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

Pirzamanbein, Behnaz LU ; Lindström, Johan LU ; Poska, Anneli LU ; Sugita, Shinya; Trondman, Anna-Kari; Fyfe, Ralph; Mazier, Florence; Nielsen, Anne Birgitte LU ; Kaplan, Jed O. and Bjune, Anne E., et al. (2014) In Ecological Complexity: An International Journal on Biocomplexity in the Environment and Theoretical Ecology 20(December 2014). p.127-141
Abstract
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... (More)
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. (Less)
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Contribution to journal
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published
subject
keywords
Land cover, Spatial modeling, Paleoecology, Pollen, Compositional data, Gaussian Markov random fields
in
Ecological Complexity: An International Journal on Biocomplexity in the Environment and Theoretical Ecology
volume
20
issue
December 2014
pages
127 - 141
publisher
Elsevier
external identifiers
  • wos:000348010800013
  • scopus:84907948370
ISSN
1476-945X
DOI
10.1016/j.ecocom.2014.09.005
project
BECC
MERGE
language
English
LU publication?
yes
id
5c3b4b67-36ce-4455-96bb-2b94727725e2 (old id 4696948)
alternative location
http://www.sciencedirect.com/science/article/pii/S1476945X1400097X
date added to LUP
2014-10-24 11:57:49
date last changed
2017-07-23 03:12:11
@article{5c3b4b67-36ce-4455-96bb-2b94727725e2,
  abstract     = {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.<br/><br>
<br/><br>
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.<br/><br>
<br/><br>
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.},
  author       = {Pirzamanbein, Behnaz and Lindström, Johan and Poska, Anneli and Sugita, Shinya and Trondman, Anna-Kari and Fyfe, Ralph and Mazier, Florence and Nielsen, Anne Birgitte and Kaplan, Jed O. and Bjune, Anne E. and B. Birks, H. John and Giesecke, Thomas and Kangur, Mikhel and Latałowa, Małgorzata and Marquer, Laurent and Smith, Benjamin and Gaillard, Marie-José},
  issn         = {1476-945X},
  keyword      = {Land cover,Spatial modeling,Paleoecology,Pollen,Compositional data,Gaussian Markov random fields},
  language     = {eng},
  number       = {December 2014},
  pages        = {127--141},
  publisher    = {Elsevier},
  series       = {Ecological Complexity: An International Journal on Biocomplexity in the Environment and Theoretical Ecology},
  title        = {Creating spatially continuous maps of past land cover from point estimates: A new statistical approach applied to pollen data},
  url          = {http://dx.doi.org/10.1016/j.ecocom.2014.09.005},
  volume       = {20},
  year         = {2014},
}