We are looking for a Master student interested in evolutionary ecology, quantitative genetics, macroevolution and biodiversity to join Tsuboi’s lab studying wing morphology of damselflies and dragonflies. You will be part of our team studying natural populations of damselflies around Lund leading by the PI, while collecting your own data for Master thesis!
Background: Why do organisms often remain similar over millions of years despite abundant genetic variation and ongoing natural selection? This long-standing evolutionary puzzle is known as the paradox of stasis. Damselflies are ideal for studying this problem because they have standing variation in wing morphology, occupy diverse habitats, and represent well-documented natural history that enables quantification of natural and sexual selection in natural populations. Our lab combines field ecology, AI-aided data acquisition from images, quantitative genetics and phylogenetic comparative method to understand why evolutionary change is often bounded within limited ranges.
Recent work from our group suggests that natural and sexual selection fluctuate in ways that are ecologically predictable, producing similar adaptive outcomes across two divergent species (Gupta et al. 2025, Journal of Evolutionary Biology 38:728-742, https://doi.org/10.1093/jeb/voaf040). This may explain why wing morphology evolves along narrow axes despite available genetic variation.
Objective: To test that the pattern of selection is determined by the same mating-system parameters in three species of pond damselflies: Enallagma cyathigerum, Ischnura elegans, and Coenagrion pulchellum.
Your role: You will measure selection and mating-system structure in wild damselfly populations around Lund by:
– conducting standardized field surveys (community composition, sex ratio, morph frequencies)
– performing fecundity assays as a fitness measure in the laboratory
– acquiring wing images with an AI-assisted pipeline
– quantify phenotypic selection using quantitative-genetic framework
What you will learn:
– field sampling and ecological census methods
– imaging and high-throughput phenotyping tools
– evolutionary quantitative genetics (selection gradients, multivariate models)
– scientific data management and statistical analysis in R
Required knowledge: Basic skills in field work and interest in natural history. The candidate will receive an extensive training on the system. A successful candidate will have an interest in phenotypic evolution. The project is intended for 60 credits master’s thesis.
Starting date: flexible, but the prospective student needs to participate field work in June and July/2026
This project contributes directly to understanding the predictability of evolution and has implications for predicting evolution and biodiversity conservation under global change.
Contact info: Masahito Tsuboi (masahito.tsuboi@biol.lu.se)