Ant Behavior and Transportation Networks

Are you interested in the project below? Awesome! PLEASE DO NOT APPLY THROUGH THE URO SITE. Instead, follow this link:  https://forms.gle/dRRVyH2yj52PfTAg6

 

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.

A key part of this work is to describe the behavior of turtle ants as they explore trees and collectively choose new nests within those trees. How do individual ants decide which way to turn when they reach a branching point? Do ants communicate about their discoveries, either indirectly via pheromones or directly by following one another? How do groups of ants choose new nests and create pathways for transporting resources between them? How are these decisions impacted by the presence of competing ant colonies? To answer these questions, we have been conducting experiments with turtle ants in the laboratory, and comparing their behavior to mathematical and computational models. This summer, we will focus on competitive interactions between ant colonies.

Project 1: Plan, perform and analyze experiments on ant nest choice and competition

Project 2: Model collective exploration, foraging and/or nest choice, using agent-based simulations, differential equation models and/or network approaches. 

Essay Prompt: What interests you about these projects and what do you hope to gain from the research experience? What makes you a good fit for one or more of these projects?

Name of research group, project, or lab
The HMC Bee Lab
Why join this research group or lab?

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. The project is 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.

Logistics Information:
Project categories
Biology
Computer Science
Engineering
Mathematics
Data Science
Student ranks applicable
First-year
Sophomore
Junior
Senior
Student qualifications

No prior background or experience is required! Students should have an interest in the complexity of the natural world and potentially in the application of quantitative tools and models to understand it. First and second-year students still exploring their interests are encouraged to apply.

 

Here is a list of skills/interests that could be useful, or which you might develop along the way. They're not requirements, but if you already have experience or interest in any of them, be sure to mention it in your application.

  • Data science and visualization, particularly with R (helpful for both projects)
  • Background/interest in ecology and animal behavior (helpful for both projects)
  • Machine shop certification and experience (helpful for Project 1)
  • Experimental design (helpful for Project 1)
  • Mathematical modeling (desired for Project 2)
  • Strong programming experience in Python (helpful for Project 2)
  • Mathematical software such as Mathematica and/or MATLAB (helpful for Project 2)
  • Simulation modeling (helpful for Project 2)
Time commitment
Summer - Full Time
Compensation
Paid Research
Number of openings
2
Techniques learned

Besides some combination of the skills and techniques listed under qualifications, you will learn to read and discuss scientific literature, and to communicate across disciplinary boundaries and with the public about your work.

Contact Information:
Mentor
Matina Donaldson-Matasci
mdonaldsonmatasci@hmc.edu
Associate Professor of Biology
Name of project director or principal investigator
Matina Donaldson-Matasci
Email address of project director or principal investigator
mdonaldsonmatasci@g.hmc.edu
2 sp. | 0 appl.
Hours per week
Summer - Full Time
Project categories
Engineering (+4)
BiologyComputer ScienceEngineeringMathematicsData Science