scholarly journals Modern pollen data from Tuchola Forest

2017 ◽  
Vol 26 ◽  
pp. 27
Author(s):  
Anna Filbrandt-Czaja
Keyword(s):  
Pollen Data ◽  
Modern Pollen

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 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.

Application and limitations of the Artemisia/Chenopodiaceae pollen ratio in arid and semi-arid China

The Holocene ◽  
2012 ◽  
Vol 22 (12) ◽  
pp. 1385-1392 ◽  
Author(s):  
Yan Zhao ◽  
Hongyan Liu ◽  
Furong Li ◽  
Xiaozhong Huang ◽  
Jinghui Sun ◽  
...  
Keyword(s):  
Arid Regions ◽  
Positive Relationship ◽  
Vegetation Types ◽  
Pollen Data ◽  
Data Synthesis ◽  
Modern Pollen ◽  
Vegetation Zones ◽  
Desert Areas ◽  
Vegetation And Climate ◽  
Semi Arid

The Artemisia/Chenopodiaceae (A/C) ratio is assumed to be a useful index for reconstructing moisture changes in arid and semi-arid regions. Thorough modern pollen studies are still lacking to understand the reliability and limitation of A/C ratio as a moisture indicator, however. Here we review how well this ratio can be applied in arid and semi-arid China on the basis of new surface pollen data, previous data synthesis and other publications. Results indicate that variance in the A/C ratio can permit identification of modern vegetation types and that the A/C ratio generally has a positive relationship with annual precipitation. However, soil salinity, vegetation community composition, human activity and sample provenance (e.g. soil and lake sediments) will affect the values of the A/C ratio in different vegetation zones and therefore the A/C ratio is not comparable in different regions. We argue that the A/C ratio can only be used to reconstruct vegetation types and climate change in regions with precipitation <450–500 mm, and in steppe, steppe desert and desert areas. Careful studies should be undertaken to understand the modern pollen–vegetation–climate relationships in various regions before using the A/C ratio to interpret vegetation and climate.

Modern pollen data from North America and Greenland for multi-scale paleoenvironmental applications

2005 ◽  
Vol 24 (16-17) ◽  
pp. 1828-1848 ◽  
Author(s):  
J. Whitmore ◽  
K. Gajewski ◽  
M. Sawada ◽  
J.W. Williams ◽  
B. Shuman ◽  
...  
Keyword(s):  
North America ◽  
Pollen Data ◽  
Multi Scale ◽  
Modern Pollen

Quantitative Estimates of Temperature Changes Over the Last 2700 Years in Michigan Based on Pollen Data

1981 ◽  
Vol 15 (2) ◽  
pp. 143-159 ◽  
Author(s):  
J. Christopher Bernabo
Keyword(s):  
Sediment Cores ◽  
The Other ◽  
Stratigraphic Correlation ◽  
Calibration Function ◽  
Climate Data ◽  
Pollen Data ◽  
Radiocarbon Dates ◽  
Temperature Changes ◽  
Fine Grained ◽  
Modern Pollen

AbstractTemperatures for the past 2700 yr are estimated using well-dated pollen data from northwestern lower Michigan. The pollen data were sampled from sediment cores of four lakes along a 75-km transect, with fine-grained morainic soils around the two western lakes and sandy outwash soils around the lakes to the east. Climatic reconstructions based on the pollen data from the sandy sites show less temperature change than the reconstructions from the other sites, because variations in the composition of the vegetation at the sandy sites are edaphically restricted. One of the cores studied was dated by counting visible annual laminations (varves). The cores from the other lakes were dated based on three radiocarbon dates per core as well as the historically determined age of the settlement horizons. All the time scales were cross-checked using pollen-stratigraphic correlation between the four sites. A calibration function was developed using a network of modern pollen and climate data covering all of lower Michigan. Based on this calibration function, the 2700-yr reconstruction for Marion Lake indicates an estimated growing-season temperature range of 1.3°C between extreme 30-yr means. Mild conditions persisted prior to ca. A.D. 400, but a cold interval occurred between ca. A.D. 500 and 800. The well-marked warm period evident from ca. A.D. 1000 to 1200 was the last time when temperatures were about equal to the 1931–1960 mean. A prolonged longed cooling occurred after A.D. 1200 and reached 1°C below the 1931–1960 mean by the 1700s. A warming of 0.5°C is indicated from ca. A.D. 1750 to 1850. The estimated temperatures for the 1830s at Marion Lake agree with the instrumental data for that period and this provides some validation of the calibration-function results.

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.

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