What do ant colonies and railroad systems have in common? Both serve to transport goods and individuals from place to place, and need to balance the often competing goals of doing so efficiently and at low cost, while also remaining robust to potential disruptions to the network. We are currently working to understand how simple organisms can work together in groups to create and maintain such transportation networks, using a multidisciplinary combination of field and laboratory experiments with turtle ants, along with mathematical and computational models.
Tree Mapping. One important part of this work is the ability to efficiently describe real transportation networks created by turtle ants in their natural habitat: mangrove trees in the Florida Keys. Our first goal is to map out the spatial location of all ant nests in a tree, and describe the potential pathways between them. While this can be done by hand, we are working to develop a method for documenting the 3D structure of a tree using terrestrial laser scanning and photogrammetry with an iPhone 12, based on existing methodology known as quantitative structural modeling. A student working over the summer was able to represent a physical tree as a (1) point cloud, (2) geometrical model of interlocking cylinders, and (3) a network as a proof of concept. The next step is to refine these processes to make them more accurate and consistent, and then (if travel restrictions allow) collect data on real trees. This project requires strong programming skills in Python and/or MATLAB as well as experience working with networks / graphs (e.g. completion of CS70 and Discrete Math).
Ant Tracking. Our second goal is to quantify the movement of ants along specific paths in laboratory experiments. We have already developed a software pipeline to automatically track ant movement from videos taken in the lab. A student working over the summer enhanced the pipeline to accurately and consistently detect specific regions of interest within videos; the next step is to test and improve the tracking of ants within those regions of interest, and use the tracker to gather and process data from the summer's experiments. This project requires strong programming skills in Python, some knowledge of computer vision, and familiarity with Github (e.g. completion of CS70 and CS121).
You will be part of a team of students working on a set of related interdisciplinary projects, using mathematics, computation and engineering to solve problems of biological interest. The variety of techniques and approaches will give you an opportunity to explore your interests and develop new skills. These research projects are part of a larger NSF-funded collaborative research project, so you will interact with a larger research group including graduate students and postdoctoral researchers at George Washington University and the University of York. There may be opportunities to continue the work in a senior thesis, present at a regional or national conference, and/or co-author future publications stemming from ongoing work.