Title:	Temporal Altitudinal Biogeographic Shifts
Version:	0.1.1
Description:	A standardized workflow to reconstruct spatial configurations of altitude-bounded biogeographic systems over time. For example, 'tabs' can model how island archipelagos expand or contract with changing sea levels or how alpine biomes shift in response to tree line movements. It provides functionality to account for various geophysical processes such as crustal deformation and other tectonic changes, allowing for a more accurate representation of biogeographic system dynamics. For more information see De Groeve et al. (2025) <doi:10.3897/arphapreprints.e151900>.
License:	GPL (≥ 3)
URL:	https://uva_ibed_piac.gitlab.io/tabs/
BugReports:	https://gitlab.com/uva_ibed_piac/tabs/-/issues
Depends:	R (≥ 2.10)
Imports:	ape, dplyr, htmltools, htmlwidgets, httr, jsonlite, geojsonio, leaflet, leaftime, leaflet.extras, mapedit, qs2, rlang, sf, stringi, terra, gpkg, RSQLite
Encoding:	UTF-8
Language:	en-US
LazyData:	true
RoxygenNote:	7.3.2
NeedsCompilation:	no
Packaged:	2025-04-29 16:55:24 UTC; jedgroev
Author:	Johannes De Groeve [aut, cre], Sietze Norder [aut], Eline Sterre Rentier [aut], Suzette Flantua [ctb], Kenneth Rijsdijk [ctb]
Maintainer:	Johannes De Groeve <j.degroeve@uva.nl>
Repository:	CRAN
Date/Publication:	2025-04-29 17:30:02 UTC

Dataset: IPCC future predictions (2021-2100)

Description

Mean global sea level rise according to different scenarios (ssp1,ssp2,ssp3,ssp5) for 2021-2040, 2041-2060 and 2081-2100. The global means were calculated from global raster datasets available for download in the interactive IPCC atlas.

Usage

IPCC_global_mean

Format

A list four RSL vectors

year_before_after_present

years before or after present

sea_level_m

meters below or above the reference sea level expressed in m.

Source

IPCC, Kirsten B; Edwards, Ross L; Taylor, Frederick W; Cheng, H; Adkins, Jess F; Gallup, Christina D; Cutler, P M; Burr, George S; Bloom, Arthur L (2003): Rapid sea-level fall and deep-ocean temperature change since the last interglacial period. Earth and Planetary Science Letters, 206(3-4), 253-271. doi:10.1016/S0012-821X(02)01107-X https://interactive-atlas.ipcc.ch/regional-information

Examples

curves <- IPCC_global_mean
 

Dataset: Bintanja's Global sea level curve (0-3000000 BP)

Description

Global sea level curve of Bintanja & van de Wal (2008) from 0 to 3000000 BP.

Usage

bintanja

Format

A vector with:

year_before_after_present

years before or after present

sea_level_m

meters below or above the reference sea level expressed in m.

Source

Bintanja, R., van de Wal, R. (2008) North American ice-sheet dynamics and the onset of 100,000-year glacial cycles. Nature 454, 869–872 (2008). doi:10.1038/nature07158

Examples

curve <- bintanja

Create an Object of Class 'tabs'

Description

Constructs an S3 object of class 'tabs' containing reconstruct output.

Usage

create_tabs_class(x)

Arguments

Value

An object of class 'tabs'.

Dataset: Cutler's Global sea level curve (0-140000 BP)

Description

Global sea level curve of Cutler et al. (2003) from 0 to 140000 BP.

Usage

cutler

Format

A vector with:

year_before_after_present

years before or after present

sea_level_m

meters below or above the reference sea level expressed in m.

Source

Cutler, Kirsten B; Edwards, Ross L; Taylor, Frederick W; Cheng, H; Adkins, Jess F; Gallup, Christina D; Cutler, P M; Burr, George S; Bloom, Arthur L (2003): Rapid sea-level fall and deep-ocean temperature change since the last interglacial period. Earth and Planetary Science Letters, 206(3-4), 253-271. doi:10.1016/S0012-821X(02)01107-X

Examples

curve <- cutler

Leaflet map of present and paleo configurations for biogeographic systems

Description

generate a timelapse or exploration visualisation for a reconstructed biomes

Usage

explore(x, timelapse = NULL, filename = NULL)

Arguments

Details

explore

Value

html file

Examples

# load data samples
sporades <- sporades()
topo <- sporades$topo
labs <- sporades$labs
correction <- sporades$correction
curve <- sporades$curve

# subset first and last period 
curve <- curve[[c(1,dim(curve)[3])]]

# reconstruct
rec <- reconstruct(topo=topo,
                   region=labs,
                   curve=curve,
                   correction=correction,
                   reclabs='name'
                   )

# metadata
md <- metadata(rec)
                   
                   
# export     
dir <- tempdir() # export to temporary directory 
export(rec, paste0(dir,'/sporades.qs2'),overwrite=TRUE) # qs2 (faster and less storage than rds) 
export(rec, paste0(dir,'/sporades.rds'), overwrite=TRUE) # rds / rdata 
export(rec, paste0(dir,'/sporades'), overwrite=TRUE)  # datasets organized in directory  
#export(rec, paste0(dir,'/sporades.zip')) # zipped datasets 
            
                   
# import
rec <- import(filename=paste0(dir,'/sporades.qs2'))
rec <- import(filename=paste0(dir,'/sporades.rds'))
rec <- import(filename=paste0(dir,'/sporades'))
    
# explore 

## tabs class object
if (interactive()){
explore(rec) # comparison present reference and topo-based
explore(rec, timelapse=3) # paleo reconstruction 
}

## from exported object 
if (interactive()){
explore(paste0(dir,'/sporades.qs2'))
explore(paste0(dir,'/sporades.qs2'), timelapse=1)
}

# get area 
area <- get_area(rec) # using object class tabs 
area <- get_area(rec$recvect) # using recvect 

area <- get_area(paste0(dir,'/sporades.qs2')) # using exported object
unlink(dir)

Export a reconstruction of class tabs in various formats

Description

export data

Usage

export(x, filename, overwrite = FALSE)

Arguments

Value

No return value, called for side effects

Author(s)

Johannes De Groeve

Examples

# load data samples
sporades <- sporades()
topo <- sporades$topo
labs <- sporades$labs
correction <- sporades$correction
curve <- sporades$curve

# subset first and last period 
curve <- curve[[c(1,dim(curve)[3])]]

# reconstruct
rec <- reconstruct(topo=topo,
                   region=labs,
                   curve=curve,
                   correction=correction,
                   reclabs='name'
                   )

# metadata
md <- metadata(rec)
                   
                   
# export     
dir <- tempdir() # export to temporary directory 
export(rec, paste0(dir,'/sporades.qs2'),overwrite=TRUE) # qs2 (faster and less storage than rds) 
export(rec, paste0(dir,'/sporades.rds'), overwrite=TRUE) # rds / rdata 
export(rec, paste0(dir,'/sporades'), overwrite=TRUE)  # datasets organized in directory  
#export(rec, paste0(dir,'/sporades.zip')) # zipped datasets 
            
                   
# import
rec <- import(filename=paste0(dir,'/sporades.qs2'))
rec <- import(filename=paste0(dir,'/sporades.rds'))
rec <- import(filename=paste0(dir,'/sporades'))
    
# explore 

## tabs class object
if (interactive()){
explore(rec) # comparison present reference and topo-based
explore(rec, timelapse=3) # paleo reconstruction 
}

## from exported object 
if (interactive()){
explore(paste0(dir,'/sporades.qs2'))
explore(paste0(dir,'/sporades.qs2'), timelapse=1)
}

# get area 
area <- get_area(rec) # using object class tabs 
area <- get_area(rec$recvect) # using recvect 

area <- get_area(paste0(dir,'/sporades.qs2')) # using exported object
unlink(dir)

Dataset: features

Description

Features that can be defined as labeling points in the default dataset. point_reference dataset has been retrieved from geoNames.

Usage

features

Format

data frame

feature_class

feature class

feature_class_description

description of the feature class

feature

feature names

Source

GeoNames https://download.geonames.org/export/dump/

Examples

f <- features

Dataset: Funza (29500 up to 1000000 BP)

Description

The ‘páramos’ UFL, i.e. high altitude mountain ecosystem in Venezuela (Northern Andes), during the last 1 million years, regularized to intervals of 1 ky.

Usage

funza

Format

A vector with:

year_before_after_present

years before or after present

tree_line_m

tree line expressed in meters above the present day reference sea level.

Source

Flantua et al. (2019) doi:10.3389/fevo.2021.615223

Examples

curve <- funza

Get area in meter

Description

Get the area based on an object of class tabs or recvect object

Usage

get_area(filename, verbose = FALSE)

Arguments

Value

tabs object

Author(s)

Johannes De Groeve

Examples

# load data samples
sporades <- sporades()
topo <- sporades$topo
labs <- sporades$labs
correction <- sporades$correction
curve <- sporades$curve

# subset first and last period 
curve <- curve[[c(1,dim(curve)[3])]]

# reconstruct
rec <- reconstruct(topo=topo,
                   region=labs,
                   curve=curve,
                   correction=correction,
                   reclabs='name'
                   )

# metadata
md <- metadata(rec)
                   
                   
# export     
dir <- tempdir() # export to temporary directory 
export(rec, paste0(dir,'/sporades.qs2'),overwrite=TRUE) # qs2 (faster and less storage than rds) 
export(rec, paste0(dir,'/sporades.rds'), overwrite=TRUE) # rds / rdata 
export(rec, paste0(dir,'/sporades'), overwrite=TRUE)  # datasets organized in directory  
#export(rec, paste0(dir,'/sporades.zip')) # zipped datasets 
            
                   
# import
rec <- import(filename=paste0(dir,'/sporades.qs2'))
rec <- import(filename=paste0(dir,'/sporades.rds'))
rec <- import(filename=paste0(dir,'/sporades'))
    
# explore 

## tabs class object
if (interactive()){
explore(rec) # comparison present reference and topo-based
explore(rec, timelapse=3) # paleo reconstruction 
}

## from exported object 
if (interactive()){
explore(paste0(dir,'/sporades.qs2'))
explore(paste0(dir,'/sporades.qs2'), timelapse=1)
}

# get area 
area <- get_area(rec) # using object class tabs 
area <- get_area(rec$recvect) # using recvect 

area <- get_area(paste0(dir,'/sporades.qs2')) # using exported object
unlink(dir)

Get and prepare correction

Description

Get and prepare a correction dataset

Usage

get_correction(
  correction = NULL,
  topo = NULL,
  curve = NULL,
  units = list(topo = "m", curve = c(names = "yr", value = "m"), correction = "mm/yr"),
  verbose = FALSE
)

Arguments

Value

A SpatRaster or vector with corrrection values in a suitable format for the reconstruct function, including a value for each time step, defined by the curve.

Author(s)

Johannes De Groeve

See Also

correction

Examples

sporades <- sporades()
topo <- sporades$topo
correction <- sporades$correction
curve <- sporades$curve

cor <- get_correction(correction=correction,
                      topo=topo,
                      curve=curve)

Get and prepare curve

Description

load a curve of interest

Usage

get_curve(curve = NULL, verbose = FALSE)

Arguments

Value

A SpatRaster or vector with curve values in a suitable format for the reconstruct function.

Author(s)

Johannes De Groeve

See Also

curve

Examples

curve <- get_curve('lambeck')
curve <- get_curve('cutler')
curve <- get_curve('IPCC')
curve <- get_curve('funza')

curve <- get_curve()
curve <- get_curve(10)
curve <- get_curve(c(0,100,200,300,400,500))

# period definition curve 
cur <- c(0,100,200,300,400,500) # altitudes
names(cur) <- c(0,1,2,3,4,5) # periods 
curve <- get_curve(cur)

# add source attribute
cur <- c(0,100,200,300,400,500) # altitudes
names(cur) <- c(0,1,2,3,4,5) # periods 
attr(cur, 'source') <- 'new curve' # curve source 
curve <- get_curve(cur) 

# custom-curve from data frame
cur <- data.frame(period=0:10, 
                  altitude=seq(0,-20,-2), 
                  source='custom')
curve <- get_curve(cur)

Get and prepare input datasets (topo, labs, curve, correction)

Description

load and prepare input datasets topo, labs, curve and correction

Usage

get_data(
  region = NULL,
  topo = NULL,
  aggregate = FALSE,
  curve = NULL,
  correction = NULL,
  reclabs = NULL,
  units = list(topo = "m", curve = c(names = "yr", value = "m"), correction = "mm/yr"),
  buffer = NULL,
  fact = 0,
  verbose = FALSE
)

Arguments

Value

a list including topo, labs, curve and correction input datasets

Author(s)

Johannes De Groeve

Examples

# load data samples
sporades <- sporades()
topo <- sporades$topo
labs <- sporades$labs
correction <- sporades$correction
curve <- sporades$curve

# subset first and last period 
curve <- curve[[c(1,dim(curve)[3])]]


data <- get_data(topo=topo, 
                 region=labs, 
                 curve=curve)
data <- get_data(topo=topo, 
                 region=labs, 
                 curve=curve, 
                 correction=correction)

# run reconstruct using prepared input datasets                  
rec <- reconstruct(data)

get_reclabs

Description

reconstruct the labels based on labeling dataset. In a second step polygons are labelled per time step based on their most recent appearance

Usage

get_reclabs(labs, recvect, noise, verbose)

Arguments

Value

SpatVector

Author(s)

Johannes De Groeve

Get and prepare region

Description

Retrieve region of interest

Usage

get_region(
  region = NULL,
  buffer = NULL,
  reclabs = NULL,
  aggregate = FALSE,
  verbose = FALSE,
  overwrite = FALSE
)

Arguments

Value

A SpatVector object with the labeling polygons for the specified extent coming from spatial object, extent or region name

See Also

region

Examples

if(interactive()){
# interactive selection
r <- get_region()
# overwrite interactive selection
r <- get_region(overwrite=TRUE)
}

# sample dataset
labs <- sporades()$labs
# labels based on "name" column
r <- get_region(region=labs)
# labels based on specific column
r <- get_region(region=labs[,'plate'],reclabs='plate')
# automatic labeling 
r <- get_region(region=labs, reclabs = FALSE)
# aggregate shapes
r <- get_region(region=labs, aggregate=TRUE)
# define by extent 
library(terra)
e <- terra::ext(labs)
r <- get_region(region=e)
e <- as.vector(e)
r <- get_region(region=e)
# add buffer
r <- get_region(region=e,buffer=10000)
r <- get_region(region=e,buffer=100000)

Import a reconstruction as class tabs object

Description

import TABS object

Usage

import(filename)

Arguments

Value

object of class tabs including a list of input (topo, labs, curve, correction) and output (recvect, recrast, recarea) datasets

Author(s)

Johannes De Groeve

Examples

# load data samples
sporades <- sporades()
topo <- sporades$topo
labs <- sporades$labs
correction <- sporades$correction
curve <- sporades$curve

# subset first and last period 
curve <- curve[[c(1,dim(curve)[3])]]

# reconstruct
rec <- reconstruct(topo=topo,
                   region=labs,
                   curve=curve,
                   correction=correction,
                   reclabs='name'
                   )

# metadata
md <- metadata(rec)
                   
                   
# export     
dir <- tempdir() # export to temporary directory 
export(rec, paste0(dir,'/sporades.qs2'),overwrite=TRUE) # qs2 (faster and less storage than rds) 
export(rec, paste0(dir,'/sporades.rds'), overwrite=TRUE) # rds / rdata 
export(rec, paste0(dir,'/sporades'), overwrite=TRUE)  # datasets organized in directory  
#export(rec, paste0(dir,'/sporades.zip')) # zipped datasets 
            
                   
# import
rec <- import(filename=paste0(dir,'/sporades.qs2'))
rec <- import(filename=paste0(dir,'/sporades.rds'))
rec <- import(filename=paste0(dir,'/sporades'))
    
# explore 

## tabs class object
if (interactive()){
explore(rec) # comparison present reference and topo-based
explore(rec, timelapse=3) # paleo reconstruction 
}

## from exported object 
if (interactive()){
explore(paste0(dir,'/sporades.qs2'))
explore(paste0(dir,'/sporades.qs2'), timelapse=1)
}

# get area 
area <- get_area(rec) # using object class tabs 
area <- get_area(rec$recvect) # using recvect 

area <- get_area(paste0(dir,'/sporades.qs2')) # using exported object
unlink(dir)

Dataset: Lambeck's Global sea level curve (0-35000 BP)

Description

Global sea level curve of Lambeck et al. (2014) from 0 to 35000 BP.

Usage

lambeck

Format

A vector with:

year_before_after_present

years before or after present

sea_level_m

meters below or above the reference sea level expressed in m.

Source

Lambeck, Kurt; Rouby, Hélène; Purcell, Anthony; Sun, Y; Sambridge, Malcom (2014): Sea level and global ice volumes from the Last Glacial Maximum to the Holocene. Proceedings of the National Academy of Sciences, 111(43), 15296-15303. doi:10.1073/pnas.1411762111

Examples

curve <- lambeck

Metadata of object of class tabs (reconstruction)

Description

retrieve dataset and column descriptions as well as the sources from reconstruction object

Usage

metadata(x)

Arguments

Value

a list of data frames with a description of columns of vector datasets and the sources of the input datasets

Author(s)

Johannes De Groeve

Examples

# load data samples
sporades <- sporades()
topo <- sporades$topo
labs <- sporades$labs
correction <- sporades$correction
curve <- sporades$curve

# subset first and last period 
curve <- curve[[c(1,dim(curve)[3])]]

# reconstruct
rec <- reconstruct(topo=topo,
                   region=labs,
                   curve=curve,
                   correction=correction,
                   reclabs='name'
                   )

# metadata
md <- metadata(rec)
                   
                   
# export     
dir <- tempdir() # export to temporary directory 
export(rec, paste0(dir,'/sporades.qs2'),overwrite=TRUE) # qs2 (faster and less storage than rds) 
export(rec, paste0(dir,'/sporades.rds'), overwrite=TRUE) # rds / rdata 
export(rec, paste0(dir,'/sporades'), overwrite=TRUE)  # datasets organized in directory  
#export(rec, paste0(dir,'/sporades.zip')) # zipped datasets 
            
                   
# import
rec <- import(filename=paste0(dir,'/sporades.qs2'))
rec <- import(filename=paste0(dir,'/sporades.rds'))
rec <- import(filename=paste0(dir,'/sporades'))
    
# explore 

## tabs class object
if (interactive()){
explore(rec) # comparison present reference and topo-based
explore(rec, timelapse=3) # paleo reconstruction 
}

## from exported object 
if (interactive()){
explore(paste0(dir,'/sporades.qs2'))
explore(paste0(dir,'/sporades.qs2'), timelapse=1)
}

# get area 
area <- get_area(rec) # using object class tabs 
area <- get_area(rec$recvect) # using recvect 

area <- get_area(paste0(dir,'/sporades.qs2')) # using exported object
unlink(dir)

Reconstruct present- and paleoconfigurations for biogeographic systems

Description

reconstruct paleo or present day landscape using a bathymetric model, island labeling dataset and a seacurve

Usage

reconstruct(
  x = NULL,
  region = NULL,
  topo = NULL,
  curve = NULL,
  correction = NULL,
  iso = 0,
  reclabs = NULL,
  buffer = NULL,
  aggregate = FALSE,
  units = list(topo = "m", curve = c(names = "yr", value = "m"), correction = "mm/yr"),
  fact = 0,
  noise = 5,
  noiserm = TRUE,
  fillholes = TRUE,
  filename = NULL,
  overwrite = FALSE,
  metrics = c("area"),
  verbose = FALSE
)

Arguments

Details

==================================================================================
INPUT
==================================================================================

input dataset may be topo, curve, correction (optional) and a labs dataset:

TOPO

Topographic and/or bathymetric raster used to identify biogeographic shapes for the extent of the selected region.

CURVE

The relative altitude of a biogeographic system per time period compared to the present expressed as a numeric vector (e.g., Lambeck, Cutler, Funza) or raster (e.g., st_curve). In the case of st_curve, the curve is returned for the extent of the selected region and resampled to the resolution of the topo dataset. If the curve is not defined, 0 is returned and a reconstruction is made for the present-day sea level.

CORRECTION

Correction numeric vector or raster harmonized with the curve and resampled to the resolution of the topo dataset. If the input correction raster or numeric vector is defined as a rate (i.e., a single value, a single raster; thus, assuming temporal linear changes in topography), a correction variable (raster/numeric vector) is returned with the same length as the curve, expressing the cumulative topographic change over time. If the correction parameter is not defined, 0 is returned.

LABS

Labeling dataset that is used for naming biogeographic shapes for the extent of the selected region.

Returned variables:

unique_id

integer: Unique identifier of a biogeographic shape in the labeling dataset.

name

character: Name of the biogeographic shape in the labeling dataset. By default this will be derived from the Global Shoreline Vector (GSV; Sayre et al. 2019), or from the mountain inventory v2 (GMBA; Snethlage et al. 2022), when reclabs is set to ‘mnts’. Otherwise, if a custom polygon reference and labeling dataset is used, the name-column will store the content of a by the user specified column. NOTE: If the labeling column is specified by the user, that one will be stored as a duplicate in the labs output under its original name.

uniquename

character: Concatenated name and unique identifier.

refx

numeric: X-coordinate (SRID=4326) of the highest point of a biogeographic shape in the labeling dataset. If the labeling dataset are points, the x-coordinate of the point is given.

refy

numeric: Y-coordinate (SRID=4326) of the highest point of a biogeographic shape in the labeling dataset. If the labeling dataset are points, the y-coordinate of the point is given.

refz

numeric: Meter above/below present sea level of the highest point within a biogeographic shape extracted through intersection with topo. If the labeling dataset are points, the z of the point is given.

refn

integer: Number of cells at the resolution of the topo within a biogeographic shape in the labeling dataset. If the labeling dataset are points, the number of cells will equal 1.

Depending from the used labeling dataset (GSV, GMDA, GeoNames) additional other columns are returned.

==================================================================================
OUTPUT
==================================================================================

RECAREA

Table expressing the area in square meters for each biogeographic shape per time period.

RECRAST

Raster expressing the reconstruction of a biogeographic region per time period within the extent of the selected region.

RECVECT

Spatial vector expressing the reconstruction per time period, identifying each polygon as a different biogeographic shape. The vector layers include a range of default attributes per biogeographic shape.
NOTE: In case reclabs=FALSE, biogeographic shapes are merged into a single multipolygon, and all attributes in the vector layers are expressed for the whole region.

Returned variables:

iso

numeric: Meter above or below the curve value (e.g., sea level position) defining the lower bound of the range of a biogeographic system

period

character: Lower bound of a time period expressed in years before/after present for a reconstruction at a specific curve value (e.g., sea level position).

curve

numeric: Curve value (e.g., sea level position) for that period. In case of a raster (e.g., st_curve; spatial-explicit curve) the average curve value is calculated within the region.

unique_id

integer: Unique identifier of a biogeographic shape for a time period.

area

numeric: Size of a biogeographic shape in square meters.

n

integer: Number of cells at the resolution of the topo within a biogeographic shape; will change if the fact parameter is modified.

x

numeric: X-coordinate in degrees (SRID=4326) of the highest point within a biogeographic shape extracted through intersection with topo. If the highest point could not be extracted, the centroid of the biogeographic shape is used.

y

numeric: Y-coordinate in degrees (SRID=4326) of the highest point within a biogeographic shape extracted through intersection with topo. If the highest point could not be extracted, the centroid of the biogeographic shape is used.

z

numeric: Meter above/below present sea level of the highest point within a biogeographic shape extracted through intersection with topo. If the highest point could not be extracted, the centroid of the biogeographic shape is used.

recid

character: Reconstructed ID, when biogeographic shapes merge over time it is named after the shape with the highest point. The ID is unique across islands with identical names.

recname

character: Reconstructed name, when biogeographic shapes merge over time it is named after the shape with the highest point. It can have the following formats:

S-<PERIOD>-<ID>

S

biogeographic shape identified in topo but not in labeling dataset; or drowned biogeographic shapes that were disconnected from a present-day existing biogeographic shape

PERIOD

The most recent period the biogeographic shape emerged.

ID

Identifier.

UNKNOWN

The name of the biogeographic shape is intersecting with the labeling dataset but unknown (only for the Global Shoreline Vector - i.e. island labeling dataset).

UNNAMED

The name of the biogeographic shape is intersecting with the labeling dataset but unnamed (only for the Global Shoreline Vector - i.e. island labeling dataset).

recnames

json: JSON object including the name and ID of intersecting reconstructed polygons (from t0 until ti, where t = time period) within a reconstructed polygon of ti.

refnames

json: JSON object including the name and ID of intersecting labeling points/polygons (from t0 until ti, where t = time period) within a reconstructed polygon of ti.

=========

Value

object of class tabs including a list of input (topo, labs, curve, correction) and output (recvect, recrast, recarea) datasets

Author(s)

Johannes De Groeve

See Also

get started

tabs object structure

Examples

# load data samples
sporades <- sporades()
topo <- sporades$topo
labs <- sporades$labs
correction <- sporades$correction
curve <- sporades$curve

# subset first and last period 
curve <- curve[[c(1,dim(curve)[3])]]

# reconstruct
rec <- reconstruct(topo=topo,
                   region=labs,
                   curve=curve,
                   correction=correction,
                   reclabs='name'
                   )

# metadata
md <- metadata(rec)
                   
                   
# export     
dir <- tempdir() # export to temporary directory 
export(rec, paste0(dir,'/sporades.qs2'),overwrite=TRUE) # qs2 (faster and less storage than rds) 
export(rec, paste0(dir,'/sporades.rds'), overwrite=TRUE) # rds / rdata 
export(rec, paste0(dir,'/sporades'), overwrite=TRUE)  # datasets organized in directory  
#export(rec, paste0(dir,'/sporades.zip')) # zipped datasets 
            
                   
# import
rec <- import(filename=paste0(dir,'/sporades.qs2'))
rec <- import(filename=paste0(dir,'/sporades.rds'))
rec <- import(filename=paste0(dir,'/sporades'))
    
# explore 

## tabs class object
if (interactive()){
explore(rec) # comparison present reference and topo-based
explore(rec, timelapse=3) # paleo reconstruction 
}

## from exported object 
if (interactive()){
explore(paste0(dir,'/sporades.qs2'))
explore(paste0(dir,'/sporades.qs2'), timelapse=1)
}

# get area 
area <- get_area(rec) # using object class tabs 
area <- get_area(rec$recvect) # using recvect 

area <- get_area(paste0(dir,'/sporades.qs2')) # using exported object
unlink(dir)

Dataset: regions

Description

mountain ranges at different hierarchical levels, islands, archipelagoes, countries and plates that can be used for region selection

Usage

regions

Format

vector

dataset

the dataset (islands,mountains) for which the region definition can be used

region

region type

name

name of the region

name_ascii

name in ascii format

Source

Islands: Sayre et al. 2019 doi:10.1080/1755876X.2018.1529714

Plates: Bird, P. (2003) doi:10.1029/2001GC000252

Archipelagoes: Weigelt et al. 2013 doi:10.5061/dryad.fv94v

Countries: from rnaturalearth https://docs.ropensci.org/rnaturalearth/

Mountains: Snethlage et al. 2022 doi:10.48601/earthenv-t9k2-1407

Examples

r <- regions

Setup - Download of default datasets

Description

download default datasets (labs, topo, curve) in default or custom directory. The datasets require 15 GB disk space.

Usage

setup()

Value

No return value, called for side effects

Author(s)

Johannes De Groeve

Examples

if(interactive()){

# download labs, topo and curve and store in custom or default directory
setup()

# reset setup
# if you want the install the datasets under a different path
options(tabs.datasetPath=NULL)
setup()
}

Sporades sample dataset including topo, labs, curve and correction

Description

Sample dataset for the Sporades Archipelago in Greece

Usage

sporades()

Value

List of input sample datasets (topo, labs, curve, correction)

Author(s)

Johannes De Groeve