Relative pollen productivities and relevant source area of pollen in the forest–steppe ecotone of northern China

© 2017 Elsevier B.V. Modeling efforts to quantitatively reconstruct vegetation from pollen have never been attempted along the forest–steppe border of China, however such studies are important in interpreting fossil pollen assemblages of vegetation change along this ecotone. In this paper, relative pollen productivity (RPP) and relevant source area of pollen (RSAP) as two important parameters in quantitative vegetation reconstruction using the LRA (Landscape Reconstruction Algorithm approach) model, are estimated from the forest–steppe ecotone north of Shanxi, China, where pollen sampling and vegetation survey were performed at 18 random sample sites. The pollen analysis results show that Artemisia, Asteraceae, Poaceae, Pinus, Picea, Quercus, Betula and Hippophae dominate the pollen assemblages with more than 80% proportion. ERV (Extended R-value) analysis showed that the RSAP is about 600 m and that around 50% of the pollen in each sample comes from beyond this distance. RPP Poaceae (pollen productivity relative to Poaceae) is estimated as more than 10 for Pinus and Hippophae and around 5 for Picea and Betula. Estimates for Artemisia (3–4) are substantially lower than those reported from other studies in the steppe biome, and for Quercus (0.5) are substantially lower than those from the forest biome in north-east China or Europe. Four additional samples were then used to test the effectiveness of two different methods for reconstruction of vegetation proportion from pollen assemblages, the Landscape Reconstruction Algorithm (LRA) and the Modern Analogue Technique (MAT) showed that both methods can give generally reasonable results with similarity index more than 0.6, but there is still some discrepancy between the two methods