Pollen Dispersal Model Research Articles

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.

Influence of Pollen Dispersal and Mating Pattern in Domestication of Intermediate Wheatgrass, a Novel Perennial Food Crop.

Intermediate wheatgrass (IWG) is a perennial forage grass that is currently being domesticated as a grain crop. It is a primarily wind-pollinated outcrossing species and expresses severe inbreeding depression when self-pollinated. Characterization of pollen dispersal, mating parameters, and change in genetic diversity due to pollen movement is currently lacking in IWG. In this study, we examined pollen dispersal in an IWG selection nursery by evaluating 846 progeny from 15 mother plants and traced their parentage to 374 fathers. A set of 2,500 genomic loci was used to characterize the population. We assigned paternity to 769 (91%) progeny and the average number of fathers per mother plant was 37, from an average of 56 progeny examined per mother. An extensive number (80%) of pollination events occurred within 10 m of the mother plants. Pollination success was not correlated with trait attributes of the paternal genotypes. Mating system analysis confirmed that IWG is highly outcrossing and inbreeding was virtually absent. Neither genetic diversity nor the genome-estimated trait values of progeny were significantly affected by pollinator distance. The distance of pollinator in an IWG breeding nursery therefore was not found to be a major contributor in maintaining genetic diversity. These findings reveal the pollen dispersal model in IWG for the first time and its effect on genetic diversity, which will be valuable in designing future IWG breeding populations. Information generated and discussed in this study could be applied in understanding gene flow and genetic diversity of other open-pollinated species.

Incorporating the field border effect to reduce the predicted uncertainty of pollen dispersal model in Asia

The presence of the field border (FB), such as roadways or unplanted areas, between two fields is common in Asian farming system. This study evaluated the effect of the FB on the cross-pollination (CP) and predicted the CP rate in the field considering and not considering FB. Three experiments including 0, 6.75, and 7.5 m width of the FB respectively were conducted to investigate the effect of distance and the FB on the CP rate. The dispersal models combined kernel and observation model by calculating the parameter of observation model from the output of kernel. These models were employed to predict the CP rate at different distances. The Bayesian method was used to estimate parameters and provided a good prediction with uncertainty. The highest average CP rates in the field with and without FB were 74.29% and 36.12%, respectively. It was found that two dispersal models with the FB effect displayed a higher ability to predict average CP rates. The correlation coefficients between actual CP rates and CP rates predicted by the dispersal model combined zero-inflated Poisson observation model with compound exponential kernel and modified Cauchy kernel were 0.834 and 0.833, respectively. Furthermore, the predictive uncertainty was reducing using the dispersal models with the FB effect.

Towards quantifying changes in forest cover in the Araucaria forest-grassland mosaic in southern Brazil

Quantitative estimates of past vegetation cover are needed both regionally so human-landscape interactions can be better understood, and globally to evaluate the effects of changing vegetation cover on the climate system. Models reducing the bias in the pollen representation of vegetation cover have been developed in the temperate regions of the northern hemisphere, while experience applying them in other parts of the world is limited. The Araucaria forest-grassland mosaic of southern Brazil is an area where open and forested plant communities exist naturally and have changed their cover over time due to changing climate and human activities. Therefore, this area is of particular interest for such studies. Modern pollen and vegetation comparisons were carried out in two protected areas: Vila Velha State Park in Paraná state and Aparados da Serra National Park in Rio Grande do Sul. Vegetation mapping and analysis focused on Araucaria angustifolia as the characteristic tree of this vegetation type. In the Araucaria forest-grassland mosaic open vegetation and woodland change at a scale of hundreds of metres. These changes are difficult to capture based on pollen proportions in surface samples. While the abundance of Poaceae pollen is not a good indicator of locally open conditions, several pollen taxa can be used as indicators of the local vegetation cover. Pollen vegetation ratios (R-values) compare well between the two study regions, indicating that pollen production of individual species within the large plant families of Poaceae and Asteraceae are similar within the overall region. Araucaria angustifolia pollen is underrepresented with regards to its vegetation cover, while Poaceae are among the highest pollen producers in the region. Diverse woodland species other than A. angustifolia were grouped as one forest taxon and as the species composition of woodlands differed between the two study areas, so did the estimated pollen productivity of this group. It would be rewarding in future investigations to estimate pollen productivity for groups of trees with the same pollen dispersal syndrome. The application of pollen dispersal models designed for closed canopy in the protected areas was challenging. Further model development is required to deal with pollen released at different levels in semi-open vegetation types.

Effectiveness of different sampling schemes in predicting adventitious genetically modified maize content in a smallholder farming system

ABSTRACT When genetically modified (GM) maize is planted in an open field, it may cross-pollinate with the nearby non-GM maize under certain airflow conditions. Suitable sampling methods are crucial for tracing adventitious GM content. By using field data and bootstrap simulation, we evaluated the performance of common sampling schemes to determine the adventitious GM content in small maize fields in Taiwan. A pollen dispersal model that considered the effect of field borders, which are common in Asian agricultural landscapes, was used to predict the cross-pollination (CP) rate. For the 2009–1 field data, the six-transect (Tsix), JM method for low expected flow (JM[L]), JM method for high expected flow (JM[H]), and V-shaped transect (TV) methods performed comparably to simple random sampling (SRS). Tsix, TV, JM(L), and JM(H) required only 13% or less of the sample size required by SRS. After the simulation and verification of the 2009–2 and 2010–1 field data, we concluded that Tsix, TV, JM(L), and systematic random sampling methods performed equally as well as SRS in CP rate predictions. Our findings can serve as a reference for monitoring the pollen dispersal tendencies of maize in countries with smallholder farming systems.

Numerical modelling of birch pollen dispersion in Canada

Simulating allergenic tree pollen is important to protect sensitive population and to support bioaerosols monitoring effort. Using the regional air quality model GEM-MACH, a simulation was conducted adopting two new main hypotheses: 1) the use of vertical correlation concept to force the vertical dispersion (a method normally used in tracer data assimilation) and, 2) the use of a puff instead of a continuous pollen release. The simulation was compared with pollen observations in Montreal and with the corresponding statistical forecasts (issued daily by the Weather Network) at several locations in the province of Quebec and elsewhere. The comparison with the simulation was found satisfactory (outperform forecasts based on persistence or pollen calendar and is also superior to numerical simulation of tree pollen done elsewhere in North America). Simulation shows that, for the 2012 pollen season, the majority (88%) of the Betula pollen measured in Montreal originated from the Laurentides region. Another result of scientific importance obtained here is that Betula pollen episodes (observed or simulated birch pollen) in Montreal occur only when the average daily temperature is in the range of 10° to 18 °C. This research is considered as a first step in forecasting bioaerosols in Canada within an air quality model.

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.

Effects of reproductive resource allocation and pollen density on fertilization success in plants

BackgroundDeclining resources due to climate change may endanger the persistence of populations by reducing fecundity and thus population fitness via effects on gamete production. The optimal mode of generative reproduction allocates the limited resources to ovule and pollen production in proportions that maximize the number of fertilized ovules in the population. In order to locate this optimum and derive reproduction modes that compensate for declined resources to maintain reproductive success, a model of gamete production, pollen dispersal, and ovule fertilization is developed. Specification of opportunities for compensation is given priority over specification of physiological or evolutionary mechanisms of adaptation. Thus model parameters summarize gametic production resources, resource investment per gamete, resource allocation as proportion of resources invested in ovules, and pollen density as size of the pollen dispersal range and proportion of pollen retained within the range. Retained pollen disperses randomly, and an ovule is fertilized if at least one pollen settles on its surface. The outcome is the expected number of fertilized ovules.ResultsMaximization of fertilization success is found to require the investment of more gametic production resources in ovules than in pollen, irrespective of the parameter values. Resource decline can be compensated by adjusting the resource allocation if the maximum expected number of fertilized ovules after the decline is not less than the expected number the population experienced before the decline. Compensation is also possible under some conditions by increasing the pollen density, either by raising a low pollen retention or by shrinking the dispersal range.ConclusionFertilization success in populations affected by resource decline may be maintainable by adjustment of the sexual allocation of gametic production resources or by increasing pollen density. The results have implications for insect pollination, sexual allocation bias, management measures, and metapopulation fragmentation.

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.

Incorporation of pollen data in source maps is vital for pollen dispersion models

Abstract. Information about distribution of pollen sources, i.e. their presence and abundance in a specific region, is important, especially when atmospheric transport models are applied to forecast pollen concentrations. The goal of this study is to evaluate three pollen source maps using an atmospheric transport model and study the effect on the model results by combining these source maps with pollen data. Here we evaluate three maps for the birch taxon: (1) a map derived by combining a land cover data and forest inventory, (2) a map obtained from land cover data and calibrated using model simulations and pollen observations, and (3) a statistical map resulting from analysis of forest inventory and forest plot data. The maps were introduced to the Enviro-HIRLAM (Environment – High Resolution Limited Area Model) as input data to simulate birch pollen concentrations over Europe for the birch pollen season 2006. A total of 18 model runs were performed using each of the selected maps in turn with and without calibration with observed pollen data from 2006. The model results were compared with the pollen observation data at 12 measurement sites located in Finland, Denmark, and Russia. We show that calibration of the maps using pollen observations significantly improved the model performance for all three maps. The findings also indicate the large sensitivity of the model results to the source maps and agree well with other studies on birch showing that pollen or hybrid-based source maps provide the best model performance. This study highlights the importance of including pollen data in the production of source maps for pollen dispersion modelling and for exposure studies.

Artificial neural networks can be used for Ambrosia pollen emission parameterization in COSMO-ART

The emission parameterization is a crucial part of numerical pollen dispersion models. This paper shows that Artificial Neural Networks (ANNs) can substantially improve the performance of the Ambrosia pollen emission in numerical pollen dispersion models such as COSMO-ART. Based on simultaneous measurement of Ambrosia pollen concentrations and meteorological variables in the source area, ANNs were trained to predict the diurnal profile of pollen emission. Six different combinations of explanatory meteorological variables were trained with five different ANN configurations resulting in 30 candidate emission models. The best network configuration for each combination of explanatory variables were used as emission parameterization in the numerical pollen dispersion model COSMO-ART. In addition, two benchmarks were implemented: an emission parameterization based on sigmoid functions and an artificial neural network using only time as an explanatory variable. The Ambrosia pollen seasons of 2015 and 2016 were simulated using the two benchmarks and the six emission parameterizations. The modelled diurnal profile of emission fluxes at 15 different sites from Serbia, Hungary and France with strong local pollen sources were compared with observed concentrations. Artificial Neural Networks based emission parameterization substantially improved the performance of the Ambrosia pollen emission in COSMO-ART compared to the emission based on the sigmoid functions in all these three countries. However, a time-related explanatory variable must be used. This suggests that the ANN-based emission parameterizations can be used at distant locations as well. On the other hand, the use of meteorological related parameters did not increase the performance compared with the time-only benchmark.

Extending the applicability of the REVEALS model for pollen-based vegetation reconstructions to coastal lagoons

Quantitative reconstruction of past plant abundance from fossil pollen data is still a challenging task for palynologists. During the last decades, mechanistic methods have been developed to convert pollen assemblages from peat and lake deposits into vegetation abundance at regional and local scale. Coastal areas are particularly sensitive to climate and environmental hazards. Thus, quantitative estimates of past vegetation are important to better understand their history and address potential effects of future environmental changes. However, assumptions of the mechanistic models of pollen dispersal and deposition originally designed for near-circular lakes and bogs located inland are violated when applied to coastal sites because of different basin shape and wind direction distribution. This study investigates how to adapt a model of pollen dispersal and deposition developed for lakes to coastal lagoons. A new geometry is defined, and it is demonstrated how some of the major formulas from previous models can be used without any modification in this singular context.

Maps From Mud—Using the Multiple Scenario Approach to Reconstruct Land Cover Dynamics From Pollen Records: A Case Study of Two Neolithic Landscapes

Pollen records contain a wide range of information about past land cover, but translation from the pollen diagram to other formats remains a challenge. In this paper, we present LandPolFlow, a software package enabling Multiple Scenario Approach (MSA) based land cover reconstruction from pollen records for specific landscapes. It has two components: a basic Geographic Information System which takes grids of landscape constraints (e.g. topography, geology) and generates possible 'scenarios' of past land cover using a combination of probabilistic and deterministic placement rules to distribute defined plant communities within the landscape, and a pollen dispersal and deposition model which simulates pollen loading at specified points within each scenario and compares that statistically with actual pollen assemblages from the same location. Goodness of fit statistics from multiple pollen site locations are used to identify which scenarios are likely reconstructions of past land cover. We apply this approach to two case studies of Neolithisation in Britain, the first from the Somerset Levels and the second from Mainland, Orkney. Both landscapes contain significant evidence of Neolithic activity, but present contrasting contexts. In Somerset, wet-preserved Neolithic remains such as trackways are abundant, but little dry land settlement archaeology is known, and the pre-Neolithic landscape was extensively wooded. In Orkney, the Neolithic archaeology includes domestic and monumental stone-built structures forming a UNESCO World Heritage Site, and the pre-Neolithic landscape was largely treeless. Existing pollen records were collated from both landscapes and correlated within a new age model framework (presented elsewhere). This allowed pollen data to be grouped into 200 year periods, or “timeslices”, for reconstruction of land cover through time using the MSA. Reconstruction suggests that subtle but clear and persistent impacts of Neolithisation on land cover occurred in both landscapes, with no reduction in impact during periods when archaeological records suggest lower activity levels. By applying the methodology to specific landscapes, we critically evaluate the strengths and weaknesses and identify potential remedies, which we then expand into consideration of how simulation can be incorporated into palynological research practice. We argue that the MSA deserves a place within the palynologist’s standard tool kit.

Modelling of pollen dispersion in the atmosphere: evaluation with a continuous 1β+1δ lidar

Pollen allergenicity plays an important role on human health and wellness. It is thus of large public interest to increase our knowledge of pollen grain behavior in the atmosphere (source, emission, processes involved during their transport, etc.) at fine temporal and spatial scales. First simulations with the Barcelona Supercomputing Center NMMB/BSC-CTM model of Platanus and Pinus dispersion in the atmosphere were performed during a 5-day pollination event observed in Barcelona, Spain, between 27 – 31 March, 2015. The simulations are compared to vertical profiles measured with the continuous Barcelona Micro Pulse Lidar system. First results show that the vertical distribution is well reproduced by the model in shape, but not in intensity, the model largely underestimating in the afternoon. Guidelines are proposed to improve the dispersion of airborne pollen by numerical prediction models.

Seeing the Wood for the Trees: Recent Advances in the Reconstruction of Woodland in Archaeological Landscapes Using Pollen Data

ABSTRACTThis paper reviews recent advances in the reconstruction of woodland cover from palynological data. Pollen sequences record the vegetation cover of past landscapes, but translating a pollen diagram into a landscape reconstruction is not straightforward. This paper focuses on the use of pollen records to address three archaeologically relevant problems, the detection of woodland presence and extent in a largely open landscape, the reconstruction of the habitat context of a specific archaeological site, and the detection of woodland management. Research seeking to quantify past land-cover using models of pollen dispersal and deposition has led to the development of algorithms and computer software linking maps of the arrangement of land-cover with simulated pollen records at possible coring points. This software can be used to carry out thought experiments and test competing hypotheses, and also underpins the Multiple Scenario Approach to the reconstruction of past land-cover. Modern datasets of pollen surface samples and associated vegetation abundances are needed to calibrate these models, and can also provide insights into how the pollen record ‘sees’ landscapes, and therefore aid interpretation of past pollen records. We demonstrate how simulation approaches and surface sample studies are improving the scientific basis of reconstruction of past landscapes, and how these approaches offer new opportunities for communication and collaboration between archaeologists and environmental specialists.

How old is the Tasmanian cultural landscape? A test of landscape openness using quantitative land‐cover reconstructions

AbstractAimTo test competing hypotheses about the timing and extent of Holocene landscape opening using pollen‐based quantitative land‐cover estimates.LocationDove Lake, Tasmanian Wilderness World Heritage Area, Australia.MethodsFossil pollen data were incorporated into pollen dispersal models and corrected for differences in pollen productivity among key plant taxa. Mechanistic models (REVEALS—Regional Estimates of VEgetation Abundance from Large Sites) employing different models for pollen dispersal (Gaussian plume and Lagrangian stochastic models) were evaluated and applied in the Southern Hemisphere for the first time.ResultsValidation of the REVEALS model with vegetation cover data suggests an overall better performance of the Lagrangian stochastic model. Regional land‐cover estimates for forest and non‐forest plant taxa show persistent landscape openness throughout the Holocene (average landscape openness ~50%). Gymnoschoenus sphaerocephalus, an indicator of moorland vegetation, shows higher values during the early Holocene (11.7–9 ka) and declines slightly through the mid‐Holocene (9–4.5 ka) during a phase of partial landscape afforestation. Rain forest cover reduced (from ~40% to ~20%) during the period between 4.2–3.5 ka.Main conclusionsPollen percentages severely under‐represent landscape openness in western Tasmania and this bias has fostered an over‐estimation of Holocene forest cover from pollen data. Treeless vegetation dominated Holocene landscapes of the Dove Lake area, allowing us to reject models of landscape evolution that invoke late‐Holocene replacement of a rain forest‐dominated landscape by moorland. Instead, we confirm a model of Late Pleistocene inheritance of open vegetation. Rapid forest decline occurred after c. 4 ka, likely in response to regional moisture decline.

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.

A matter of dispersal: REVEALSinR introduces state-of-the-art dispersal models to quantitative vegetation reconstruction

The REVEALS model is applied in quantitative vegetation reconstruction to translate pollen percentage data from large lakes and peatlands into regional vegetation composition. The model was first presented in 2007 and has gained increasing attention. It is a core element of the Landcover 6k initiative within the PAGES project. The REVEALS model has two critical components: the pollen dispersal model and pollen productivity estimates (PPEs). To study the consequences of model settings, we implemented REVEALS in R. We use a state-of-the-art Lagrangian stochastic dispersal model (LSM) and compare model outcomes with calculations based on a conventional Gaussian plume dispersal model (GPM). In the LSM turbulence causes pollen fall speed to have little effect on the dispersal pattern whereas fall speed is a major factor in the GPM. Dispersal models are also used to derive PPEs. The unrealistic GPM produces PPEs that do not describe actual pollen productivity, but rather serve as a basin specific correction factor. A test with pollen and vegetation data from NE Germany shows that REVEALS performs best when applied with the LSM. REVEALS applications with the GPM can produce realistic results, but only if unrealistic PPEs are used. We discuss the derivation of PPEs and further REVEALS applications. Our REVEALS implementation is freely available as the ‘REVEALSinR’ function within the R package DISQOVER. REVEALSinR offers an environment for experimentation and analysing model sensitivities. We encourage further experiments and welcome comments on our tool.

Characteristic pollen source area and vertical pollen dispersal and deposition in a mixed coniferous and deciduous broad-leaved woodland in the Changbai mountains, northeast China

Pollen influx (number of pollen grains cm−2 year−1) can objectively reflect the dispersal and deposition features of pollen within a certain time and space, and is often used as a basis for the quantitative reconstruction of palaeovegetation; however, little is known about the features and mechanisms of vertical dispersal of pollen. Here we present the results from a 5 year (2006–2010) monitoring program using pollen traps placed at different heights from ground level up to 60 m and surface soil samples in a mixed coniferous and deciduous broad-leaved woodland in the Changbai mountains, northeastern China. The pollen percentages and pollen influx from the traps have very similar characteristics to the highest values for Betula, Fraxinus, Quercus and Pinus, among the tree taxa and Artemisia, Chenopodiaceae and Asteraceae among the herb taxa. Pollen influx values vary significantly with height and show major differences between three distinct layers, above-canopy (≥32 m), within the trunk layer (8 ≤ 32 m) and on the ground (0 m). These differences in pollen influx are explained by differences in (i) the air flows in each of these layers and (ii) the fall speed of pollen of the various taxa. We found that the pollen recorded on the ground surface is a good representation of the major part of the pollen transported in the trunk space of the woodland. Comparison of the pollen influx values with the theoretical, calculated “characteristic pollen source area” (CPSA) of 12 selected taxa indicates that the pollen deposited on the ground surface of the woodland is a fair representation with 85–90 % of the total pollen deposited at a wind speed of 2.4 m s−1 coming from within ca. 1–5 km for Pinus and Quercus, ca. 5–10 km for Ulmus, Tilia, Oleaceae and Betula, ca. 20–40 km for Fraxinus, Poaceae, Chenopodiaceae, Populus and Salix, and ca. 30–60 km for Artemisia; it is also a good representation with 90–98 % of the total pollen deposited coming from within 60 km at a wind speed of 2.4 m s−1, or 100 km at a wind speed: 6 m s−1, for the 12 selected taxa used in the CPSA calculation. Furthermore, comparison with the vegetation map of the area around the sampling site shows that the pollen deposited on the ground represents all plant communities which grow in the study area within 70 km radius of the sampling site. In this study, the pollen percentages obtained from the soil surface samples are significantly biased towards pollen taxa with good preservation due to thick and robust pollen walls. Therefore, if mosses are available instead, soil samples should be avoided for pollen studies, in particular for the study of pollen-vegetation relationships, the estimation of pollen productivities and quantitative reconstruction of past vegetation. The results also indicate that the existing model of pollen dispersal and deposition, Prentice’s model, provides a fair description of the actual pollen dispersal and deposition in this kind of woodland, which suggests that the application of the landscape reconstruction algorithm would be relevant for reconstruction of this type of woodland in the past.

Pollen-based quantitative reconstructions of Holocene regional vegetation cover (plant-functional types and land-cover types) in Europe suitable for climate modelling.

We present quantitative reconstructions of regional vegetation cover in north-western Europe, western Europe north of the Alps, and eastern Europe for five time windows in the Holocene [around 6k, 3k, 0.5k, 0.2k, and 0.05k calendar years before present (bp)] at a 1° × 1° spatial scale with the objective of producing vegetation descriptions suitable for climate modelling. The REVEALS model was applied on 636 pollen records from lakes and bogs to reconstruct the past cover of 25 plant taxa grouped into 10 plant-functional types and three land-cover types [evergreen trees, summer-green (deciduous) trees, and open land]. The model corrects for some of the biases in pollen percentages by using pollen productivity estimates and fall speeds of pollen, and by applying simple but robust models of pollen dispersal and deposition. The emerging patterns of tree migration and deforestation between 6k bp and modern time in the REVEALS estimates agree with our general understanding of the vegetation history of Europe based on pollen percentages. However, the degree of anthropogenic deforestation (i.e. cover of cultivated and grazing land) at 3k, 0.5k, and 0.2k bp is significantly higher than deduced from pollen percentages. This is also the case at 6k in some parts of Europe, in particular Britain and Ireland. Furthermore, the relationship between summer-green and evergreen trees, and between individual tree taxa, differs significantly when expressed as pollen percentages or as REVEALS estimates of tree cover. For instance, when Pinus is dominant over Picea as pollen percentages, Picea is dominant over Pinus as REVEALS estimates. These differences play a major role in the reconstruction of European landscapes and for the study of land cover-climate interactions, biodiversity and human resources.