Evaluating the effect of flowering age and forest structure on pollen productivity estimates

Abstract

Pollen productivity estimates (PPEs) are indispensable prerequisites for quantitative vegetation reconstructions. Estimates from different European regions show a large variability and it is uncertain whether this reflects regional differences in climate and soil or is brought about by different assessments of vegetation abundance. Forests represent a particular problem as they consist of several layers of vegetation and many tree species only start producing pollen after they have attained ages of several decades. Here we used detailed forest inventory data from north-eastern Germany to investigate the effect of flowering age and understory trees on PPEs. Pollen counts were obtained from 49 small to medium sized lakes chosen to represent the different forest types in the region. Surface samples from lakes within a closed forest of Fagus yielded disproportionate amounts of Fagus pollen, increasing its PPE and the variability of all other estimates. These samples were removed from further analysis but indicate a high trunk-space component that is not considered in the Prentice-Sugita pollen dispersal and deposition model. Results of the restricted dataset show important differences in PPEs based on the consideration of flowering age and understory position. The effect is largest for slow growing and/or late flowering trees like Fagus and Carpinus while it is minimal for species that flower early in their development like Betula and Alnus. The large relevant source area of pollen (RSAP) of 7 km obtained in this study is consistent with the landscape structure of the region.

Two hundred years of land-use change in the South Swedish Uplands: comparison of historical map-based estimates with a pollen-based reconstruction using the landscape reconstruction algorithm

“…Underestimation of the LRAbased woodland relative to the orthophoto-based cover around Å bodasjön may be caused partially by young plantations of trees that do not produce pollen in great quantity. Matthias et al (2012) show that Picea and Pinus reach their flowering age at 40 and 20 years, respectively. Therefore a young plantation will not produce much pollen while it will appear like a dense forest on an aerial photograph Local land-use dynamics for the last 200 years around two lakes This section integrates the LRA-based estimates of landuse changes and the historical development of the social, economic and technological aspects of the local communities to discuss the land-use dynamics around Å bodasjön and Lindhultsgöl (Fig.…”

Palynological perspectives on vegetation survey: a critical step for model-based reconstruction of Quaternary land cover

“…Management of the local environment may alter pollen production. For example, grassland managed by grazing is likely to produce less Poaceae pollen than grassland managed as hay meadow, and the age structure of a managed forest affects the proportion of trees which have reached flowering age and thus produce pollen (Matthias et al, 2012). Differences in pollen production may also be driven by variations in local climate across Europe, either by direct climatic effects on flowering or through genotypic variation.…”

“…Andersen, 1970;Hjelle, 1998;Broström et al, 2004;Mazier et al, 2008;von Stedingk et al, 2008) or lake surface sediments (e.g. Soepboer et al, 2007;Poska et al, 2011;Hjelle and Sugita, 2012;Matthias et al, 2012). Collection of surrounding vegetation data will necessarily differ between the use of traps/moss polsters and lake sediments, and the methodology selected in the present paper is based on the use of surface moss samples for pollen collection.…”

Replicability of data collected for empirical estimation of relative pollen productivity

“…Lake surface sediment samples are another option (e.g. Soepboer et al, 2007;Poska et al, 2011;Hjelle and Sugita, 2012;Matthias et al, 2012). However, pollen taphonomy in lake sediments is not fully understood, and because lakes have larger pollen source areas than moss polsters (e.g.…”

“…Sugita et al, 2010;Mazier et al, 2012), or lake surface sediments (e.g. Soepboer et al, 2007;Poska et al, 2011;Hjelle and Sugita, 2012;Matthias et al, 2012) with the vegetation around the sampling point. The studies reviewed by Broström et al (2008) used different methods of vegetation survey so it is unclear whether the assumption of constant RPP is in error or whether different methods lead to systematically different values.…”