Webbläsaren som du använder stöds inte av denna webbplats. Alla versioner av Internet Explorer stöds inte längre, av oss eller Microsoft (läs mer här: * https://www.microsoft.com/en-us/microsoft-365/windows/end-of-ie-support).

Var god och använd en modern webbläsare för att ta del av denna webbplats, som t.ex. nyaste versioner av Edge, Chrome, Firefox eller Safari osv.

Fältarbete på Färskesjön 2013

Anne Birgitte Nielsen

Universitetslektor

Fältarbete på Färskesjön 2013

Creating spatially continuous maps of past land cover from point estimates: A new statistical approach applied to pollen data

Författare

  • Behnaz Pirzamanbein
  • Johan Lindström
  • Anneli Poska
  • Shinya Sugita
  • Anna-Kari Trondman
  • Ralph Fyfe
  • Florence Mazier
  • Anne Birgitte Nielsen
  • Jed O. Kaplan
  • Anne E. Bjune
  • H. John B. Birks
  • Thomas Giesecke
  • Mikhel Kangur
  • Małgorzata Latałowa
  • Laurent Marquer
  • Benjamin Smith
  • Marie-José Gaillard

Summary, in English

Reliable estimates of past land cover are critical for assessing potential effects of anthropogenic land-cover changes on past earth surface-climate feedbacks and landscape complexity. Fossil pollen records from lakes and bogs have provided important information on past natural and human-induced vegetation cover. However, those records provide only point estimates of past land cover, and not the spatially continuous maps at regional and sub-continental scales needed for climate modelling.



We propose a set of statistical models that create spatially continuous maps of past land cover by combining two data sets: 1) pollen-based point estimates of past land cover (from the REVEALS model) and 2) spatially continuous estimates of past land cover, obtained by combining simulated potential vegetation (from LPJ-GUESS) with an anthropogenic land-cover change scenario (KK10). The proposed models rely on statistical methodology for compositional data and use Gaussian Markov Random Fields to model spatial dependencies in the data.



Land-cover reconstructions are presented for three time windows in Europe: 0.05, 0.2, and 6 ka years before present (BP). The models are evaluated through cross-validation, deviance information criteria and by comparing the reconstruction of the 0.05 ka time window to the present-day land-cover data compiled by the European Forest Institute (EFI). For 0.05 ka, the proposed models provide reconstructions that are closer to the EFI data than either the REVEALS- or LPJ-GUESS/KK10-based estimates; thus the statistical combination of the two estimates improves the reconstruction. The reconstruction by the proposed models for 0.2 ka is also good. For 6 ka, however, the large differences between the REVEALS- and LPJ-GUESS/KK10-based estimates reduce the reliability of the proposed models. Possible reasons for the increased differences between REVEALS and LPJ-GUESS/KK10 for older time periods and further improvement of the proposed models are discussed.

Avdelning/ar

  • Matematisk statistik
  • Institutionen för naturgeografi och ekosystemvetenskap
  • MERGE: ModElling the Regional and Global Earth system
  • BECC: Biodiversity and Ecosystem services in a Changing Climate

Publiceringsår

2014

Språk

Engelska

Sidor

127-141

Publikation/Tidskrift/Serie

Ecological Complexity: An International Journal on Biocomplexity in the Environment and Theoretical Ecology

Volym

20

Issue

December 2014

Dokumenttyp

Artikel i tidskrift

Förlag

Elsevier

Ämne

  • Earth and Related Environmental Sciences
  • Probability Theory and Statistics

Nyckelord

  • Land cover
  • Spatial modeling
  • Paleoecology
  • Pollen
  • Compositional data
  • Gaussian Markov random fields

Status

Published

ISBN/ISSN/Övrigt

  • ISSN: 1476-945X