Frontiers in Microbiology,
Год журнала:
2024,
Номер
15
Опубликована: Март 14, 2024
Saline
water
irrigation
(SWI)
plays
an
important
role
in
alleviating
resource
shortages.
At
the
same
time,
salt
input
of
affects
soil
microorganisms
which
participate
various
ecological
processes
terrestrial
ecosystems.
However,
responses
microbial
functional
potential
to
long-term
SWI
remains
unclear.
Therefore,
Metagenomics
method
was
utilized
cotton
fields
under
reveal
profiles
associated
with
carbon
and
nitrogen
cycles.
Results
indicated
that
impacted
cycles
significantly.
Especially,
salinity
inhibited
relative
abundances
sacC
vanB
,
are
degradation
genes.
also
affected
gene
abundance
degradation,
dissimilatory
nitrate
reduction,
nitrification.
Moreover,
significantly
increased
Candidatus_Cloacimonetes
both
In
discussion,
we
used
person
analysis
found
salinity,
pH,
ammonium
were
factors
affecting
genes
taxa.
Overall,
this
study
influenced
specific
taxa
abundance,
may
lead
predictable
outcomes
for
cycling,
is
great
importance
exploring
impact
on
environments.
Reviews of Geophysics,
Год журнала:
2025,
Номер
63(1)
Опубликована: Янв. 2, 2025
Abstract
Physical
and
chemical
erosion
associated
with
water
both
affect
land–atmosphere
carbon
exchanges.
However,
previous
studies
have
often
addressed
these
processes
separately
or
used
oversimplified
mechanisms,
leading
to
ongoing
debates
uncertainties
about
erosion‐induced
fluxes.
We
provide
an
overview
of
the
on‐site
uptake
fluxes
induced
by
physical
(0.05–0.29
Pg
C
yr
−1
,
globally)
(0.26–0.48
).
Then,
we
discuss
off‐site
dynamics
(during
transport,
deposition,
burial).
Soil
organic
mineralization
during
transport
is
nearly
0.37–1.20
on
globe.
also
summarize
overall
into
estuaries
(0.71–1.06
)
identify
sources
different
types
within
them,
most
which
are
land
erosion.
Current
approaches
for
quantifying
physical‐erosion‐induced
vertical
focus
two
distinct
temporal
scales:
short‐term
(ranging
from
minutes
decades),
emphasizing
net
flux,
long‐term
(spanning
millennial
geological
timescales),
examining
fate
eroded
over
extended
periods.
In
addition
direct
measurement
modeling
approaches,
estimation
using
indicators
riverine
material
popular
constraining
chemical‐erosion‐driven
Lastly,
highlight
key
challenges
related
To
overcome
potential
biases
in
future
studies,
strongly
recommend
integrated
research
that
addresses
a
well‐defined
timescale.
A
comprehensive
understanding
mechanisms
driving
lateral
crucial
closing
global
budget.
Ecology Letters,
Год журнала:
2023,
Номер
26(10), С. 1803 - 1814
Опубликована: Авг. 17, 2023
Soil
microbial
respiration
is
expected
to
show
adaptations
changing
temperatures,
greatly
weakening
the
magnitude
of
feedback
over
time,
as
shown
in
labile
carbon
substrates.
However,
whether
such
thermal
adaptation
persists
during
long-term
soil
decomposition
substrates
decrease
decomposability
remains
unknown.
Here,
we
conducted
a
6-year
incubation
experiment
natural
and
arable
soils
with
distinct
properties
under
three
temperatures
(10,
20
30°C).
Mass-specific
was
consistently
lower
higher
suggesting
occurrence
persistence
decomposition.
Furthermore,
changes
community
composition
function
largely
explained
respiratory
adaptation.
If
generally
occurs
large
low-decomposability
pools,
warming-induced
losses
may
be
than
previously
predicted
thus
not
contribute
much
greenhouse
warming.
Climate smart agriculture.,
Год журнала:
2024,
Номер
1(1), С. 100001 - 100001
Опубликована: Апрель 24, 2024
Modeling
soil
organic
carbon
(SOC)
is
helpful
for
understanding
its
distribution
and
turnover
processes,
which
can
guide
the
implementation
of
effective
measures
(C)
sequestration
enhance
land
productivity.
Process-based
simulation
with
high
interpretability
extrapolation,
machine
learning
modeling
flexibility
are
two
common
methods
investigating
SOC
turnover.
To
take
advantage
both
methods,
we
developed
a
hybrid
model
by
coupling
two-carbon
pool
microbial
modeling.
Here,
assessed
model's
predictive,
mapping,
capabilities
process
on
Ningbo
region.
The
results
indicate
that
density-dependence
(β
=
2)
biomass
performed
better
in
parameters
microbial-based
C
cycle,
such
as
use
efficiency
(CUE),
mortality
rate,
assimilation
rate.
By
integrating
this
optimal
random
forest
(RF)
model,
improved
prediction
accuracy
SOC,
an
increased
R2
from
0.74
to
0.84,
residual
deviation
1.97
2.50,
reduced
root-mean-square
error
4.65
3.67
g
kg−1
compared
conventional
RF
model.
As
result,
predicted
exhibited
spatial
variation
provided
abundant
details.
Microbial
CUE
potential
input,
represented
net
primary
productivity,
emerged
factors
driving
Projections
under
CMIP6
SSP2-4.5
scenario
revealed
regional
loss
areas
was
mainly
caused
decreased
induced
climate
change.
Our
findings
highlight
combining
microbial-explicit
improve
understand
feedback
changing
climate.
