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Treeline identification from pollen data: beyond the limit?

Treeline identification from pollen data: beyond the limit?
Treeline identification from pollen data: beyond the limit?
Aim The boreal tree line is a prominent biogeographic feature, the position of which reflects climatic conditions. Pollen is the key sensor used to reconstruct past tree line patterns. Our aims in this study were to investigate pollen– vegetation relationships at the boreal tree line and to assess the success of a modified version of the biomization method that incorporates pollen productivity and dispersal in distinguishing the tree line.
Location Northern Canada (307 sites) and Alaska (316 sites).
Methods The REVEALS method for estimating regional vegetation composition from pollen data was simplified to provide correction factors to account for differential production and dispersal of pollen among taxa. The REVEALS-based correction factors were used to adapt the biomization method and applied as a set of experiments to pollen data from lake sediments and moss polsters from the boreal tree line. Proportions of forest and tundra predicted from modern pollen samples along two longitudinal transects were compared with those derived from a vegetation map by: (1) a tally of ‘correct’ versus ‘incorrect’ assignments using vegetation in the relevant map pixels, and (2) a comparison of the shape and position of north–south forest-cover curves generated from all transect pixels and from pollen data. Possible causes of bias in the misclassifications were assessed.
Results Correcting for pollen productivity alone gave fewest misclassifications and the closest estimate of the modern mapped tree line position (Canada, + 300 km; Alaska, + 10 km). In Canada success rates were c. 40–70% and all experiments over-predicted forest cover. Most corrections improved results over uncorrected biomization; using only lakes improved success rates to c. 80%. In Alaska success rates were 70–80% and classification errors were more evenly distributed; there was little improvement over uncorrected biomization.
Main conclusions Corrected biomization should improve broad-scale reconstructions of spatial patterns in forest/non-forest vegetation mosaics and across climate-sensitive ecotones. The Canadian example shows this is particularly the case in regions affected by taxa with extremely high pollen productivity (such as Pinus). Improved representation of actual vegetation distribution is most likely if pollen data from lake sediments are used because the REVEALS algorithm is based on the pollen dynamics of lake-based systems.
0305-0270
1792-1806
Binney, Heather A.
6e994c91-6de7-4a8d-8f50-babf146c8691
Gething, Peter W.
6afb7d8c-8816-4c03-ae73-55951c8b197f
Nield, Joanna M.
173be2c5-b953-481a-abc4-c095e5e4b790
Sugita, S
fff2625b-84d7-4843-9225-ecc6f34084ca
Edwards, Mary E.
4b6a3389-f3a4-4933-b8fd-acdfef72200e
Binney, Heather A.
6e994c91-6de7-4a8d-8f50-babf146c8691
Gething, Peter W.
6afb7d8c-8816-4c03-ae73-55951c8b197f
Nield, Joanna M.
173be2c5-b953-481a-abc4-c095e5e4b790
Sugita, S
fff2625b-84d7-4843-9225-ecc6f34084ca
Edwards, Mary E.
4b6a3389-f3a4-4933-b8fd-acdfef72200e

Binney, Heather A., Gething, Peter W., Nield, Joanna M., Sugita, S and Edwards, Mary E. (2011) Treeline identification from pollen data: beyond the limit? Journal of Biogeography, 38 (9), 1792-1806. (doi:10.1111/j.1365-2699.2011.02507.x).

Record type: Article

Abstract

Aim The boreal tree line is a prominent biogeographic feature, the position of which reflects climatic conditions. Pollen is the key sensor used to reconstruct past tree line patterns. Our aims in this study were to investigate pollen– vegetation relationships at the boreal tree line and to assess the success of a modified version of the biomization method that incorporates pollen productivity and dispersal in distinguishing the tree line.
Location Northern Canada (307 sites) and Alaska (316 sites).
Methods The REVEALS method for estimating regional vegetation composition from pollen data was simplified to provide correction factors to account for differential production and dispersal of pollen among taxa. The REVEALS-based correction factors were used to adapt the biomization method and applied as a set of experiments to pollen data from lake sediments and moss polsters from the boreal tree line. Proportions of forest and tundra predicted from modern pollen samples along two longitudinal transects were compared with those derived from a vegetation map by: (1) a tally of ‘correct’ versus ‘incorrect’ assignments using vegetation in the relevant map pixels, and (2) a comparison of the shape and position of north–south forest-cover curves generated from all transect pixels and from pollen data. Possible causes of bias in the misclassifications were assessed.
Results Correcting for pollen productivity alone gave fewest misclassifications and the closest estimate of the modern mapped tree line position (Canada, + 300 km; Alaska, + 10 km). In Canada success rates were c. 40–70% and all experiments over-predicted forest cover. Most corrections improved results over uncorrected biomization; using only lakes improved success rates to c. 80%. In Alaska success rates were 70–80% and classification errors were more evenly distributed; there was little improvement over uncorrected biomization.
Main conclusions Corrected biomization should improve broad-scale reconstructions of spatial patterns in forest/non-forest vegetation mosaics and across climate-sensitive ecotones. The Canadian example shows this is particularly the case in regions affected by taxa with extremely high pollen productivity (such as Pinus). Improved representation of actual vegetation distribution is most likely if pollen data from lake sediments are used because the REVEALS algorithm is based on the pollen dynamics of lake-based systems.

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More information

Published date: September 2011
Organisations: Geography & Environment

Identifiers

Local EPrints ID: 197231
URI: https://eprints.soton.ac.uk/id/eprint/197231
ISSN: 0305-0270
PURE UUID: 114696f4-208c-4eab-9ad8-8c44fda690fa
ORCID for Joanna M. Nield: ORCID iD orcid.org/0000-0002-2657-0525
ORCID for Mary E. Edwards: ORCID iD orcid.org/0000-0002-3490-6682

Catalogue record

Date deposited: 20 Sep 2011 14:56
Last modified: 19 Jun 2018 00:34

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