res.comp | R Documentation |

The function calculates resilience indices on a `data.frame`

, e.g., of tree-ring series, after Lloret et al. (2011; i.e. resistance, recovery, (relative) resilience), Thurm et al. (2016; recovery period, total growth reduction) and Schwarz et al. (2020; average growth reduction, average recovery rate), useful to analyze growth responses of individual trees prior, during and after extreme events / disturbances. The component 'resistance' is conceptually identical to 'abrupt growth changes' as described in Schweingruber et al. (1990; cf. `pointer.rgc`

). 'Recovery' is the ability of tree growth to recover after disturbance, whereas 'resilience' reflects the ability of trees to reach pre-disturbance growth levels. Weighting of the resilience by the experienced growth reduction results in 'relative resilience'. 'Recovery period' (or: 'growth recovery time') is the time needed to reach pre-disturbance growth levels again. 'Total growth reduction' reflects the cumulative growth reduction in the year of disturbance as well as the associated years in the recovery period. 'Average growth reduction' is the total growth reduction divided by the length of the recovery period. 'Average recovery rate' is the mean percentual recovery over the recovery period.

```
res.comp(data, nb.yrs = c(4,4), max.yrs.rec = 10)
```

`data` |
a |

`nb.yrs` |
a |

`max.yrs.rec` |
a |

The function calculates various resilience indices after Lloret et al. (2011), Thurm et al. (2016) and Schwarz et al. (2020). The output provides different matrices with resilience indices for individual tree-ring series and years.

In calculating resilience indices the number of pre- and post disturbance years (

), as well as the maximum number of years to be considered in defining the recovery period (`nb.yrs`

) can be specified.
`max.yrs.rec`

The function returns a `list`

containing the following components:

`resist` |
a |

`recov` |
a |

`resil` |
a |

`rel.resil` |
a |

`rec.period` |
a |

`avg.rec.rate` |
a |

`tot.abs.grow.red` |
a |

`tot.rel.grow.red` |
a |

`avg.abs.grow.red` |
a |

`avg.rel.grow.red` |
a |

`nb.series` |
a |

`spec.param` |
a |

Marieke van der Maaten-Theunissen, Ernst van der Maaten and Mario Trouillier.

Lloret, F., Keeling, E.G. and Sala, A. (2011) Components of tree resilience: effects of successive low-growth episodes in old ponderosa pine forests. *Oikos* 120: 1909-1920.

Schwarz, J., Skiadaresis, G., Kohler, M., Kunz, J., Schnabel, F., Vitali, V. and Bauhus, J. (2020) Quantifying growth responses of trees to drought — a critique of commonly used resilience indices and recommendations for future studies. *Current Forestry Reports* 6: 185-200.

Schweingruber, F.H., Eckstein, D., Serre-Bachet, F. and Bräker, O.U. (1990) Identification, presentation and interpretation of event years and pointer years in dendrochronology. *Dendrochronologia* 8: 9-38.

Thurm, E.A., Uhl, E. and Pretzsch, H. (2016) Mixture reduces climate sensitivity of Douglas-fir stem growth. *Forest Ecology and Management* 376: 205-220.

```
## Calculate resilience indices on tree-ring series
data(s033)
res <- res.comp(s033)
```

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