Soil
moisture
is
a
key
regulator
of
hydrological
cycle
and
closely
related
to
vegetation
growth
climate
changes.
However,
exactly
how
soil
content
(SMC)
anomalies
on
the
Loess
Plateau
respond
large-scale
teleconnection
remails
unclear.
Here,
based
1
km
daily
dataset
using
in
situ
measurement
machine
learning,
we
demonstrated
that
there
was
an
interdecadal
fluctuation
from
2000
2020
sensitive
areas
restoration
(SAVR)
Plateau,
with
only
13.3%
whose
tendency
passed
significant
level
0.05.
Spatially,
summer
SMC
greater
than
5
m3/m3
(less
-5
m3/m3)
accounted
for
28.1%
(15.4%)
positive
(negative)
anomalous
years,
this
discrepancy
can
be
attributed
distinct
circulation
pattern
water
vapor
transport.
We
found
asymmetrical
distribution
atmospheric
patterns
between
negative
years.
In
years
SMC,
combination
low-pressure
system
around
Lake
Baikal
westward
expansion
western
Pacific
subtropical
high
triggered
sustained
southerly
west
flank,
strengthened
meridional
transport
south
China
north
North
China.
during
anticyclone
prevailed
over
transported
northwestward
central-eastern
rather
Plateau.
Under
above
patterns,
accumulation
approximately
4.1-fold
more
abundant
corresponding
upward
sinking
motions,
further
leading
less
summer,
respectively.
The
conclusions
study
have
implications
excavating
early
warning
information
natural
sustainable
management
Land Degradation and Development,
Journal Year:
2024,
Volume and Issue:
35(17), P. 5295 - 5307
Published: Oct. 10, 2024
ABSTRACT
Overgrazing
affects
the
grass‐livestock
balance
and
endangers
grassland
ecological
security.
Despite
extensive
studies
conducted
on
identifying
quantifying
grazing
intensity,
there
is
still
room
for
improvement
in
research
gridding
particularly
areas
with
limited
data
Qinghai–Tibet
Plateau.
Therefore,
we
proposed
a
intensity
spatialization
method
using
geographically
weighted
random
forest
(GWRF)
to
gain
further
insights
into
spatial
heterogeneity
of
alpine
intensity.
This
incorporates
multiple
remote
sensing
related
human
activities
natural
factors,
as
well
annual
livestock
statistics
at
township
level
over
several
years,
while
adequately
considering
autocorrelation
Additionally,
employed
Lindeman
Merenda
Gold
(LMG),
geographical
detector
model,
structural
equation
model
(SEM)
assess
contribution
influence
path
driving
factors
We
also
utilize
partial
correlation
analysis
dual‐phase
mapping
examine
impact
distribution
The
results
demonstrate
that
GWRF‐based
accurately
predicts
by
demonstrating
its
consistency
township‐scale
(
R
2
=
0.92
p
<
0.01),
RMSE
1.07).
provides
valuable
technical
support
pastoral
availability.
evaluate
trends
observe
an
increase
Gar
Purang
counties.
Furthermore,
population
density,
normalized
difference
vegetation
index
(NDVI),
temperature
are
identified
three
influential
affecting
areas.
other
indirectly
influencing
density
NDVI
levels,
their
interactions
amplify
overall
influence.
technique
has
demonstrated
significant
45.92%
0.01)
study
area,
emphasizing
substantial
Our
novel
framework
spatially
analyzing
unraveling
intricated
mechanisms
behind
spatiotemporal
changes,
Forests,
Journal Year:
2024,
Volume and Issue:
15(8), P. 1334 - 1334
Published: Aug. 1, 2024
Vegetation,
being
a
core
component
of
ecosystems,
is
known
to
be
influenced
by
natural
and
anthropogenic
factors.
This
study
used
the
annual
mean
Normalized
Difference
Vegetation
Index
(NDVI)
as
vegetation
greenness
indicator.
The
variation
in
NDVI
on
Hainan
Island
was
analyzed
using
Theil–Sen
median
trend
analysis
Mann–Kendall
test
during
2000–2019.
influence
factors
driving
mechanism
spatial
pattern
explored
Multiscale
Weighted
Regression
(MGWR)
model.
Additionally,
we
employed
Boosted
Tree
(BRT)
model
explore
their
contribution
NDVI.
Then,
MGWR
utilized
predict
future
patterns
based
precipitation
temperature
data
from
different
Shared
Socioeconomic
Pathway
(SSP)
scenarios
for
period
2021–2100.
results
showed
that:
(1)
forests
significantly
increased
2000
2019,
with
an
average
increase
rate
0.0026/year.
(2)
R2
0.93,
which
more
effective
than
OLS
(R2
=
0.42)
explaining
relationship.
regression
coefficients
ranged
−10.05
0.8
(p
<
0.05).
Similarly,
Gross
Domestic
Product
(GDP)
varied
between
−5.98
3.28
0.05);
(3)
played
most
dominant
role
influencing
activities
result
relative
contributions
83.2%
forest
changes
(16.8%
contributed
activities).
(4)
under
SSP119,
SSP245,
SSP585
2021
2100,
projected
have
overall
decreasing
all
scenarios.
reveals
change
relationship
factors,
can
guide
medium
long-term
dynamic
monitoring
evaluation
tropical
Island.
Soil
moisture
is
a
key
regulator
of
hydrological
cycle
and
closely
related
to
vegetation
growth
climate
changes.
However,
exactly
how
soil
content
(SMC)
anomalies
on
the
Loess
Plateau
respond
large-scale
teleconnection
remails
unclear.
Here,
based
1
km
daily
dataset
using
in
situ
measurement
machine
learning,
we
demonstrated
that
there
was
an
interdecadal
fluctuation
from
2000
2020
sensitive
areas
restoration
(SAVR)
Plateau,
with
only
13.3%
whose
tendency
passed
significant
level
0.05.
Spatially,
summer
SMC
greater
than
5
m3/m3
(less
-5
m3/m3)
accounted
for
28.1%
(15.4%)
positive
(negative)
anomalous
years,
this
discrepancy
can
be
attributed
distinct
circulation
pattern
water
vapor
transport.
We
found
asymmetrical
distribution
atmospheric
patterns
between
negative
years.
In
years
SMC,
combination
low-pressure
system
around
Lake
Baikal
westward
expansion
western
Pacific
subtropical
high
triggered
sustained
southerly
west
flank,
strengthened
meridional
transport
south
China
north
North
China.
during
anticyclone
prevailed
over
transported
northwestward
central-eastern
rather
Plateau.
Under
above
patterns,
accumulation
approximately
4.1-fold
more
abundant
corresponding
upward
sinking
motions,
further
leading
less
summer,
respectively.
The
conclusions
study
have
implications
excavating
early
warning
information
natural
sustainable
management
