From pollen percentage to vegetation cover: evaluation of the Landscape Reconstruction Algorithm in western Norway

Abstract

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 LOVEbased 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.

Long‐term changes in regional vegetation cover along the west coast of southern Norway: The importance of human impact

“…Twenty‐three mainly wind‐pollinated taxa (Appendix ) were selected for analysis. Pollen productivity estimates – important input parameters to REVEALS – for 19 of these have been evaluated against vegetation maps from western Norway (Hjelle et al., ). We present cover estimates of Plantago lanceolata , cereals (pollen productivity separated into Cerealia ( Avena , Hordeum and Triticum types) and Secale ), Calluna and Poaceae separately, whereas cover estimates for individual tree and shrub taxa were combined into tree cover, forest (trees and shrubs) cover and thermophilous tree cover.…”

“…This study aims to demonstrate overall trends in the plant cover of the region by applying the REVEALS model (Regional Estimates of VEgetation Abundance from Large Sites; Sugita, ) – the first step of the LRA – for reconstruction of regional vegetation within a 50–100‐km radius of pollen sites. REVEALS has been evaluated (e.g., Hellman, Gaillard, Broström, & Sugita, ; Sugita, Parshall, Calcote, & Walker, ; Soepboer, Sugita, & Lotter, ; Abraham, Oušková, & Kuneš, ; Hjelle, Mehl, Sugita, & Andersen, ) with encouraging results. Regional vegetation has been estimated using REVEALS (e.g., Fyfe et al., ; Marquer et al., ; Kuneš et al., ; Mehl & Hjelle, ), and all papers point to more open vegetation during the Holocene, than indicated by pollen percentages.…”

Quantified moorland vegetation and assessment of the role of burning over the past five millennia

“…Developments in understanding the pollen–vegetation relationship have resulted in improved approaches to the quantification of vegetation cov es and resulted in the Landscape Reconstruction Algorithm (LRA; Sugita, ,b). Much effort has gone into the parameterization of this new approach (Broström et al., ; Mazier et al., ), and it is now possible to estimate the relative abundance of key taxa around pollen sites separate from the ‘background’ vegetation (Cui et al., ; Hjelle et al, ; Trondman et al., ). Where networks of pollen sites exist, it is possible to generate spatially explicit, quantified past vegetation abundances using pollen count data.…”

From deciduous forest to open landscape: application of new approaches to help understand cultural landscape development in western Norway

“…The Landscape Reconstruction Algorithm (LRA) is an approach developed to deal with the challenges-differences in pollen production and dispersal between species-and convert pollen percentages into vegetation cover (Sugita 2007a, b). So far, estimates achieved from this approach are found to be representative of the vegetation in Denmark, Switzerland, Sweden, Estonia and Norway (Hellman et al 2008;Nielsen and Odgaard 2010;Soepboer et al 2010;Fredh 2012;Cui et al 2013;Overballe-Petersen et al 2013;Poska et al 2014;Hjelle et al 2015), and it has been applied to reconstruct vegetation cover on different spatial scales (e.g. Nielsen et al 2012;Fyfe et al 2013;Cui et al 2014;Marquer et al 2014;Hultberg et al 2015;Trondman et al 2015).…”