Relative Pollen Productivity Estimates 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.

Evaluation of relative pollen productivities in temperate China for reliable pollen-based quantitative reconstructions of Holocene plant cover.

The Landscape Reconstruction Algorithm (LRA) is regarded as the soundest 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 model-the first step in the LRA-to evaluate the reliability of RPPs estimates of 10 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 Cichorioideae are slightly overrepresented, and the RVs of all tree taxa are underrepresented 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 (100km and 75km for the entire region and the subregion, respectively), whereas the RVs of all tree taxa are more similar to OBVs collected from longer distances (150km and 100km for the entire region and the subregion, respectively). Furthermore, our findings highlight the importance to test different sizes of area for vegetation surveys for evaluation of the RVs given that the appropriate size of vegetation survey may vary between low pollen producers (mainly herbs) and high pollen producers (mainly trees). We consider that the LOO strategy is the best approach in this case study for evaluating the RPP estimates from surface moss polsters. The evaluation confirms the reliability of the obtained RPP estimates for their potential application in quantitative reconstruction of vegetation abundance in temperate China.

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.

Validation of relative pollen productivities for major tropical plant taxa: An empirical test using the REVEALS model in Hainan, China

The reliability of estimates of tropical lowland vegetation cover based on lacustrine pollen records has long been debated. Here, we assess the reliability of relative pollen productivity estimates (RPPs) obtained in tropical Hainan island using surface pollen assemblages from six reservoirs and the Regional Estimates of Vegetation Abundance from Large Sites (REVEALS) model. The resulting REVEALS estimates are compared to observations of vegetation coverin the studied region and pollen percentages. The REVEALS estimates for most tropical taxa including Poaceae, Moraceae, Euphorbiaceae, Mallotus/Macaranga, Castanopsis/Lithocarpus, were more similar to the observed vegetation cover than estimates based on simple pollen percentages, suggesting that the previously reported RPPs are reliable. The REVEALS estimates for some taxa (i.e. Rubiaceae and Anacardiaceae) are comparable to those based on pollen percentages, but RPPs for these taxa are difficult to evaluate. However, the pollen percentages for some taxa including Asteraceae and Papilionaceae agree better with the observed vegetation cover than the REVEALS corrections, implying either that there are problems with the corresponding RPPs or that there is bias in the observed vegetation data used for validation. We suggest that the reliability of the RPPs for plant taxa in tropical areas depends strongly on their abundance in the pollen and vegetation data: high abundance implies high reliability and vice versa. REVEALS cover estimates for groups of taxa consistently agreed well with observed vegetation cover, suggesting that the REVEALS model can be applied even in tropical regions if individual species are grouped, which may be useful when reconstructing historical landscape changes in tropical Asia.

Pollen-based temporal-spatial land cover reconstruction in North China for the last 6,000 years

Based on 74 fossil pollen records and relative pollen productivity estimates for 29 plant taxa, we produced a quantitative reconstruction of regional vegetation change in North China over the past 6,000 years, using the combined MAT-REVEALS approach. The results include the spatial dynamics of the five main land cover types (Pinus, coniferous trees excluding Pinus, deciduous trees, grassland and bare ground) for three time slices: 6 ka, 3 ka and 0.05 ka. From 6 ka to the present, the total vegetation cover decreased from 64% to 61% (i.e., bare ground increased from 36% to 39%), mainly because of decreases in the cover of deciduous trees (from 19% to 14%). At the same time, the cover of coniferous trees increased (from 10% to 14%), and that of herb plants was largely unchanged (from 34% to 33%). The vegetation cover was greater at high latitudes and altitudes than at lower latitudes and in lowland areas. On the regional scale, temperate coniferous forest with Larix and Betula was dominant in the Greater Khingan Mountains, while in the Changbai Mountains, deciduous forest (decreasing from 72% to 56%) gradually transitioned to coniferous-deciduous mixed forest (Pinus and coniferous trees increased from 1% to 18%). The deciduous forest was dominated by Quercus, Betula and Pinus and occurred mainly in the warm temperate mountains of North China, where the vegetation cover was relatively high before 3 ka (>70%), before decreasing substantially to 55% at 0.05 ka. Grassland with Artemisia and Poaceae was the main land cover type in the North China Plain and in the temperate steppe region where forest vegetation was relatively sparse. The spatial dynamics of the land cover types appear to have been affected by climate change; climatic cooling in the second half of the Holocene led to the southward migration of coniferous trees. At the same time, human activities were likely the cause of the reduction of the regional vegetation cover, especially the tree cover.

Quantitative vegetation reconstruction in the Central North China Plain of the last 3000 years based on the REVEALS model

The North China Plain is a region where the natural vegetation was increasingly influenced by human activities from ∼3000 cal yr B.P. (Zhang et al., 2017; Peng, 2019). We used pollen, charcoal and sediments from the Dacaozhuang Holocene profile in Ningjinpo, central North China Plain, in combination estimates of relative pollen productivity, to quantitatively reconstruct vegetation changes over the last 3000 years using the REVEALS model. Our aims were to study the combined effects of climate change and human activities on the zonal vegetation. The principal findings are as follows. 1) During 3000–2600 cal yr B.P., the study area was strongly influenced by the Yellow River, leading to a complex pollen source area, which is inappropriate for REVEALS models. Since 2600 cal yr B.P., the sediments were mainly supplied by rivers originating in the Taihang Mountains, and the reconstructed tree coverage was generally less than 20%, while that of herbaceous plants such as Artemisia, Poaceae and Asteraceae was more than 50%. This indicates that the study area was predominantly grassland with trees sparsely distributed in the mountains. 2) Crop plants (Poaceae≥35 μm, and Fagopyrum), and the occurrence of synanthropic plants like Brassicaceae and Urtica/Humulus, together with a high sedimentary content of coarse charcoal particles (>100 μm), indicate substantial disturbance of the natural vegetation by human activities from 2600 cal yr B.P. 3) During the Medieval Warm Period (1300–600 cal yr B.P.), the concentration of charcoal and the proportion of synanthropic plants were relatively high, indicating strong human activity. Nevertheless, the proportion of trees, dominated by Pinus and Quercus, was substantially higher (increasing to more than 19%) compared with the previous interval, indicating an increase in forest vegetation and thus a strong climatic influence on the vegetation. 4) During the periods of the Ming and Qing Dynasties (after 500 cal yr B.P.), the concentration of charcoal and crop plants reached a maximum and the tree coverage decreased substantially (to 4.8%), indicating the highest level of human influence on the vegetation. The shift to a cool and dry climate may also have contributed to the reduction of trees within the landscape.

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.

Quantitative reconstruction of the vegetation of the Qinhuangdao area, western coast of Bohai Sea, North China, during the Little Ice Age

It is widely recognized that the climate of the Little Ice Age (LIA) was generally cold. However, there are differences in the climate response of the vegetation in different regions during the LIA, and high-resolution quantitative research is lacking. Here, we present a high-resolution pollen analysis and the Landscape Reconstruction Algorithm (LRA) based on relative pollen productivity, combined with AMS 14C dating, to quantitatively reconstruct the vegetation response to climate and sea level change on the western coast of Bohai Sea. The main findings are as follows: (1) The coverage of the main plant taxa reconstructed using estimates of relative pollen productivity was closer to the actual vegetation conditions than that based on pollen percentages. (2) Since ∼1250 A.D., the study area was occupied by temperate deciduous broadleaved forest, dominated by Quercus, with a smaller proportion of Pinus forest. The regional vegetation types did not change significantly, but the forest cover decreased gradually from ∼60% in the Middle Warm Period (MWP, 1250–1310 A.D.) to ∼40% in the LIA (1310–1610 A.D.), due to the combined influences of climate and human activities. (3) The composition of herbaceous plants changed substantially during the LIA. In the early LIA (1310–1450 A.D.), the climate became cold and dry and the sea level began to fall, resulting in a substantial increase in the proportion of Poaceae (∼10%). In the middle of the LIA (1450–1610 A.D.), the climate became colder and drier, the sea level fell further, and the lagoon shrank. In response, there was an increase in drought and salt-tolerant Chenopodiaceae (∼10%) and Artemisia (∼5%), a substantial increase in Selaginella sinensis supplied by fluvial processes.

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.

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.

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.

Compilation of relative pollen productivity (RPP) estimates and taxonomically harmonised RPP datasets for single continents and Northern Hemisphere extratropics

Abstract. Relative pollen productivity (RPP) estimates are fractionate values, often in relation to Poaceae, that allow vegetation cover to be estimated from pollen counts with the help of models. RPP estimates are especially used in the scientific community in Europe and China, with a few studies in North America. Here we present a comprehensive compilation of available northern hemispheric RPP studies and their results arising from 51 publications with 60 sites and 131 taxa. This compilation allows scientists to identify data gaps in need of further RPP analyses but can also aid them in finding an RPP set for their study region. We also present a taxonomically harmonised, unified RPP dataset for the Northern Hemisphere and subsets for North America (including Greenland), Europe (including arctic Russia), and China, which we generated from the available studies. The unified dataset gives the mean RPP for 55 harmonised taxa as well as fall speeds, which are necessary to reconstruct vegetation cover from pollen counts and RPP values. Data are openly available at https://doi.org/10.1594/PANGAEA.922661 (Wieczorek and Herzschuh, 2020).

Influence of plant coverage and environmental variables on pollen productivities: evidence from northern China

Pollen productivity is a critical parameter in the interpretation of pollen-vegetation relationships, and in the quantitative reconstructions of past vegetation from fossil pollen records. One-year monitoring records were collected for 143 pollen traps in various parts of northern China, together with modern vegetation data. Absolute Pollen Productivity Estimates (APPE) were calculated for 11 taxa using the ratio of pollen influx to plant coverage at each applicable sampling site, in which the plants of the target taxon were present. Relative Pollen Productivity Estimates (RPPE) were calculated for the 11 taxa (taking Poaceae as the reference taxon) at those sites in which each taxon occurred together with Poaceae. Artemisia and Chenopodiaceae were found to have the highest RPPEs and the largest RPPEs ranges, while Pinus and Quercus also had higher RPPEs than Poaceae; Abies, Betula, Larix, Picea and Cyperaceae had relatively low RPPEs. Variations in RPPE between different areas may be explained by variations in climatic conditions, plant coverage and land use practices which might influence plant growing situation. Marked effect that variations in pollen productivity can have on vegetation reconstructions was demonstrated by applying these distinct RPPEs to reconstructions of Holocene vegetation in the Lake Daihai area (northern China), such as a large range of RPPE produces a large range of plant coverage. Variations in RPPEs within a single taxon, related to vegetation coverage and climatic conditions, therefore need to be considered in future vegetation reconstructions.

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 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.

Pollen-based quantitative land-cover reconstruction for northern Asia covering the last 40 ka cal BP

Abstract. We collected the available relative pollen productivity estimates (PPEs) for 27 major pollen taxa from Eurasia and applied them to estimate plant abundances during the last 40 ka cal BP (calibrated thousand years before present) using pollen counts from 203 fossil pollen records in northern Asia (north of 40∘ N). These pollen records were organized into 42 site groups and regional mean plant abundances calculated using the REVEALS (Regional Estimates of Vegetation Abundance from Large Sites) model. Time-series clustering, constrained hierarchical clustering, and detrended canonical correspondence analysis were performed to investigate the regional pattern, time, and strength of vegetation changes, respectively. Reconstructed regional plant functional type (PFT) components for each site group are generally consistent with modern vegetation in that vegetation changes within the regions are characterized by minor changes in the abundance of PFTs rather than by an increase in new PFTs, particularly during the Holocene. We argue that pollen-based REVEALS estimates of plant abundances should be a more reliable reflection of the vegetation as pollen may overestimate the turnover, particularly when a high pollen producer invades areas dominated by low pollen producers. Comparisons with vegetation-independent climate records show that climate change is the primary factor driving land-cover changes at broad spatial and temporal scales. Vegetation changes in certain regions or periods, however, could not be explained by direct climate change, e.g. inland Siberia, where a sharp increase in evergreen conifer tree abundance occurred at ca. 7–8 ka cal BP despite an unchanging climate, potentially reflecting their response to complex climate–permafrost–fire–vegetation interactions and thus a possible long-term lagged climate response.

Novel methods of estimating relative pollen productivity: A key parameter for reconstruction of past land cover from pollen records

Reconstructing land cover from pollen data using mathematical models of the relationship between them has the potential to translate the many thousand pollen records produced over the last 100 years (over 2300 radiocarbon-dated pollen records exist for the UK alone) into formats relevant to ecologists, archaeologists and climate scientists. However, the reliability of these reconstructions depends on model parameters. A key parameter is Relative Pollen Productivity (RPP), usually estimated from empirical data using ‘Extended R Value analysis’ (ERV analysis). Lack of RPP estimates for many regions is currently a major limitation on reconstructing global land cover. We present two alternatives to ERV analysis, the Modified Davis Method and an iteration method, which use the same underlying model of the relationship between pollen and vegetation to estimate RPP from empirical data, but with different assumptions. We test them in simulation against ERV analysis, and use a case study of a problematic empirical dataset to determine whether they have the potential to increase the speed and geographic range of RPP estimation. The two alternative methods are shown to perform at least as well as ERV analysis in simulation. We also present new RPP estimates from southeastern sub-tropical China for nine taxa estimated using the Modified Davis Method. Adding these two methods to the ‘toolkit’ for land cover reconstruction from pollen records opens up the possibility to estimate a key parameter from existing datasets with less field time than using current methods. This can both speed up the inclusion of more of the globe in past land cover mapping exercises such as the PAGES Landcover6k working group and improve our understanding of how this parameter varies within a single taxon and the factors control that variation.

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.