Relevant Source Area Of Pollen Research Articles

BACKLAND: spatially explicit and high‐resolution pollen‐based BACKward LAND‐cover reconstructions

Studying the interactions between humans, land‐cover and biodiversity is necessary for the sustainable management of socio‐ecosystems and requires long‐term reconstructions of past landscapes, improving the integration of slow processes. The main source of information on past vegetation is fossil pollen, but pollen data are biased by inter‐taxonomic differential production and dispersal. The landscape reconstruction algorithm (LRA) approach is the most widely used to correct for these biases. The LOVE algorithm (LOcal Vegetation estimates), the second step in the LRA approach, also estimates the spatial extent of the local vegetation reconstruction zone (the relevant source area of pollen, RSAP). While LRA estimates have already been integrated into certain past land‐cover mapping approaches, none have been designed to allow the diachronic reconstruction of a land‐cover mosaic over the long term combining the following points: the direct integration of LOVE estimates as a source of variability in the composition and distribution of pollen taxa, without multiple scenarios, and the integration of spatiotemporal autocorrelation in the taxa distribution between periods. Here, we propose an innovative approach for BACKward LAND‐cover reconstruction (BACKLAND), combining these points and estimating the past land‐cover mosaic within a set of RSAPs. Based on three stages using parsimonious assumptions and easy‐to‐implement probabilistic and statistical tools, this approach requires LOVE estimates of sites close enough to each other for their RSAPs to overlap, botanical data, a digital elevation model and two recent land‐cover maps. Developed and tested on a small study area within the mountain landscape of the Bassiès valley (French Pyrenees), BACKLAND achieved the reconstruction of a past land‐cover map representing eight land‐cover types at a spatial resolution of 20 m with a good level of accuracy. We show in this study the originality of this approach and discuss its potential for palaeoenvironmental studies, historical ecology and the management of socio‐ecosystems.

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.

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.

Linking modern pollen accumulation rates to biomass: Quantitative vegetation reconstruction in the western Klamath Mountains, NW California, USA

Quantitative reconstructions of vegetation abundance from sediment-derived pollen systems provide unique insights into past ecological conditions. Recently, the use of pollen accumulation rates (PAR, grains cm−2 year−1) has shown promise as a bioproxy for plant abundance. However, successfully reconstructing region-specific vegetation dynamics using PAR requires that accurate assessments of pollen deposition processes be quantitatively linked to spatially-explicit measures of plant abundance. Our study addressed these methodological challenges. Modern PAR and vegetation data were obtained from seven lakes in the western Klamath Mountains, California. To determine how to best calibrate our PAR-biomass model, we first calculated the spatial area of vegetation where vegetation composition and patterning is recorded by changes in the pollen signal using two metrics. These metrics were an assemblage-level relevant source area of pollen (aRSAP) derived from extended R-value analysis ( sensu Sugita, 1993) and a taxon-specific relevant source area of pollen (tRSAP) derived from PAR regression ( sensu Jackson, 1990). To the best of our knowledge, aRSAP and tRSAP have not been directly compared. We found that the tRSAP estimated a smaller area for some taxa (e.g. a circular area with a 225 m radius for Pinus) than the aRSAP (a circular area with a 625 m radius). We fit linear models to relate PAR values from modern lake sediments with empirical, distance-weighted estimates of aboveground live biomass (AGLdw) for both the aRSAP and tRSAP distances. In both cases, we found that the PARs of major tree taxa – Pseudotsuga, Pinus, Notholithocarpus, and TCT (Taxodiaceae, Cupressaceae, and Taxaceae families) – were statistically significant and reasonably precise estimators of contemporary AGLdw. However, predictions weighted by the distance defined by aRSAP tended to be more precise. The relative root-mean squared error for the aRSAP biomass estimates was 9% compared to 12% for tRSAP. Our results demonstrate that calibrated PAR-biomass relationships provide a robust method to infer changes in past plant biomass.

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 in the forest steppe landscape of southeastern Romania

Estimates of relative pollen productivity (RPP) represent key input parameters for model-based quantitative reconstructions of past vegetation cover. In this study, we provide the first RPP estimates for 13 taxa from the forest steppe ecoregion in southeastern Romania (southeastern Europe). We used modern pollen assemblages from 26 points together with vegetation surveys and mapping, covering a 1.5 km radius around each sampling site. We have estimated the relevant source area of pollen (RSAP) and pollen productivity for 13 taxa relative to Poaceae using the ERV (Extended R-value model), sub-model 3, as this model shows the best goodness of fit. The estimated RSAP is about 100 m and falls within the range of RSAP estimates of moss pollsters and forest hollows from other RPP-related studies. Results show that Rubiaceae (7.97), Apiaceae (5.91), Artemisia (5.89) and Fraxinus (2.99) are high pollen producers compared to Poaceae, while Plantago lanceolata (0.58), Fabaceae (0.40), Acer (0.30), Rosaceae (0.29), Carpinus orientalis (0.24), Cerealia (0.22) and Asteraceae (0.16) are low pollen producers with lower RPPs than Poaceae. Quercus (1.10) has a pollen productivity close to that of Poaceae. The RPPs for Carpinus orientalis and Fabaceae are published here the first time for Europe. The high pollen producing plants include both entomophilous and anemophilous species, while the low pollen producers are mostly entomophilous species. Our results form an essential contribution to improving the accuracy of quantitative reconstruction of forest steppe ecoregion in Europe and generally in regions with a similar climate and vegetation setting.

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.

A Landscape Reconstruction Algorithm and pedoanthracological data reveal Late Holocene woodland history in the lowlands of the NE Czech Republic

We aim to obtain composition of the regional vegetation from the pollen record in the high mountains, to use it in the interpretation of the pollen record from the lowlands via a Landscape Reconstruction Algorithm (LRA), and to then compare the pedoanthracological data with the LRA result based on dissimilarity coefficient.We used five pollen sequences from summits of the Eastern Sudetes (NE Czech Republic), and two pollen cores were analysed in the adjacent Litovelské Pomoraví lowlands. The same lowland woodland was sampled in six pedoanthracological sections. All records cover the Late Holocene period.Site-to-site variability of the pollen spectra from the mountains was found to be low. Regional vegetation inferred from shallowest pollen samples corresponds to present-day vegetation inferred from forestry data. Mountain sites represent regional components and can substitute for large sites in an LRA.Mean LRA estimates were more similar to mean charcoal spectra than they were to mean pollen percentages. LRA estimates of Quercus and Fraxinus in the lowlands match the pedoanthracological evidence regarding individual sites. LRA estimates and charcoal spectra both show that the main dominant (>50%) in the woodland studied was Quercus.Mismatching evidence resided in a small number of the determined charcoals and there were differences between some assumptions of the LRA and the real-world conditions. Alnus and Tilia produced higher pollen signals on the expanse of Fagus and Abies, which were recorded by charcoals within the Relevant Source Area of Pollen (RSAP), which varied from a 35 to a 255meter radius, and ranged with the value from forest hollows.Comparability of LRA vegetation estimates and charcoal percentages is still at the level of complementary evidence. However, a quantitative approach shifts the character to substitutable evidence, with potential to provide the same vegetation estimates by both proxies.

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.

Relation between modern pollen rain, vegetation and climate in northern China: Implications for quantitative vegetation reconstruction in a steppe environment

Vegetation reconstructions from palaeoecological records depend on adequate understanding of relationships between modern pollen, vegetation and climate. A key parameter for quantitative vegetation reconstructions is the Relative Pollen Productivity (RPP). Differences in both environmental and methodological factors are known to alter the RPP estimated significantly, making it difficult to determine whether the underlying pollen productivity does actually vary, and if so, why. In this paper, we present the results of a replication study for the Bashang steppe region, a typical steppe area in northern China, carried out in 2013 and 2014. In each year, 30 surface samples were collected for pollen analysis, with accompanying vegetation survey using the “Crackles Bequest Project” methodology. Sampling designs differed slightly between the two years: in 2013, sites were located completely randomly, whilst in 2014 sampling locations were constrained to be within a few km of roads. There is a strong inter-annual variability in both the pollen and the vegetation spectra therefore in RPPs, and annual precipitation may be a key influence on these variations. The pollen assemblages in both years are dominated by herbaceous taxa such as Artemisia, Amaranthaceae, Poaceae, Asteraceae, Cyperaceae, Fabaceae and Allium. Artemisia and Amaranthaceae pollen are significantly over-represented for their vegetation abundance. Poaceae, Cyperaceae and Fabaceae seem to have under-represented pollen for vegetation with correspondingly lower RPPs. Asteraceae seems to be well-represented, with moderate RPPs and less annual variation. Estimated Relevant Source Area of Pollen (RSAP) ranges from 2000 to 3000m. Different sampling designs have an effect both on RSAP and RPPs and random sample selection may be the best strategy for obtaining robust estimates. Our results have implications for further pollen-vegetation relationship and quantitative vegetation reconstruction research in typical steppe areas and in other open habitats with strong inter-annual variation.

Testing quantitative pollen dispersal models in animal-pollinated vegetation mosaics: An example from temperate Tasmania, Australia

Reconstructing past vegetation abundance and land-cover changes through time has important implications in land management and climate modelling. To date palaeovegetation reconstructions in Australia have been limited to qualitative or semi-quantitative inferences from pollen data. Testing pollen dispersal models constitutes a crucial step in developing quantitative past vegetation and land cover reconstructions. Thus far, the application of quantitative pollen dispersal models has been restricted to regions dominated by wind-pollinated plants (e.g. Europe) and their performance in a landscape dominated by animal-pollinated plant taxa is still unexplored. Here we test, for the first time in Australia, two well-known pollen dispersal models to assess their performance in the wind- and animal-pollinated vegetation mosaics of western Tasmania. We focus on a mix of wind- (6 taxa) and animal- (7 taxa) pollinated species that comprise the most common pollen types and key representatives of the dominant vegetation formations. Pollen Productivity Estimates and Relevant Source Area of Pollen obtained using Lagrangian Stochastic turbulent simulations appear to be more realistic when compared to the results from the widely used Gaussian Plume Model.