res.comp: Calculate resilience indices

View source: R/res.comp.R

res.compR Documentation

Calculate resilience indices

Description

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.

Usage

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

Arguments

data

a data.frame with tree-ring series (raw or detrended) as columns and years as rows (e.g., output of read.rwl, bai.in or bai.out of package dplR)

nb.yrs

a vector specifying the number of years for pre- and post-disturbance periods to be considered in calculating resilience components after Lloret et al. (2011). Defaults to 4 for both periods.

max.yrs.rec

a numeric specifying the maximum length of the recovery period to be considered. Defaults to 10.

Details

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

Value

The function returns a list containing the following components:

resist

a matrix with resistance values (i.e. relative growth changes) for individual tree-ring series

recov

a matrix with recovery values for individual tree-ring series

resil

a matrix with resilience values for individual tree-ring series

rel.resil

a matrix with relative resilience values for individual tree-ring series

rec.period

a matrix with recovery periods for individual tree-ring series in years with decimal places (cf. Fig. 2 in Thurm et al. 2016). In case of no growth reduction (and thus no recovery), 0 is given as output. Inf indicates that no recovery occurred within the period as specified by max.yrs.rec

avg.rec.rate

a matrix with average recovery rates for individual tree-ring series as percentage, calculated as 1 / rec.period * 100. In case of no growth reduction (and thus no recovery), NA is given as output. Inf indicates that no recovery occurred within the period as specified by max.yrs.rec

tot.abs.grow.red

a matrix with total absolute growth reduction values for individual tree-ring series. 0 and Inf are given as output as for rec.period

tot.rel.grow.red

a matrix with total growth reduction for individual tree-ring series expressed as percentage. 0 and Inf are given as output as for rec.period

avg.abs.grow.red

a matrix with average absolute growth reduction, i.e. total absolute growth reduction divided by the number of full years needed for recovery. 0 and Inf are given as output as for rec.period

avg.rel.grow.red

a matrix with average growth reduction expressed as percentage. 0 and Inf are given as output as for rec.period

nb.series

a data.frame with the number of series for which the diverse indices could be calculated, with years in rows and indices in columns

spec.param

a data.frame specifying the arguments used in the calculation

Author(s)

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

References

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.

Examples

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


pointRes documentation built on May 8, 2022, 1:05 a.m.