The CAREERS Cyberteam grant helped establish the computational aspects of the project (i.e., using computer clusters and running models using R code) for me and introduced me to a wider range of computationally based projects that helped me as I worked through issues. The principal discipline, ecological oceanography, requires computational methods to make sense of data and the world -- and developing distribution models for important and vulnerable mesophotic coral ecosystems is a great contribution.
The impacts likely extend to various earth science disciplines that think about the natural world in computational ways (e.g., grid formats, environmental variables, resolution) because increasing resolution size can help us understand greater intricacies and processes in the world -- but also lead to higher uncertainty in our predictions.
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Modeling the distribution of coral reefs and how they might shift in climate change is important to society because of the ecosystem services that reefs provide - from fish habitat, to nutrient cycling.
We learned how to (1) gather and build the data layers required for habitat suitability modeling, (2) build the code base to process and run the data through distribution models, (3) use UNITY computer cluster to troubleshoot and run the models in an efficient manner on powerful machines, and (4) interpret preliminary results. We made progress in Python and arcpy, R, and UNITY interactive sessions.
We created a habitat suitability model for mesophotic coralline algae beds in the Flower Garden Banks National Marine Sanctuary at high-resolution (5 m) for the first time.