spatialwarnings: Early Spatial-Warnings of Ecosystem Degradation

In spatialwarnings: Spatial Early Warning Signals of Ecosystem Degradation

Early Spatial-Warnings of Ecosystem Degradation

Description

Many dynamical systems such as ecosystems exhibit non-linear responses to changes in their external drivers, resulting in possible wide state shifts with strong ecological or economical consequences. This often happens when a system exhibit a change in its stability properties as a threshold is crossed, e.g. going from multiple stable states to a single stable state. For a few decades, much research has been dedicated to finding a way to anticipate these tipping points in ecological systems. This has led to the development of several indicators, i.e. metrics based on spatial structure, that could reflect the proximity of an ecosystem to a tipping point.

This package implements the computation of these indicators, or early-warning signals (EWS), on spatial raster data. High-level functions and methods provide familiar workflows to compute the indicators and display their variations along environmental gradients or time-series. Lower-level functions are also available to integrate early-warning signals into different workflows.

Main functions provided by this package:

"Workflow" functions, which may compute several indicators at once:

• generic_sews: Generic spatial EWS

• spectral_sews: Spectrum-based EWS

• patchdistr_sews: EWS based on patch-size distributions

• kbdm_sews: Kolmogorov complexity

• flowlength_sews: Flow length

• variogram_sews: Variogram-based indicators

Individual indicators, which may be used to compute raw indicator values on a single matrix:

• raw_cg_moran: lag-1 spatial autocorrelation

• raw_cg_variance: Spatial variance

• raw_cg_skewness: Spatial skewness

• raw_sdr: Spectral density ratio (SDR)

• indicator_psdtype: Patch-size distribution shape

• indicator_plrange, raw_plrange : Power-law range

• raw_kbdm: Kolmogorov complexity

• raw_flowlength_uniform: Flow Length

• raw_variogram_metrics: Variogram-based metrics

The package homepage is available at Github and a user guide is also available.

spatialwarnings documentation built on March 21, 2022, 5:08 p.m.