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From pollen percentage to vegetation cover: evaluation of the Landscape Reconstruction Algorithm in western Norway
Author(s) -
HJELLE KARI LOE,
MEHL INGVILD KRISTINE,
SUGITA SHINYA,
ANDERSEN GIDSKE LEKNÆS
Publication year - 2015
Publication title -
journal of quaternary science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.142
H-Index - 94
eISSN - 1099-1417
pISSN - 0267-8179
DOI - 10.1002/jqs.2769
Subject(s) - pollen , vegetation (pathology) , abundance (ecology) , physical geography , land cover , vegetation cover , geography , geology , ecology , land use , biology , medicine , pathology
The Landscape Reconstruction Algorithm (LRA) with the two models REVEALS and LOVE is developed to transform pollen percentage data to vegetation cover. This paper presents the first study to evaluate LRA in a region with large topographic variations within a short distances. The REVEALS model estimates regional vegetation abundance based on pollen assemblages from large lakes (100–500 ha). Pollen surface samples from one large and 28 small lakes are used together with a combination of regionally derived pollen productivity estimates and available estimates from other regions of Europe. The results show a good relationship between REVEALS‐estimated forest cover and vegetation abundance based on the CORINE land‐cover data. The REVEALS results using various sets of pollen assemblages from small lakes were comparable to those using one large lake. Local vegetation abundance using the LOVE model was estimated around 26 lakes. For common taxa, such as Pinus and Poaceae, the LOVE‐based estimates of plant abundance match well with the distance‐weighted plant abundances based on vegetation maps. Our results indicate that the LRA approach is effective for reconstruction of long‐term vegetation changes in western Norway and other regions with high topographic relief when no major gradients exist in the pollen data.