Ecological Indicators,
Journal Year:
2023,
Volume and Issue:
148, P. 110089 - 110089
Published: March 6, 2023
Located
in
the
hilly
and
mountainous
central
area
of
national
ecological
security
strategic
pattern
(described
as
"two
barriers
three
green
belts"),
southern
Jiangxi
is
an
important
barrier
southeast
China
a
pilot
for
mountains-rivers-forests-farmlands-lakes-grasslands
restoration
projects.
In
recent
years,
rapid
economic
development
region
changes
land
use,
agricultural
intensification,
population
urbanization
have
severely
tested
this
ecosystem
on
which
people
depend
their
survival.
Currently,
studies
ecosystems
interactions
from
single
spatial
perspective
sprung
up,
but
only
few
comprehensively
analyzed
different
scales
to
facilitate
sustainable
regional
ecosystems.
Multi-scale
should
be
carried
out
quantitatively
understand
relationship
between
services
(ESs)
socio-natural
drivers,
attempt
find
suitable
scale
assess
ESs
or
achieve
complementary
advantages
by
combining
multi-scales
so
conduct
hierarchical
management
ESs.
Therefore,
better
interplay
goals
development,
we
evolutionary
patterns,
trade-offs,
synergies
our
analysis,
also
looked
at
bundling
drivers
seven
township
watershed
2000–2020
Jiangxi.
Crop
production,
meat
water
yield,
carbon
storage,
soil
retention,
habitat
quality,
forest
recreation
were
specifically
quantified,
redundancy
analysis
was
used
explore
influence
degree
precipitation,
temperature,
elevation,
slope,
GDP,
density
The
results
showed
that
most
increased
Jiangxi,
indicating
temporal
heterogeneity.
effect
trade-off
synergy
variation
similar,
amplitude
different.
Compared
with
scale,
overall
bundle
identified
clustered
scale.
addition,
Cluster
4
3
can
identify
high-value
areas
study
area.
growth
GDP
caused
main
driving
factors
difference
two
Our
provide
recommendations
governance
support
conducting
comprehensive
spatio-temporal
mechanisms
scales.
Ecological Indicators,
Journal Year:
2022,
Volume and Issue:
135, P. 108573 - 108573
Published: Jan. 19, 2022
Understanding
the
relationships
between
ecosystem
services
(ESs)
is
important
for
management
and
sustainable
development.
However,
most
studies
used
synergies
trade-offs
to
infer
ESs
relationships,
while
bundles
was
infrequently
involved.
Research
on
spatiotemporal
dynamics
potential
drivers
of
changes
still
lacking.
In
this
study,
we
quantified
mapped
10
in
1986,
1992,
1998,
2004,
2010,
2015
Yellow
River
Delta
(YRD)
region.
The
hotspots
analysis
first
discern
areas
high
low
supplies,
Spearman
correlation
then
applied
examining
ESs.
K-means
clustering
algorithm
identify
bundles,
Random
Forest
further
1986
2015.
Results
showed
that:
(1)
with
natural
ecosystems
were
reduced,
artificial
increased;
(2)
temporal
correlations
two
consecutive
years
similar
patterns,
spatial
changed
greatly;
(3)
types
increased,
provided
by
replaced
ecosystems;
(4)
increase
wetlands,
built-up
lands,
agricultural
yields,
as
well
decrease
marsh
lands
determinant
ES
bundles.
Our
findings
are
expected
enhance
current
understanding
contribute
targeted
coastal
areas.
Ecological Indicators,
Journal Year:
2022,
Volume and Issue:
140, P. 109058 - 109058
Published: June 15, 2022
Understanding
the
scale
effects
of
ecosystem
service
(ES)
supply–demand
balances
and
drivers
is
critical
to
hierarchical
management.
However,
it
remains
unclear
how
relationships
ES
driving
factors
change
with
scale.
In
this
study,
we
first
quantified
food
production
(FP),
water
yield
(WY),
soil
conservation
(SC),
carbon
storage
(CS),
habitat
quality
(HQ)
at
pixel
county
scales
in
2000
2020
Zhejiang
Province.
Then,
analyzed
trade-offs/synergies
different
scales.
Finally,
performed
correlation
analysis
applied
a
random
forest
model
explore
socioecological
these
ESs.
Our
work
showed
that
supplies
FP,
WY,
SC
increased,
while
those
CS
HQ
decreased
from
2020.
ESs
were
more
spatially
heterogeneous
than
FP
short
supply,
gaps
between
their
supply
demand
grew
over
time.
Some
mismatches
disappeared
From
scale,
directions
changed
slightly,
but
intensities
significantly.
The
temperature,
altitude,
percentage
forestland
normalized
difference
vegetation
index
(NDVI)
had
positive
on
HQ,
SC,
population
density
(POP),
gross
domestic
product
artificial
land
(PA)
negative
effects.
degree
influence
most
increased
increasing
NDVI
was
important
factor
for
CS,
precipitation
WY.
importance
POP
PA
both
time
Ultimately,
overall
should
be
considered
accurate
management
measures
implemented
promote
effective
This
study
emphasizes
necessity
considering
sustainable
Ecological Indicators,
Journal Year:
2022,
Volume and Issue:
144, P. 109539 - 109539
Published: Oct. 10, 2022
High-intensity
human
activities
have
changed
land
use/land
cover
(LULC)
patterns
in
the
Huangshui
River
Basin
(HRB),
which
has
brought
significant
challenges
to
ecosystems
sustainable
development.
Discerning
ecosystem
service
dynamic
characteristics
and
responses
under
different
use/cover
change
(LUCC)
scenarios
are
necessary
increase
public
willingness
pay
for
guide
decision-making
process.
We
examined
LULC
spatiotemporal
dynamics
HRB
from
2000
2020
coupled
Markov-chain,
multi-objective
programming
(MOP),
patch-generating
use
simulation
(PLUS)
models
optimize
simulate
spatial
pattern
five
scenarios:
natural
development
scenario
(NDs),
city
expansion
(CEs),
ecological
protection
(EPs),
economic
(EDs),
balance
(EEBs).
Given
regional
differences,
a
spatially
modified
value
(ESV)
assessment
model
was
proposed
evaluate
ESV.
Factors
driving
ESV
stratified
heterogeneity
were
identified
using
geographic
detectors.
Ecosystem
sensitivity
response
LUCC
discriminated
against
elasticity
model.
The
study
area
dominated
by
56.86–60.40
%
grassland
33.11–36.27
cropland.
Grassland
cropland
decreased
579.75
km2
423.87
over
period
2000–2020,
while
other
areas
such
as
forestland,
water
area,
construction
land,
barren
increased
289.81
km2,
140.77
489.10
83.96
respectively.
Land
conversion
mainly
occurred
among
grassland,
cropland,
land.
Total
39,665
million
yuan
2020,
an
of
2.25
compared
2000.
NDs,
EPs,
EDs,
EEBs
0.34
%,
1.04
2.01
7.78
respectively
that
CEs
0.17
%.
coefficient
0.43
during
2010–2020,
indicating
1
would
result
average
changes
services
not
very
marked
HRB.
Elevation
dominant
driver
effects
elevation
on
should
receive
more
attention
management.
Multi-objective
optimization
multi-scenario
analysis
effectively
guided
land-use
planning
involved
uncertainty,
complexity,
interaction.
EPs
may
be
suitable
future
Ecological Indicators,
Journal Year:
2023,
Volume and Issue:
155, P. 110926 - 110926
Published: Sept. 18, 2023
Changes
in
land
use/land
cover
(LULC)
can
impact
water
yield
(WY)
by
altering
the
structural
layout
and
functions
of
terrestrial
ecosystems.
Therefore,
to
ensure
regional
economic
ecosystem
sustainability,
it
is
critical
investigate
correlation
between
LULC
change
WY.
The
GMOP-PLUS-InVEST
(GPI)
coupling
model
based
on
gray
multi-objective
optimization
model,
patch-generating
use
simulation
integrated
valuation
services
trade-offs
was
used
this
study.
Establishing
three
different
scenarios:
business
as
usual
(BAU),
development
scenario
(ED),
ecological
conservation
(EC)
predict
distribution
pattern
Nansi
Lake
Basin
(NLB)
2035,
obtain
WY
from
2000
2035.
Getis-Ord
Gi*
Anselin
Local
Moran's
I
were
spatial–temporal
features
at
grid
scale.
results
indicated
that:
(1)
dominant
types
NLB
farmland
construction
land.
primary
transfer
trend
encroaching
due
acceleration
urbanization
process
policy
intervention.
(2)
2035
showed
that
BAU
had
a
continuous
for
nearly
20
years;
Under
ED,
intensity
encroachment
accelerating;
EC,
an
apparent
increase
proportion
could
be
seen,
contradiction
eased,
which
expected
more
line
with
planning
objectives.
(3)
significant
effect
From
continued
increase,
under
scenarios
ED
>
EC
BAU.
Spatially
always
high
value
south
west
NLB.
GPI
service
evaluation,
providing
ideas
rational
future
LULC.
Research
have
reference
significance
formulation
policies
protection
restoration
environment
