trlsmoopsp: Smoothed tree list data from permanent sample plots

In biometrics: Functions and Datasets for Forest Biometrics and Modelling

Smoothed tree list data from permanent sample plots

Description

Temporal tree-level variables (smoothed-values) within four sample plots in an experimental forest in Austria. The dataframe contains all the variables for all trees, where observation gaps were filled from monotone increasing predictive functions. Plot sizes are 2500 m^{2} (approx.) and the current dataframe only keeps the measurement years having a more reliable amount of records.

Usage

data(trlsmoopsp)

Format

Contains tree-level variables, as follows:

plot

Plot number.

tree

Tree identificator.

year

Year of measurement.

species

Species code as follows: PCAB=Picea abies, LADC=Larix decidua, PNSY=Pinus sylvestris, FASY=Fagus Sylvatica, QCPE=Quercus petraea, BTPE=Betula pendula.

obs

Observation in this year.

dbh

Diameter at breast-height, in cm.

toth

Tree height, in m.

hcb

Height to the crown base, in m.

Source

The Austrian Research Center for Forests established a spacing experiment with Norway spruce (Picea abies) in the Vienna Woods. In the 'Hauersteig' experiment, several tree-level variables were measured within four sample plots over time. Data were retrieved from the paper cited below, where several details might be worth reading.

References

- Kindermann G. Kristofel F, Neumann M, Rossler G, Ledermann T & Schueler. 2018. 109 years of forest growth measurements from individual Norway spruce trees. Sci. Data 5:180077 \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1038/sdata.2018.77")}

Examples

data(trlsmoopsp)
df<-trlsmoopsp    
head(df) 
table(df$year,df$plot)
tapply(df$dbh, list(df$year,df$plot), length)

biometrics documentation built on April 4, 2025, 12:35 a.m.