ROPES Reveals Past Land Cover and PPEs From Single Pollen Records

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-la...

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Main Authors: Martin Theuerkauf, John Couwenberg
Format: Article
Language:English
Published: Frontiers Media S.A. 2018-04-01
Series:Frontiers in Earth Science
Subjects:
Online Access:http://journal.frontiersin.org/article/10.3389/feart.2018.00014/full
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spelling doaj-b99efdc070064c239cca4176440102d02020-11-24T23:57:57ZengFrontiers Media S.A.Frontiers in Earth Science2296-64632018-04-01610.3389/feart.2018.00014331722ROPES Reveals Past Land Cover and PPEs From Single Pollen RecordsMartin Theuerkauf0Martin Theuerkauf1John Couwenberg2John Couwenberg3Working Group on Peatland Studies and Palaeoecology, Institute of Botany and Landscape Ecology, University of Greifswald, Greifswald, GermanyPartner in the Greifswald Mire Centre, Greifswald, GermanyWorking Group on Peatland Studies and Palaeoecology, Institute of Botany and Landscape Ecology, University of Greifswald, Greifswald, GermanyPartner in the Greifswald Mire Centre, Greifswald, GermanyQuantitative 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-analog situations of the past. ROPES is available within the R package DISQOVER.http://journal.frontiersin.org/article/10.3389/feart.2018.00014/fullDISQOVERlandcover reconstructionpalynologypollen accumulation ratespollen productivity estimatesvegetation history
collection DOAJ
language English
format Article
sources DOAJ
author Martin Theuerkauf
Martin Theuerkauf
John Couwenberg
John Couwenberg
spellingShingle Martin Theuerkauf
Martin Theuerkauf
John Couwenberg
John Couwenberg
ROPES Reveals Past Land Cover and PPEs From Single Pollen Records
Frontiers in Earth Science
DISQOVER
landcover reconstruction
palynology
pollen accumulation rates
pollen productivity estimates
vegetation history
author_facet Martin Theuerkauf
Martin Theuerkauf
John Couwenberg
John Couwenberg
author_sort Martin Theuerkauf
title ROPES Reveals Past Land Cover and PPEs From Single Pollen Records
title_short ROPES Reveals Past Land Cover and PPEs From Single Pollen Records
title_full ROPES Reveals Past Land Cover and PPEs From Single Pollen Records
title_fullStr ROPES Reveals Past Land Cover and PPEs From Single Pollen Records
title_full_unstemmed ROPES Reveals Past Land Cover and PPEs From Single Pollen Records
title_sort ropes reveals past land cover and ppes from single pollen records
publisher Frontiers Media S.A.
series Frontiers in Earth Science
issn 2296-6463
publishDate 2018-04-01
description 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-analog situations of the past. ROPES is available within the R package DISQOVER.
topic DISQOVER
landcover reconstruction
palynology
pollen accumulation rates
pollen productivity estimates
vegetation history
url http://journal.frontiersin.org/article/10.3389/feart.2018.00014/full
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