Package 'sitree'

Calculate Development Class of the Stand

Description

Calculates the development class of the stand according to the Norwegian National Forest Inventory.

Usage

calculate.development.class(SI.spp, SI.m, stand.age.years)

Arguments

SI.spp	Species for which the SI is calculated (1 = spruce, 2 = pine, 3 = deciduous).
SI.m	Site index (SI) in m.
stand.age.years	Age of the stand in years.

Details

Development classes 1 (regeneration) to 5 (mature).

Value

It returns a vector with the development class of the stands (values 1 to 5).

Author(s)

Clara Anton Fernandez [email protected]

Examples

calculate.development.class (SI.spp = c(1, 1, 2),
   SI.m = c(23,11,11),
   stand.age.years = c(120, 80, 40))

---

DBH Increment Function by Bollandsas and Naesset (2009)

Description

Implementation of the diameter at breast height function published by Bollandsås and Næsset (2009).

Usage

dbhi.BN2009(tr, fl, common.vars, this.period, ...)

Arguments

tr	A trList class object.
fl	A list describing the plot data.
common.vars	A list with at least variables QMD.cm, i.stand, and SBA.m2.ha.
this.period	The period for which to calculate DBH increment.
...	Ignored

Value

A vector with DBH increments in mm for all trees in tr.

Author(s)

Clara Anton Fernandez [email protected]

References

Bollandsås, O. M and Næsset, E. (2009). Weibull Models for Single-Tree Increment of Norway Spruce, Scots Pine, Birch and Other Broadleaves in Norway. Scandinavian Journal of Forest Research 24 (1): 54.

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))

common.vars <-  prep.common.vars.fun(
  tr = tr.i,
  fl = fl,
  i.period       = 0,
  this.period    = "t0",
  common.vars    = "NULL",
  vars.required  = c("QMD.cm", "i.stand"),
  period.length = 5
)
 
dbhi.BN2009(tr.i, fl, common.vars$res , this.period = "t0",
            species.spruce = c(1, 2, 3),
            species.pine =  c(10, 11, 20, 21, 29),
            species.harw =  c(30, 31))

---

Growth of Dead Trees

Description

A very simple function to estimate the growth of dead trees between the last measurement and their death. Dead trees are assumed to die in the middle of the period. The growth before the death of the tree is assumed to be half of the growth for the whole period, both in terms of DBH and height.

Usage

dead.trees.growth(dt, growth, mort, this.period)

Arguments

dt	A list of trees with at least two elements: dbh.mm and height.dm.
growth	A data frame with columns dbh.inc.mm and hgt.inc.dm.
mort	A TRUE/FALSE vector with the predicted mortality for each living tree in this period.
this.period	The period where the dead trees were last seen alive (last measured DBH).

Value

Returns a data frame of same length as dt with two elements

dbh.mm	DBH in mm
height.dm	Height in dm

Author(s)

Clara Anton Fernandez [email protected]

Examples

dead.trees.growth(
  dt = list(dbh.mm = data.frame   (t0 = c(75, 90, 25, 24)),
            height.dm = data.frame(t0 = c(190, 210, 110, 90))),
  growth = data.frame(dbh.inc.mm = c(7, 9, 2, 1),
                      hgt.inc.dm = c(11, 12, 8, 10)),
  this.period = "t0"
)

---

Plot Data

Description

Plot data

Usage

data(fl)

Format

The list contains the following elements

plot.id

unique ID for each stand that corresponds to plot.id in the tr dataset

SI.m

Site index in m

SI.spp

Species code for which SI.m is measured

prop.plot

Proportion of the plot covered by this stand (0-full plot, 2-20%, 3-30%, 4-40%, ..., 8-80%)

ha2plot

multiplier to convert from "per ha" to "per plot", e.g. basal area per ha to basal area per plot

tree2ha

multiplier to convert numbers "per tree" to "per ha", e.g. basal area per tree to basal area per ha

soil.depth. 1234

soil depth 1(shallow)-4(deep)

land.use

land use classification

land.type

land type classification

veg.type

vegetation type

subplot.size.m2

size of the subplot correponding to the stand in square meters

plot.size.m2

Plot size in square meters

kom

Municipality code

region

region where the plot lies

skidding.distance.100m

skidding distance in 100m

slope.per

slope in percentatge

lat.det

latitude in degrees

alt.m

altitude in meters

utm.s33.ov.m

UTM E-W coordinates of the plot

utm.s33.snv.m

UTM S-N coordinates of the plot

stand.age.years

data frame with stand age in years, only the first column, t0, is filled up

management

data frame will management codes for each period

Source

This dataset is derived from the Norwegian National Forest Inventory

Examples

data(fl)
str(fl)

---

Finds Variables Required on Functions

Description

Tries to find the variables to be calculated through the parameters of the functions.

Usage

fn.vars.required(my.functions, ...)

Arguments

my.functions	A list of functions to be used during the simulation
...	Use this to add any funciton that might not be included in my.functions

Value

It returns a vector with the name of the potential variables required.

Author(s)

Clara Anton Fernandez [email protected]

Examples

fn.vars.required (my.functions = list(
                             fn.growth     = "grow.dbhinc.hgtinc",
                             fn.dbh.inc    = "dbhi.BN2009",
                             fn.hgt.inc    = "height.korf", 
                             fn.mort       = "mort.B2007",
                             fn.recr       = "recr.BBG2008",
                             fn.management = "management.prob",
                             fn.tree.removal = "mng.tree.removal",
                             fn.modif      = NULL, 
                             fn.prep.common.vars = "prep.common.vars.fun"
                           ),
                      "BBG2008")

---

Growth and Height Increment Function Wrapper

Description

A growth and height increment function wrapper that can be used with or without a height increment function.

Usage

grow.dbhinc.hgtinc(tr, fl, common.vars, this.period, functions, ...)

Arguments

tr	A trList class object.
fl	A list describing the plot data.
common.vars	A list with at least variables spp (species classification in categories: spruce, pine, birch and other), and SBA.m2.ha.
this.period	The period for which to calculate growth.
functions	A list defining the functions to be used in sitree.
...	Further arguments to be passed to DBH increment and height increment functions.

Details

A growth function should calculate both dbh and height increment. This function calls two functions, defined in functions as fn.dbh.inc and fn.hgt.inc to estimate those.

Value

Returns a data frame with two elements dbh.inc.mm (DBH increment in mm), hgt.inc.dm (Height increment in dm)-

Author(s)

Clara Anton Fernandez [email protected]

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))

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


grow.dbhinc.hgtinc (tr = tr.i,
                    fl = fl,
                    common.vars = common.vars$res,
                    this.period = "t0",
                    functions = list(
                        fn.growth     = 'grow.dbhinc.hgtinc',
                        fn.mort       = 'mort.B2007',
                        fn.recr       = 'recr.BBG2008',
                        fn.management = 'management.prob',
                        fn.tree.removal = 'mng.tree.removal',
                        fn.modif      = NULL, #'ext.modif.fun',
                        fn.prep.common.vars = 'prep.common.vars.fun'
                    ),
		    fn.dbh.inc = "dbhi.BN2009",
                    fn.hgt.inc =  "height.korf", 
                    species.spruce = c(1, 2, 3),
                    species.pine =  c(10, 11, 20, 21, 29),
                    species.harw =  c(30, 31)
                    )

---

Simple height function

Description

A simple tree height function based on tree species, and DBH. It returns the difference between the height at the current period (this.period) and the next period.

Usage

height.korf(common.vars, this.period, tr,  dbh.inc.mm, ...)

Arguments

common.vars	A list with at least an element named 'spp' with the species group composition.
this.period	The period for which to calculate the height of the trees.
tr	A trList.
dbh.inc.mm	A vector with the projected dbh increment.
...	Currently not used

Value

A vector with tree heights increments in dm.

Author(s)

Clara Anton Fernandez [email protected]

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))

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"),
  period.length = 5
)
height.korf(common.vars = common.vars$res, this.period = 't0', 
    tr.i, fl, dbh.inc.mm = runif(nrow(tr.i$data$dbh.mm), 5, 80))

---

Final felling and thinning functions for Norwegian forest

Description

Estimates de probability of a stand to be harvested or thinning following Anton-Fernandez et al. (20012).

Usage

management.prob(tr, fl, fun.final.felling = "harv.prob",
fun.thinning = "thin.prob", common.vars, this.period, next.period, ...)

harv.prob(region, skidding.distance.100m, AgeTo5, vuprha.m3.ha,
slope.per, SI.m, SI.spp)

thin.prob(region, skidding.distance.100m, AgeTo5, vuprha.m3.ha, slope.per, SI.m, SI.spp)

Arguments

tr	A trList class object.
fl	A list describing the plot data.
fun.final.felling	Function to use to calculate final felling.
fun.thinning	Function to use to calculate thinning.
common.vars	A list with at least variables dev.class and vuprha.m3.ha.
this.period	The period for which to calculate final felling and thinning probability.
next.period	The next period to the one for which final felling and thinning probability are to be calculated.
...	Further arguments
region	A vector containing the region in Norway where every plot is situated.
skidding.distance.100m	A vector containing skidding for each plot.
AgeTo5	A vector containing number of years to development class 5 for each plot.
vuprha.m3.ha	Volume per ha in cubic meters per ha for each plot.
slope.per	Slope, in percentatge, for each plot.
SI.m	Site index (SI) in m.
SI.spp	Species for which the SI is calculated (1 = spruce, 2 = pine, 3 = deciduous).

Value

It returns a list with one element:

mng	a vector with the management to apply to each plot.

Author(s)

Clara Anton Fernandez [email protected]

References

Antón-Fernández, C. and Astrup, R. 2012 Empirical harvest models and their use in regional business-as-usual scenarios of timber supply and carbon stock development. Scandinavian Journal of Forest Research, 27, 4, 379–392.

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))

common.vars <-  prep.common.vars.fun(
  tr = tr.i,
  fl = fl,
  i.period       = 0,
  this.period    = "t0",
  common.vars    = "NULL",
  vars.required  = c("spp", "SBA.m2.ha", "QMD.cm", "vuprha.m3.ha", "AgeTo5"),
  period.length = 5
)
fl$management <- data.frame(matrix(NA, ncol = tr.i$nperiods,
                                   nrow = nrow(tr.i$data$dbh.mm)))
names(fl$management) <- paste0("t", 1:tr.i$nperiods)

management.prob(tr.i,
                fl,
                fun.final.felling = "harv.prob",
                fun.thinning = "thin.prob",
                common.vars = common.vars$res,
                this.period = "t0",
                next.period = "t1")

harv.prob(region = fl$region[1:3],
          skidding.distance.100m = fl$skidding.distance.100[1:3],
          AgeTo5 = c(50, 20, 15),
          vuprha.m3.ha = common.vars$res$vuprha.m3.ha[1:3],
          slope.per = fl$slope.per[1:3],
          SI.m = fl$SI.m[1:3],
          SI.spp = fl$SI.spp[1:3])

thin.prob(region = fl$region[1:3],
          skidding.distance.100m = fl$skidding.distance.100[1:3],
          AgeTo5 = c(50, 20, 15),
          vuprha.m3.ha = common.vars$res$vuprha.m3.ha[1:3],
          slope.per = fl$slope.per[1:3],
          SI.m = fl$SI.m[1:3],
          SI.spp = fl$SI.spp[1:3]
)

---

Function to remove trees

Description

Define how trees are going to be removed in plots with some sort of management that involves removal (e.g final felling, thinning).

Usage

mng.tree.removal(tr, fl, common.vars, this.period, next.period, ...)

Arguments

tr	A trList class object.
fl	A list describing the plot data.
common.vars	A list with at least variable vol.wo.tr.m3.ha
this.period	The period for which to calculate final felling and thinning probability.
next.period	The next period to the one for which final felling and thinning probability are to be calculated.
...	A list containing at least an element named per.vol.harv, that should contain the percentatge of volume removed within each plot/stand.

Value

Returns a TRUE/FALSE vector of length equal to the number of trees in tr.

Author(s)

Clara Anton Fernandez [email protected]

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))

common.vars <-  prep.common.vars.fun(
  tr = tr.i,
  fl = fl,
  i.period       = 0,
  this.period    = "t0",
  common.vars    = "NULL",
  vars.required  = c("vol.wo.tr.m3.ha", "vuprha.m3.h"),
  period.length = 5,
  species.spruce = c(1, 2, 3),
  species.pine = c(10, 11, 20, 21, 29),
  species.harw = c(30, 31)
)

fl$management <- data.frame(matrix(NA, ncol = tr.i$nperiods,
                                   nrow = length(fl$plot.id)))
names(fl$management) <- paste0("t", 1:tr.i$nperiods)

management <- management.prob(tr.i,
                fl,
                fun.final.felling = "harv.prob",
                fun.thinning = "thin.prob",
                common.vars = common.vars$res,
                this.period = "t0",
                next.period = "t1")
fl$management[, "t1"] <- management$management
remove.tree <- mng.tree.removal(tr = tr.i,
                                fl = fl,
                                common.vars = common.vars$res,
                                this.period = "t0",
                                next.period = "t1",
                                per.vol.harv =  0.83 )
sum(remove.tree)

---

Mortality Function by Bollandsas (2007)

Description

Implementation of the individual tree mortality function published by Bollandsås (2007) doi:10.1080/02827580802477875 .

Usage

mort.B2007(tr, fl, common.vars, this.period, ...)

Arguments

tr	A trList class object.
fl	A list describing the plot data.
common.vars	A list with at least variables spp (species classification in categories: spruce, pine, birch and other), and SBA.m2.ha.
this.period	The period for which to calculate mortality.
...	Ignored.

Value

A TRUE/FALSE vector for all trees in tr.

Author(s)

Clara Anton Fernandez [email protected]

References

Bollandsås O. Uneven-aged Forestry in Norway: Inventory and Management Models. [Ås, Norway]: Norwegian University of Life Sciences, Department of Ecology and Natural Resource Management; 2007.

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))

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"),
  period.length = 5
)
dead.trees <- mort.B2007(tr.i, fl, common.vars$res, this.period = 't0')
sum(dead.trees)

---

Volumes for Norwegian species

Description

These functions calculate tree volume with or without bark for the main species in Norway, that is, Norway spruce, Scots pine, Sitka spruce, birch, and ... following Braastad (1966), Brantseg (1967), and Vestjordet (1967).

Usage

picea.abies.vol(dbh, trh, bark, units)
picea.abies.volV(dbh, trh, bark, units)
pinus.sylvestris.vol(dbh, trh, bark, units)
pinus.sylvestris.volV(dbh, trh, bark, units)
sitka.vol(dbh, trh, bark, units)
harw.nor.vol(tsl, dbh, trh, bark, units)

Arguments

dbh	A vector with diameters at breast height in mm with bark.
trh	A vector with tree heights in cm.
bark	If tree volume should be calculated with bark, "mb", or wihtout bark, "ub".
units	"l" in liters, "c" in cubic centimeters.
tsl	Tree species 30 (), 31(), 32 (), 40(), 41(), 50(), NA. This only affects the calculations of diameter without bark.

Value

Returns tree volume in the selected units.

References

Braastad, H. 1966. Volumtabeller for bjoerk [Volume tables for birch]. Meddelelser fra Det norske Skogforsøksvesen 21: 23–78. Brantseg, A. 1967. Furu sønnafjells. Kubering av staaende skog. Funksjoner og tabeller [Volume functions and tables for Scots pine. South Norway]. Meddelelser fra Det norske Skogforsøksvesen 22: 695–739. Vestjordet, E. 1967. Funksjoner og tabeller for kubering av staaende gran [Functions and tables for volume of standing trees. Norway spruce]. Meddelelser fra Det norske Skogforsøksvesen 22. Ås, Norway: Norwegian Forest and Landscape Institute.

Examples

harw.nor.vol(tsl = c(30,31), dbh = c(45, 25), trh = c(120, 80), bark = "ub", units = "l")

---

Function to Calculate Common Variables

Description

A function to calculate common variables needed to estimate growth, death, etc.

Usage

prep.common.vars.fun(tr, fl, i.period, this.period, common.vars, vars.required,
period.length, n.periods, ...)

Arguments

tr	A trList class object.
fl	A list describing the plot data.
i.period	The number of period (from 0 to nperiods) for which to calculate the comon variables.
this.period	The period for which to calculate the common variables.
common.vars	A list with existing common variables.
vars.required	Variables to be calculated.
period.length	Length of the periods, in years.
n.periods	Number of periods.
...	Further arguments, data, etc.

Details

This is an example of a prep.common.vars file. A prep.common.vars (prepare common variables) is needed for the simulation. It is in this file that additional variables needed for the particular functions used in the simulation are calculated. For example, to calculate quadratic mean diameter, basal area, or volume.

Value

A list

res	A list with the common variables.
fl	Updated fl

Author(s)

Clara Anton Fernandez [email protected]

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))

common.vars <-  prep.common.vars.fun(
  tr = tr.i,
  fl = fl,
  i.period       = 0,
  this.period    = "t0",
  common.vars    = "NULL",
  vars.required  = c("vol.wo.tr.m3.ha", "vuprha.m3.h"),
  period.length = 5
)
str(common.vars)

---

Quadratic Mean Diameter

Description

Calculates quadratic mean diameter.

Usage

QMD.cm.f(x.mm)

Arguments

x.mm	DBH in mm.

Details

It ignores not finite values like NA, and calculates the QMD for the rest of the trees.

Value

The QMD in cm of x.mm.

Author(s)

Clara Anton Fernandez [email protected]

Examples

QMD.cm.f(50)
QMD.cm.f(c(51, NA))
QMD.cm.f(c(51, 42, 120, 57))

---

Recover dbh and height at time of death

Description

Removes all dbh and height data that corresponds to the live of the tree, and adds the dbh and height at time of death to the dbh.mm and height.dm in the data field.

Usage

recover.last.measurement(tr.list.dead)

Arguments

tr.list.dead

a trListDead object

Details

It removes all dbh and height data from the data field, adds the dbh and height at time of death, and converts any potential NAs created in the process to 0.

Value

It returns the same object (a trListDead object) with all data on dbh and height removed. For each tree there is only one observation of dbh and height in the data field, the estimated dbh and height at time of death.

Author(s)

Clara Anton Fernandez [email protected]

Examples

set.seed(2017)
res <- sitree (tree.df   = tr,
                stand.df  = fl,
                functions = list(
                    fn.growth     = 'grow.dbhinc.hgtinc',
                    fn.mort       = 'mort.B2007',
                    fn.recr       = 'recr.BBG2008',
                    fn.management = 'management.prob',
                    fn.tree.removal = 'mng.tree.removal',
                    fn.modif      = NULL, #'ext.modif.fun',
                    fn.prep.common.vars = 'prep.common.vars.fun'
                ),
                n.periods = 5,
                period.length = 5,
                mng.options = NA,
                print.comments = FALSE,
		fn.dbh.inc = "dbhi.BN2009",
                fn.hgt.inc =  "height.korf", 
                species.spruce = c(1, 2, 3),
                species.pine = c(10, 11, 20, 21, 29),
                species.harw = c(30, 31),
                fun.final.felling = "harv.prob",
                fun.thinning      = "thin.prob",
                'BN2009',
                'BBG2008', 'SBA.m2.ha', 'spp','pr.spru.ba', 'QMD.cm',
                per.vol.harv = 0.83
                )
dead <- recover.last.measurement(res$dead)
str(dead)
removed <- recover.last.measurement(res$removed)
str(removed)

---

Recovers the State

Description

It adds dead and removed trees to tr. This is an internal function that should not be run, in general, by a regular user.

Usage

recover.state(tr, dead.trees, removed.trees)

Arguments

tr	A trList class object.
dead.trees	A trListDead class object.
removed.trees	A trListDead class object.

Details

In order to make calculations easier and lighter memory wise, at each cycle (period) of the simulation all removed (harvested) and dead trees are removed from tr, which only keeps alive trees at the current period. Once the simulation is finished recover.state returns all dead and removed trees to the last tr, so sitree can return a full list, including all trees alive at any point during the simulation, of trees.

Value

A trList class object.

Author(s)

Clara Anton Fernandez [email protected]

---

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)

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.

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).

Author(s)

Clara Anton Fernandez [email protected]

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)

---

Individual Tree Simulator

Description

Simulates the growth of individual trees in several plots, including management and keeping record of dead and removed trees. It can also include the effect of external modifiers such as climate change. The SiTree package is described in Antón-Fernández, C., & Astrup, R. (2022). https://doi.org/10.1016/j.softx.2021.100925

Usage

sitree(tree.df, stand.df, functions, n.periods = 5, period.length,
mng.options = NA, print.comments = FALSE,..., ext.mod.first = TRUE)

Arguments

tree.df	A data frame with individual tree data. It should include four columns named 'plot.id' (an ID for the plot/stand that the tree belongs to), treeid (a unique ID for the tree), dbh (a measure of horizontal dimension), height (a measure of vertical dimension), tree.sp (tree species)
stand.df	A data frame or list with neccessary data on the stand (e.g. slope, site index). It should include a 'plot.id' that matches the one in tree.df and a 'plot.size.m2', the plot size in m2. 'plot.size.m2' is only used in the summary.sitree function to calculate figures by ha.
functions	A list describing the basic functions. It should include a minimum of a function for growth (fn.growth), for diameter (or basal area) increment, for height increment (height.korf), mortality (fn.mort), recruitment (fn.recr), management (fn.management), tree removal (fn.tree.removal), and external modifiers (fn.modif). fn.management, fn.tree.removal, and fn.modif, can be missing.
n.periods	Number of periods to simulte (numeric).
period.length	The length of the periods (e.g. 5 years).
mng.options	Management options and definitions to be passed further.
print.comments	TRUE/FALSE Print comments. It is meant to help debugging new functions.
...	Further arguments to pass to functions used during simulation.
ext.mod.first	If TRUE (default) the external modifier functions will be run before fn.prep.common.vars.

Value

Returns a list with all live, dead, removed trees, and some plot information like stand age in years at each period, and management applied at each plot at each period.

Author(s)

Clara Anton Fernandez [email protected]

References

Antón-Fernández, C., & Astrup, R. (2022). SiTree: A framework to implement single-tree simulators. SoftwareX, 18, 100925. https://doi.org/10.1016/j.softx.2021.100925

Examples

result.sitree <- sitree (tree.df   = tr,
                           stand.df  = fl,
                           functions = list(
                             fn.growth     = 'grow.dbhinc.hgtinc',
                             fn.mort       = 'mort.B2007',
                             fn.recr       = 'recr.BBG2008',
                             fn.management = 'management.prob',
                             fn.tree.removal = 'mng.tree.removal',
                             fn.modif      = NULL, #'ext.modif.fun',
                             fn.prep.common.vars = 'prep.common.vars.fun'
                           ),
                           n.periods = 5,
                           period.length = 5,
                           mng.options = NA,
                           print.comments = FALSE,
                           fn.dbh.inc = "dbhi.BN2009",
                           fn.hgt.inc =  "height.korf", 
                           fun.final.felling = "harv.prob",
                           fun.thinning      = "thin.prob",
                           per.vol.harv = 0.83
                           )
str(result.sitree)
set.seed(2017)
result.sitree <- sitree (tree.df   = stand.west.tr,
                           stand.df  = stand.west.st,
                           functions = list(
                             fn.growth     = 'grow.dbhinc.hgtinc',
                             fn.mort       = 'mort.B2007',
                             fn.recr       = 'recr.BBG2008',
                             fn.management = NULL,
                             fn.tree.removal = NULL,
                             fn.modif      = NULL, 
                             fn.prep.common.vars = 'prep.common.vars.fun'
                           ),
                           n.periods = 20,
                           period.length = 5,
                           mng.options = NA,
                           print.comments = FALSE,
                           fn.dbh.inc = "dbhi.BN2009",
                           fn.hgt.inc =  "height.korf"
                         )

---

Summary plots

Description

It produces 5 summary plots (stand basal area, number of stems, average height of tallest 10 trees, number of dead trees, and number of harvested trees)

Usage

sitree.summary(sitrees.res, plots, by.stand = TRUE, plot = FALSE,
                           plot.all.together = FALSE, with.legend = FALSE)

Arguments

sitrees.res	An object result of running sitree().
plots	Plots to be printed (1: stand basal area, 2: number of stems, 3: average height of tallest 10 trees, 4: number of dead trees, 5: number of harvested trees)
by.stand	TRUE/FALSE TRUE prints plot by stand (figures by ha), if FALSE it prints plots with totals (divides values per ha by 'plot.size' and multiplies by 10.000 to obtain total values)
plot	TRUE/FALSE if plots are printed
plot.all.together	if TRUE all plots are plotted in a single page
with.legend	if TRUE a legend will be added to the plot when by.stand == TRUE

Value

It passes the required plots in a named list. It plot is TRUE it also prints the required plots.

Author(s)

Clara Anton Fernandez [email protected]

See Also

sitree

Examples

require(sitree)
res <- sitree (tree.df   = tr,
               stand.df  = fl,
               functions = list(
                   fn.growth     = 'grow.dbhinc.hgtinc',
                   fn.mort       = 'mort.B2007',
                   fn.recr       = 'recr.BBG2008',
                   fn.management = 'management.prob',
                   fn.tree.removal = 'mng.tree.removal',
                   fn.modif      = NULL, 
                   fn.prep.common.vars = 'prep.common.vars.fun'
               ),
               n.periods = 5,
               period.length = 5,
               mng.options = NA,
               print.comments = FALSE,
               fn.dbh.inc = "dbhi.BN2009",
               fn.hgt.inc =  "height.korf", 
               species.spruce = c(1, 2, 3),
               species.pine = c(10, 11, 20, 21, 29),
               species.harw = c(30, 31),
               fun.final.felling = "harv.prob",
               fun.thinning      = "thin.prob",
               per.vol.harv = 0.83
               )

summary.plots <- sitree.summary(res, plots = 1:6, by.stand = FALSE, plot = TRUE)

---

sitree2data.frame and sitree2dataframe.all

Description

sitree2data.frame converts trList and trListDead class objects to data.frames. sitree2data.frame converts all output of sitree to a data.frame

Usage

sitree2dataframe(tr.dt)
sitree2dataframe.all(sitree.res)

Arguments

tr.dt	A trList or trListDead object.
sitree.res	An object resulting from running sitree.

Details

As implemented, it expects to have a 'removed' element on sitree2dataframe.all. For an alternative when the simulation has no harvest see the exaples below.

Value

sitree2dataframe return a data.frame with dbh, height, and species by period. sitree2dataframe.all returns a list

live	A data.frame with dbh, height, and species of the trees alive at each period.
dead	A data.frame with dbh, height, and species of the trees found dead at each period.
removed	A data.frame with dbh, height, and species of the trees removed at each period.

Author(s)

Clara Anton Fernandez

Examples

n.periods <- 10

# Run a simulation with the example functions
res <- sitree (tree.df   = tr,
               stand.df  = fl,
               functions = list(
                     fn.growth     = 'grow.dbhinc.hgtinc',
                     fn.mort       = 'mort.B2007',
                     fn.recr       = 'recr.BBG2008',
                     fn.management = 'management.prob',
                     fn.tree.removal = 'mng.tree.removal',
                     fn.modif      = NULL, 
                     fn.prep.common.vars = 'prep.common.vars.fun'
                 ),
                 n.periods = n.periods,
                 period.length = 5,
                 mng.options = NA,
                 print.comments = FALSE,
                 fn.dbh.inc = "dbhi.BN2009",
                 fn.hgt.inc =  "height.korf", 
                 species.spruce = c(1, 2, 3),
                 species.pine = c(10, 11, 20, 21, 29),
                 species.harw = c(30, 31),
                 fun.final.felling = "harv.prob",
                 fun.thinning      = "thin.prob",
                 'BN2009',
                 'BBG2008', 'SBA.m2.ha', 'spp','pr.spru.ba', 'QMD.cm',
                 per.vol.harv = 0.83
                 )

dbh.mm <- sitree2dataframe(res$live)
res.dt <- sitree2dataframe.all(res)



## The function is currently defined as

---

Species classifcation

Description

Classifies the tree species into four species groups

Usage

sp.classification(tree.sp, species.spruce, species.pine, species.harw)

Arguments

tree.sp	Tree species code.
species.spruce	A vector with the codes used to define 'spruce' group .
species.pine	A vector with the codes used to define 'pine' group .
species.harw	A vector with the codes used to define the 'birch' group .

Value

Returns a vector with the classification of tree.sp into one of these four groups: spruce, pine, birch, and other. spruce group is defined by species.spruce, pine group is defined by species.pine, and birch is defined by species.harw. If a species does not fall within any of these three groups is classified as 'other'.

Author(s)

Clara Anton Fernandez [email protected]

Examples

sp.classification(tr$tree.sp, species.spruce = c(1,15),
                           species.pine = c(2,34),
                           species.harw = c(3,4))

---

Stand and plot characteritics for stand.west.tr

Description

Dataset with stand and plot data for stand.west.tr

Usage

stand.west.st

Format

A data frame with 4 observations on the following 7 variables.

plot.id

unique ID for each plot

SI.m

site index in meters

kom

municipality code

SI.spp

species for which site index is measured

plot.size.m2

plot size in m2

tree2ha

multiplier to convert values per tree to per hectare

lat.deg

latitude of the plots in degrees

subplot.size.m2

plot size in m2, this is a dummy variable needed for some of the calculations

Examples

stand.west.st
str(stand.west.st)

---

A whole stand dataset

Description

This dataset describes a whole stand of 1019 m2 and spacing 1.25x1.25m. The stand is divided in 4 plots of approximately 250 m2. All trees are Norway spruce.

Usage

stand.west.tr

Format

A data frame with 651 observations on the following 5 variables.

dbh

diameter at breast height in mm

height

tree height in dm

plot.id

a unique ID for each plot

treeid

a unique ID for each tree

tree.sp

tree species, a factor with levels 1 2 3 10 11 20 21 29 30 31 32 40 41 42 43 44 48 49 50 51 52 53 54 55 56 57 58 59 70

Examples

stand.west.tr
str(stand.west.tr)

---

Binding lists

Description

This function is only used internally to bind vectors, data frames, and lists.

Usage

toBindLists(x, y)

Arguments

x	A vector, data frame or list.
y	Object of the same type as x.

Value

It returns a vector, a data frame or a list depending on x.

Author(s)

Clara Anton Fernandez [email protected]

Examples

## Example of how toBindLists works with data frames
x <- data.frame(1:10, ncol = 2)
names(x) <- c('a', 'b')
y <- data.frame(1:20, ncol = 2)
names(y) <- names(x)
j <- toBindLists(x, y)
j

## with vectors
x <- c(1:3)
y <- (8:15)
j <- toBindLists(x, y)
j

## with lists
x <- data.frame(1:10, ncol = 2)
names(x) <- c('a', 'b')
y <- data.frame(1:20, ncol = 2)
names(y) <- names(x)

x <- list(x = x, y = y)

xx <- data.frame(1:10, ncol = 3)
names(xx) <- c('a', 'b')
yy <- data.frame(1:20, ncol = 3)
names(yy) <- names(xx)

y <- list(xx = xx, yy= yy)

j <- toBindLists(x, y)
j

---

Individual Tree Data

Description

A data frame with data to create the trList object needed to run sitree.

Usage

data("tr")

Format

The data frame contains the following columns

plot.id

unique ID for each stand that corresponds to plot.id in the fl dataset

treeid

unique ID for each tree

dbh

dbh in mm

height

height of the tree in dm

tree.sp

tree species code

Source

This dataset is derived from the Norwegian National Forest Inventory.

Examples

data(tr)
hist(tr$dbh)

---

Class "trList"

Description

Describes the Reference Class trList, which is used to store data on live trees.

Extends

All reference classes extend and inherit methods from "envRefClass".

Fields

data:

Object of class list containing the unique stand ID (plot.id), the tree ID (treeid), and dbh (dbh.mm) and height (height.dm) for all the periods

nperiods:

Object of class integer containing the number of period that should be simulated

Methods

extractTrees(i):

Removes trees from the objectd, for example when trees die or are harvested

as.list():

converts this class to a list

show():

shows the first 20 trees

getTrees(i, j):

get the information for i trees and j periods without deleting the data

addTrees(value):

adds trees to the object

Note

trList objects should not be modified inside any user function. Any change should be made by the sitree function. Reference class objects are mutable, they don’t use R’s usual copy-on-modify semantics, but are modified in place. So, if you want to modify, for example for a posterior analysis of the results, any trList object I recommend to make a copy of the object first, using $copy(), e.g. my.tr.list$copy().

Author(s)

Clara Anton Fernandez [email protected]

See Also

trListDead

Examples

showClass("trList")

---

Class "trListDead"

Description

A Reference Class for dead trees.

Extends

Class "trList", directly.

All reference classes extend and inherit methods from "envRefClass".

Fields

data:

Object of class list containing the unique stand ID, the tree ID, and dbh and height for all the periods. Only data from the periods were the tree was alive is stored in this field

nperiods:

Object of class integer containing the number of period that should be simulated

last.measurement:

Object of class data.frame containing tree ID, dbh, height, and period when the tree was "found" dead

Methods

last.time.alive():

It estimates when the trees where last "seen" alive

addTrees(value):

It add trees to the trlistDead object

remove.next.period(next.period):

It removed the data from the period when the tree was seen "dead". The next period is calculated so the dbh and height at time of death can be estimated

The following methods are inherited (from the corresponding class): extractTrees ("trList"), as.list ("trList"), show ("trList"), getTrees ("trList"), addTrees ("trList")

Note

This class is meant to keep the data of the dead trees in a similar way as the live trees, but with some extra information such as diameter and height at death.

Author(s)

Clara Anton Fernandez [email protected]

See Also

trList, ~~~

Examples

showClass("trListDead")

---

Tree volume for Norwegian conditions

Description

Calculates tree volume following the equations used in the Norwegian national forest inventory

Usage

volume.norway(dbh.mm, height.dm, tree.sp, kom, vol.reduksjon = NULL, 
vol.w = TRUE, vol.wo = TRUE)

Arguments

dbh.mm	tree dbh in mm
height.dm	tree height in dm
tree.sp	tree species following the same codification as the Norwegian NFI
kom	municipality code
vol.reduksjon	volume reduction in 100
vol.w	TRUE/FALSE if volume with bark needs to be calculated
vol.wo	TRUE/FALSE if volume without bark needs to be calculated

Value

It returns a list with up to two elements:

vol.w.tr.m3	volume with bark per tree in m3
vol.wo.tr.m3	volume without bark per tree in m3

Examples

volume.norway(dbh.mm = c(50,70), height.dm = c(17,20), tree.sp = c(1, 10), kom = c(623, 623))

---