Evolution in nature and society

Data science and evolution

The main focus of my current research is on understanding evolutionary processes in nature and society in data-driven ways. In the past few years we worked a lot with the global mammalian fossil record, documenting evolutionary history of life.

The global fossil record refers documents and characterises evidence about organisms that existed at different times and places during the Earth’s history. One of the major directions in computational analysis of such data is to reconstruct environmental settings, track climate changes over millions of years and understand global change and evolutionary processes in general.

Rapidly growing global biospheric databases, such as NOW coordinated from Helsinki, aggregate and accumulate findings and knowledge that geoscientists acquired over many years. These databases are big data of palaeontology. The datasets are compiled from different sources, they are to an extent subjective, include specific biases and uncertainties, data sparseness and quality varies over time and space. These datasets are complemented by high volume and large velocity satellite observations of the modern day world, which are needed for training and calibration of predictive models, and require scalable and robust computing.

Selected publications

  • Reconciling taxon senescence with the Red Queen’s hypothesis by Žliobaitė et al. 2018 in Nature. DOI

  • A survey of computational methods for fossil data analysis by Žliobaitė et al. 2017 in Evolutionary Ecology Research. DOI

  • Herbivore teeth predict climatic limits in Kenyan ecosystems by Žliobaitė et al. 2016 in PNAS. DOI

  • An ecometric analysis of the fossil mammal record of the Turkana Basin by Fortelius et al. 2016 in Philosophical Transactions B. DOI


Media coverage

Last updated 2018 April