Evidence map›Paper›PMID 35915724›Full record

ArticleJournal of biogeography2022

A new method based on surface-sample pollen data for reconstructing palaeovegetation patterns.

Esmeralda Cruz-Silva, Sandy P Harrison, Elena Marinova, I Colin Prentice

Abstract read
In one paragraph

Article in Journal of biogeography, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Esmeralda Cruz-SilvaSchool of Archaeology, Geography & Environmental Science Reading University Reading UK.ORCID https://orcid.org/0000-0003-2906-9290
Sandy P HarrisonSchool of Archaeology, Geography & Environmental Science Reading University Reading UK.ORCID https://orcid.org/0000-0001-5687-1903
Elena MarinovaLaboratory for Archaeobotany Baden-Württemberg Cultural Heritage State Office Geienhofen-Hemmenhofen Germany.ORCID https://orcid.org/0000-0003-3793-3317
I Colin PrenticeGeorgina Mace Centre for the Living Planet, Department of Life Sciences Imperial College London Ascot UK.ORCID https://orcid.org/0000-0002-1296-6764

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aim: Biomisation has been the most widely used technique to reconstruct past regional vegetation patterns because it does not require an extensive modern pollen dataset. However, it has well-known limitations including its dependence on expert judgement for the assignment of pollen taxa to plant functional types (PFTs) and PFTs to biomes. Here we present a new method that combines the strengths of biomisation with those of the alternative dissimilarity-based techniques. Location: The Eastern Mediterranean-Black Sea Caspian Corridor (EMBSeCBIO). Taxon: Plants. Methods: Modern pollen samples, assigned to biomes based on potential natural vegetation data, are used to characterize the within-biome means and standard deviations of the abundances of each taxon. These values are used to calculate a dissimilarity index between any pollen sample and every biome, and thus assign the sample to the most likely biome. We calculate a threshold value for each modern biome; fossil samples with scores below the threshold for all modern biomes are thus identified as non-analogue vegetation. We applied the new method to the EMBSeCBIO region to compare its performance with existing reconstructions. Results: The method captured changes in the importance of individual taxa along environmental gradients. The balanced accuracy obtained for the EMBSeCBIO region using the new method was better than obtained using biomisation (77% vs. 65%). When the method was applied to high-resolution fossil records, 70% of the entities showed more temporally stable biome assignments than obtained using biomisation. The technique also identified likely non-analogue assemblages in a synthetic modern dataset and in fossil records. Main conclusions: The new method yields more accurate and stable reconstructions of vegetation than biomisation. It requires an extensive modern pollen dataset, but is conceptually simple, and avoids subjective choices about taxon allocations to PFTs and PFTs to biomes.

Indexed as

biomesbiomisationEastern MediterraneanEMBSeCBIOpalaeovegetationpollen datapotential natural vegetationvegetation changevegetation reconstruction

Identifiers

PMID35915724
PMCPMC9328394

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.