Ecological restoration zoning of territorial space in China: An ecosystem health perspective
Journal of Environmental Management,
Год журнала:
2024,
Номер
364, С. 121371 - 121371
Опубликована: Июнь 15, 2024
Язык: Английский
Linking landscape patterns to rainfall-runoff-sediment relationships: A case study in an agriculture, forest, and urbanization-dominated mountain watershed
Ecological Indicators,
Год журнала:
2025,
Номер
172, С. 113279 - 113279
Опубликована: Фев. 25, 2025
Язык: Английский
Characteristics of Ecosystem Services in Megacities Within the Yellow River Basin, Analyzed Through a Resilience Perspective: A Case Study of Xi’an and Jinan
Sustainability,
Год журнала:
2025,
Номер
17(8), С. 3371 - 3371
Опубликована: Апрель 10, 2025
Megacities
in
developing
countries
are
still
undergoing
rapid
urbanization,
with
different
cities
exhibiting
ecosystem
services
(ESs)
heterogeneity.
Evaluating
ESs
among
various
and
analyzing
the
influencing
factors
from
a
resilience
perspective
can
effectively
enhance
ability
of
to
deal
react
quickly
risks
uncertainty.
This
approach
is
also
crucial
for
optimizing
ecological
security
patterns.
study
focuses
on
Xi’an
Jinan,
two
important
megacities
along
Yellow
River
China.
First,
we
quantified
four
both
cities:
carbon
storage
(CS),
habitat
quality
(HQ),
food
production
(FP),
soil
conservation
(SC).
Second,
analyzed
synergies
trade-offs
between
these
using
bivariate
local
spatial
autocorrelation
Spearman’s
rank
correlation
coefficient.
Finally,
conducted
driver
analysis
Geographic
Detector.
Results:
(1)
The
temporal
distribution
Jinan
quite
different,
but
show
lower
ES
levels
urban
core
area.
(2)
showed
strong
synergistic
effect.
Among
them,
CS-HQ
had
strongest
synergy
0.93.
In
terms
space,
north
dominated
by
low–low
clustering,
while
south
high–high
clustering.
FP-SC
trade-off
effect
−0.35
2000,
which
gradually
weakened
over
time
was
mainly
distributed
northern
area
city
where
cropland
construction
were
concentrated.
(3)
Edge
density,
patch
NDVI
have
greatest
influence
CS
Jinan.
DEM,
slope,
density
HQ.
Temperature,
edge
impact
temperature
FP
cities.
SC.
Landscape
fragmentation
has
great
CS,
HQ,
SC
Due
insufficient
research
data,
this
focused
only
middle
reaches
River.
However,
results
provide
new
solving
problem
regional
sustainable
development
directions
ideas
follow-up
field.
Язык: Английский
Spatial Prediction of Soil Water Content by Bayesian Optimization–Deep Forest Model with Landscape Index and Soil Texture Data
Agronomy,
Год журнала:
2024,
Номер
14(12), С. 3039 - 3039
Опубликована: Дек. 19, 2024
The
accurate
prediction
of
the
spatial
variability
for
soil
water
content
(SWC)
in
farmland
is
essential
resource
management
and
sustainable
agricultural
development.
However,
natural
factors
introduce
uncertainty
result
poor
alignment
when
predicting
SWC,
leading
to
low
accuracy.
To
address
this,
this
study
introduced
a
novel
indicator:
landscape
indices.
These
indices
include
largest
patch
index
(LPI),
edge
density
(ED),
aggregation
(AI),
cohesion
(COH),
contagion
(CON),
division
(DIV),
percentage
like
adjacencies
(PLA),
Shannon
evenness
(SHEI),
diversity
(SHDI).
A
Bayesian
optimization–deep
forest
(BO–DF)
model
was
developed
leverage
these
SWC.
Statistical
analysis
revealed
that
exhibited
skewed
distributions
weak
linear
correlations
with
SWC
(r
<
0.2).
Despite
incorporating
variables
into
BO–DF
significantly
improved
accuracy,
R2
increasing
by
35.85%.
This
demonstrated
robust
nonlinear
fitting
capability
Spatial
mapping
using
indicated
high-value
areas
were
predominantly
located
eastern
southern
regions
Yellow
River
Delta
China.
Furthermore,
SHapley
additive
explanation
(SHAP)
highlighted
key
drivers
findings
underscore
potential
as
valuable
prediction,
supporting
regional
strategies
Язык: Английский