Extended R-value Research Articles

Relative Pollen Productivity Estimates for Mediterranean Plant Taxa: A New Study Region in Turkey

This study estimates relative pollen productivity (RPP) for plant taxa from Southern Anatolia, an important region in the Mediterranean with a long history of human settlements. RPP estimates are required for quantitative pollen-based reconstruction of past land cover modelling. The application of the reconstruction by the REVEALS model in the Mediterranean basin is constrained due to the scarcity of the RPP values specific to the region. To better understand the relationship between vegetation cover and land use in the Mediterranean area, the present study aims to provide a set of RPPs for Turkey and the Mediterranean region. The study area centres around Gölhisar Lake in southwestern Turkey. Modern pollen data are collected from moss pollsters from 21 sites together with vegetation surveys. RPP estimates for the main taxa characteristic of the Mediterranean region are obtained (referenced to evergreen Quercus t.) using the extended R-value (ERV) model through the analysis of modern pollen assemblages. The most reliable results are acquired with the ERV sub-model 2 and Prentice’s taxon-specific method (using a Gaussian plume dispersal model) to distance-weighted vegetation data, corresponding to a Relative Source Area of Pollen (RSAP) value of 102 m. RPPs of dominant taxa in the study area are obtained for Quercus coccifera/Fagaceae (1 ± 0), Juniperus/Cupressaceae (0.279 ± 0.001), Fabaceae (0.008 ± 0.000), Pinus/Pinaceae (5.782 ± 0.011), and Poaceae (0.112 ± 0.001) and are comparable with other RPPs obtained in the Mediterranean region.

Relative Pollen Productivity Estimates for Major Plant Taxa in Middle Subtropical China

Relative pollen productivity (RPP) is a key parameter for quantitative reconstruction of past vegetation cover. However, RPP estimates are rarely obtained in the subtropical and tropical regions. In this study, the extended R-value (ERV) model was used to estimate RPP for major plant taxa in the evergreen broadleaved and mixed forests in middle subtropical China based on soil samples and vegetation data from 23 sites. The best result was obtained with the combinations of ERV sub-model 3 and Prentice’s or 1/d vegetation distance-weighting method. The relevant source area of pollen (RSAP) of the soil samples was estimated to be ca. 500 m. RPP on the basis of ERV sub-model 3 and Prentice’s model was obtained for seven taxa and the ranking is as follows: Castanopsis (1 ± 0), Ilex (0.352 ± 0.031), Mallotus (0.221 ± 0.028), Liquidambar (0.115 ± 0.007), Cyclobalanopsis (0.107 ± 0.006), Camelia (0.033 ± 0.001), Symplocos (0.010 ± 0.002). RPPs for Cyclobalanopsis, Camelia, Ilex, and Symplocos which are dominant elements in the subtropical evergreen broadleaved forests were first obtained. Our result demonstrates a significant effect of pollen dispersal models on the estimates of RPPs. The RPPs obtained in this study provide an important basis for quantitative vegetation reconstruction in the subtropical region of China.

Relative pollen productivity estimates for alpine meadow in the Qinghai-Tibet Plateau and their potential significance for paleovegetation reconstruction

Alpine meadow is a common vegetation type in the Qinghai-Tibet Plateau. The Extended R-Value (ERV) model was then used to estimate the Relevant Source Area of Pollen (RSAP) and the RPPs of five major plant taxa in the study area. Log-likelihood curves indicated that the combination of the Prentice-Sugita-Sutton model with sub-model 3 provided the best results, with an estimated RSAP of 1235 m. The RPPs of other plant taxa were lower than for Cyperaceae (=1); the RPPs for Asteraceae and Polygonaceae were similar (0.798 ± 0.162 and 0.772 ± 0.121); and those for Rosaceae (0.182 ± 0.076) and Ranunculaceae (0.084 ± 0.102) were much lower. The leave-one-out method and a comparison of the RPPs with the results of previous studies for the study area demonstrated that our RPPs are stable and credible and can be used as a modern reference for pollen-based paleovegetation reconstruction in the Qinghai-Tibet Plateau.

Modern Pollen Assemblages From Lake Sediments and Soil in East Siberia and Relative Pollen Productivity Estimates for Major Taxa

Modern pollen–vegetation–climate relationships underpin palaeovegetation and palaeoclimate reconstructions from fossil pollen records. East Siberia is an ideal area for investigating the relationships between modern pollen assemblages and near natural vegetation under cold continental climate conditions. Reliable pollen-based quantitative vegetation and climate reconstructions are still scarce due to the limited number of modern pollen datasets. Furthermore, differences in pollen representation of samples from lake sediments and soils are not well understood. Here, we present a new pollen dataset of 48 moss/soil and 24 lake surface-sediment samples collected in Chukotka and central Yakutia in East Siberia. The pollen–vegetation–climate relationships were investigated by ordination analyses. Generally, tundra and taiga vegetation types can be well distinguished in the surface pollen assemblages. Moss/soil and lake samples contain generally similar pollen assemblages as revealed by a Procrustes comparison with some exceptions. Overall, modern pollen assemblages reflect the temperature and precipitation gradients in the study areas as revealed by constrained ordination analysis. We estimate the relative pollen productivity (RPP) of major taxa and the relevant source area of pollen (RSAP) for moss/soil samples from Chukotka and central Yakutia using Extended R-Value (ERV) analysis. The RSAP of the tundra-forest transition area in Chukotka and taiga area in central Yakutia are ca. 1300 and 360 m, respectively. For Chukotka, RPPs relative to both Poaceae and Ericaceae were estimated while RPPs for central Yakutia were relative only to Ericaceae. Relative to Ericaceae (reference taxon, RPP = 1), Larix, Betula, Picea, and Pinus are overrepresented while Alnus, Cyperaceae, Poaceae, and Salix are underrepresented in the pollen spectra. Our estimates are in general agreement with previously published values and provide the basis for reliable quantitative reconstructions of East Siberian vegetation.

Relative pollen productivities of major woody plant taxa in deciduous broadleaved forest in the Ziwuling Mountains of the central Chinese Loess Plateau

Accurate estimates of relative pollen productivity (RPP) values are fundamental to the use of fossil pollen records to quantitatively reconstruct paleovegetation. Based on a pollen dataset from moss polster and related vegetation data for 34 sites in the central part of the Ziwuling Mountains (central Chinese Loess Plateau, with a temperate–warm temperate climate), we estimated the relevant source area of pollen (RSAP) and the RPP values of 8 major woody plant taxa in deciduous broadleaved forest, using the Extended R-Value (ERV) model. The best results were obtained with ERV sub-model 2 and the inverse distance (1/d) method to distance weight the vegetation data. The RSAP was estimated to be 855 m and the rank order of the RPP values for the 8 major woody plant taxa is as follows: Betula (2.083 ± 0.091), Syringa (1.367 ± 0.087), Quercus (1 ± 0, the reference taxon), Pinus (0.791 ± 0.036), Ulmus (0.643 ± 0.062), Carpinus (0.621 ± 0.122), Malus (0.035 ± 0.015), and Acer (0.035 ± 0.025). Repeatability tests using the leave-one-out and K-fold methods showed that the RPP values of all 8 major woody plant taxa have a good reproducibility, which indicates that the RPP values are consistent in the study area. Comparison of the RPP values of the major plant taxa from deciduous broadleaved forest in temperate and warm temperate regions shows that the RPP values for the same pollen taxon may differ significantly between different areas. For example, the RPP for Pinus in areas with dominantly natural vegetation is much lower than for areas where the vegetation has been substantially altered by human activity. We suggest that differences in vegetation/landscape characteristics (including community structure and species composition/abundance) are the major causes of the difference. Therefore, changes in the regional landscape should be considered when choosing suitable RPP values for quantitative paleovegetation reconstruction.

Do Local Habitat Conditions Affect Estimates of Relative Pollen Productivity and Source Area in Heathlands?

Relative Pollen Productivity is an essential parameter for quantitative reconstruction of past land cover from pollen records, but published studies have produced a range of different values for the same taxa. Heathland habitats have limited plant diversity and strong spatial patterning, therefore are useful case studies to investigate aspects of pollen dispersal and deposition, but the estimated spatial area “sensed” by pollen records in these habitats also varies widely between studies. In this study, we estimate pollen productivity from two different microhabitats in a heathland ecosystem in order to investigate the role of local environmental conditions in any observed differences. Vegetation survey was carried out using the Crackles Bequest Project method, pollen assemblages from moss samples counted using standard methods, and relative pollen productivity and estimated source area derived using Extended R-Value analysis. Analysis of the data suggests that at least two pollen source areas exist at the sites studied, reflecting scales of landscape organisation. Microhabitat does not appear to have a marked effect on estimates of Relative Pollen Productivity in this heathland system. This study confirms earlier findings that the estimates obtained for some taxa from heathlands are substantially different than those from agricultural landscapes, especially Poaceae. The findings suggest that the factors controlling Relative Pollen Productivity are still not fully understood, and that differences between locations may reflect real, habitat-led differences. Further investigation of this parameter, which is central to reconstruction of past land cover from pollen records whether overtly incorporated via an algebraic model or less explicitly present via ecological narrative, biomisation or modern analog approaches, is clearly necessary.

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

Pollen productivity estimates (PPEs) are a key parameter for quantitative land-cover reconstructions from pollen data. PPEs are commonly estimated using modern pollen-vegetation data sets and the extended R-value (ERV) model. Prominent discrepancies in the existing studies question the reliability of the approach. We here propose an implementation of the ERV model in the R environment for statistical computing, which allows for simplified application and testing. Using simulated pollen-vegetation data sets, we explore sensitivity of ERV application to (1) number of sites, (2) vegetation structure, (3) basin size, (4) noise in the data, and (5) dispersal model selection. The simulations show that noise in the (pollen) data and dispersal model selection are critical factors in ERV application. Pollen count errors imply prominent PPE errors mainly for taxa with low counts, usually low pollen producers. Applied with an unsuited dispersal model, ERV tends to produce wrong PPEs for additional taxa. In a comparison of the still widely applied Prentice model and a Lagrangian stochastic model (LSM), errors are highest for taxa with high and low fall speed of pollen. The errors reflect the too high influence of fall speed in the Prentice model. ERV studies often use local scale pollen data from for example, moss polsters. Describing pollen dispersal on his local scale is particularly complex due to a range of disturbing factors, including differential release height. Considering the importance of the dispersal model in the approach, and the very large uncertainties in dispersal on short distance, we advise to carry out ERV studies with pollen data from open areas or basins that lack local pollen deposition of the taxa of interest.

Modern pollen-vegetation relationships in the Taihang Mountains: Towards the quantitative reconstruction of land-cover changes in the North China Plain

Pollen-based land cover reconstructions are important for understanding the history of regional environmental responses to natural and anthropogenic factors, and for managing the ecological environment. The vegetation in the mountain landscape of North China has been significantly influenced by human activities, and evaluating the pollen-vegetation relationship for the region is important for reconstructing anthropogenic land-cover changes in the North China Plain. In this study, 35 sampling sites were randomly selected in representative vegetation zones of the Taihang Mountains in North China. Based on a detailed vegetation survey (field work combined with the analysis of remote sensing images), we evaluated the pollen-vegetation relationships in the area. In addition, the relevant pollen source area (RSAP) of the sampling sites and the relative pollen productivity (RPP) of the major plant taxa were estimated using ERV (Extended R-Value) models. The results show that the pollen spectra in the Taihang Mountains reliably reflect the vegetation landscape of different altitudinal zones. The estimated RSAP in the Taihang Mountains is ~ 600 m. Using Poaceae as a reference taxon (RPP = 1), the RPPs of the dominant plant taxa in the Taihang Mountains can be ordered as follows: Pinus > Hippophae > Caryophyllaceae > Betula > Quercus > Rhododendron > Artemisia > Asteraceae > Cyperaceae. Our results suggest the importance and complexity of RPP estimates in the Taihang Mountains, and provide valuable implications for improving the accuracy of reconstructions of land-cover changes in the North China Plain.

Key parameters for landscape evolution and anthropogenisation estimation in the Kamchia River downstream region (Eastern Bulgaria)

Pollen productivity еstimate (PPE) and relevant source area of pollen (RSAP) are critical parameters for quantitative interpretations of pollen data in palaeolandscape and palaeoecological reconstructions, and for analyses of the landscapes evolution and anthropogenisation as well. In light of this, the present paper endeavours to calculate PPE of key plant taxa and to define the RSAP in the Kamchia River Downstream Region (Eastern Bulgaria) in order to use them in landscape simulations and estimations. For the purposes of this research, a dataset of pollen counts from 10 modern pollen samples together with corresponding vegetation data, measured around each sample point in concentric rings, were collected in 2020. Three submodels of the Extended R-Value (ERV) model were used to relate pollen percentages to vegetation composition. Therewith, in order to create a calibrated model, the plant abundance of each pollen type was weighed by distance in GIS environment. The findings led to the conclusion that most of the tree taxa have PPE higher than 1 (ERV3 submodel). Cichoriceae, Fabaceae and Asteraceae have lower PPE.

Relative pollen productivity estimates of savanna taxa from southern Africa and their application to reconstruct shrub encroachment during the last century

To understand the resilience of African savannas to global change, quantitative information on the long-term dynamics of vegetation is required. Past dynamics can be reconstructed with the REVEALS model, which requires pollen productivity estimates (PPE) that are calibrated using surface pollen and vegetation data. Here we calculated PPE values for five savanna taxa using the extended R-value (ERV) model and two pollen dispersal options: the Gaussian plume model (GPM) and the Lagrangian stochastic model (LSM). The ERV calculations failed to produce a reliable PPE for Poaceae. We therefore used Combretaceae as the reference taxon – although values obtained with Poaceae as the reference taxon are presented in the supplement. Our results indicate that Combretaceae is the taxon with the highest pollen productivity and Grewia the taxon with the lowest productivity. Acacia and Dichrostachys are intermediate pollen producers. We find no clear indication of whether the GPM PPEs or the LSM PPEs are more realistic, but the differences between these values confirmed that the pollen fall speed has a greater effect in the modelling of GPM than in the LSM. We also applied REVEALS to the pollen record of Lake Otjikoto (northern Namibia) and obtained the first quantitative reconstruction of the last 130 years of vegetation history in the region. Cover estimates for Poaceae indicate the predominance of a semi-open landscape throughout the 20th century, while cover values below 50% since the 21st century correspond to a thick savanna. This change in grass cover is associated with the spread of Vachellia, Senegalia and Grewia reflecting an encroached state.

Relative pollen productivity estimates of major plant taxa and relevant source area of pollen in the warm-temperate forest landscape of northern China

Relative pollen productivity (RPP) is critical for quantitative vegetation reconstruction of past vegetation cover. The Extended R-value (ERV) model is commonly used for estimating RPP. In this study, we used modern pollen assemblages from 30 randomly selected surface sample sites, and these and vegetation data were applied to an ERV model to estimate pollen productivity of Pinus, Quercus, Corylus, Artemisia, Chenopodiaceae, Asteraceae and Caryophyllaceae relative to Poaceae. Estimates of the relevant source area of pollen (RSAP) was also obtained. Three different ERV sub-models were operated against the data. Sub-model 1 produced the best goodness of fit for the data and the RPP values estimated with this sub-model show that the highest producer among arboreal pollen taxa is Pinus (12.85 ± 1.26) and among the herb pollen taxa is Caryophyllaceae (7.28 ± 0.14). The results of ERV analysis suggest that RSAP in surface samples is ca. 400 m.

Relative pollen productivities of the major plant taxa of subtropical evergreen–deciduous mixed woodland in China

ABSTRACTQuantifying the relationship between pollen and vegetation is an essential step in the pollen‐based quantitative reconstruction of past vegetation cover. In this study, we use the Extended R‐Value (ERV) model and a modern dataset of pollen (collected from moss polsters) and related vegetation from 50 sites in the Daba Mountains (subtropical China) to (i) estimate the relevant source area of pollen (RSAP) of the moss samples and the relative pollen productivities (RPPs) of nine major plant taxa‐characteristic of the region, and (ii) evaluate the obtained RPPs. The RSAP estimates of moss polsters vary between 225 and 610 m depending on the ERV submodels and models of pollen dispersal and deposition used. The RPP estimates are different from values published in previous studies from temperate and subtropical China. This may be explained by differences in methodology, climate and vegetation (species composition and spatial distribution), of which vegetation is probably the most important factor. The ranking of the RPP estimates for the nine taxa is Pinus > Juglandaceae > D − Quercus (deciduous Quercus) > Poaceae > Rosaceae > Cyperaceae > Anacardiaceae > Castanea > Fabaceae. We use a ‘leave‐one‐out’ cross‐validation strategy and the Landscape Reconstruction Algorithm (LRA) for pollen‐based reconstruction of regional and local plant cover to evaluate the ERV model‐based RPP estimates. Both the REVEALS (Regional Estimates of VEgetation Abundance from Large Sites)‐based and the LOVE (LOcal Vegetation Estimates)‐based plant cover using the RPP estimates are closer to the modern vegetation composition than pollen percentages, thus confirming the applicability of the ERV model and the LRA approach in subtropical China.

Evaluating quantitative pollen representation of vegetation in the tropics: A case study on the Hainan Island, tropical China

Complex pollen-vegetation relationships in tropical environments have long been a challenge for the interpretation of pollen spectra in terms of vegetation cover. Here, we test the application of the widely-used Extended R-Value (ERV) model in the tropical secondary and planted woodlands of the Hainan Island (China) to estimate relative pollen productivities (RPPs) for common plant taxa occurring as pollen in surface and fossil samples of the region. We collected pollen (soil samples) and related vegetation data within 1500 m radius at 23 random distributed sites within an area of 50 km × 100 km. We found a large difference between the modern pollen assemblages and the related vegetation composition in terms of number and dominance of taxa. We tested the three existing ERV sub-models and three methods to distance-weight vegetation cover, i.e. 1/d, the Prentice’s model (using a Gaussian Plume dispersal model, GPM), and the Lagrangian stochastic dispersal model (LSM). The LSM appears to be inappropriate for our dataset. The combination of ERV sub-model 2 and Prentice’s model using nine anemophilous and zoophilous (or with “messy” pollination syndrome) taxa was found to provide the best results. The relevant source area of pollen (RSAP) of the soil samples was estimated to ca. 1000–1500 m. The ranking of RPPs is as follows: Castanopsis-Lithocarpus (19.44 ± 0.17) > Asteraceae (8.74 ± 0.05) > Moraceae (6.52 ± 0.08) > Euphorbiaceae (5.22 ± 0.1) > Papilionaceae (2.66 ± 0.05) > Mallotus-Macaranga (2.21 ± 0.08) > Anacardiaceae (1.77 ± 0.04) > Rubiaceae (1.29 ± 0.02) > Poaceae (=1). Violation of the ERV model assumptions of anemophily and stationarity of vegetation composition influenced the performance of the ERV analysis in this study and implied careful evaluation of the results. Nevertheless, the obtained RPPs are considered reliable and will allow to quantify the relative cover of the nine plant taxa in the past. Further studies of this kind will be worthwhile to obtain additional RPP values for a larger number of tropical taxa, even though quantification of past plant cover in the tropics will remain a challenge. The numerous zoophilous taxa may either be absent of the pollen record, or exhibit pollen-vegetation relationships for which the ERV-model is not successful in estimating RPPs. These plant taxa will require other approaches for their quantification in the past.

Relative pollen productivity estimates for alpine meadow vegetation, northeastern Tibetan Plateau

A promising method of reconstructing past vegetation from pollen records uses mathematical models of the relationship between pollen and vegetation. These can be calibrated using the extended R-value (ERV) approach on datasets of modern pollen assemblages and related vegetation surveys. This study presents the results of calibrating the pollen-vegetation models for non-arboreal pollen types in alpine meadow habitats on the Tibetan Plateau. Surface soil samples were analysed for pollen and the surrounding vegetation was recorded at 30 randomly located sites in the Zoige basin, northeastern Tibetan Plateau. ERV analysis found that the most reliable results were obtained when using ERV sub-models 1 and 2, and distance-weighting the vegetation data by applying the taxon-specific Prentice–Sutton method. The relevant source area of pollen for these soil samples was found to be ca. 200 m. Relative pollen productivities (RPP) of 15 non-arboreal taxa were estimated relative to Cyperaceae (RPPCyp). The taxa can be divided into three groups according to their RPPs, those with high RPPCyp values > 1.68 (Thalictrum, Artemisia, Caryophyllaceae, Chenopodiaceae and Plantago), those with moderate values (0.42–0.62) (Taraxacum-type, Apiaceae, Polygonum and Aster-type), and those with low values < 0.4 (Gentianaceae, Potentilla, Brassicaceae, Saussurea-type and Poaceae). The RPP values obtained from our study differ from those of previous studies in other parts of China, and form the basis for future reconstruction of palaeovegetation on the Tibetan Plateau through model-based methods, such as the Landscape Reconstruction Algorithm, or Multiple Scenario Approach.

Relative pollen productivity estimates for vegetation reconstruction in central-eastern Europe inferred at local and regional scales

Understanding pollen-vegetation relationships is crucial for accurate land-cover and climate reconstructions, yet important parameters for quantifying past vegetation abundance are mostly unknown for large parts of Europe harbouring temperate thermophilous ecosystems. We collected pollen and vegetation data in central-eastern Europe, a region covered by patchy cultural landscapes of high biodiversity to estimate relative pollen productivity (RPP) for important pollen-equivalent taxa. Our study area was situated in the south-western part of the White Carpathians (Czechia–Slovakia borderland), where we collected 40 modern moss pollen samples scattered over 250 km2 and mapped vegetation within 100 m around each pollen site. Additional vegetation data were compiled from Forest management plans, Natura 2000 habitat mapping and floristic inventories over the entire area. We calculated RPP (referenced to Poaceae) by testing two approaches: the extended R-value (ERV) model by estimating relevant source area of pollen and the REVEALS-based productivity using regional scale vegetation estimates. Two models were applied to depict pollen dispersal: Lagrangian stochastic and the Gaussian plume (Prentice) models. We estimated RPP for 16 taxa using the ERV model and an additional nine taxa using REVEALS. Both approaches found Plantago lanceolata-type to be a high pollen producer, Quercus medium-to-high, Asteraceae subf. Cichorioideae, Anthemis-type, Ranunculus acris-type and Rubiaceae low-to-medium and Brassicaceae and Senecio-type as low pollen producers. Results for other, mainly tree taxa, significantly differed in both approaches mainly due to largely uneven representation in both local and regional vegetation. In comparison with other studies, our data demonstrate a high variability in the estimated RPPs which could be influenced by climatic conditions or potentially vegetation structure. We suggest that the accuracy of RPP estimates could be enhanced by comparing modern pollen data with large-scale vegetation data in the future.

Relative pollen productivity estimates and changes in Holocene vegetation cover in the deciduous forest of southeastern Quebec, Canada

The Regional Estimates of VEgetation Abundance from Large Sites (REVEALS) model was used to quantify Holocene changes in vegetation cover in the deciduous forest of southeastern Quebec, Canada. The Extended R-Value (ERV) model was used to obtain relative pollen productivity estimates (PPEs) for eight tree taxa and to determine the relevant source area of pollen (RSAP) for lakes in this ecosystem. Modern vegetation was estimated using pollen data from 16 small (&lt;0.5 km2) lakes and a species-level vegetation survey of southern Quebec. The RSAP was estimated to be within 1600 m of the lakes. Tsuga, Fagus, and Quercus were the most productive taxa, and Populus and Acer were the lowest. Reconstructed changes in absolute vegetation cover show a high abundance of Picea followed by Populus in the early Holocene. The reconstructed values for Populus suggest that it was widely distributed across the landscape. Abies and Acer were dominant on the landscape during the late to mid-Holocene, and an increase in Picea during the Neoglacial is more significant than in percentage diagrams. The REVEALS results provide estimates of land-cover change that are more realistic and informative than the use of pollen percentages alone.

Relative pollen productivity estimates for major plant taxa of cultural landscapes in central eastern China

In this study we estimate relative pollen productivity (RPP) for plant taxa characteristic of human-induced vegetation in ancient cultural landscapes of the low mountain ranges of Shandong province in eastern temperate China. RPP estimates are required to achieve pollen-based reconstructions of Holocene plant cover using modelling approaches based on Prentice’s and Sugita’s theoretical background and models (REVEALS and LOVE). Pollen counts in moss samples and vegetation data from 36 sites were used in the Extended R-Value (ERV) model to estimate the relevant source area of pollen (RSAP) of moss polsters and RPP of major plant taxa. The best results were obtained with the ERV sub-model 3 and Prentice’s taxon-specific method (using a Gaussian Plume dispersal model) to distance weight vegetation data. RSAP was estimated to 145 m using the maximum likelihood method. RPP was obtained for 18 taxa of which two taxa had unreliable RPP (Amaranthaceae/Chenopodiaceae and Vitex negundo). RPPs for Castanea, Cupressaceae, Robinia/Sophora, Aster/Anthemis-type, Cannabis/Humulus, Caryophyllaceae, Brassicaceae and Galium-type are the first ones for China. Trees, except Robinia/Sophora (RPP = 0.78 ± 0.03) have larger RPPs than herbs other than Artemisia (RPP = 24.7 ± 0.36). The RPPs for Quercus, Pinus and Artemisia are comparable with other RPPs obtained in China, the RPPs for Pinus, Quercus, Ulmus, Cyperaceae and Galium-type with the mean RPPs obtained in Europe, and RPP for Cupressaceae with that for Juniperus in Europe. The values for Aster/Anthemis-type, Caryophyllaceae, Asteraceae SF Cichorioideae and Juglans differ from the few RPPs available in China and/or Europe.

More reliable pollen productivity estimates and relative source area of pollen in a forest-steppe ecotone with improved vegetation survey

Pollen productivity estimates (PPEs) and the relevant source area of pollen (RSAP) are critical to the reconstruction of past plant abundances. Extended R-value (ERV) models are commonly used for developing PPEs and estimating the RSAP. In this study, in the forest-steppe ecotone of northern China that is sensitive to climate change and significant in vegetation openness reconstruction, pollen data from surface sediment samples of 24 lakes and high-resolution data of vegetation within the lake basins were applied to ERV models to calculate the PPEs of Pinus, Quercus, Betula, Ulmus, Poaceae, Artemisia, Chenopodiaceae, Compositae, and Cyperaceae and the RSAP of different lake sizes. The PPEs of arboreal pollen were higher than herbaceous pollen, and Chenopodiaceae had the highest productivity of herbaceous pollen taxa. The RSAP of lakes with an average lake radius of 400 m was estimated to be 1600 m. Our results suggested that PPEs and RSAP are region specific and that RSAP is also lake size specific even within the same region. Although environmental factors and imperfections in the ERV models may affect the accuracy of results, our study emphasized that a systematic vegetation survey considering zonal and azonal vegetation, the forest and steppe mosaic, and the vertical vegetation belt can help improve the PPEs and RSAP in areas with complicated vegetation distribution, such as the forest-steppe ecotone.

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

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 600m and that around 50% of the pollen in each sample comes from beyond this distance. RPPPoaceae (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.

Relative pollen productivity estimates for common taxa of the northern Siberian Arctic

Pollen productivity estimates (PPE) are used to quantitatively reconstruct variations in vegetation within a specific distance of the sampled pollen archive. Here, for the first time, PPEs from Siberia are presented. The study area (Khatanga region, Krasnoyarsk territory, Russia) is located in the Siberian Sub-arctic where Larix is the sole forest-line forming tree taxon. Pollen spectra from two different sedimentary environments, namely terrestrial mosses (n=16) and lakes (n=15, median radius~100m) and their surrounding vegetation were investigated to extract PPEs. Our results indicate some differences in pollen spectra between moss and lake pollen. Larix and Cyperaceae for example obtained higher representation in the lacustrine than in terrestrial moss samples. This highlights that in calibration studies, modern and fossil datasets should use archives of similar sedimentary origin. Results of an Extended R-Value model were applied to assess the relevant source area of pollen (RSAP) and to calculate the PPEs for both datasets. As expected, the RSAP of the moss samples was very small (about 10m) compared to the lacustrine samples (about 25km). Calculation of PPEs for the six most common taxa yielded generally similar results for both datasets. Relative to Poaceae (reference taxon, PPE=1) Betula nana-type (PPEmoss: 1.8, PPElake: 1.8) and Alnus fruticosa-type (PPEmoss:6.4, PPElake:2.9) were overrepresented while Cyperaceae (PPEmoss:0.5, PPElake:0.1), Ericaceae (PPEmoss: 0.3, PPElake<0.01), Salix (PPEmoss:0.03, PPElake<00.1) and Larix (PPEmoss: <0.01, PPElake:0.2) were under-represented in the pollen spectra compared to the vegetation in the RSAP. The estimation for the dominant tree in the region, Larix gmelinii, is the first published result for this species, but needs to be considered very preliminary. The inferred sequence from over- to under-representation is mostly consistent with results from Europe; however, the absolute values show some differences. Gathering vegetation data was limited by the remoteness of our study area and a lack of high-resolute satellite imagery and vegetation maps. Our estimate may serve as a first reference to strengthen future vegetation reconstructions in this climate-sensitive region.