Spatial Early Warning Signals of Ecosystem Degradation

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


spatialwarnings v1.3 (Release date: 2018-12)

New indicators:

  • Planar flowlength (Mayor et al. 2013, Rodriguez et al. 2017)
  • Kolmogorov complexity based on Block Decomposition Method (Dakos and Soler-Toscano 2016)


  • Enable parallel computation of patch size distributions
  • Added a dataset of aerial view of vegetation in Arizona ('arizona')
  • Added functions to compute the coarse-grained variance/skewness on a single matrix

Bug fixes and code improvements:

  • Added missing methods exports for custom indicators
  • Fixed the patch labelling for non-square images
  • General code cleanup and improvement

Documentation and description changes:

spatialwarnings v1.2 (Release date: 2018-06)

Bug fixes:

  • Compilation errors should be fixed on Solaris
  • Fixed coarse-graining bug when input values are non-integer

spatialwarnings v1.1 (Release date: 2018-06)

This release provides changes as to satisfy referees' comments prior to the publication of the package, as long as minor improvements in documentation.

New features:

  • Support for custom indicators (see ?create_indicator)

Minor changes:

  • Documentation improvements
  • Safer handling of small matrices in SDR computation

Name changes

  • *_spews functions are now deprecated in favor of *_sews functions

Bug fixes

  • Counting patches in matrices with 1 line or 1 column does not crash R anymore
  • The R package should now build on Solaris

spatialwarnings v1.0 (Release date: 2017-11-03)

Initial release

Reference manual

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3.0.2 by Alexandre Genin, a month ago

Browse source code at

Authors: Alain Danet , Alexandre Genin , Vishwesha Guttal , Sonia Kefi , Sabiha Majumder , Sumithra Sankaran , Florian Schneider

Documentation:   PDF Manual  

MIT + file LICENSE license

Imports Rcpp, ggplot2, plyr, stats, utils, future.apply, gsl, segmented

Depends on future

Suggests moments, poweRlaw, reshape2, testthat, covr, acss, mgcv, gstat, sp, raster

Linking to Rcpp, RcppArmadillo

See at CRAN