Research

The predator gut microbiome 

Previous work has demonstrated high within-species variation in how quickly predators learn to recognise and avoid aposematic prey, and this heterogeneity is considered to play an important role in the evolution and maintenance of prey defences. In my research, I am investigating what maintains the observed variation in predator behaviour by focusing on an unexplored mechanism: a predator’s gut microbiome. Evidence from humans and laboratory animals shows that the gut microbiome influences learning, memory and foraging choices (‘the microbiome-gut-brain axis’), and theoretical models predict feedback loops between gut microbiome, diet and host behaviour. I aim to bring this to the ecologically relevant context by testing whether there is a feedback loop between the predator gut microbiome, cognition, foraging decisions and consumption of prey toxins, and how this may mediate selection pressures for prey defences.

I use wild-caught great tits as model predators, and combine several methods that include manipulating birds’ gut microbiome with prey toxins, quantifying gut microbial compositions from faecal samples using 16s rRNA sequencing, and conducting behavioural experiments. 

Main collaborators: 

Suvi Ruuskanen, Phillip Watts, Gabrielle Davidson

Social information use by predators

Predators can gather information about prey profitability in two ways: by interacting with prey directly (personal information) or by observing the foraging behaviour of other predators (social information). In my research, I am aiming to understand how predators use these two types of information, and how this influences selection pressures for prey defences. For example, conspicuous aposematic prey are predicted to suffer high predation from naive predators, but this initial predation cost may be reduced if predators learn about prey defences by observing negative foraging experiences of others. On the other hand, social information about the presence of palatable mimics might alter model-mimic dynamics by increasing predation on both mimics and their defended models.

I use blue tits and great tits as model predators to investigate how social information influences their foraging decisions. This includes controlled laboratory experiments where social information can be manipulated with video playback, as well as field experiments that investigate social transmission in the wild predator population.

Main collaborators: 

Rose Thorogood, Johanna Mappes, Hannah Rowland

Recent publications:

    Hämäläinen, L., Hoppitt, W., Rowland, H.M., Mappes, J., Fulford, A.J., Sosa, S., & Thorogood, R. (2021). Social transmission in the wild can reduce predation pressure on novel prey signals. Nature Communications. 12, 3978. https://doi.org/10.1038/s41467-021-24154-0 

    Hämäläinen, L., Rowland, H.M., Mappes, J., & Thorogood, R. (2022). Social information use by predators: Expanding the information ecology of prey defences. Oikos, e08743. https://doi.org/10.1111/oik.08743 

Variation in warning signals

Aposematic animals warn predators of their unprofitability with conspicuous warning signals. Predators need to learn to recognise these signals and because consistent warning signals are easier to learn, selection is expected favour signal uniformity. However, many aposematic species have variable warning colouration, and I am seeking to understand what maintains this variation within and between populations. 

We are using Australian Amata nigriceps moths as a study system. The moths are chemically defended and have orange and black wing colouration that varies greatly among individuals. To investigate the factors maintaining this variation, we have conducted predation experiments, reared moths in the laboratory and carried out toxicity and palatability assays.

Main collaborators: 

Marie Herberstein, Georgina Binns

Recent publications:

Binns, G.E., Hämäläinen, L., Kemp, D.J., Rowland, H.M., Umbers, K.D.L., Herberstein, M.E. (2022). Additive genetic variation, but not temperature, influences warning signal expression in Amata nigriceps moths (Lepidoptera: Arctiinae). Ecology and Evolution. 12, e9111. https://doi.org/10.1002/ece3.9111 

Hämäläinen, L., Binns, G.E., Hart, N.S., Mappes, J., McDonald, P.G., O'Neill, L., Rowland, H.M., Umbers, K.D.L., Herberstein, M.E. (2023)Predator selection on multicomponent warning signals in an aposematic moth. Behavioral Ecology. https://doi.org/10.1093/beheco/arad097