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Creating spatially continuous maps of past land cover from point estimates: A new statistical approach applied to pollen data
Lund Univ.
Lund Univ.
Lund Univ ; Tallinn Univ Technol, Estonia.
Tallinn Univ Technol, Estonia.
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2014 (English)In: Ecological Complexity: An International Journal on Biocomplexity in the Environment and Theoretical Ecology, ISSN 1476-945X, Vol. 20, 127-141 p.Article in journal (Refereed) Published
Abstract [en]

Reliable estimates of past land cover are critical for assessing potential effects of anthropogenic land-cover changes on past earth surface-climate feedbacks and landscape complexity. Fossil pollen records from lakes and bogs have provided important information on past natural and human-induced vegetation cover. However, those records provide only point estimates of past land cover, and not the spatially continuous maps at regional and sub-continental scales needed for climate modelling. We propose a set of statistical models that create spatially continuous maps of past land cover by combining two data sets: 1) pollen-based point estimates of past land cover (from the REVEALS model) and 2) spatially continuous estimates of past land cover, obtained by combining simulated potential vegetation (from LPJ-GUESS) with an anthropogenic land-cover change scenario (KK10). The proposed models rely on statistical methodology for compositional data and use Gaussian Markov Random Fields to model spatial dependencies in the data. Land-cover reconstructions are presented for three time windows in Europe: 0.05, 0.2, and 6 ka years before present (BP). The models are evaluated through cross-validation, deviance information criteria and by comparing the reconstruction of the 0.05 ka time window to the present-day land-cover data compiled by the European Forest Institute (EFI). For 0.05 ka, the proposed models provide reconstructions that are closer to the EFI data than either the REVEALS- or LPJ-GUESS/KK10-based estimates; thus the statistical combination of the two estimates improves the reconstruction. The reconstruction by the proposed models for 0.2 ka is also good. For 6 ka, however, the large differences between the REVEALS- and LPJ-GUESS/KK10-based estimates reduce the reliability of the proposed models. Possible reasons for the increased differences between REVEALS and LPJ-GUESS/KK10 for older time periods and further improvement of the proposed models are discussed. (C) 2014 Elsevier B.V. All rights reserved.

Place, publisher, year, edition, pages
2014. Vol. 20, 127-141 p.
Keyword [en]
Land cover, Spatial modeling, Paleoecology, Pollen, Compositional data, Gaussian Markov random fields
National Category
Earth and Related Environmental Sciences
Research subject
Environmental Science, Paleoecology
Identifiers
URN: urn:nbn:se:lnu:diva-40090DOI: 10.1016/j.ecocom.2014.09.005ISI: 000348010800013OAI: oai:DiVA.org:lnu-40090DiVA: diva2:788074
Available from: 2015-02-12 Created: 2015-02-12 Last updated: 2016-10-25Bibliographically approved
In thesis
1. Pollen-based quantitative reconstruction of land-cover change in Europe from 11,500 years ago until present - A dataset suitable for climate modelling
Open this publication in new window or tab >>Pollen-based quantitative reconstruction of land-cover change in Europe from 11,500 years ago until present - A dataset suitable for climate modelling
2014 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The major objective of this thesis was to produce descriptions of the land vegetation-cover in Europe for selected time windows of the Holocene (6000, 3000, 500, 200, and 50 calendar years before present (BP=1950)) that can be used in climate modelling. Land vegetation is part of the climate system; its changes influence climate through biogeophysical and biogeochemical processes. Land use such as deforestation is one of the external forcings of climate change.  Reliable descriptions of vegetation cover in the past are needed to study land cover-climate interactions and understand the possible effects of present and future land-use changes on future climate.

We tested and applied the REVEALS (Regional Estimates of VEgetation Abundance from Large Sites) model to estimate past vegetation in percentage cover over Europe using pollen records from lake sediments and peat bogs. The model corrects for the biases of pollen data due to intraspecific differences in pollen productivity and pollen dispersion and deposition in lakes and bogs. For the land-cover reconstructions in Europe and the Baltic Sea catchment we used 636 (grouped by 1˚x1˚ grid cells) and 339 (grouped by biogeographical regions) pollen records, respectively. The REVEALS reconstructions were performed for 25 tree, shrub and herb taxa. The grid-based REVEALS reconstructions were then interpolated using a set of statistical spatial models.

We show that the choice of input parameters for the REVEALS application does not affect the ranking of the REVEALS estimates significantly, except when entomophilous taxa are included. We demonstrate that pollen data from multiple small sites provide REVEALS estimates that are comparable to those obtained with pollen data from large lakes, however with larger error estimates. The distance between the small sites does not influence the results significantly as long as the sites are at a sufficient distance from vegetation zone boundaries. The REVEALS estimates of open land for Europe and the Baltic Sea catchment indicate that the degree of landscape openness during the Holocene was significantly higher than previously interpreted from pollen percentages. The relationship between Pinus and Picea and between evergreen and summer-green taxa may also differ strongly whether it is based on REVEALS percentage cover or pollen percentages. These results provide entirely new insights on Holocene vegetation history and help understanding questions related to resource management by humans and biodiversity in the past. The statistical spatial models provide for the first time pollen-based descriptions of past land cover that can be used in climate modelling and studies of land cover-climate interactions in the past.

Place, publisher, year, edition, pages
Växjö: Linnaeus University Press, 2014
Series
Linnaeus University Dissertations, 193/2014
Keyword
pollen data, REVEALS model, model testing, land vegetation, land-cover, Holocene, Europe
National Category
Climate Research Environmental Sciences
Identifiers
urn:nbn:se:lnu:diva-40775 (URN)978-91-87925-21-4 (ISBN)
Public defence
2014-11-07, Fullriggaren, Langången 2, Kalmar, 09:30 (English)
Opponent
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Available from: 2015-03-11 Created: 2015-03-10 Last updated: 2015-03-11Bibliographically approved

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Trondman, Anna-KariMarquer, LaurentGaillard, Marie-José
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