fishes. Perhaps an oyster reef proximity variable, since oysters cannot survive if there is no substrate on which they can settle.

I really enjoy the head-scratching and puzzle aspects of this work, though. When Kim and I meet to talk about these problems we get to talk through the pros and cons of multiple solutions and avenues of inquiry, which makes this work exciting. Stay tuned for next week's blog, where I will focus on oyster research across North America, as a precursor to my conference presentation.

This week, I put a bookmark, or perhaps a dog ear, in a small chapter of my post-doc. Today was the last meeting of a committee I joined to further career development and education opportunities for the members of the Coastal and Estuarine Research Federation. Most of our committees are 2-year commitments but I joined at an unconventional time because of the timing of my postdoctoral position. We've made such important progress toward the development of longstanding initiatives, including the mentorship program I'm spearheading, to support the members.

This bookmark is only temporary, as we new iterations of the committees will begin shortly after our November conference, so the goodbyes we said during our meeting today were merely, "see-you-laters." However, the timing of this bookmark also means that we are only two weeks away from leaving for the conference.

A short blog this week, but I know that next week I will be writing about some of the complexities of creating ecosystem models. If you are interested in how we determine suitable conditions for our 200+ organisms in the ecosystem model, then stay tuned! And as always, you can connect with me using the Contact Me page, which sends an email, or you can leave comments, which are visible to all visitors.

This week was a week of outreach activities at and outside of the lab. We spent yesterday testing out the BlueBoat, which may become a part of future outreach activities, and we discussed the possibility of attaching a GoPro to record field videos for future educational and outreach content. This past weekend, I supported a workforce development initiative activity in coastal Louisiana where we brought undergraduates from six universities to conduct field work, learn about how marine and coastal scientists answer questions regarding local environmental changes, and explore coastal Louisiana and its waterways. This week I also conducted three virtual classroom visits, supporting teachers and their students by answering marine biology and marine science career questions as part of the Skype A Scientist program.

Saturday, the lab will set up a station at the Gulf Coast Research Laboratory Community Day, where families can learn about and interact with the USM coastal research units and laboratories through hands-on activities, games, and expeditions. While we initially considered setting up a BlueBoat obstacle course for participants to explore interesting marine technologies, our marine education center is already hosting a remotely operated vehicle exhibit, so we instead have a food web building competition for all participants.

This will be a great weekend to interface with our community and teach about the amazing work occurring at our Gulf Coast Research Laboratory. While I know many who read this blog are not local, anyone who is interested in attending can find more details here. 

This week, after much preparation, the lab put together and started testing our BlueBoat. The BlueBoat is an uncrewed surface vessel, that measures approximately 94 cm x 120 cm or 37 in x 47 in and weighs approximately 14.5 kg or 32 pounds. Users operate the BlueBoat with a remote control and can add additional hardware to the boat, including sonar, temperature and depth sensors, and more, all for the purpose of collecting real-time or near real-time hydrographic and water quality data. Kim and I got to see the BlueBoat in action when we supported a teacher professional development workshop in Louisiana, where a lab at LSU outfitted their BlueBoat with water quality sensors that inspired our own purchase and future build. After we finish testing the boat without any additional attachments, we will be sending it to a colleague in the marine science and engineering division so that he and his lab can create add-ons to support our two water quality sensors. These two sensors will allow us to deploy the boat and collect water temperature, conductivity/salinity, depth, dissolved oxygen, and nitrate data as we pilot the boat through the waters of the Mississippi Sound and its rivers.

Today, Hannah-the lab's new graduate student-and I finished running all the electronics checks after constructing the boat on Tuesday. The electronics checks involved a lot of troubleshooting, as one step involved calibrating the internal compass system and rotating the boat on different axes. Any passersby would have seen us moving the boat up and down and rocking as if it was facing heavy wave action. We also tested the propellers and motors, realized that we had initially screwed in the wrong section of the propellers, and attached and configured the wireless controller. Not bad for a day in the lab.

Next week we will be taking the boat for in-water testing at the lab, using the docks at the Marine Education Center. This test will help us evaluate how easy the boat is to pilot, whether the electronics cooperate when we are not in the lab, and give us some insight into what transporting the boat to and from the field will require. I can't wait to update you next week after we test this amazing equipment out.

​Stay tuned!

This week in the lab, I continued putting some finishing touches on my oyster mortality project. I have a few items left to wrap up, but I am excited that I'm nearly done with this major project. I do recognize, however, that finishing these steps will not mark the completion of the project. I will need to present this work, get feedback from my presentation, incorporate that feedback into my writing, and then send the work off for independent peer review.

What do I mean when I say that I stitched together a figure? Well, the coding program that I use for my work has wonderful plotting functions but sometimes I don't know the best way to create a narrative plot using the program. For instance, if I need to make a plot of a map, I will likely use ArcGIS or Matlab, two programs that are not my coding program, but excel with geographic information and plots. If I want to plot data points and modify the shapes or colors, the coding program I use is well suited for the task. If I want to combine maps and data points, then I will likely create separate assets and merge them in an illustration program, which is what I worked through this week.

One of the aspects of my project is comparing oyster mortality in the Mississippi Sound during freshwater discharge events to oyster mortality reported in the scientific literature across North America. Much of this literature is from studies in the Chesapeake Bay, but there are also studies as far north as Maine and as far south as the Yucatan peninsula. My goal with the figure is to show both the mortality rates and the location of each study, in case there are interesting geographic trends, so I made my data plot in my coding program, created independent maps in ArcGIS, and then stitched the components together outside of these two programs. One of the benefits of completing this process across multiple programs is that I feel I have more control over the look of the end product and I can quickly add the components to PowerPoint and evaluate how the finished presentation looks.

This week at the lab, we continued writing our Tipping Points project report, and I spent most of my time reworking figures, editing materials, and helping contextualize aspects of the work we started when I got hired. However, since nearly all of my week focused on these tasks, I thought I would spend this week's blog explaining the upcoming two months, as Kim and I will be finishing old projects, starting new projects, and supporting outreach activities.

October: In October, we will be transitioning from our Tipping Points project to spatio-temporal modeling to evaluate how Bonnet Carré Spillway operations affect the health of fish, shellfish, and fisheries in the Mississippi Sound and Bight. This is an expansion of some aspects of the Tipping Points project, but we are adding in the entire model domain, evaluating results across all model groups, and incorporating some additional scenarios. We are waiting on a few assets for this project, but we will get started shortly, as Kim will present this work at the upcoming CERF 2025 in early November. I will be finishing my oyster mortality project within the next few weeks and I have started building my presentation for CERF 2025. Additionally, in the first few weeks of October, I will be speaking with multiple school groups for Skype A Scientist and supporting a MissDelta undergraduate workforce development initiative in southern Louisiana. Then the week after, Kim and I will be welcoming families and community members at the GCRL Community Day.

November: In early November, Kim and I will present our research at CERF 2025 along with many other members of our USM family. After the conference, we will likely have the information necessary to start the spatio-temporal model runs for the MissDelta project. These model runs will be based on potential Mississippi River management scenarios and how the evolution of the Mississippi River and Delta will affect the fish, shellfish, and fisheries of the Mississippi Sound and Bight. I will also spend a lot of November writing, as I hope to have my oyster mortality work ready for submission by the end of December and another planned manuscript ready by May. This second manuscript will be the focus of a later blog, because I think the journal's request for manuscripts highlights an important gap in scientific publications. 

Stay tuned for more updates about our work here in southern Mississippi.

This week has been all about making small progress toward major tasks. We have a lot of upcoming deadlines and we are working to reach those by drafting reports, adjusting figures, running new calculations, and holding meetings to discuss these items. Our biggest task is preparing a project report for peer review, followed by an annual reporting requirement. The project report is the result of our Tipping Points model runs and evaluation, which you can read more about on my Research page. Our team is currently writing and editing our narrative of how Bonnet Carré Spillway operations affected oyster mortality as simulated by our ecosystem model. This project reconstructs the northern Gulf of Mexico ecosystem from 2000-2017 and then evaluates how oysters-and other animals not involved in our report-respond to altered salinity and temperature regimes in the Mississippi Sound from the Spillway operations. This is my first time working on a report that will not become a journal manuscript, as this report will go through a slightly different peer review process and our end product will be a scientific report; think more similar to a government report or document and less like a scientific journal article.  

Our annual reporting is to wrap up our year 2 of the MissDelta project. While this project started two years ago, our team is ending our first year of work, as we delayed our start time so that the field collections team could gather data needed for our modeling work and so that some of the economic and management partners could organize their ideas before we started working on the modeling component. This delayed start is especially important because unlike the Tipping Points project where our team proposed model scenarios to run, the MissDelta scenarios will come from partnerships and conversations with community members. Until we know what management scenarios they'd like to test, we can't complete model runs for the project, except to help prepare the model for these future scenarios. The annual reporting, though, is a key component to a project of this size-38 experts across 14 institutions (plus postdocs, graduate students, and undergraduates)-as it informs our funding agency of our progress, challenges we've faced, and ways that we've approached obstacles along the way. 

Finally, I made more progress this week with my oyster mortality side project. I got the physical data from the model neatly packaged into files, I got additional physical model data to use as a potential alternative, and today I gathered more data. Why so much data? The resolution, or spatial and temporal detail, of each of these data sources are quite different. While I would love to use the most detailed models with daily measurements at really fine spatial scales, those data are not always available. Therefore, I've grabbed three different sets of data to explore so I can decide which best suits the needs of this project. 

I don't know what we have coming up in the near future at the lab, so I can't say what the focus of next week's blog will be, but stick around to find out. And, as always, feel free to contact me if you have any questions or thoughts.

While last week's map is still a secret, this week I worked on another map for my own research, although this map was useful for only a few days. While the oyster monitoring data I have from the Mississippi Department of Marine Resources includes temperature, salinity, and dissolved oxygen data, these data are point data, which means they represent data collected at one point in time: the time when employees counted and recorded oysters. However, we know that organisms respond to cues in their environment at different times-perhaps times around spawning, reproduction, lunar cycles-and these response times are often asynchronous with our sampling and monitoring efforts. Therefore, while the environmental data I have during the oyster monitoring is useful, data leading up to these sampling events may (keyword) provide more explanatory power. 

Many research teams within the United States and across the globe build complex mathematical and hydrodynamic models that explain features of our oceans, including the movement of sediment, wave action, currents, temperature, and salinity. For many of these models, the researchers create accessible data files, stored and available for public use, although these data files are quite massive (a few gigabytes for half a day of data). Since my work spans more than a decade, the file size required for all my data would be quite large, which is why I turned to looking at maps. The model I found for my work provides a preview image per file that looks like the one depicted below. The image is interactive, meaning I can click on any modeled area of the image and extract the data for that feature. As long as I know which grid square belongs to which location in my own research, I can click and extract the temperature and salinity information from the otherwise massive data file. 

Why would I click the files and points independently rather than program my computer to extract the data? That's a great question, and I'm so glad you and I had the same thought. I started this data extraction process by writing lines of computer code to automate the extraction process. Today I ran those lines of code and it took 2.5 hours to extract data from 28 files, or 28 days-worth of data. Considering that I need to complete this process for perhaps 1000 days, I wanted to increase my processing speed by performing the manual clicking task while the computer completed automated processing. Hence, the colored squares I added to this map so that I could recognize the grid cells that I needed to click. 

Today, though, I happily finished working with the manual system, as I thought more carefully about how my code extracted and processed the data files. What makes the files so large is the amount of data points and the amount of values per data point. Instead of extracting all the data within a single file, I rewrote the code to extract just the variables I wanted at only the locations relevant to my research. This modification turned a 2.5 hour data extraction and processing step to a 3 minute step for 28 days of data, which is immensely helpful, and means no more manual clicks. So thank you, map, for your service, and while it was fun to make an MS Paint creation, I'll stick to the automatic processing.

I am hoping to write an extended feature next week on the BlueBoat, as it arrived at the lab, but that blog may be delayed by our plans to outfit it with additional gear. There will still be a blog next week, though, don't worry!

I spent most of this week at the lab preparing a draft report of the results of our ecosystem model runs. We are working with the team to put together all draft components shortly so that we can combine the parts into one cohesive narrative about how spillway operations affect the hydrodynamics of the Mississippi Sound and how changes to the environmental conditions affect the oysters in the area. As we wrap up this project we are starting to work toward our next project, which is similar in scope but not in detail. Our next project, which will likely be a short project, is to evaluate how the MidBreton Sediment Diversion and its associated changes to the Mississippi Sound hydrodynamics affect the health of fish, shellfish, and their fisheries. For this project, Kim and I will be working in Ecospace, so integrating the time and space components of the model. The prospect of working with Ecospace is exciting because the models run differently compared to Ecosim. For Ecosim, every time I wanted to update the environmental variables, I would need to copy and paste the new variables into the associated locations. For Ecospace, however, we create a folder of maps that include the mapped environmental variables for each month, and once the model reaches the appropriate month, it grabs a new map from the folder. 

Speaking of maps, this week I also worked on a secret map for my own research. While I am working with Kim on all the ecosystem modeling projects, I also am completing my research on oyster mortality in the sound based on field monitoring data. For this project, I created a new map this week for a feature that I can't discuss at this time. I will say that I am really enjoying learning how to use ArcGIS - our spatial analysis and mapping program - to troubleshoot problems and create solutions. This new map would not have been possible without this program. I have a few more items to investigate for this project, and the end is in sight. The goal is to present a finished research project at the upcoming CERF meeting in November and I know that's feasible even while working on it in conjunction with our lab's other priority tasks and projects.

Stay tuned for more updates, including an upcoming extended feature on the BlueBoat which we purchased and will be receiving in the coming weeks.

This week was a busy one at the lab, with presentations, paperwork, and projects. As I make more progress with my own research, I am going back through the literature on oyster mortality to evaluate how my findings compare to those across the United States. Additionally, I am looking at how other researchers calculate mortality, as there are a few different types of calculable mortality and multiple ways to calculate many of these mortality metrics. As I want to be able to draw direct comparisons with the published literature, I have to evaluate the language the authors use to describe their methods and the calculation methods, as some metrics may over- or underestimate mortality.

Additionally, this week I finished and sent off paperwork for a potential collaboration with two other Mississippi universities. This paperwork is brand new to me, as it is for a permit to conduct research on vertebrates. The permitting paperwork requires a detailed description of the work, the purpose of the research, documented alternatives to the specific methods, and additional forms depending on the extent of the research, the chemicals involved, and the handling and housing methods for the animals. Our goal in submitting this permit is to conduct stomach content analyses for fish collections in the Mississippi Sound to inform our ecosystem model. This work is part of a workforce development initiative, seeking to get local undergraduate and graduate students involved in marine and coastal science careers in their communities. We will not hear back from the approval committee for between two to six weeks, but stay tuned for updates on this project.

Additionally, I forgot to mention that I have made some small changes to the website. I have included additional tabs under the Research page, which link you to the various projects I am working on. Each project page includes a description of the work, the questions I am trying to answer with this work, and any upcoming events or talks related to the project. Feel free to check out these new features of the website.

This week started our Fall semester at USM and with it, our start of semester lab meeting, where each member spoke about their plans for the upcoming semester. We welcomed in a new graduate student and said a soft goodbye to our outgoing student, although he will still be with us for some time, just not as a student. Therefore, this week, I thought I'd write about my semester goals and give everyone an overview of what I'm working on and the projects I'm planning to complete this fall.

I am currently working on three projects at the lab, and I expect to finish at least two of the three this fall. My oyster mortality project, where I'm working to understand how freshwater inflow from repeated Bonnet Carré Spillway operations has affected the health of oysters in the Mississippi Sound, is in a good place. I mentioned that I will present this work at the November CERF conference in Virginia, and today I made a good step toward that goal. My hope and current plan is to have a manuscript ready to submit by the end of December based on this work, and this will mark the first manuscript of my postdoc, first work on organisms larger than nematodes, and I will likely submit this work to a journal I have not published in previously. Additionally, we are working to wrap up our project modeling how Bonnet Carre Spillway operations affect the survivorship of oysters in the Mississippi Sound. Does this project sound eerily similar to my own independent research? Definitely. The key difference, though, is that for my work I am using fisheries independent monitoring data and calculating survivorship metrics, while the ecosystem modeling work consists of us building an entire ecosystem model, that we give monthly environmental data and yearly biomass data to train the model and then use the Bonnet Carré Spillway operations and associated environmental variables to investigate how oyster survivorship would change. More simply: my work isolates the oysters and the environment while the larger project uses all available information about the ecosystem to predict oyster health. We plan to finish this work and submit a report on the outcomes of this project by the end of the fall semester.

The third project is another modeling project, but this one focuses on the Mid-Breton Sediment Diversion or MBSD, which is a diversion of the Mississippi River meant to help restore coastal land by transporting freshwater and the sediment therein to nearby Louisiana basins. Changes to the Mississippi River that affect freshwater discharge--and especially those that increase suspended sediments--in the Mississippi Sound and Bight may have adverse effects on the fish and shellfish, so our team will be modeling the ecological impacts of the diversion. You can read more about the diversion using the link here. 

Besides these large projects and updates, I will be continuing my work with the MissDelta Workforce Development Initiative to support the recruitment of local students to the coastal and marine science workforce and I will be working on some other small projects, with updates to come in the next months. So stay tuned for another great year of blogs, marine science research, and everything coastal Mississippi.

This week I worked on my oyster mortality project at the lab, which I wrote about a few weeks prior. Those weeks ago, I explained that while the Mississippi Department of Marine Resources reported that they collected data every week during the 2019 double opening of the Bonnet Carré Spillway, those data were not included in our initial data request when we started our work. I'm pleased to let you all know that after submitting an additional, slightly more detailed public data request, I received the 2019 weekly report from MDMR. These data are so important because they provide the only documented weekly snapshot of the health of Mississippi Sound oyster reefs during this unprecedented event. The data also help shape the story of how operations of the Bonnet Carré Spillway have affected the oysters throughout the past decade or so, providing, therefore, fine and broad scale details on the natural history of the local ecosystem.

As of today, I have finished approximately half of my work on this project and I have moved on to evaluating another measurement of oyster health where I am also incorporating these newly acquired 2019 data. The end goals for this work are to: (1) Evaluate how freshwater inflow has affected the health of oysters in the Mississippi Sound, and (2) Evaluate how oyster mortality in the Mississippi Sound compares to mortalities across North America. I am partially through goal 1 and I started goal 2 a while ago, collecting data on oyster mortality from publications across North America. However, since I took a step back to work on other projects and to wait for the 2019 data, I will search the literature again in case there are new publications reporting on oyster health.

I hope to have this project done by the end of September, as I will be presenting this work at the Coastal and Estuarine Research Federation conference this November. The month between the two events gives me plenty of time to edit this narrative into a 12-minute presentation format, to practice the presentation, and to record the presentation, as the conference asks all presenters to provide a video recording for those who cannot attend the talk but are interested in learning about the work.

Next week starts the Fall 2025 semester at USM and we have lots of exciting events on the horizon. Stay tuned to learn more about all the work we are doing in the fish ecology lab.

I spent a few days this week preparing to move our modeling into the more complicated spatiotemporal domain, which was a fun learning experience. One of the biggest features that our spatiotemporal model needs to incorporate is the complex spatial features of our model domain. Since we know that many of our organisms have preferred habitat types, and some of these habitat types are physical features rather than temperature or salinity ranges, we need to include these physical features in the model to help inform habitat suitability and survivorship calculations. This week, therefore, I learned how to take our maps from ArcGIS and put them into our modeling software by creating ASCII files. An ASCII file is a standardized file format (like a .txt or .csv file), that stores information as text, which can be read by many computer programs. If you're not familiar with computing or computer files, you can think of an ASCII file as a common language between computer programs. By generating an ASCII file, I can take data from one computer program and give it to another program to understand. Such is the case here, where I'm taking maps from a geospatial mapping and analysis program (ArcGIS) and reading them into our ecosystem modeling program. The ASCII file contains rows and columns of information, and because our maps have exact coordinates for the physical features, we need to ensure that we are assigning the data to the correct row and column combination. Here, our amazing graduate student, David, wrote a set of code that evaluates the percent overlap between our map features and the grid cells, so that each row and column combination fits together like a mosaic and paints a beautiful picture of our marshland and oyster reef habitats. 

What I especially appreciate about the process of converting between the ArcGIS map and the ASCII file is that I can import the completed file into our modeling software to visualize the data and then import that same file into the mapping software, which provides a higher resolution image (clearer, more detailed picture) of the same map. Therefore, I get to check the outcome multiple times to evaluate whether or not the conversion and coding were successful.

Next week is going to be a break from this geospatial modeling work and back to oyster mortality modeling, as I have some exciting news to share about the other research that I'm doing. It'll have to wait until next week though, so stay tuned!