MARCO POLO stands for MAnipulating pollen sums to ReCOnstruct POllen of Local Origin. The model, introduced by Mrotzek et al. 2017, is a tool for quantitative vegetation reconstruction at the stand scale from pollen records of small sites. MARCO POLO compares a pollen record from a small site with an adjacent regional record from a large water body or peatland to determine the (extra-)local component that dominates pollen deposition at the small site.

Hitherto, the Landscape Reconstruction Algorithm (LRA) has been the only truly quantitative approach to stand-scale palynology. However, the LRA requires information on pollen productivity and dispersal, which is not always available. The alternative approach MARCO POLO is solely based on pollen values and does not rely on a pollen dispersal function. In a stepwise fashion, MARCO POLO removes those pollen types from the pollen sum whose values are significantly higher than in a neighbouring large basin. The resulting regional pollen sum is free of the disturbing factor of (extra-)local pollen. Based on this sum, comparison with the pollen record from the large basin allows calculating sharp (extra-)local signals.

Treating the (extra-)local pollen portion with representation factors (R-values, Davis 1963) then produces a quantitative reconstruction of the stand-scale vegetation composition. Whereas correction factors are available for (most) arboreal taxa (e.g. Andersen 1970, Bradshaw 1981), they are generally lacking for taxa indicative of open vegetation and human activity. Yet, the tool is able to detect presence/absence of taxa even if correction factors are not available.

How-to

We have implemented Marco Polo in R and provide the code and example data from the paper. For testing, download and unpack code + example into a suitable working folder (here just D:/MarcoPolo) and run it like this:

setwd("D:/MarcoPolo")
source("MarcoPolo_v.0.5.R")
results <- MarcoPolo(datafile = "MarcoPoloExampleData.xlsx", resultfile = "MarcoPoloExampleData_Results.csv")

The results will be written in the results variable and the file specified.

References

Andersen S.T. (1970) The relative pollen productivity and pollen representation of North European trees, and correction factors for tree pollen spectra: determined by surface pollen analyses from forests. Danmarks Geol Undersøgelse Række 2 96:99.

Bradshaw R.H.W. (1981) Modern pollen-representation factors for Woods in South-East England. Journal of Ecology 69:45–70.

Davis M.B. (1963) On the theory of pollen analysis. American Journal of Science 261:897–912.