Forests,
Journal Year:
2022,
Volume and Issue:
13(10), P. 1592 - 1592
Published: Sept. 29, 2022
An
accurate
estimate
of
the
site
index
is
essential
for
informing
decision-making
in
forestry.
In
this
study,
we
developed
(SI)
models
using
stem
analysis
data
to
and
dominant
height
growth
Larix
gmelinii
var.
principis-rupprechtii
northern
China.
The
included
5122
height–age
pairs
from
75
trees
29
temporary
sample
plots
(TSPs).
Nine
commonly
used
functions
were
parameterized
modeling
method,
which
accounts
heterogeneous
variance
autocorrelation
time-series
introduces
plot-level
random
effects
model.
results
show
that
Duplat
Tran-Ha
I
model
with
described
largest
proportion
variation.
This
accurately
evaluated
quality
predicted
tree
natural
forests
Guandi
Mountain
region.
As
an
important
supplement
improving
methods
evaluation,
may
serve
as
a
fundamental
tool
scientific
management
larch
forests.
research
can
inform
evaluation
predict
forest
area
well
provide
theoretical
basis
at
similar
sites.
Frontiers in Plant Science,
Journal Year:
2023,
Volume and Issue:
14
Published: July 27, 2023
Stand
biomass
models
can
be
used
as
basic
decision-making
tools
in
forest
management
planning.
The
Moso
bamboo
(Phyllostachys
pubescens)
forest,
a
major
system
tropical
and
subtropical
regions,
represents
substantial
carbon
sink,
slowing
down
the
rise
of
greenhouse
gas
concentrations
earth's
atmosphere.
Bamboo
stand
are
important
for
assessment
contribution
to
terrestrial
ecosystem.
We
constructed
model
using
destructively
sampled
data
from
45
sample
plots
that
were
located
across
Yixing
state-owned
farm
Jiangsu
Province,
China.
Among
several
variables
predictors
models,
mean
diameter
at
breast
height
(MDBH),
(MH),
canopy
density
(CD)
contributed
significantly
model.
To
increase
model's
accuracy,
we
introduced
effects
block
random
effect
into
through
mixed-effects
modeling.
described
large
part
variation
(R2
=
0.6987),
higher
than
ordinary
least
squares
regression
0.5748).
Our
results
show
an
increased
with
increasing
MH
CD,
confirming
our
biological
logic.
proposed
may
have
implications;
example,
it
combined
other
estimate
biomass,
sequestration,
different
growth
stages.
Frontiers in Plant Science,
Journal Year:
2023,
Volume and Issue:
14
Published: March 30, 2023
Height
to
crown
base
(HCB)
is
an
important
predictor
variable
for
forest
growth
and
yield
models
of
great
significance
bamboo
stem
utilization.
However,
existing
HCB
built
so
far
on
the
hierarchically
structured
data
are
arbor
forests,
not
applied
forests.
Based
fitting
acquired
from
38
temporary
sample
plots
Phyllostachys
edulis
forests
in
Yixing,
Jiangsu
Province,
we
selected
best
model
(logistic
model)
among
six
basic
extended
it
by
integrating
variables,
which
involved
evaluating
impact
13
variables
HCB.
Block-
plot-level
random
effects
were
introduced
account
nested
structures
through
mixed-effects
modeling.
The
results
showed
that
height,
diameter
at
breast
total
basal
area
all
individuals
with
a
larger
than
subject
bamboo,
canopy
density
contributed
significantly
more
variation
other
did.
Introducing
two-level
resulted
significant
improvement
accuracy
model.
Different
sampling
strategies
evaluated
response
calibration
(model
localization),
optimal
strategy
was
identified.
prediction
substantially
improved,
increase
number
samples
calibration.
our
findings,
recommend
use
four
randomly
per
provide
compromise
between
measurement
cost,
efficiency,
accuracy.
Forests,
Journal Year:
2022,
Volume and Issue:
13(4), P. 604 - 604
Published: April 12, 2022
The
forest
mortality
models
developed
so
far
have
ignored
the
effects
of
spatial
correlations
and
climate,
which
lead
to
substantial
bias
in
prediction.
This
study
thus
tree
for
Prince
Rupprecht
larch
(Larix
gmelinii
subsp.
principis-rupprechtii),
one
most
important
species
northern
China,
by
taking
those
into
account.
In
addition
these
factors,
our
include
both
tree—and
stand—level
variables,
information
was
collated
from
temporary
sample
plots
laid
out
across
forests.
We
applied
Bayesian
modeling,
is
novel
approach
build
multi-level
models.
compared
performance
constructed
through
combination
selected
predictor
variables
explored
their
corresponding
on
individual
mortality.
precisely
predicted
at
three
ecological
scales
(individual,
stand,
region).
model
levels
plot
stand
with
different
site
condition
(block)
outperformed
other
forms
(model
block
level
alone
fixed
model),
describing
significantly
larger
variations,
accounted
multiple
sources
unobserved
heterogeneities.
Results
showed
that
sum
squared
diameter
than
estimated
diameter,
mean
annual
precipitation
positively
correlated
mortality,
while
ratio
average
arithmetic
difference
temperature
negatively
correlated.
Our
results
will
significant
implications
identifying
various
including
could
large
influence
predict
scales.
Forests,
Journal Year:
2022,
Volume and Issue:
13(6), P. 823 - 823
Published: May 25, 2022
Height
to
crown
base
(HCB)
is
an
important
variable
used
as
a
predictor
of
forest
growth
and
yield.
This
study
developed
nonlinear,
mixed-effects
HCB
model
through
inclusion
plot-level
random
effects
using
data
from
29
sample
plots
distributed
across
state-owned
Yixing
farm
in
Jiangsu
province,
eastern
China.
Among
several
variables
evaluated
the
analyses,
bamboo
height,
canopy
density,
total
basal
area
with
diameter
larger
than
that
subject
individual
contributed
significantly
variations.
The
improved
prediction
accuracy
significantly,
indicating
variations
within
were
substantial.
was
localized
four
sampling
strategies,
identified
two
medium-sized
bamboos
by
at
breast
height
per
plot
resulted
smallest
error.
strategy,
which
would
balance
both
measurement
cost
potential
error,
may
be
applied
estimate
localization
nonlinear
for
moso
