BIOdry (version 0.4)

ringApply: Multilevel apply

Description

Wrapper of Map to apply functions on multilevel data series and preserve factor-level structure in the outputs.

Usage

ringApply(rd, lv = 1, fn = "scacum", ...)

Arguments

rd

data.frame. Multileve ecological data series.

lv

numeric position, or character name, of an ecological factor in the processed MEDS.

fn

character name of the function to be evaluated (see details). Default 'scacum' computes scaled-cummulative radii.

...

Further arguments in the function being specified fn argument (see details)

Value

object preserving initial factor-level columns.

Details

Other functions such as rtimes, scacum, amod, or wlai can be implemented. Function arguments should be formulated as suggested in mapply, with no vectorized arguments being stored in a MoreArgs list. This function is implemented by modelFrame for recursive modeling of MEDS.

References

Lara, W., F. Bravo, D. Maguire. 2013. Modeling patterns between drought and tree biomass growth from dendrochronological data: A multilevel approach. Agric. For. Meteorol., 178-179:140-151.

Examples

##Multilevel ecological data series (MEDS) of tree-ring widths:
data(Prings05,envir = environment())
## Radial increments measured on 2003:
data(Pradii03,envir = environment())    
## MEDS of monthly precipitation sums and average temperatures:
data(PTclim05,envir = environment())

##Time units in Prings05 object are sinchronized at tree level
##with 'rtimes' function:
dfm1 <- ringApply(Prings05,lv = 2,fn = 'rtimes')
str(dfm1)
##time units from time 1 to time 9:
subset(dfm1,time%in%c(1:9,NA))

## Cummulative radial increments are processed at 'sample' level:
dfm2 <- ringApply(dfm1,lv = 'sample',y = Pradii03,fn = 'scacum')
str(dfm2)    
##Allometric modeling at 'sample' level:
dfm3 <- ringApply(dfm2,lv = 'sample',fn = 'amod',
                  MoreArgs = list(mp = c(1,1,0.25 * pi,2),
                                  un = c('mm','m')))
str(dfm3)

## seasonal years from 'October' to 'September':
cl1 <- ringApply(PTclim05,lv = 'year',fn = 'moveYr')
tail(cl1,15)
##using ringApply() function to compute multilevel aridity indexes 
##('wlai' function) at 'year' level:
wl <- ringApply(cl1,lv = 'year',fn = 'wlai')
str(wl)#only time units with 12 months are evaluated 

## A plot of the modeled fluctuations of aridity
d <- groupedData(lmeForm(wl),wl)
plot(d)