growth {CTFS} | R Documentation

## Annual Growth Rates by Categories (User defined groups)

### Description

Computes annual growth rate for all trees or any user defined categorization of trees. Two growth rates can be computed: simple change in dbh over time and relative growth rate. Unrealistically high and low values are removed from the summary values. Growth rate in mm dbh per year, relative growth rate in % change in dbh per year, standard deviation or 95% confidence limits, and sample size are provided. Two datasets must be used, one for each census.

### Usage

    growth(census1, census2,
            rounddown = FALSE, method = "I", stdev = FALSE,
            mindbh = 10, err.limit = 4, maxgrow = 75,
            split1 = NULL, split2 = NULL)

### Arguments

`census1` | name of census datafile for first census, must be a dataframe, must be of same length as `census2`
`census2` | name of census datafile for second census, must be a dataframe, must be of same length as `census1`
`rounddown` | logical value in caps. When TRUE, if either of census is < 55, then the `floor` of the dbh value / 5 is provided. When FALSE, no change in the dbh is made.
`method` | character indicating the type of growth rate to be calculated. When "I" the annual change in dbh is provided. When "E" the relative growth rate is provided. see `CTFS.growth` for more details on `method`.
`stdev` | logical value in caps. When TRUE, the standard deviation of growth is provided. When FALSE, a 95% condfidence interval is provided. The confidence limits are not computed.
`mindbh` | minimum DBH in `census1` for inclusion in computation.
`err.limit` | number of standard deviations: used for determining if an individual tree growth rate is too high or low for inclusion.
`maxgrow` | maximum absolute growth rate, mm per year: used for determining if an individual tree growth rate is too high for inclusion.
`split1` | a vector of categorical values of the same length as `census` which groups trees into classes of interest for which growth values are computed. This vector can be composed of characters or numbers.
`split2` | a second vector of categorical values of the same length as `census` which groups trees into classes of interest for which growth values are computed. This vector can be composed of characters or numbers.

### Details

See `CTFS.growth` for details on the computation of growth rates and associated functions.

Any two censuses on a datafile must be used. They do not have to be sequential, only that `census1` has to be before `census2`.

The vectors `split1` and `split2` must be of the same length as `census1` and `census2` but can contain NA.

The results of `growth` can be organized into dataframes with the use of `assemble.demography`.

### Value

`growth` returns a list of arrays with the values of `split1` as the first dimension and the values of `split2` as the second dimension of the array. The array contains the following named components:

`$N0` | the number of trees used to compute growth rate
`$rate` | the annual mean growth rate in mm per year or % per year, type determined by the argument `method`
`$clim` | the 95% confidence limit based on a normal distribution
`$dbhmean` | the mean dbh in mm for trees used to compute growth rate
`$meanyrs` | mean number of years between census for trees used in growth rate computation.
`$date0` | mean date of first census
`$date1` | mean date of second census

If the vector(s) `split1` and `split2` are provided by the user, then growth rates and associated statistics are computed for each value of the vectors. The vectors are nested so that growth rates is computed for each category of `split2` within each category of `split1`

### Author(s)

Rick Condit and Pamela Hall

### See Also

`CTFS.growth`

### Examples

    ## Not run:
    1. Default use of growth()

    growth.all.out <- growth(tst.bci90.full,tst.bci95.full)
    growth.all.out

    2. Create a vector of species names for each tree to compute growth
    rates for each species.

    bci.spp.vct <- tst.bci90.full$sp
    names(growth.spp.out)
    growth.spp.out$rate

    3.  Create 2 vectors: the first of habitats based on the quad location
    of each tree and the second of tree species names.

    bci.hab.vct <- sep.quadinfo(tst.bci90.full,bciquad.info,by.col="hab")
    growth.spp.hab.out <- growth(tst.bci90.full,tst.bci95.full,split1=bci.spp.vct,split2=bci.hab.vct)
    growth.spp.hab.out$rate

    ## End(Not run)

[Package CTFS version 1.00 Index]