Preparing for Space

This week, I worked on tasks related to side projects - including workforce development initiatives, manuscript writing assistance, and oyster mortality. While I am not in the process of writing a manuscript, though I have one in its early stages related to oyster mortality, Kim is working on some writing and needed a document that no longer exists. She asked me if I wouldn't mind trying to piece together the document based on work from a previous postdoc, which turned into a fun scavenger hunt-like project. I searched through databases, old files, and the literature to put together this much-needed resource for Kim's writing.

Additionally, Kim and I met with colleagues at other Mississippi universities to talk about a workforce development project that would increase collaboration between our schools, support an undergraduate-to-graduate school pipeline between these HBCUs (historically black colleges and universities) and USM. I am excited to take the lead on developing this project and writing the grant in hopes of securing funding to support students in the coastal and marine sciences.

Finally, I have also been thinking about the upcoming move from our current modeling system to moving into space. All of the ecosystem modeling we've done has considered temporal (time) dynamics and not spatial dynamics, but we are going to be moving to spatiotemporal dynamics likely next week. While I've mentioned the different modeling aspects in previous blogs, I thought I would spend a little part of this week's blog mentioning the differences between the temporal and spatiotemporal modeling frameworks. For both of these modeling types, we have already constructed a balanced ecosystem model, which means that we have incorporated each model group's diet components, growth models, biomasses, and the amount that is lost to fishing and other mortality sources so that the amount of mass we start with during a model run is the amount of mass we end with in a model run. We then use this balanced model to evaluate changes in each model component across time and space by incorporating temporal and/or spatial components that cause shifts in the biomasses within each model group. For instance, in our work we add in the monthly ocean temperatures which may create stressful conditions for some model groups. In our temporal model, we apply the environmental components equally across our model, since we are not incorporating the geographic space. This means that most model groups are receiving the same environmental information, though there are some exceptions and ways around this feature that we employ. In our spatiotemporal model, we have each model group initially distributed equally across the model domain (geographic space) and these environmental components are not uniform across the domain. Instead, subsections of the domain have unique environmental data provided by our physical modeling team. You can imagine the domain looks like a heat map or a chalk pastel artwork, where the subsections near each other likely share a resemblance. In the spatiotemporal model, organisms are able to move from subsection to subsection and the model incorporates new environmental data each month, which informs the suitable habitat space for each model group.

Does this sound confusing? It likely seems confusing without pictures, so my goal next week is to try and use some scientific literature figures to explain hypothetical scenarios. Stay tuned for what will look like a fast-paced game of chess.