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

The Holocene ◽  
2021 ◽  
pp. 095968362110417
Author(s):  
Martin Theuerkauf ◽  
John Couwenberg
Keyword(s):  
Model Selection ◽  
Pollen Dispersal ◽  
Local Scale ◽  
Pollen Deposition ◽  
Data Sets ◽  
Pollen Data ◽  
Modern Pollen ◽  
Dispersal Model ◽  
Pollen Productivity ◽  
Fall Speed

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.

Pollen productivity estimates strongly depend on assumed pollen dispersal

The Holocene ◽  
2012 ◽  
Vol 23 (1) ◽  
pp. 14-24 ◽  
Author(s):  
Martin Theuerkauf ◽  
Anna Kuparinen ◽  
Hans Joosten
Keyword(s):  
Pollen Dispersal ◽  
Pollen Grains ◽  
Data Sets ◽  
Pollen Data ◽  
Data Set ◽  
Model Studies ◽  
Pollen Productivity ◽  
Dispersal Distances ◽  
Value Model ◽  
Pollen Dispersal Models

Past plant abundance may be reconstructed from pollen data if dispersal distances of pollen and pollen productivities of each taxon are known. Using surface sediment samples from small and medium sized, closed and near circular lakes from lowland Central Europe, we tested the validity of three pollen dispersal models by comparing empirical pollen data from each lake with simulated pollen data derived from applying various pollen dispersal models to vegetation data from rings situated up to 100 km from each site. Pollen assemblages simulated with a Lagrangian stochastic (LS) model best fit real pollen assemblages, simulations with the commonly used Prentice model on pollen dispersal underestimated the amount of pollen arriving from distances larger than 10 km and overestimated the differences in dispersal distances between lighter ( Pinus) and heavier ( Fagus, Picea) pollen grains. The LS model appeared to provide more appropriate simulations. Pollen productivity estimates (PPEs) calculated for the data set showed that the choice of the dispersal model has great impact on the results. If derived with the Prentice model, PPEs for Fagus and Picea are three times higher than with the LS model. Studies on pollen productivities thus need to consider the apparent limitations of the Prentice model. We suggest an alternative approach, which uses simulations instead of the extended R-value model, to calculate PPEs. The approach is flexible in the use of dispersal functions and produced consistent results for two independent data sets from small and medium sized lakes.

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

2021 ◽  
Vol 5 (1) ◽  
pp. 86-93
Author(s):  
Stoyan Ivanov Vergiev ◽  
Mariana Filipova-Marinova ◽  
Daniela Toneva ◽  
Todorka Stankova ◽  
Diyana Dimova ◽  
...  
Keyword(s):  
Source Area ◽  
Critical Parameters ◽  
Vegetation Composition ◽  
Pollen Data ◽  
Plant Abundance ◽  
Pollen Type ◽  
Modern Pollen ◽  
Downstream Region ◽  
Pollen Productivity ◽  
Gis Environment

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.

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

The Holocene ◽  
2019 ◽  
Vol 29 (7) ◽  
pp. 1109-1112
Author(s):  
Julien Azuara ◽  
Florence Mazier ◽  
Vincent Lebreton ◽  
Shinya Sugita ◽  
Nicolas Viovy ◽  
...  
Keyword(s):  
Environmental Changes ◽  
Coastal Lagoons ◽  
Pollen Dispersal ◽  
Local Scale ◽  
Mechanistic Models ◽  
Pollen Data ◽  
Plant Abundance ◽  
Quantitative Reconstruction ◽  
Quantitative Estimates ◽  
Lake Deposits

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.

Modern pollen-vegetation-climate relationships and pollen productivity estimates for common East Siberian taxa

2021 ◽  
Author(s):  
Rongwei Geng ◽  
Andrei Andreev ◽  
Stefan Kruse ◽  
Yan Zhao ◽  
Ulrike Herzschuh ◽  
...  
Keyword(s):  
Field Survey ◽  
Source Area ◽  
Soil Samples ◽  
Lake Surface ◽  
East Siberia ◽  
Climate Conditions ◽  
Modern Pollen ◽  
Pollen Productivity ◽  
Paleoclimate Reconstructions ◽  
R Value

<p>East Siberia is an ideal area for investigating the relationships between modern pollen assemblages and vegetation under the extremely cold and dry climate conditions. These relationships are the basis of paleovegetation and paleoclimate reconstructions from fossil pollen records. Pollen productivity estimates (PPE) are required for reliable pollen-based quantitative vegetation reconstructions. Here, we present a new pollen dataset of 48 moss/soil and 24 lake surface sediment samples collected from Chukotka and Yakutia. Generally, tundra and taiga vegetation sites can be well distinguished in the surface pollen assemblages from East Siberia. Moss/soil and lake samples have mostly similar pollen assemblages but contents of some pollen taxa may vary significantly in different sample types. We classified drone images based on field survey to obtain high-resolute vegetation data. Pollen counts in moss/soil samples and vegetation data can? be used in the Extended R-Value (ERV) model to estimate the relevant source area of pollen (RSAP) and the PPEs of major plant taxa. The result of PPE calculation for most common taxa (Alnus, Betula, Cyperaceae, Ericaceae, Larix, Pinus and Salix) can be used to improve vegetation reconstructions.</p>

scholarly journals The Relative Pollen Productivity and Pollen Representation of North European Trees, and Correction Factors for Tree Pollen Spectra. Determined by Surface Pollen Analyses from Forests

1970 ◽  
Vol 96 ◽  
pp. 1-99
Author(s):  
Svend Th. Andersen
Keyword(s):  
Tree Species ◽  
Small Sample ◽  
Forest Composition ◽  
Pollen Deposition ◽  
Correction Factors ◽  
Tree Crown ◽  
Tree Pollen ◽  
Surface Samples ◽  
Pollen Productivity ◽  
Pollen Analyses

The present work deals primarily with a determination of the relative pollen productivity of various trees from North Europe by means of their representation in pollen analyses of surface samples from forests, with the aim to calculate correction factors for pollen diagrams.Surface samples from 2 forests in Denmark were examined. The forest composition was determined by tree crown areas and tree basal areas in small sample plots. The relation of the tree crown areas to the tree basal areas was determined for the various tree species, and the data for crown area composition, basal area composition and tree frequency were compared.The pollen preservation in the various surface samples was examined.Data on wind conditions are mentioned in the chapter about pollen dispersal in the forest, and the various modes of pollen transfer are discussed. The amount of exotic pollen in the samples is used as a calculation basis for the tree pollen frequencies, and the occurrence and composition of the exotic pollen is discussed.The relationship of the forest composition to the tree pollen deposition is discussed. Pollen deposition and pollen productivity is expressed by a regression equation. The relative pollen productivity of the tree species is expressed in relation to a reference species, in the present case Fagus silvatica. Pollen representation and relative pollen representation are determined by a comparison of pollen percentages with percentages for areal frequency.Pollen productivity factors, pollen representation and correction factors were determined for Danish species of Quercus, Betula, Alnus, Carpinus, Ulmus, Fagus, Tilia and Fraxinus by means of the pollen frequencies in the surface samples. Corrected pollen percentages were compared with the tree areal percentages in the sample plots. Data for the pollen frequencies of forest plants other than the trees are presented. The data on trees from Denmark are compared with other data from Northern Europe, and correction factors were calculated for species of Pinus, Picea and Abies.Tree pollen spectra from outside the forest are discussed and the relative pollen representation is calculated. The present calculations of the relative pollen productivity of the trees are compared with previous estimates, and the application of the correction factors to pollen diagrams is discussed.

scholarly journals Relación lluvia de polen-vetación en selvas de Quintana Roo

2017 ◽  
pp. 31 ◽  
Author(s):  
Gerald A. Islebe ◽  
Rogel Villanueva-Gutiérrez ◽  
Odilón Sánchez-Sánchez
Keyword(s):  
Zea Mays ◽  
Quintana Roo ◽  
Vegetation Types ◽  
Pollen Data ◽  
Indicator Taxa ◽  
Modern Pollen ◽  
Pollen Content ◽  
Ordination Techniques ◽  
Ordination Analysis ◽  
Pollen Rain

Modern pollen rain was studied along a 450 km long transect between Cancun-La Unión (Belizean border). Ten moss samples were collected in different vegetation types and analyzed for pollen content. The data were analyzed with classification (TWINSPAN), ordination analysis (DCA) and different association indices. Classification and ordination techniques allowed us to recognize three different pollen signals from semievergreen forest (with Maclura, Apocynaceae, Moraceae, Sapotaceae, Araceae, Cecropia, Celtis, Eugenia and Bursera), acahual (with con Coccoloba, Metopium, Anacardiaceae, Urticales, Melothria, Croton, Palmae) and disturbed vegetation (with Zea mays, Mimosa and Asteraceae ) . The degree of over-representation and underrepresentation of the pollen data with respect to the modem vegetation was established, being under-represented mostly entomophilous species. We can conclude that the actual pollen signal can be used for calibrating paleosignals, if clear groups of indicator taxa can be established.

scholarly journals Nearest neighbour models for local and regional avalanche forecasting

2002 ◽  
Vol 2 (3/4) ◽  
pp. 247-253 ◽  
Author(s):  
M. Gassner ◽  
B. Brabec
Keyword(s):  
Cross Validation ◽  
Local Scale ◽  
Swiss Federal Institute ◽  
Hazard Evaluation ◽  
Data Sets ◽  
Nearest Neighbour ◽  
Avalanche Forecasting ◽  
Federal Institute ◽  
Cross Country ◽  
Avalanche Warning

Abstract. This paper presents two avalanche forecasting applications NXD2000 and NXD-REG which were developed at the Swiss Federal Institute for Snow and Avalanche Re-search (SLF). Even both are based on the nearest neighbour method they are targeted to different scales. NXD2000 is used to forecast avalanches on a local scale. It is operated by avalanche forecasters responsible for snow safety at snow sport areas, villages or cross country roads. The area covered ranges from 10 km2 up to 100 km2 depending on the climatological homogeneity. It provides the forecaster with ten most similar days to a given situation. The observed avalanches of these days are an indication of the actual avalanche danger. NXD-REG is used operationally by the Swiss avalanche warning service for regional avalanche forecasting. The Nearest Neighbour approach is applied to the data sets of 60 observer stations. The results of each station are then compiled into a map of current and future avalanche hazard. Evaluation of the model by cross-validation has shown that the model can reproduce the official SLF avalanche forecasts in about 52% of the days.

Staminodes influence pollen removal and deposition rates in nectar-rewarding self-incompatible Phanera yunnanensis (Caesalpinioideae)

2019 ◽  
Vol 35 (1) ◽  
pp. 34-42
Author(s):  
Menglin Wang ◽  
Shuyin Huang ◽  
Manru Li ◽  
Doyle McKey ◽  
Ling Zhang
Keyword(s):  
Fruit Set ◽  
Removal Rate ◽  
Apis Cerana ◽  
Pollen Dispersal ◽  
Adaptive Significance ◽  
Western China ◽  
Pollen Deposition ◽  
Deposition Rates ◽  
Flower Visitation ◽  
Pollen Removal

AbstractStaminodes are sterile stamens that produce no pollen, exhibit diverse structures and perform various functions. Flowers of Phanera yunnanensis possess three fertile stamens with large anthers and long filaments, and seven staminodes with tiny anthers and short filaments. To investigate the adaptive significance of staminodes in this species, we studied effects of staminode removal on pollen removal and deposition, flower visitation rate and fruit set in Xishuangbanna, south-western China. Four species of nectar-foraging pollinators visited flowers, mostly Amegilla zonata and Apis cerana (2.80 ± 0.15 and 1.76 ± 0.41 visits h−1 per flower, respectively). Staminode removal did not affect fruit set, but increased visitation by A. cerana by 2.6-fold, reduced visitation by A. zonata by 68% and increased the pollen removal rate for both pollinators (all effects were significant). Staminode removal significantly reduced pollen deposition rate for A. zonata, but not for A. cerana. These results suggest that the staminodes of P. yunnanensis filter which insects act as pollinators and affect pollen removal and deposition rates. By reducing pollen removal rates, staminodes may implement a pollen-dispensing schedule that spreads pollen dispersal from individual flowers over multiple pollinators. By altering pollen deposition rates, staminodes may influence reproductive fitness in other ways.

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

2020 ◽  
Vol 95 ◽  
pp. 23-42 ◽  
Author(s):  
Mathias Trachsel ◽  
Andria Dawson ◽  
Christopher J. Paciorek ◽  
John W. Williams ◽  
Jason S. McLachlan ◽  
...  
Keyword(s):  
United States ◽  
Forest Dynamics ◽  
Pollen Dispersal ◽  
Parameter Estimates ◽  
Vegetation Composition ◽  
Northeastern United States ◽  
Bayesian Hierarchical ◽  
Pollen Productivity ◽  
Vegetation Models ◽  
Anthropogenic Land Use

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.

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