Spatiotemporal Analytical Modelling for Paleobiology
Radical changes in the Earth’s biome as a consequence of climate change will fundamentally affect human society and its relation to the natural world. How can we best model species dynamics, to make predictions for the future? Wh...
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Información proyecto STAMP
Duración del proyecto: 61 meses
Fecha Inicio: 2023-05-12
Fecha Fin: 2028-06-30
Líder del proyecto
KOBENHAVNS UNIVERSITET
No se ha especificado una descripción o un objeto social para esta compañía.
TRL
4-5
Presupuesto del proyecto
1M€
Descripción del proyecto
Radical changes in the Earth’s biome as a consequence of climate change will fundamentally affect human society and its relation to the natural world. How can we best model species dynamics, to make predictions for the future? What are the main drivers underlying these dynamics, and how are these changing as we enter the Anthropocene? A great compass for biotic changes we will see in coming decades is the study of changes the Earth has experienced before – from alterations in the distribution of terrestrial and marine mammals, to the dynamic changes in the range and connectivity of forests. There is now a wealth of historic and prehistoric records documenting these processes, including pollen and fossil records, ancient genomes and sedimentary DNA. Here, I propose a research programme called Spatiotemporal Analytical Modelling for Paleobiology (STAMP) to link these disparate types of paleobiological records with the methodological tools of spatiotemporal process analysis. I will focus on three empirical research areas: 1) reconstruction of megafauna species ranges across the late Pleistocene and Holocene; 2) reconstruction of boreal paleo-forest dynamics; 3) study of the historical resilience and mobility of arctic marine mammals. These empirical projects will be supported by two computational approaches to inference: one based on descriptive spatiotemporal modelling, and another based on dynamic simulation-based inference. STAMP will produce a new conceptual paradigm for thinking about paleobiological data and create a statistical methodology that will be widely applicable to palaeontologists, geneticists, paleo-botanists and ecologists worldwide. Ultimately, it will empower the next generation of paleo-scientists with powerful tools to use the living past as a spatial roadmap into the future.