recruitment {CTFS} | R Documentation |
Computes annual recruitment rate for all trees or any user defined categorization of trees. Any two census datasets can be provided in order of date of census. The annual recruitment rate and other statistics are computed for user defined categories.
recruitment(census1, census2, mindbh=10, alivecode = c("A", "AB", "AS"), split1 = NULL, split2 = NULL)
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 |
mindbh |
minimum DBH in census1 for inclusion in computation. |
alivecode |
character, codes of the variable status
that indicate the tree is alive. The most general valid categories are: "A" and
"AB" and "AS". |
split1 |
a vector of categorical values of the same
length as census which groups trees into classes of
interest for which mortality 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 mortality values are computed. This vector can be
composed of characters or numbers. |
See CTFS.recruitment
for details on the computation of
recruitment 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.
Take care when creating a split vector based on dbh. The only valid dbh for a recruit is in the second census of any given interval. Recruits do not have a valid dbh for the first census of an interval as they are not large enough yet to enter the census. If the first census is used, then no recruits will be identified. So a dbh vector should be based on the dbh of the tree in the second census. The inverse is true for mortality. Therefore the same dbh split vector CANNOT be used for computations of recruitment and mortality. Use a dbh vector based on the census1 for mortality and on census2 for recruitment.
The results of recruitment
can be organized into
dataframes with the use of assemble.demography
.
recruit
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:
$N1 |
the number of living trees at the second census |
$R |
the number of trees that were recruited between the first and second census |
$rate |
the recruitment rate in %/year |
$lower |
the lower 95% confidence |
$upper |
the upper 95% confidence |
$time |
mean number of years between census for trees used in recruitment 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 recruitment rates and associated statistics are computed
for each value of the vectors. The vectors are nested so that
recruitment rates is computed for each category of split2
within each category of split1
. recruitment values are
returned for all levels of each vector and if no value can be
computed then 0 or NA is returned as appropriate.
Rick Condit and Pamela Hall
## Not run: 1. Default use of recruit() rec.out <- recruitment(tst.bci90.full,tst.bci95.full) rec.out 2. Create a vector of habitat for each tree based on the quadrate location of tree habitat.vct <- sep.quadinfo(tst.bci90.full,bciquad.info) rec.hab.out <- recruitment(tst.bci90.full,tst.bci95.full,split1=habitat.vct) ## End(Not run)