Version 0.9 of the disqover package is now available. The new version includes two new functions (MarcoPolo and edar), plotting tools for REVEALSinR and MarcoPolo, a much improved help and a number of smaller corrections.

The MarcoPolo function is an implementation of the MARCO POLO approach (Mrotzek et al. 2017). The approach aims for stand scale vegetation reconstructions from pollen data. MARCO POLO combines pollen data from very small sites (with much (extra)local pollen deposition) with pollen data from large sites (with regional pollen deposition). The approach is based on iterative  manipulations of the pollen sum. In the package, the MarcoPolo function comes with example data from the publication for illustration and testing. The package also provides the plotMP() function for plotting the results.

The edar function is an implementation of the Extended Downscaling Approach (EDA, Theuerkauf and Couwenberg 2017). The approach aims to detect past vegetation patterns and plant communities within landscapes. To that end, EDA applies iterative forward modelling to fit vegetation composition to robust landscape patterns by comparing simulated with observed pollen deposition. Again, the R function comes with example data for illustration and testing.

The new disqover version includes some changes for the REVEALSinR function. Most importantly, the first column of the data should now include ages or depth. See help for the details. Plotting is now available with the plotREVEALS() function. Two main options are available. First, a diagram with seperate columns (type = “single”):

Example plot of REVEALSinR with the Lake Tiefer See data (single column version)

The second version is a stacked diagram (type = “stacked”):

Example plot of REVEALSinR with the Lake Tiefer See data (stacked version)

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