Behnaz Pirzamanbin
Biträdande universitetslektor
POLLENOMICS: Decoding the Farming History of Europe Using a Bayesian Approach Combining Compositional Data with a Point Process
Författare
Summary, in English
This study uniquely combines advanced continental-scale data from
two distinct sources: pollen-based land cover (PbLC) and ancient DNA
(aDNA), developing a novel statistical model for spatiotemporal reconstructions
of past land use across Europe.
The aDNA data serves as a proxy for human habitation, differentiating
anthropogenic and natural land cover from PbLC reconstruction. This
will be accomplished using a Bayesian hierarchical model that combines
compositional data, Gaussian Markov random fields and point process
models.
This groundbreaking approach gives insights into the environmental
impacts of Holocene human migration and subsistence practices, and
marks a major advancement in understanding human-environmental dynamics
over millennia.
two distinct sources: pollen-based land cover (PbLC) and ancient DNA
(aDNA), developing a novel statistical model for spatiotemporal reconstructions
of past land use across Europe.
The aDNA data serves as a proxy for human habitation, differentiating
anthropogenic and natural land cover from PbLC reconstruction. This
will be accomplished using a Bayesian hierarchical model that combines
compositional data, Gaussian Markov random fields and point process
models.
This groundbreaking approach gives insights into the environmental
impacts of Holocene human migration and subsistence practices, and
marks a major advancement in understanding human-environmental dynamics
over millennia.
Avdelning/ar
- Statistiska institutionen
- MERGE: ModElling the Regional and Global Earth system
- eSSENCE: The e-Science Collaboration
- LTH profilområde: Teknik för hälsa
- Molekylär biovetenskap
- BECC: Biodiversity and Ecosystem services in a Changing Climate
- Institutionen för naturgeografi och ekosystemvetenskap
- LTH profilområde: Aerosoler
- Matematisk statistik
Publiceringsår
2024-02
Språk
Engelska
Dokumenttyp
Konferensbidrag: abstract
Ämne
- Physical Geography
- Probability Theory and Statistics
- Other Earth Sciences (including Geographical Information Science)
Conference name
Bayes@Lund 2024
Conference date
2024-03-06 - 2024-03-07
Conference place
Lund, Sweden
Aktiv
Published