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spatialwarnings (version 3.1.0)

Spatial Early Warning Signals of Ecosystem Degradation

Description

Tools to compute and assess significance of early-warnings signals (EWS) of ecosystem degradation on raster data sets. EWS are spatial metrics derived from raster data -- e.g. spatial autocorrelation -- that increase before an ecosystem undergoes a non-linear transition (Genin et al. (2018) ).

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Install

install.packages('spatialwarnings')

Monthly Downloads

301

Version

3.1.0

License

MIT + file LICENSE

Issues

9

Pull Requests

0

Stars

14

Forks

4

Maintainer

Alexandre Genin

Last Published

September 6th, 2024

Functions in spatialwarnings (3.1.0)

label

Labelling of unique patches and detection of percolation.
forestgap

A list of binary matrices and their associated parameters
indicator_psdtype

Change in patch-size distributions types
generic_sews

Generic Spatial Early-Warning signals
lsw_sews

Indicators based on the LSW distribution
kbdm_sews

Indicator based on Kolmogorov Complexity
patchdistr_sews

Early-warning signals based on patch size distributions
patchdistr_sews_plot

Early-warning signals based on patch size distributions
raw_kbdm

Kolmogorov complexity of a matrix
raw_flowlength_uniform

Flow length (uniform slope)
raw_cg_variance

Spatial variance indicator
raw_clustering

Clustering of pairs
serengeti

Serengeti dataset
pl_fit

Distribution-fitting functions
raw_structvar

Structural variance
plot_spectrum

Display the r-spectrum of a spectral_sews object
rspectrum

r-spectrum
raw_sdr

Spectral Density Ratio (SDR) indicator
raw_moran

Spatial correlation at lag 1
patchdistr_sews_predict

predict method for patchdistr_sews objects
raw_plrange

Power-law range indicator
patchsizes

Get patch sizes.
raw_cg_moran

Moran's Index at lag of 1
xmin_estim

Estimate the minimum patch size of a power-law distribution
variogram_sews_predict

predict() method for variogram_sews objects
raw_cg_skewness

Skewness indicator
reexports

Objects exported from other packages
raw_variogram_metrics

Variogram parameters
variogram_sews

Early-Warning signals based on variograms (EXPERIMENTAL)
plot.simple_sews_test

Spatial early-warning signals: display of trends
simple_sews

simple_sews objects
variogram_sews_plot

Early-warning signals based on variograms
spectral_sews

Spectrum-based spatial early-warning signals.
spatialwarnings

Early Spatial-Warnings of Ecosystem Degradation
convert_to_matrix

Convert an object to a matrix
display_matrix

Plot a matrix
dLSW

The Lifshitz-Slyozov-Wagner distribution
flowlength_sews

Flowlength connectivity indicator (uniform topography)
dda

Density-dependent aggregation model
create_indicator

Custom Spatial Early-Warning signals
extract_variogram

extract_variogram() method for variogram_sews objects
extract_spectrum

Extract the r-spectrum from objects
coarse_grain

Matrix coarse-graining
indictest

Significance-assessment of spatial early-warning signals
indicator_plrange

Power-law range indicator
arizona

Aerial views of vegetation from Arizona, USA