Tree models Scots pine dominated stands in Northern Sweden

user_name Erik Valinger
user_organisation Swedish University of Agricultural Sciences
Faculty of Forestry
Department of Silviculture
S-901 83 Umea
Sweden
date 20th May 1997
model_name Tree characteristic model
description Describes probability of snow and wind damage at sites using
tree characteristics from the thickest sample tree at each sample plot.
software Developed in SAS 6.10 but Excel 7.0 will do
operating_system PC Windows 95
isumm There are five input variables in model.
The risk of damage is modeled using the characteristics volume over bark,
clear bole height, relative crown length, breast height taper,
and ratio of height to diameter at breast height.
Valid only for Scots pine in north Sweden.
Ispecfile Similar to that for earlier Umea models
iexpspecfile n/a
ivar1 Volume over bark (v)
ifile1 ?
idescr1 m3
isensitiv1 Sensitive
isensdescr1 Logistic procedure
ivar2 Clear bole height (cbh)
ifile2 ?
idescr2 Height to living crown, m
isensitiv2 Sensitive
isensdescr2 Logistic procedure
ivar3 Relative crown length (rcl)
ifile3 ?
idescr3 proportion (0 to 1)
isensitiv3 Sensitive
isensdescr3 Logistic procedure
ivar4 Breast height taper (brt)
ifile4 ?
idescr4 Diameter at breast height/height-1.3, cm/m
isensitiv4 Sensitive
isensdescr4 Logistic procedure
ivar5 Ratio height to diameter at breast height (rhd)
ifile5 ?
idescr5 m/cm
isensitiv5 Sensitive
isensdescr5 Logistic procedure
csumm Volume over bark 1.2052
Clear bole height -0.3210
Relative crown length -3.2955
Breast height taper 1.0413
Ratio height to diameter at breast height 4.2336
Model ntprob=1-(1/(1+exp(-5.1597+(1.2052*v)-(0.3210*cbh)-(3.2955*rcl)
+(1.0413*brt)+(4.2336*rhd))))
(then multiply by 100 to get the result in percent)
cspecfile None
cexpspecfile none
osumm ntall
ospecfile ?
oexpspecfile See above
ovar1 ntprob
ofile1 ?
odescr1 Site probability of snow and wind damage
stat_meth Logistic procedure for probability of damage from snow and wind
at a site using tree characteristics when dominating species is Scots pine
Chi-square for covariates 107.005 with 5 DF (p=0.0001)
Pr > Chi-square
Intercept 0.0002
v 0.0001
cbh 0.0001
>rcl 0.0002
brt 0.0001
rthd 0.0001
mech_mth n/a
log_meth Logistic model
ntprob=1-(1/(1+exp(-5.1597+(1.2052*v)-(0.3210*cbh)-3.2995*rcl)+
(1.0413*brt) +(4.2336*rhd))))
(then the result multiplied by 100 to get in percent)
scope Model developed from a sample of data from whole Sweden (1114 sample plots).
2% of the plots had one or more damaged sample trees, damage=1.
Model have been proven to predict damage well by cross-validation
other ?
copyright Swedish University of Agricultural Sciences
Faculty of Forestry
Department of Silviculture
contact Associate Professor Erik Valinger