lnu.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Pollen-based quantitative land-cover reconstruction for northern Asia covering the last 40 ka cal BP
Helmholtz Ctr Polar & Marine Res, Germany;Chinese Acad Sci, China.
Helmholtz Ctr Polar & Marine Res, Germany.
Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.ORCID iD: 0000-0002-2025-410X
Show others and affiliations
2019 (English)In: Climate of the Past, ISSN 1814-9324, E-ISSN 1814-9332, Vol. 15, no 4, p. 1503-1536Article in journal (Refereed) Published
Abstract [en]

We collected the available relative pollen productivity estimates (PPEs) for 27 major pollen taxa from Eurasia and applied them to estimate plant abundances during the last 40 ka cal BP (calibrated thousand years before present) using pollen counts from 203 fossil pollen records in northern Asia (north of 40 degrees N). These pollen records were organized into 42 site groups and regional mean plant abundances calculated using the REVEALS (Regional Estimates of Vegetation Abundance from Large Sites) model. Time-series clustering, constrained hierarchical clustering, and detrended canonical correspondence analysis were performed to investigate the regional pattern, time, and strength of vegetation changes, respectively. Reconstructed regional plant functional type (PFT) components for each site group are generally consistent with modern vegetation in that vegetation changes within the regions are characterized by minor changes in the abundance of PFTs rather than by an increase in new PFTs, particularly during the Holocene. We argue that pollen-based REVEALS estimates of plant abundances should be a more reliable reflection of the vegetation as pollen may overestimate the turnover, particularly when a high pollen producer invades areas dominated by low pollen producers. Comparisons with vegetation-independent climate records show that climate change is the primary factor driving land-cover changes at broad spatial and temporal scales. Vegetation changes in certain regions or periods, however, could not be explained by direct climate change, e.g. inland Siberia, where a sharp increase in evergreen conifer tree abundance occurred at ca. 7-8 ka cal BP despite an unchanging climate, potentially reflecting their response to complex climate-permafrost-fire-vegetation interactions and thus a possible long-term lagged climate response.

Place, publisher, year, edition, pages
Copernicus Gesellschaft MBH , 2019. Vol. 15, no 4, p. 1503-1536
National Category
Climate Research Ecology Physical Geography
Research subject
Environmental Science, Paleoecology
Identifiers
URN: urn:nbn:se:lnu:diva-88792DOI: 10.5194/cp-15-1503-2019ISI: 000480290300001Scopus ID: 2-s2.0-85070473152OAI: oai:DiVA.org:lnu-88792DiVA, id: diva2:1346569
Available from: 2019-08-28 Created: 2019-08-28 Last updated: 2020-12-14Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Li, FurongGaillard, Marie-José

Search in DiVA

By author/editor
Li, FurongGaillard, Marie-José
By organisation
Department of Biology and Environmental Science
In the same journal
Climate of the Past
Climate ResearchEcologyPhysical Geography

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 168 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf