Journal of Geophysical Research Biogeosciences,
Journal Year:
2022,
Volume and Issue:
127(12)
Published: Dec. 1, 2022
Long-running
eddy
covariance
flux
towers
provide
insights
into
how
the
terrestrial
carbon
cycle
operates
over
multiple
timescales.
Here,
we
evaluated
variation
in
net
ecosystem
exchange
(NEE)
of
dioxide
(CO
Nature Communications,
Journal Year:
2023,
Volume and Issue:
14(1)
Published: Nov. 29, 2023
Drought
is
often
thought
to
reduce
ecosystem
photosynthesis.
However,
theory
suggests
there
potential
for
increased
photosynthesis
during
meteorological
drought,
especially
in
energy-limited
ecosystems.
Here,
we
examine
the
response
of
(gross
primary
productivity,
GPP)
drought
across
water-energy
limitation
spectrum.
We
find
a
consistent
increase
eddy
covariance
GPP
spring
ecosystems
(83%
sites).
Half
sensitivity
precipitation
was
predicted
solely
from
wetness
index
(R2
=
0.47,
p
<
0.001),
with
weaker
relationships
summer
and
fall.
Our
results
suggest
increases
55%
vegetated
Northern
Hemisphere
lands
(
>30°
N).
then
compare
these
terrestrial
biosphere
model
outputs
remote
sensing
products.
In
contrast
trends
detected
data,
mean
always
declined
under
deficits
after
controlling
air
temperature
light
availability.
While
products
captured
observed
negative
ecosystems,
models
proved
insufficiently
sensitive
deficits.
Earth system science data,
Journal Year:
2024,
Volume and Issue:
16(1), P. 15 - 34
Published: Jan. 4, 2024
Abstract.
Leaf
area
index
(LAI)
and
fraction
of
photosynthetically
active
radiation
(FPAR)
are
critical
biophysical
parameters
for
the
characterization
terrestrial
ecosystems.
Long-term
global
LAI/FPAR
products,
such
as
moderate
resolution
imaging
spectroradiometer
(MODIS)
Visible
Infrared
Imaging
Radiometer
Suite
(VIIRS),
provide
fundamental
dataset
accessing
vegetation
dynamics
studying
climate
change.
However,
existing
products
suffer
from
several
limitations,
including
spatial–temporal
inconsistencies
accuracy
issues.
Considering
these
this
study
develops
a
sensor-independent
(SI)
data
record
(CDR)
based
on
Terra-MODIS/Aqua-MODIS/VIIRS
standard
products.
The
SI
CDR
covers
period
2000
to
2022,
at
spatial
resolutions
500
m/5
km/0.05∘,
8
d/bimonthly
temporal
frequencies
available
in
sinusoidal
WGS1984
projections.
methodology
includes
(i)
comprehensive
analyses
sensor-specific
quality
assessment
variables
select
high-quality
retrievals,
(ii)
application
tensor
(ST-tensor)
completion
model
extrapolate
LAI
FPAR
beyond
areas
with
(iii)
generation
various
projections
resolutions,
(iv)
evaluation
by
direct
comparisons
ground
indirectly
through
reproducing
results
trends
documented
literature.
This
paper
provides
analysis
each
step
involved
CDR,
well
ST-tensor
model.
Comparisons
truth
suggest
an
RMSE
0.84
(0.15
FPAR)
units
R2
0.72
(0.79),
which
outperform
Terra/Aqua/VIIRS
is
characterized
low
time
series
stability
(TSS)
value,
suggesting
more
stable
less
noisy
than
sensor-dependent
counterparts.
Furthermore,
mean
absolute
error
(MAE)
also
lower,
that
comparable
retrievals.
trend
agree
previous
studies,
enhanced
capabilities
utilize
Overall,
integration
multiple
satellite
sources
use
advanced
gap
filling
modeling
techniques
improve
ensuring
reliability
long-term
carbon
cycle
modeling,
land
policy
development
informed
decision-making
sustainable
environmental
management.
open
access
under
Creative
Commons
Attribution
4.0
License
https://doi.org/10.5281/zenodo.8076540
(Pu
et
al.,
2023a).
Abstract
Many
regions
of
the
planet
have
experienced
an
increase
in
fire
activity
recent
decades.
Although
such
increases
are
consistent
with
warming
and
drying
under
continued
climate
change,
driving
mechanisms
remain
uncertain.
Here,
we
investigate
effects
increasing
atmospheric
carbon
dioxide
concentrations
on
future
using
seven
Earth
system
models.
Centered
time
doubling,
multi-model
mean
percent
change
emissions
is
66.4
±
38.8%
(versus
1850
concentrations,
fixed
land-use
conditions).
A
substantial
associated
enhanced
vegetation
growth
due
to
biogeochemical
impacts
at
60.1
46.9%.
In
contrast,
radiative
impacts,
including
drying,
yield
a
negligible
response
1.7
9.4%.
model
representation
processes
remains
uncertain,
our
results
show
importance
dynamics
dioxide,
potentially
important
policy
implications.
Ecological Indicators,
Journal Year:
2024,
Volume and Issue:
163, P. 112140 - 112140
Published: May 16, 2024
Climate
change
is
one
of
dominators
driving
the
greening
vegetation
worldwide,
which
expected
to
enhance
land
carbon
sink
and
mitigate
global
warming.
The
sensitivity
greenness
climate
fluctuant
regulated
by
other
environmental
factors.
However,
drivers
mechanisms
behind
remain
unclear
so
far.
Here,
we
hired
long-term
satellite-based
index
(NDVI),
climatic
variables,
nitrogen
deposition,
atmospheric
CO2
records
investigate
variations
its
across
Eurasia.
To
obtain
timeseries
temperature
(γNDVITEM)
precipitation
(γNDVIPRE),
applied
multi-regression
models
regressed
on
NDVI
in
each
9-year
moving
windows.
results
showed
that
area
limited
low
temperatures
substantially
shrunk,
while
deficit
increased
during
1982–2015.
Specifically,
significantly
decreasing
γNDVITEM
γNDVIPRE
accounted
for
29.8%
20.1%,
respectively,
remarkably
increasing
about
18.2%
24.5%,
vegetated
lands
Declining
was
widely
observed
most
biomes,
including
tropical
subtropical
moist
broadleaf
forests,
temperate
mixed
coniferous
croplands,
deserts
xeric
shrublands.
Substantially
merely
found
montane
grasslands
shrublands,
dry
nonlinear
regimes
proved
biome
types.
Spatially,
rather
than
elevated
factors
(temperature,
precipitation,
radiation)
jointly
dominated
nearly
45%
48%
Eurasia
respectively.
Our
uncovered
apparent
pattern
changes
highlighted
necessity
unfold
underlying
based
plant
physiology
traits.
AGU Advances,
Journal Year:
2022,
Volume and Issue:
3(4)
Published: July 6, 2022
Forests
provide
natural
climate
solutions
for
sequestering
carbon
and
mitigating
change,
yet
are
increasingly
threatened
by
increasing
temperature
disturbance.
Understanding
these
threats
requires
accurate
information
on
vegetation
dynamics
their
drivers,
which
is
currently
lacking
in
many
regions
experiencing
rapid
change
such
as
California.
To
address
this,
we
combined
remote
sensing
observations
with
geospatial
databases
to
develop
annual
maps
of
cover
(tree,
shrub,
herbaceous)
disturbance
type
(fire,
harvest,
forest
die-off)
California
at
30
m
resolution
from
1985
2021.
Considering
both
changes
fraction
areal
extent,
lost
4,566
km2
its
tree
area
(6.7%
relative
initial
cover)
since
1985.
Substantial
gains
during
the
1990s
were
more
than
offset
fire-driven
declines
2000,
resulting
greater
shrub
herbaceous
area.
Tree
loss
occurred
all
ecoregions
but
was
most
severe
southern
mountains,
where
losses
wildfire
not
compensated
regrowth
undisturbed
areas.
Fires
generally
summer
temperatures
17.5°C,
whereas
net
gain
often
cooler
areas,
suggesting
that
ongoing
warming
threatening
forests
California's
undergoing
transformation,
rates
posing
substantial
potential
risks
integrity
terrestrial
sink.
PeerJ,
Journal Year:
2023,
Volume and Issue:
11, P. e15593 - e15593
Published: June 23, 2023
The
global
potential
distribution
of
biomes
(natural
vegetation)
was
modelled
using
8,959
training
points
from
the
BIOME
6000
dataset
and
a
stack
72
environmental
covariates
representing
terrain
current
climatic
conditions
based
on
historical
long
term
averages
(1979-2013).
An
ensemble
machine
learning
model
stacked
regularization
used,
with
multinomial
logistic
regression
as
meta-learner
spatial
blocking
(100
km)
to
deal
autocorrelation
points.
Results
cross-validation
for
classes
show
an
overall
accuracy
0.67
R2logloss
0.61,
"tropical
evergreen
broadleaf
forest"
being
class
highest
gain
in
predictive
performances
(R2logloss
=
0.74)
"prostrate
dwarf
shrub
tundra"
lowest
-0.09)
compared
baseline.
Temperature-related
were
most
important
predictors,
mean
diurnal
range
(BIO2)
shared
by
all
base-learners
(i.e.,random
forest,
gradient
boosted
trees
generalized
linear
models).
next
used
predict
future
periods
2040-2060
2061-2080
under
three
climate
change
scenarios
(RCP
2.6,
4.5
8.5).
Comparisons
predictions
epochs
(present,
2061-2080)
that
increasing
aridity
higher
temperatures
will
likely
result
significant
shifts
natural
vegetation
tropical
area
(shifts
forests
savannas
up
1.7
×105
km2
2080)
around
Arctic
Circle
tundra
boreal
2.4
2080).
Projected
maps
at
1
km
resolution
are
provided
probability
hard
IUCN
(six
aggregated
classes).
Uncertainty
(prediction
error)
also
should
be
careful
interpretation
projections.