 Reconstruction of past human land use from pollen data and anthropogenic land cover changesBehnaz Pirzamanbein and Johan Lindström Environmetrics, 2022, vol. 33, issue 6 Abstract: 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. We developed a Bayesian hierarchical model 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 modelers 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. Date: 2022 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:wly:envmet:v:33:y:2022:i:6:n:e2743 Ordering information: This journal article can be ordered from Access Statistics for this article More articles in Environmetrics from John Wiley & Sons, Ltd. |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.