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 Behnaz Pirzamanbein . Foto

Behnaz Pirzamanbin

Biträdande universitetslektor

 Behnaz Pirzamanbein . Foto

Reconstruction of past human land use from pollen data and anthropogenic land cover changes

Författare

  • Behnaz Pirzamanbein
  • Johan Lindström

Summary, in English

Accurate maps of past land cover and human land use are necessary for studying the impact of anthropogenic land-cover changes, such as deforestation, on the climate. The maps of past land cover should ideally be separated into naturally occurring vegetation and human-induced changes, thereby enabling the quantification of the effect of human land use on the past climate. A Bayesian hierarchical model is developed that combines fossil pollen-based reconstructions of actual land cover with estimates of past human land use. The model interpolates the fractions of unforested land as well as coniferous and broadleaved forest from the pollen data and uses the human land-use estimates to decompose the unforested land into natural vegetation and human deforestation. This results in maps of both natural and human-induced vegetation, which can be used by climate modellers to quantify the influence of deforestation on the past climate. The model was applied to five time periods from 1900 CE to 4000 BCE over Europe. The model uses a latent Gaussian Markov random field (GMRF) for the interpolation and Markov chain Monte Carlo for the estimation. The sparse precision matrix of the GMRF, together with an adaptive Metropolis-adjusted Langevin step, allows for rapid inference.

Avdelning/ar

  • MERGE: ModElling the Regional and Global Earth system
  • Statistiska institutionen
  • LTH profilområde: Aerosoler
  • eSSENCE: The e-Science Collaboration
  • BECC: Biodiversity and Ecosystem services in a Changing Climate
  • Matematisk statistik

Publiceringsår

2023

Språk

Engelska

Dokumenttyp

Konferensbidrag: abstract

Ämne

  • Probability Theory and Statistics
  • Climate Science

Conference name

Computational and Methodological Statistics

Conference date

2023-12-16 - 2023-12-18

Conference place

Berlin, Germany

Aktiv

Published