Description Usage Arguments Details See Also Examples

Plot early-warning signals based on patch size distributions

1 2 3 4 |

`x` |
An object as produced by |

`along` |
A vector providing values over which the indicator trend
will be plotted. If |

`...` |
Further arguments passed to methods |

`best_only` |
Plot only the best fit the empirical (inverse cumulative) patch-size distribution with an overlay of the estimated fits. |

`plrange` |
Plot the power-law range |

The `plot`

function will produce a complex figure summarizing the change
in patch size distributions along a set of values. The figure has two
panels:

the upper panel shows the percolation status of empty (

`FALSE`

) and occupied cells (`TRUE`

), and shows the mean value (proportion of`TRUE`

values). The background shows the proportion of each type of distribution for each unique values of the`along`

vector.the bottom panel displays the power-law range

The `plot_spectrum`

function displays each distribution in an
individual facet, with an overlay of the best distribution fit and a blue
bar showing the power-law range. This mode of representation can be
cumbersome when working with a high number of matrices but displays the
full shape of the distributions.

1 2 3 4 5 6 7 8 9 10 11 12 13 | ```
## Not run:
data(forestgap)
psd_indic <- patchdistr_spews(forestgap)
plot(psd_indic, along = forestgap.pars[ ,"d"])
# When along is non-numeric, bars are used for display
plot(psd_indic, along = as.factor(forestgap.pars[ ,"d"]))
# Display individual distributions
plot_distr(psd_indic, along = forestgap.pars[ ,"d"])
## End(Not run)
``` |

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