ROPES reveals past land cover and pollen productivity estimates from single pollen records
- 1Institute of Botany and Landscape Ecology, University of Greifswald, Germany
- 2Greifswald Mire Centre, Germany
Quantitative reconstructions of past vegetation cover commonly require pollen productivity estimates (PPEs). PPEs are calibrated in extensive and rather cumbersome surface-sample studies, and are so far only available for selected regions. Moreover, it may be questioned whether present-day pollen-landcover relationships are valid for palaeo-situations. We here introduce the ROPES approach that simultaneously derives PPEs and mean plant abundances from single pollen records. ROPES requires pollen counts and pollen accumulation rates (PARs, grains cm-2 year-1). Pollen counts are used to reconstruct plant abundances following the REVEALS approach. The principle of ROPES is that changes in plant abundance are linearly represented in observed PAR values. For example, if the PAR of pine doubles, so should the REVEALS reconstructed abundance of pine. Consequently, if a REVEALS reconstruction is ‘correct’ (i.e. ‘correct’ PPEs are used) the ratio ‘PAR over REVEALS’ is constant for each taxon along all samples of a record. With incorrect PPEs, the ratio will instead vary. ROPES starts from random (likely incorrect) PPEs, but then adjusts them using an optimization algorithm with the aim to minimize variation in the ‘PAR over REVEALS’ ratio across the record. ROPES thus simultaneously calculates mean plant abundances and PPEs.
We illustrate the approach with test applications on nine synthetic pollen records. The results show that good performance of ROPES requires data sets with high underlying variation, many samples and low noise in the PAR data. ROPES can deliver first landcover reconstructions in regions for which PPEs are not yet available. The PPEs provided by ROPES may then allow for further REVEALS-based reconstructions. Similarly, ROPES can provide insight in pollen productivity during distinct periods of the past such as the Lateglacial. We see a potential to study spatial and temporal variation in pollen productivity for example in relation to site parameters, climate and land use. It may even be possible to detect expansion of non-pollen producing areas in a landscape. Overall, ROPES will help produce more accurate landcover reconstructions and expand reconstructions into new study regions and non-analogue situations of the past.
ROPES will be available within the R package DISQOVER.
Keywords: DISQOVER, landcover reconstruction, palynology, Pollen accumulation rates, Pollen productivity estimates, vegetation history
Received: 17 Nov 2017;
Accepted: 09 Feb 2018.
Edited by:Thomas Giesecke, University of Göttingen, Germany
Reviewed by:Andria Dawson, University of California, Berkeley, United States
Per Sjögren, UiT The Arctic University of Norway, Norway
Copyright: © 2018 Theuerkauf and Couwenberg. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Dr. Martin Theuerkauf, University of Greifswald, Institute of Botany and Landscape Ecology, Soldmannstraße 15, Greifswald, 17489, Germany, firstname.lastname@example.org