About me
I am currently doing a PhD in ecology at the University of Zurich (UZH) in the Predictive Ecology Group led by Prof. Owen L. Petchey (OLP) and which I will conclude towards the end of 2024. I am fascinated by the complexity and diversity of ecological systems and I strive to discover and explain new things about them. I am always keen to extend my horizon with new methods, topics and collaborations about and beyond my current scientific focus.
I have a Master in Biostatistics (UZH, 2018-2020, thesis supervisors: Prof. Reinhard Furrer and OLP) and a Bachelor in Biology (Major) and Environmental Sciences (Minor, UZH, 2015-2018).
My research
The focus of my PhD research is on ecological forecasting and associated questions such as:
- What makes certain ecological systems and measures more predictable than others?
- Are there general relations between species or ecosystem characteristics and how well these can be predicted?
- How do such relations scale with environmental change/stressors?
To tackle these questions I work at the intersection of data and theory. I conduct quantitative analyses (e.g. estimation of species interactions and networks) and forecasts, with a special focus on reproducibility and open science.
Model system
I often work with laboratory based microbial aquatic ecosystems (i.e. protist microcosms). For instance, in a team led by Dr. Romana Limberger (RL) we recently carried out 2 long-term (9 months, ~120 time points) microcosm experiments in which we manipulated biodiversity and stressors (soon™ to be published).
I also work with observational data (e.g. lake plankton monitoring optimization, a collaboration with Dr. Francesco Pomati, Stefanie Merkli, Dr. Ewa Merz and OLP, more info here) and with simulations.
Data analysis
I generally use various non-parametric (machine learning) approaches to forecasting (such as empirical dynamic modelling, random forest and recurrent neural networks) and arima. For instance, I, Dr. Stephan B. Munch, OLP and coauthors investigated how taxa abundance forecasts depend on ecological complexity within and across systems and found that generalist species are forecasted better than specialists (more info here).
In my current research project I am working with a more mechanistic approach to forecasting, in which I combine population dynamics with generalized additive models.
Other projects
During my Bachelor studies I did a 3 months internship with Dr. Frank Pennekamp (main supervisor) and OLP. In the project, we found that warming can cause a destabilizing type switch in a predator-prey functional response (more info here). For this publication, I won the 2019 Elton Prize (best research paper in the Journal of Animal Ecology by an early career author).
I am also coauthor in two microbiology projects led by Dr. Marcel Suleiman in which we studied the effects of multiple stressors on bacterial communities kept in special Winogradsky columns, and in a projects led by RL in which we investigated the role of functional diversity in regime shifts (see the publications tab).
Selected Publications
Daugaard, U., Petchey, O.L. & Pennekamp, F. (2019). Warming can destabilize predator–prey interactions by shifting the functional response from Type III to Type II. Journal of Animal Ecology, 88, 1575–1586.
Daugaard, U., Munch, S., Inauen, D., Pennekamp, F. & Petchey, O. (2022). Forecasting in the face of ecological complexity: number and strength of species interactions determines forecast skill in ecological communities. Ecology Letters.
Daugaard, U., Merkli, S., Merz, E., Pomati, F. & Petchey, O.L. (2024). The dependence of forecasts on sampling frequency as a guide to optimizing monitoring in community ecology. Ecosphere, 15, e4786.