We Make A Model More Complicated

This week has been all about running and calibrating our ecosystem model. As I've mentioned previously, this model is quite large and because of its size, small items can cause big complications. Some of these complications come from the predator-prey interactions in the model, while others may stem from the environmental variables we've included to drive foraging behaviors (the response curves I've written about before). Additionally, complications arise in our models because of the underlying purpose of modeling: to describe events that happened using available data or to describe events that might happen using available data. The availability of data, therefore, strengthens or limits a model's ability to function as scientists intend. However, in many cases the scientists who collect the data or even design the data collection procedure are not the scientists who perform the modeling or build the models. The separation between the data collection team and the modeling team means and the general lack of 24/7 monitoring data means the modeling team works with what is available and decides how best to use the data to answer their questions. This week, I worked to create a set of temperature and salinity data for different areas within our model domain to best replicate the spatial use of model groups. For instance, red snapper are key fish in the model, but they are an offshore species and therefore likely don't encounter the salinities and temperatures from the nearshore environment. Alternatively, small coastal sharks like bonnethead sharks are more nearshore animals and may spend more of their time within the barrier islands of our model domain. By creating multiple sets of temperature and salinity data, we can work to replicate conditions relevant to the different life histories and habitats of our model groups. The inclusion of multiple spatially-explicit data sets obviously complicates our model regarding how much computing power is necessary. These tasks are exciting though because I get to do a lot of computer coding and calculations to determine how the salinity and temperature changes at specific geographic locations across time.

Aside from my work in the lab, I will be spending this weekend as a judge for a graduate student research symposium held this year at USM. Graduate students from multiple gulf coast universities will travel to present their research in oral and poster presentations at USM and I will be there to listen, give feedback, and discuss this work with these fantastic students. I love this part of my job because I can offer constructive feedback in a low-stress environment, encourage new and interesting research avenues and questions, and listen to research talks I may not have sought out if I chose talks as a conference attendee.

I don't know what's coming up for next week, but I will be sure to let you know all the exciting things that are happening in the lab during next week's blog. Stay tuned and have a great week!