I study how organisms make decisions that are essential to their survival and reproduction.
You can check out my CV here or learn more about me and my research below.
Behavior is born from decision-making. Understanding behavior therefore entails a deep understanding of how organisms decide among alternatives. I experimentally manipulate options presented to animals to understand the underlying decision-making rules and mechanisms that animals use to choose mates, forage, and choose social groups.
mate choice and decision-making in swordtails
One aspect of my current research combines computer vision and animation technology with insights from cognitive scientists to study how female fish make mate choice decisions. I use poeciliid fish, a family of livebearing fish with internal fertilization, to test fundamental assumptions about how females choose mates. Using synthetic, digital male stimuli allows me to control for the effects of male behavior on female mating preferences, decouple traits that are typically correlated, and generate repeatable female preference responses.
Below is an example animation I present to female fish:
decision-making in slime molds
I also study how slime molds choose among different food options. Slime molds are giant unicellular amoebas that are an attractive system for studying decision-making because of their simplicity. How much of our behavior is reflected in a simple slime mold that lacks even a nervous system?
Below is a time-lapse video of a slime mold making a choice among four food disks containing oats over the course of two days:
Reding, L. and M. Cummings. Does sensory expansion benefit asexual species? An olfactory discrimination test in Amazon mollies. 2015. Behavioral Ecology.
Reding, L. Increased hatching success as a direct benefit of polyandry in birds. 2015. Evolution.
Reding, L. P, J. P. Swaddle, and H. A. Murphy. Sexual selection hinders adaptation in experimental populations of yeast. 2013. Biology Letters.
I’ve TA’ed introduction to ecology and evolution at UT for three semesters. I use of a lot of different techniques in my teaching and each time I TA a course I approach it armed with the experience of the previous semester.
I use a variety of approaches in my teaching:
grouping dissimilar students. I distribute a survey at the beginning of the class to get a feel for each student’s personality and strengths. I use their responses to make groups with different types of people: business majors are paired with biology majors, students confident in their mastery of the material are paired with those whose understanding is shakey, native English speakers are paired with those for which English is a second language. The result is balanced groups in which students can learn from one another.
mid-semester evaluations. I ask students to fill out evaluations halfway through the semester so I know if there are major things I need to change about my teaching styles and how I meet students’ needs.
one thing you didn’t understand. One thing I plan to do in the future is to have each student write down one idea or concept they’re still a little shakey on at the end of each class. These anonymous submissions have worked for other teachers in identifying concepts that need to be reviewed at the beginning of the next class.
problem sets. I distribute lengthy, ungraded problem sets before exams so that students can test their mastery of the material
weekly quizzes. I use weekly quizzes to ensure that students are keeping up with the material.
fall 2013: 4.5 / 5.0
spring 2015: 4.5 / 5.0
summer 2015: 4.8 / 5.0
I’ve been fortunate enough to participate in the GK-12 program at UT. This goal of this program is to facilitate communication between university researchers and K-12 teachers and students. I’ve gotten to teach 4th and 5th grade girls about the properties of light, I’ve donned a 13-foot dinosaur to help kids imagine what life on Earth used to be like, and I’ve been able to judge numerous science fairs in the Austin area.
mentoring high school students
This past year I’ve had the opportunity to mentor a high school student from a local Austin high school. With my and another graduate student’s help, she was able to form a question on her own and design an experiment to test it. Next year I’m excited to be involved in the same program.
I’ve also been lucky to mentor undergraduates–seven during my time here at UT so far. Some have gone on to graduate school and have completed REU programs at other universities.
I enjoy coding in R, Python, and bash.
I find myself dissatisfied with the plotting defaults and types of plots that can be produced with base R, so I created a plotting package that implements (1) good defaults for various types of graphs and (2) adds new types of graphs with an emphasis on categorical x continuous data.
I’ve written code to do various other tasks, like coordinating two computers to show video on three-four screens simultaneously, brew beer according to a precise temperature series, scramble video stimuli for use in behavior trials, and various other things.