modelFrame {BIOdry}

Dendroclimatic-fluctuations modeling

Description

This function develops recursive evaluation of functions for one-level modeling (FOLM) and LME detrending of dendroclimatic chronologies.

Usage

modelFrame(rd, fn = list("rtimes", "scacum", "amod"), lv = list(2, 
    1, 1), form = "tdForm", ...)

Arguments

rd

data.frame or list. Dendroclimatic chronology or Multilevel ecological data series.

fn

list. Names of the functions for one-level modeling to be recursively implemented.

lv

list. numeric positions in the factor-level labels of rd to implement the one-level functions. If rd is a MEDS, then character names of the factor-level columns.

form

character or NULL. Name of a detrending formula. Two in-package methods are available: the default tdForm or lmeForm.

...

Further arguments in mUnits, or in the functions for one-level modeling, or in the lme function/methods, or in the detrending formula.

Details

Defaults model fluctuations in tree-ring width chronologies via recursive implementation of four FOLM: rtimes, scacum, amod, and frametoLme. Nevertheless, other FOLM can be implemented to model aridity-index fluctuations(see example with climatic data). Processed chronologies are detrended with lme function and other nlme methods . Internal algorithm uses shiftFrame arguSelect and ringApply functions. Consequently, arguments that are not iterated over factor-level labels in the processed data are specified in 'MoreArgs' lists (see examples). Arguments in modelFrame objects can be updated with update function.

Value

Threefold list with fluctuations in fluc, groupedData object in model, and model call in call.

Author(s)

Wilson Lara <[e-mail]>, Felipe Bravo <[e-mail]>

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

    ##TRW chronology (mm) and inside-bark radii
    data(Pchron,envir = environment())
    
    ## Parameters of allometric model to compute Diameter at Breast
    ## Height over bark (DBH, cm) from diameter inside bark (dib, cm)
    ## and Total Tree Biomass (TTB, kg tree -1 ) from DBH (Lara
    ## et. al. 2013):
    biom_param <- c(2.87, 0.85, 0.05, 2.5)

    ## Modeling tree-biomass fluctuations while accounting for
    ## within-plot source variability (see defaults in "modelFrame"
    ## function)
     
     trwf <- modelFrame(Pchron,
                        to = 'cm',
                        MoreArgs = list(mp = c(2,1, biom_param)),
                        log.t = FALSE,
                        on.time = FALSE)
 
    ## Climatic records:
    data(Temp,envir = environment())
    data(Prec,envir = environment())
    ## Aridity-index fluctuations:
     
     aif <- modelFrame(rd = list(Prec, Temp),
                       fn = list('moveYr','wlai'),
                       lv = list('year','year'),
                       form = 'lmeForm')
     summary(aif$'model')