Evaluation of relative pollen productivities in temperate China for reliable pollen-based quantitative reconstructions of Holocene plant cover - Li, Furong; Gaillard, Marie-José; Xie, Siqi; Huang, Kangyou; Cui, Qiaoyu; Fyfe, Ralph; Marquer, Laurent; Sugita, Shinya (Frontiers in Plant Science, 2023)
The Landscape Reconstruction Algorithm (LRA) is regarded as the most rigorous approach for quantifying taxon-specific plant cover from pollen data. The reliability of relative pollen productivity (RPP) estimates is fundamental in the accuracy of quantitative vegetation reconstruction using the LRA approach. Inconsistent RPP estimates produced by different studies can cast doubt on the reliability and applicability of quantitative vegetation reconstruction. Therefore, it is crucial that the RPP estimates are evaluated before being applied for quantitative vegetation reconstruction. We have tested two alternative approaches, namely a leave-one-out cross-validation (LOO) method, and a splitting-by-subregion strategy, using surface pollen assemblages and the REVEALS modelthe first step of the LRAto evaluate the reliability of RPPs estimates of ten target taxa obtained in the cultural landscape of Shandong. We compared the REVEALS estimates (RVs) with observations of regional vegetation abundance (OBVs) and pollen proportions (PPs). The RVs of all taxa are generally closer to OBVs than PPs and the degree of similarity depends strongly on the abundance of individual taxa in plant and pollen, taxa dominant in the region show the highest similarity between RVs and OBVs, such as Artemisia, Poaceae, and Humulus. The RVs of all herb taxa except Humulus and Asteraceae SF Cichorium, are slightly over-represented, and the RVs of all tree taxa are under-represented except for Castanea. The comparison of RVs with OBVs collected from different spatial extents shows that the RVs of all herb taxa are more similar to OBVs collected from shorter distances, while the RVs of all tree taxa are more similar to OBVs collected from longer distances. Furthermore, our findings point to the importance of collecting adequate temporal and spatial resolution vegetation survey data from various distances in evaluating the RVs, and that the spatial representation of the REVEALS model is strongly related to the characteristics of taxa, and size of the deposition basin. We consider the LOO strategy is the better approach for evaluating the RPP estimates from surface moss polsters. We confirm the reliability of the obtained RPP estimates for their potential applications in the quantitative reconstruction of vegetation abundance in temperate China.