Anett Kiss

Anett Kiss

Details

Name: Anett Kiss
Position: DPhil student (Environmental Research NERC DTP)
Email: anett.kiss@env-res.ox.ac.uk

AUTOBIOGRAPHY:

I graduated from The University of Edinburgh with a BSc in Ecology in 2020. During my honours project supervised by Dr Ally Phillimore, I investigated the trends in spring phenology of common frogs (Rana temporaria) and newts (Triturus and Lissotriton spp) in response to recent climate change across the UK. I used Nature’s Calendar citizen science records applied to a Bayesian multivariate mixed model framework, aiming to identify the cues that drive timing and separate the contributions of plasticity and microevolution to the observed advance in amphibian breeding times as a response to global warming. Furthermore, I explored how spatiotemporal variations in the degree of trophic asynchrony between frog and newt phenologies might influence their demographic trends and evolutionary responses under future predicted climate change scenarios.

Previously, I volunteered as a fieldwork assistant for the St Kilda Soay Sheep Project, as well as Dr Ally Phillimore’s Phenoweb group studying the relationship between climate and trophic mismatch in the tree-caterpillar-blue tit woodland food web.

RESEARCH INTERESTS:

My broad interests lie in understanding the mechanisms by which organisms respond to variations in their environment and using this knowledge to predict the population and fitness impacts of climate change. During my DPhil supervised by Prof Ben Sheldon and Dr Ella Cole, I hope to characterise the costs and benefits of environment-induced breeding decision adjustments (eg. laying initiation, incubation duration, clutch size) in woodland passerines using field experiments combined with the long-term phenological records on the Wytham Tits.  By quantifying the extent of plasticity in the timing and duration of each reproductive stage and characterising how different life-history traits might co-adapt to optimise fitness, I ultimately hope to establish more integrated models aimed at predicting the demographic and fitness consequences experienced by woodland passerines in the face of climate change.