Search

Establishing a quantitative relationship between modern pollen and vegetation remains a pivotal but intricate pursuit within the field of Quaternary palynology. The R-value, a well-established and traditional metric characterized by its simplicity and direct applicability, serves to calibrate the nonlinear disparities between surface pollen and modern vegetation. This study entails the construction of a comprehensive pollen R-value dataset for China derived from R-values published between 1987 and 2021. The dataset, compiled after rigorous screening, calibration, and standardization processes, encompasses 898 modern pollen sampling sites and 2115 pollen R-value data entries, encapsulating 152 pollen taxa spanning 65 families and 113 genera. Synthesizing the extracted R-values yielded the following insights: (1) A macrospatial analysis validates previously established knowledge at a site-specific scale. Evidently, pollen R-value variations across China are statistically significant. Approximately two-thirds of pollen taxa exhibit underrepresentation (e.g., Taxodiaceae, Corylus, Nitraria, Tamarix, Cyperaceae, Poaceae, and Fabaceae), while the remaining one-third display overrepresentation (e.g., Pinus, Picea, Betula, Ephedra, Chenopodiaceae, and Artemisia). The degree of underrepresentation surpasses that of over-representation, and the representation patterns of Castanea, Quercus, Polygonaceae, and Asteraceae are contingent upon vegetation types. (2) Pollen R-values follow distinct spatial distribution patterns within China. In the woody vegetation region of eastern China, R-values progressively decline from north to south, correlating with rising temperatures and precipitation. Conversely, in herbaceous vegetation regions of northern and western China, R-values decrease from east to west and from northeast to southwest, corresponding to increased aridity. Nevertheless, pollen R-values manifest variation contingent on pollen taxa, vegetation types, and climatic regions, even differing for the same taxa across varying vegetation types and climatic conditions. This highlights the intricate nature of pollen R-values and their interpretation of pollen-vegetation relationships. (3) Pollen R-values and relative pollen production estimates exhibit resemblances and a modest positive correlation. However, adjudicating between them as representatives of vegetation requires nuanced consideration, as both metrics convey pollen representation within vegetation, demonstrating the multifaceted relationships they share with modern vegetation. Further recommendations suggest that when assessing pollen representation in modern vegetation, fossil pollen content should be weighted using either the median or log-transformed R-value. This approach underscores the necessity of comprehensively accounting for divergences and convergences across various spatial scales and vegetation types, particularly the disparities observed within identical pollen taxa across dissimilar regions. [ABSTRACT FROM AUTHOR]

Benefiting from the rapid development of environmental DNA (eDNA) technologies, sedimentary DNA (sedDNA) emerges as a promising tool for monitoring plant compositions in remote regions. The Tibetan Plateau (TP), renowned for its harsh environment and numerous ponds and lakes, presents a potentially demanding region for the application of sedDNA on vegetation investigations. Here, we used the g and h universal primers for the P6 loop region of the chloroplast trnL (UAA) intron to amplify plant DNA in surface sediments from 59 ponds and small lakes on the southwestern TP. The applicability and limitations of using plant DNA metabarcoding for modern vegetation monitoring and palaeo-vegetation reconstructions have been assessed by comparing sedDNA, pollen, and vegetation survey data. Our results showed that plant DNA metabarcoding recorded 186 terrestrial taxa, of which 30.1% can be identified at the species level. The plant sedDNA approach can effectively disclose the dominant plant taxa (including Asteraceae, Cyperaceae and Poaceae) and significant vegetation assemblages in the vicinity of the investigated sites. The number of taxa and taxonomic resolution of plant sedDNA exceeded that of pollen analysis (75 taxa detected, 5.3% can be identified at species level). Unlike pollen that retains a broad spectrum of regional plant signals (including Pinus and Artemisia), plant sedDNA mirrors very local plants, underscoring its utility in local vegetation monitoring and reconstructions. To conclude, plant DNA metabarcoding of (small) lake sediments warrant increased attention in the future for local vegetation monitoring and reconstructions on the TP. [ABSTRACT FROM AUTHOR]