sitree (version 0.1-15)

recr.BBG2008: Recruitment function following BBG2008

Description

It creates a list of new trees based on the functions from BBG2008, Bollandsås et al. (2008) doi:10.1080/02827580801995315 . BBG2008 functions estimates recruitment on a plot based on stand basal area, SI, and pine, spruce, birch, and other broadleaved species abundance. The implementation of this function is stochastic, not deterministic. So, if run several times without setting a seed, the results will vary.

Usage

recr.BBG2008(tr, fl, common.vars, i.period, this.period, next.period, ...)
BBG2008 (SBA.m2.ha, SI.m, pr.spru.ba, pr.pine.ba, pr.birch.ba, 
    pr.other.ba)

Value

Returns a data frame with two columns for each of the four species, one for the probability of positive recruitment (spruce.p, pine.p, birch.p, other.p), and one for the conditional expected recruitment (spruce.e, pine.e, birch.e, other.e).

Arguments

tr

A trList object

fl

A list describing the plot information

common.vars

A list with at least 3 elements: a vector named SBA.m2.ha, stand basal area in m2; a data frame named pr.spp.ba, with the percentatge of basal area by species with column names spru, pine, birch, and other, and a vector named i.tree with the stands corresponding to each tree.

i.period

The number of period (from 0 to nperiods) for which to calculate recruitment.

this.period

Period to use to estimate next period recruitment.

next.period

Period for which to calculate recruitment.

SBA.m2.ha

Stand basal area in m2 per ha.

SI.m

Site index (SI) in m.

pr.spru.ba

Percentatge of spruce in terms of basal area.

pr.pine.ba

Percentatge of pine in terms of basal area.

pr.birch.ba

Percentatge of birch in terms of basal area.

pr.other.ba

Percentatge of other species in terms of basal area.

...

Not used.

Author

Clara Anton Fernandez

References

Bollandsås, O. M., Buongiorno, J., and Gobakken T. (2008). Predicting the Growth of Stands of Trees of Mixed Species and Size: A Matrix Model for Norway. Scandinavian Journal of Forest Research 23(2). 167-178.

Examples

foo.matrix <-  matrix(0, nrow = length(tr$dbh), ncol = (5 +1))
colnames(foo.matrix) <- paste("t", 0:5, sep = "")
foo.dbh <- foo.height <- foo.matrix
foo.dbh[,1] <- tr$dbh
foo.height[,1] <- tr$height

trl <- list(
  plot.id  = tr$plot.id,
  treeid    = tr$treeid,
  dbh.mm    = foo.dbh,
  height.dm = foo.height,
  yrs.sim   = rep(0, nrow(tr)),
  tree.sp   = factor(tr$tree.sp)
)
tr.i <- trList$new(data = trl, nperiods = as.integer(5))

## create a fake dead trees and removed trees.

common.vars <-  prep.common.vars.fun(
  tr = tr.i,
  fl = fl,
  this.period    = "t0",
  i.period       = 0,
  common.vars    = "NULL",
  mng.options    = NA,
  vars.required  = c("spp", "SBA.m2.ha", "pr.spru.ba"),
  period.length = 5,
  species.spruce = c(1, 2, 3),
  species.pine = c(10, 11, 20, 21, 29),
  species.harw = c(30, 31)
)

recr <- recr.BBG2008(tr.i, fl, common.vars$res, i.period = 0, this.period = "t0",
                     next.period = "t1")
str(recr)
bbg <- BBG2008 (common.vars$res$SBA.m2.ha[common.vars$res$i.tree],
                fl$SI.m,
                common.vars$res$pr.spp.ba$spru[common.vars$res$i.tree],
                common.vars$res$pr.spp.ba$pine[common.vars$res$i.tree],
                common.vars$res$pr.spp.ba$birch[common.vars$res$i.tree], 
                common.vars$res$pr.spp.ba$other[common.vars$res$i.tree])
str(bbg)