Bayesian reconstruction of past land‐cover from pollen data: model robustness and sensitivity to auxiliary variables

Behnaz Pirzamanbein, Anneli Poska, Johan Lindström

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Realistic depictions of past land cover are needed to investigate prehistoric environmental changes, effects of anthropogenic deforestation, and long term land cover‐climate feedbacks. Observation based reconstructions of past land cover are rare and commonly used model based reconstructions exhibit considerable differences. Recently Pirzamanbein, Lindström, Poska, and Gaillard (Spatial Statistics, 24:14‐‐31,2018) developed a statistical interpolation method that produces spatially complete reconstructions of past land cover from pollen assemblage. These reconstructions incorporate a number of auxiliary datasets raising questions regarding the method's sensitivity to different auxiliary datasets.

Original languageEnglish
Article numbere2018EA00057
JournalEarth and Space Science
Issue number1
Number of pages24
Publication statusPublished - 2019

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