The extended downscaling approach: A new R-tool for pollen-based reconstruction of vegetation patterns

The Holocene ◽  
2016 ◽  
Vol 27 (8) ◽  
pp. 1252-1258 ◽  
Author(s):  
Martin Theuerkauf ◽  
John Couwenberg
Keyword(s):  
R Package ◽  
Landscape Patterns ◽  
Statistical Computing ◽  
Pollen Deposition ◽  
Vegetation Patterns ◽  
Vegetation Composition ◽  
Large Lakes ◽  
Pollen Productivity ◽  
Complex Settings ◽  
Landscape Units

The extended downscaling approach (EDA) is a quantitative method in palynology that aims to detect past vegetation patterns and communities in the landscape. The EDA uses iterative forward modelling to fit vegetation composition to robust landscape patterns by comparing simulated with actually observed pollen deposition. The approach employs a set of pollen records, preferably from medium sized to large lakes or peatlands, as well as maps of robust landscape patterns, such as soils and relief. So far, the EDA has been applied in simple settings with only few taxa. To be able to apply the model also in more complex situations, we have implemented the EDA in the R environment for statistical computing. We here test the performance of the EDAinR function in five synthetic scenarios of increasing complexity. In all cases, the EDA is well able to reconstruct vegetation composition, also on rare landscape units. If uncertainty is added both to the pollen data and pollen productivity estimates, the EDA still correctly reconstructs species composition on more than 90% of the total landscape in all scenarios, underlining that the EDA performs well also in complex settings. The EDAinR function will be available within the R package DISQOVER.

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 Vegetation survey of the Khomas Hochland in central-western Namibia: syntaxonomical descriptions

Bothalia ◽  
2021 ◽  
Vol 51 (2) ◽  
Author(s):  
Ben Strohbach
Keyword(s):  
Vegetation Composition ◽  
Vegetation Survey ◽  
Data Set ◽  
Grassland Biome ◽  
Botanical Diversity ◽  
Riverine Habitats ◽  
Landscape Units ◽  
Great Escarpment ◽  
Fifth Order

Background: The Great Escarpment of southern Africa takes the form of an extended mountainous highland in central-western Namibia, commonly referred to as the ‘Khomas Hochland’. It is regarded as an area of high botanical diversity. Yet only few localised studies on the vegetation composition are available. The Khomas Hochland is formed on the southern part of the Damara Orogen and dominated by metamorphosed sediments. Climatically it forms a transition between the hot desert of the Namib and the slightly cooler hot steppe in the inland.Objectives: To classify and provide syntaxonomical descriptions of the vegetation of the Khomas Hochland.Methods: A dataset comprising 1151 relevés and 914 species was compiled from various surveys, mostly collected under, and to the standards of, the umbrella project ‘Vegetation Survey of Namibia’. For first classifications, the data set was reduced to a synusial set consisting of trees, shrubs, dwarf shrubs and grasses only.Results: The classification resulted in four major landscape units, being the Pre-Namib and Escarpment zone, the Khomas Hochland proper, riverine habitats as well as surrounding lowlands. The classification was further refined using Cocktail procedures to produce 30 associations, one with four sub-associations. These are described in this paper.Conclusion: A classification of synoptic data grouped the associations into five orders and one undefined cluster of associations on specialised desert habitats. Four of these orders correspond to the habitat types identified in the first classification. The fifth order, the Senegalio hereroensis–Tarchonanthoetalia camphorathi, represents high mountains of the central Khomas Hochland, which link biogeographically to the grassland biome in South Africa.

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.

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.

scholarly journals Motivation, values, and work design as drivers of participation in the R open source project for statistical computing

2015 ◽  
Vol 112 (48) ◽  
pp. 14788-14792 ◽  
Author(s):  
Patrick Mair ◽  
Eva Hofmann ◽  
Kathrin Gruber ◽  
Reinhold Hatzinger ◽  
Achim Zeileis ◽  
...  
Keyword(s):  
Quantitative Methods ◽  
Linear Models ◽  
R Package ◽  
Work Design ◽  
Social Characteristics ◽  
Statistical Computing ◽  
Hybrid Form ◽  
R Project ◽  
Design Characteristics ◽  
Psychological Scales

One of the cornerstones of the R system for statistical computing is the multitude of packages contributed by numerous package authors. This amount of packages makes an extremely broad range of statistical techniques and other quantitative methods freely available. Thus far, no empirical study has investigated psychological factors that drive authors to participate in the R project. This article presents a study of R package authors, collecting data on different types of participation (number of packages, participation in mailing lists, participation in conferences), three psychological scales (types of motivation, psychological values, and work design characteristics), and various socio-demographic factors. The data are analyzed using item response models and subsequent generalized linear models, showing that the most important determinants for participation are a hybrid form of motivation and the social characteristics of the work design. Other factors are found to have less impact or influence only specific aspects of participation.

scholarly journals EvolQG - An R package for evolutionary quantitative genetics

F1000Research ◽  
2015 ◽  
Vol 4 ◽  
pp. 925 ◽  
Author(s):  
Diogo Melo ◽  
Guilherme Garcia ◽  
Alex Hubbe ◽  
Ana Paula Assis ◽  
Gabriel Marroig
Keyword(s):  
Covariance Matrix ◽  
Quantitative Genetics ◽  
Quantitative Traits ◽  
Sampling Error ◽  
R Package ◽  
Mathematical Representation ◽  
Statistical Computing ◽  
Genetic Covariance ◽  
Error Matrix ◽  
Error Corrections

We present an open source package for performing evolutionary quantitative genetics analyses in the R environment for statistical computing. Evolutionary theory shows that evolution depends critically on the available variation in a given population. When dealing with many quantitative traits this variation is expressed in the form of a covariance matrix, particularly the additive genetic covariance matrix or sometimes the phenotypic matrix, when the genetic matrix is unavailable. Given this mathematical representation of available variation, the EvolQG package provides functions for calculation of relevant evolutionary statistics, estimation of sampling error, corrections for this error, matrix comparison via correlations and distances, and functions for testing evolutionary hypotheses on taxa diversification.

scholarly journals Shp2graph: Tools to Convert a Spatial Network into an Igraph Graph in R

2018 ◽  
Vol 7 (8) ◽  
pp. 293 ◽  
Author(s):  
Binbin Lu ◽  
Huabo Sun ◽  
Paul Harris ◽  
Miaozhong Xu ◽  
Martin Charlton
Keyword(s):  
Network Analysis ◽  
Road Network ◽  
R Package ◽  
Statistical Computing ◽  
Spatial Network ◽  
Computing Environment ◽  
Vast Array ◽  
Urban Road ◽  
Analytical Tools ◽  
Statistical Functions

In this study, we introduce the R package shp2graph, which provides tools to convert a spatial network into an ‘igraph’ graph of the igraphR package. This conversion greatly empowers a spatial network study, as the vast array of graph analytical tools provided in igraph are then readily available to the network analysis, together with the inherent advantages of being within the R statistical computing environment and its vast array of statistical functions. Through three urban road network case studies, the calculation of road network distances with shp2graph and with igraph is demonstrated through four key stages: (i) confirming the connectivity of a spatial network; (ii) integrating points/locations with a network; (iii) converting a network into a graph; and (iv) calculating network distances (and travel times). Throughout, the required R commands are given to provide a useful tutorial on the use of shp2graph.

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.

scholarly journals RCX – an R package adapting the Cytoscape Exchange format for biological networks

2021 ◽  
Author(s):  
Florian J Auer ◽  
Frank Kramer
Keyword(s):  
Biological Networks ◽  
Data Exchange ◽  
R Package ◽  
Statistical Computing ◽  
Biological Knowledge ◽  
Data Types ◽  
Web Technologies ◽  
Standard Data ◽  
Exchange Format ◽  
Web Standards

Motivation: The Cytoscape Exchange (CX) format is a JSON-based data structure designed for the transmission of biological networks using standard web technologies. It was developed by the network data exchange (NDEx), which itself serves as online commons to share and collaborate on biological networks. The Cytoscape software for the analysis and visualization of biological networks contributes further elements to capture the visual layout within the CX format. However, there is a fundamental difference between web standards and R of how data has to be structured. Results: Here we present a software package to create, handle, validate, visualize and convert networks in CX format to standard data types and objects within R. Networks in this format can serve as a source for biological knowledge, and also capture the results of the analysis of those while preserving the visual layout across all platforms. The RCX package connects the R environment for statistical computing with platforms for collaboration, analysis and visualization of biological networks. Availability: RCX is a free and open-source R package, available via GitHub (https://github.com/frankkramer-lab/RCX) and submitted to Bioconductor.

scholarly journals Self-Organizing Processes in Landscape Pattern and Resilience: A Review

ISRN Ecology ◽  
2012 ◽  
Vol 2012 ◽  
pp. 1-18 ◽  
Author(s):  
Donald L. DeAngelis
Keyword(s):  
Large Scale ◽  
Alternative Stable States ◽  
Bare Soil ◽  
Landscape Patterns ◽  
Vegetation Patterns ◽  
Vegetation Types ◽  
Stable States ◽  
Common Basis ◽  
Different Types ◽  
Halophytic Plants

Environmental conditions influence the way different types of vegetation are distributed on various scales from the landscape to the globe. However, vegetation does not simply respond passively but may influence its environment in ways that shape those distributions. On the landscape scale, feedbacks from vegetation can lead to patterns that are not easily interpreted as merely reflecting external abiotic conditions. For example, sharp ecotones exist between two vegetation types, even if the basic abiotic gradient is slight, somewhere along the gradient. These are observed in transitions between numerous pairs of ecosystem types, such as tree/grassland, tree/mire, tree tundra, and halophytic plants/glycophytic plants. More complex spatial vegetation patterns may also exist, such as alternating stripes or irregular patterns of either two types of vegetation or vegetation and bare soil. One purpose of this paper is to emphasize that these two types of patterns, sharp ecotones between vegetation types and large-scale landscape patterns of vegetation, both have a common basis in the concept of bistability, in which alternative stable states can occur on an area of land. Another purpose is to note that an understanding of the basis of these patterns may ultimately help in management decisions.

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