Movement analysis of zooplankton through filming
How does the behaviour of plankton change with respect to environmental cues (ultraviolet radiation, temperature, food)?
Zooplankton is a fundamental part of the aquatic food web by transferring energy from lower to higher trophic levels. Within zooplankton, rotifers often numerically dominate communities and can achieve significant biomass under certain environmental conditions (Obertegger et al. 2007). Movement of organisms is fundamental to life, and research on movement contributes to our understanding of ecological and evolutionary processes (Nathan et al. 2008). In the past, rotifer behaviour has been filmed (Coulon et al. 1983, santos-Medrano et al. 2001) but most studies use manual tracking of the swimming path and only few use automated tracking of individuals. With the advent of a cheap and easy-to-use system for plankton filming (Colangeli et al. 2016) and the use of open source software such as R and ImageJ, plankton movement and behaviour can be studied at a much larger scale with respect to the number of individuals studied and at a smaller scale with respect to the details under study than it has been done so far. In nature, zooplankton has to constantly sense its environment to find food and mates, to avoid predators, and to find optimal environmental conditions. The project aims 1) to film zooplankton that is exposed to environmental cues such as ultraviolet radiation (UVR), temperature, and algal food and 2) to understand by using sophisticated models of animal behaviour, that until now have mainly applied to macroscopic organisms, how microscopic organisms react and optimize their response. Thus, this project aims at answering fundamental questions of population and niche dynamics. Understanding how organisms interact with each other and their environment contributes to a better management of populations, communities and ecosystems, and the services they provide.
Understanding the spatio-temporal dynamics of rotifer behaviour is a central theme of the proposal. Exposure time can range from minutes to days to cover different scales of temporal resolution, important to understand behavioural variability. Important steps of the project are the culture of study organisms, filming and data analysis. In case culturing does not succeed, zooplankton from nearby freshwater can also be used. For the exposure to UVR, different UVR leds emitting different wavelengths can be used. It is known that rotifers sense UVR (Colangeli et al. 2019) that is harmful to live; however, their sensitivity to different wavelengths is unknown. Microscopic organisms swimming in water have to cope with a high viscosity (Beveridge et al. 2010). Viscosity changes with temperature. Thus, the project will investigate if and how swimming patterns change with changing temperature. Zooplankton mostly rely on algal food. The project will investigate how swimming patters change with changing food concentration and food quality (exposed to UVR). Similar experiments have already performed with Brachionus (Kuefler et al. 2013), that is easy to culture. However, zooplankton does not only consist of this species, and to get a comprehensive understanding of the variability of zooplankton behaviour we need experiments with different species and data analysis using sophisticated techniques. An additional value is the consideration of rotifer traits (Obertegger & Flaim 2018). Within the proposal, the traits of species under study will be considered to understand at which scale the dynamics of population can be predicted from the their traits. The trait-based approach will give a more mechanistic understanding independent of species identity.
Aims of the Project
Investigate differences in movement of different species with respect to environmental cues
Investigate relationship between quorum sensing and behaviour
Sex differences in behaviour of zooplankton
Methods to be used
Culturing techniques, filming, models of movement ecology applied to microscopic organisms
Specialised skills the student will need
Will to learn new things such as culture of rotifers and algae, curiosity, technical understanding of camera settings, basic knowledge of R
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