Pre-Season Precipitation and Temperature Have a Larger Influence on Vegetation Productivity than That of the Growing Season in the Agro-Pastoral Ecotone in Northern China
Agriculture,
Journal Year:
2025,
Volume and Issue:
15(2), P. 219 - 219
Published: Jan. 20, 2025
Climate
change
and
human
activities
are
reshaping
the
structure
function
of
terrestrial
ecosystems,
particularly
in
vulnerable
regions
such
as
agro-pastoral
ecotones.
However,
extent
to
which
climate
impacts
vegetation
growth
these
areas
remains
poorly
understood,
largely
due
modifying
effects
human-induced
land
cover
changes
on
sensitivity
climatic
variations.
This
study
utilizes
satellite-derived
indices,
datasets,
data
investigate
influence
both
ecotone
northern
China
(APENC)
from
2001
2022.
The
results
reveal
that
productivity,
indicated
by
kernel
Normalized
Difference
Vegetation
Index
(kNDVI),
varies
depending
type
APENC.
Moreover,
ridge
regression
modeling
shows
pre-season
conditions
(i.e.,
precipitation
temperature)
have
a
stronger
positive
impact
growing-season
productivity
than
growing
season
temperature,
while
effect
vapor
pressure
deficit
(VPD)
is
negative.
Notably,
kNDVI
exhibits
significant
(p
<
0.05)
34.12%
region
negative
VPD
38.80%.
model
explained
89.10%
total
variation
(R2
=
0.891).
These
findings
not
only
emphasize
critical
role
historical
contemporary
shaping
but
also
provide
valuable
insights
into
how
adjust
agricultural
animal
husbandry
management
strategies
improve
regional
adaptation
based
information
previous
seasons
fragile
regions.
Language: Английский
Advancements in Monitoring Tree Phenology Under Global Change: A Comprehensive Review
Dalong Jiang,
No information about this author
Xu Zuo,
No information about this author
Tao Nie
No information about this author
et al.
Forests,
Journal Year:
2025,
Volume and Issue:
16(5), P. 771 - 771
Published: April 30, 2025
This
comprehensive
review
explores
recent
advancements
in
monitoring
tree
phenology
the
context
of
global
change.
As
climate
change
continues
to
alter
ecosystems
worldwide,
understanding
has
become
increasingly
crucial
for
predicting
ecological
responses
and
informing
conservation
strategies.
examines
traditional
ground-based
observation
methods,
highlights
their
strengths
limitations,
discusses
integration
modern
technologies
such
as
remote
sensing,
digital
cameras,
sensor
networks.
Special
attention
is
given
role
citizen
science
initiatives
expanding
phenological
data
collection.
also
addresses
challenges
posed
by
monitoring,
including
shifting
patterns
complexities.
Furthermore,
it
applications
research,
ecosystem
management,
biodiversity
conservation.
The
paper
concludes
identifying
future
directions
emerging
that
promise
revolutionize
emphasizing
need
interdisciplinary
collaboration
standardized
methodologies
enhance
our
a
rapidly
changing
world.
Language: Английский
Twenty-Year Variability in Water Use Efficiency over the Farming–Pastoral Ecotone of Northern China: Driving Force and Resilience to Drought
Xiaonan Guo,
No information about this author
Meng Wu,
No information about this author
Zhijun Shen
No information about this author
et al.
Agriculture,
Journal Year:
2025,
Volume and Issue:
15(11), P. 1164 - 1164
Published: May 28, 2025
Water
use
efficiency
(WUE),
as
an
important
metric
for
ecosystem
resilience,
has
been
identified
to
play
a
significant
role
in
the
coupling
of
carbon
and
water
cycles.
The
farming–pastoral
ecotone
Northern
China
(FPENC),
which
is
highly
susceptible
drought
due
scarcity,
long
recognized
ecologically
fragile
zone.
ecological
restoration
projects
have
mitigated
land
degradation
maintain
sustainability
dryland.
However,
process
greening
drylands
potential
impact
availability.
A
comprehensive
analysis
WUE
FPENC
can
help
understand
absorption
consumption.
Using
gross
primary
production
(GPP)
evapotranspiration
(ET)
data
from
MODerate
resolution
Imaging
Spectroradiometer
(MODIS),
alongside
biophysical
variables
cover
information,
spatio-temporal
variations
2003
2022
were
examined.
Additionally,
its
driving
force
resilience
also
revealed.
Results
indicated
that
annual
mean
fluctuated
between
0.52
2.60
gC
kgH2O−1,
showing
non-significant
decreasing
trend
across
FPENC.
Notably,
averaged
underwent
decline
before
2012
(p
<
0.05),
then
showed
slight
increased
=
0.14)
during
year
afterward
(i.e.,
2013–2022).
In
terms
climatic
controls,
temperature
(Temp)
soil
volumetric
content
(VSWC)
dominantly
affected
2012;
VPD
(vapor
pressure
deficit),
VSWC,
Temp
controls
2013
2022.
findings
suggest
wetter
atmosphere
moisture
contribute
WUE.
total,
59.2%
was
shown
be
non-resilient,
grassland
occupy
majority
area,
located
Mu
Us
Sandy
Horqin
Sand
Land.
These
results
underscore
importance
factors
regulation
over
highlight
necessity
focused
research
on
responses
climate
change,
particularly
extreme
events
like
droughts,
future.
Language: Английский
Increased Contribution of Extended Vegetation Growing Season to Boreal Terrestrial Ecosystem GPP Enhancement
Remote Sensing,
Journal Year:
2024,
Volume and Issue:
17(1), P. 83 - 83
Published: Dec. 28, 2024
Rapid
Arctic
warming
is
driving
significant
changes
in
boreal
vegetation
phenology
and
productivity.
The
potentially
asynchronous
response
of
these
processes
could
substantially
alter
the
relative
impacts
phenological
shifts
on
variations
gross
primary
productivity
(GPP),
but
this
remains
poorly
understood.
objective
study
to
quantify
impact
extension
ecosystem
GPP
across
different
periods
from
1982
2018.
To
achieve
this,
we
developed
a
statistical
model
that
integrates
physiology,
introduced
new
metric,
Relative
Increment
Effect
(RIE),
assess
contribution
increase.
Our
analysis
revealed
became
dominant
driver
increment
over
time.
Specifically,
overall
RIE
for
increased
by
22%
earlier
period
(P1:
1982–2000,
3.2)
more
recent
(P2:
2001–2018,
3.93).
This
increase
was
pronounced
grass
shrub
ecosystems.
Spatial
patterns
showed
increases
were
particularly
concentrated
at
high
latitudes,
especially
northern
Siberia.
These
findings
suggested
playing
an
increasing
role
regulating
productivity,
with
implications
carbon
budget
under
future
scenarios.
Language: Английский