Reply to Theuerkauf and Couwenberg (2020) comment on: “Pollen-based reconstruction of Holocene land-cover in mountain regions: Evaluation of the Landscape Reconstruction Algorithm in the Vicdessos valley, northern Pyrenees, France”

Abstract

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Pollen productivity estimates strongly depend on assumed pollen dispersal II: Extending the ERV model

“…The suitability of the Kuparinen LSM for local-scale ERV studies needs further evaluation, for example by re-analysis of existing ERV studies (cf. Marquer et al, 2020; Theuerkauf and Couwenberg, 2020).…”

Middle to late Holocene plant cover variation in relation to climate, fire, and human activity in the Songnen grasslands of northeastern China

“…Note that a Gaussian Plume Model (GPM) was used as a dispersal model scheme as no RPP values based on other dispersal modelling schemes are available so far. Pros and cons of using a GPM model for the REVEALS runs can be found in Marquer et al (2020). Finally, four Z max distances were selected for these scenarios: 10, 20, 50, and 100 km.…”

“…Fourth, pollen data are discussed in terms of pollen proportion and no modelling schemes have been applied to correct the inter-taxonomic differences in production, dispersal, and deposition of pollen. This means that plants characterized by high pollen productivities and high transportation abilities are overestimated in the pollen proportion compared to the "real" vegetation (e.g., Sugita, 1994;Xu et al, 2007;Gaillard et al, 2008;Marquer et al, 2014;Marquer et al, 2020). To reduce the uncertainties associated with this fourth issue, the temporal resolution of the pollen archives must be improved and pollen-based vegetation modelling approaches should be performed to consider the production, dispersal, and d e p o s i t i o n o f t h e d i ff e r e n t p o l l e n t y p e s i n t h e vegetation reconstructions.…”

Spatial and temporal patterns of upland vegetation over the last 200 years in the northern pyrenees: Example from the Bassiès valley, Ariège, France

“…Thus the overestimation caused by the mountain site sampling bias is amplified when sites locally record high proportions of arboreal pollen due to their geographical proximity to tree stands. The use of a Lagrangian Stochastic Model (LSM) as pollen dispersal scheme (Kuparinen et al, n.d.;Theuerkauf et al, 2016Theuerkauf et al, , 2013 instead of a GPM could help pollen-based mountain vegetation reconstructions, but more work needs to be done before the LSM scheme can be adopted (Marquer et al, 2020b). Overall, the LRA approach is a significant improvement in pollen-based mountain vegetation reconstruction at the local-and landscape-scales over pollen percentages alone as it reduces the overestimation of broadleaved and pine forests.…”