Pollen Productivity Estimates Research Articles

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.

Spatially explicit, quantitative reconstruction of past vegetation based on pollen or charcoal data as a tool for autecology of trees

ContextThe determination of autecological preferences based on long-term vegetation dynamics is hampered by the lack of realistic estimates for past occurrence and abundance patterns. Palaeoecological record has still rather character of points than spatially continuous maps.ObjectivesTo infer long-term autecological preferences of trees from reconstructed vegetation. Compare reconstructions based on pollen and charcoals.MethodsWe employed to the regional training set of 58 sites the Extended Downscaling Approach (EDA) using nine topographic factors clustered in 8 habitat classes, data on pollen productivity estimates, fossil pollen, charcoal sequences from soil and archaeological contexts. Based on abundances and habitat preferences from the last 9 millennia, we calculated the autecological preferences of tree taxa, using multivariate statistics.ResultsThe significant spatiotemporal patterns between soil-charcoal and pollen-based EDA validated the reconstruction, the use of both records in the EDA, and the EDA model. One of the topographic indices—vertical distance to channel network—evidenced the following: the closest taxon to the groundwater is Picea; Abies, Betula, Pinus and Quercus have intermediate distances; Fagus grows far from the channel network and Corylus even further.ConclusionsThe EDA model linked past forest composition to realistic topography. Such a spatially explicit reconstruction produced by our new algorithm allows inferring the relationship between past plant communities and environmental variables. The long-term preferences of tree species to habitat characteristics match their current autecological demands. This might be a breakthrough in quantitative plant paleoecology.

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.

Estimation of absolute pollen productivity based on the flower counting approach: A review

Pollen productivity estimate (PPE) is one of the parameters necessary for pollen-based quantitative reconstruction of vegetation in the past. This paper summarizes and reviews the absolute PPEs (aPPEs) that were obtained with the area-based flower counting approach since the 1970s. The data for 23 species of trees are available from Japan and for 22 species of Poaceae from Japan, Spain, and Morocco. The aPPE values vary from 1 to 60 [1012 grains·ha−1·year−1], and are comparable to those previously reported in Europe and using different methods and approaches. The mean aPPEs of temperate conifers, such as Sciadopitysverticillata, Cryptomeria japonica, and Chamaecyparis obtusa, are as high as those of some of the common broadleaved trees, Castanea mollissima, Castanopsis cuspidata, and Alnus spp. The mean aPPEs of Abies firma, Fagus crenata, and Betula platyphylla are low, and those of Pinus densiflora, Quercus spp., Juglans ailanthifolia, Carpinus tchonoskii, Aesculus turbinata, and Poaceae spp. are intermediate. The relative PPE (rPPE) values of the arboreal taxa (relative to Poaceae), calculated using the aPPEs presented here, are smaller than those obtained in Western Europe and China based on the Extended R-value model approach. Differences in the sampling and analytical methods, as well as the interregional differences in Poaceae pollen productivity, might have contributed to the discrepancies observed. Although further studies are necessary, the flower counting approach is practical and informative for species-specific estimates of absolute pollen productivity and provides critical parameters for quantitatively reconstructing past vegetation in absolute units using the rates of pollen accumulation in sediments.

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.

Estimation of pollen productivity and dispersal: How pollen assemblages in small lakes represent vegetation

AbstractQuantitative understanding of vegetation dynamics over timespans beyond a century remains limited. In this regard, the pollen‐based reconstruction of past vegetation enables unique research opportunities by quantifying changes in plant community compositions during hundreds to thousands of years. Critically, the methodological basis for most reconstruction approaches rests upon estimates of pollen productivity and dispersal. Previous studies, however, have reached contrasting conclusions concerning these estimates, which may be perceived to challenge the applicability and reliability of pollen‐based reconstruction. Here we show that conflicting estimates of pollen production and dispersal are, at least in part, artifacts of fixed assumptions of pollen dispersal and insufficient spatial resolution of vegetation data surrounding the pollen‐collecting lake. We implemented a Bayesian statistical model that related pollen assemblages in surface sediments of 33 small lakes (<2 ha) in the northeastern United States, with surrounding vegetation ranging from 101 to >105 m from the lake margin. Our analysis revealed three key insights. First, pollen productivity is largely conserved within taxa and across forest types. Second, when local (within a 1‐km radius) vegetation abundances are not considered, pollen‐source areas may be overestimated for some common taxa (Cupressaceae, Pinus, Quercus, and Tsuga). Third, pollen dispersal mechanisms may differ between local and regional scales; this is missed by pollen‐dispersal models used in previous studies. These findings highlight the complex interactions between vegetation heterogeneity on the landscape and pollen dispersal. We suggest that, when estimating pollen productivity and dispersal, both detailed local and extended regional vegetation must be taken into account. Also, both deductive (mechanistic models) and inductive (statistical models) approaches are needed to better understand the emergent properties of pollen dispersal in heterogeneous landscapes.

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.

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.

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.

Reply to Theuerkauf and Couwenberg (2020) comment on: “Pollen-based reconstruction of Holocene land-cover in mountain regions: Evaluation of the Landscape Reconstruction Algorithm in the Vicdessos valley, northern Pyrenees, France”

Comments on Marquer et al. (2020) by Theuerkauf and Couwenberg (2020) revisit two issues important for pollen-based reconstruction of past vegetation with the Landscape Reconstruction Algorithm (LRA;Sugita, 2007a,2007b) and related models: the selection of pollen dispersal model and the appropriate use of pollen productivity estimates. We are aware of those issues, and our paper addresses those questions and advises for caution and necessary future steps to improve model-based reconstruction of vegetation in mountain environments and elsewhere. This reply restates briefly some of the important take-home messages fromour study and presents our suggestion and proposal in response toTheuerkauf and Couwenberg’s comments.

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.

Comparison of settlement-era vegetation reconstructions for STEPPS and REVEALS pollen–vegetation models in the northeastern United States

AbstractReconstructions of prehistoric vegetation composition help establish natural baselines, variability, and trajectories of forest dynamics before and during the emergence of intensive anthropogenic land use. Pollen–vegetation models (PVMs) enable such reconstructions from fossil pollen assemblages using process-based representations of taxon-specific pollen production and dispersal. However, several PVMs and variants now exist, and the sensitivity of vegetation inferences to PVM selection, variant, and calibration domain is poorly understood. Here, we compare the reconstructions, parameter estimates, and structure of a Bayesian hierarchical PVM, STEPPS, both to observations and to REVEALS, a widely used PVM, for the pre–Euro-American settlement-era vegetation in the northeastern United States (NEUS). We also compare NEUS-based STEPPS parameter estimates to those for the upper midwestern United States (UMW). Both PVMs predict the observed macroscale patterns of vegetation composition in the NEUS; however, reconstructions of minor taxa are less accurate and predictions for some taxa differ between PVMs. These differences can be attributed to intermodel differences in structure and parameter estimates. Estimates of pollen productivity from STEPPS broadly agree with estimates produced for use in REVEALS, while comparison between pollen dispersal parameter estimates shows no significant relationship. STEPPS parameter estimates are similar between the UMW and NEUS, suggesting that STEPPS parameter estimates are transferable between floristically similar regions and scales.

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.