eSSENCE@LU 10:4 - POLLENOMICS: Decoding the farming history of Europe using advanced statistics to combine ancient DNA with paleo-pollen data

The goal of the project is to combine reconstruction of human migration based on ancient DNA data with pollen-based land cover data, which we term Pollenomics, to create a new proxy-based Land Use and Land Cover Change (LULCC) dataset for Europe. Improving the prediction accuracy of LULCC models serves various purposes, ranging from identifying agricultural practices that maximise future food production (crop yields) under different future climates scenarios to optimising conservation strategies for preserving critical ecosystems and biodiversity. Moreover, it can improve our capacity to evaluate how urban areas will withstand climate-induced changes and guide sustainable land-use planning for resilient and adaptable cities.