ACS Synthetic Biology,
Год журнала:
2024,
Номер
13(12), С. 3812 - 3826
Опубликована: Ноя. 21, 2024
The
study
of
ecosystems,
both
natural
and
artificial,
has
historically
been
mediated
by
population
dynamics
theories.
In
this
framework,
quantifying
numbers
related
variables
(associated
with
metabolism
or
biological-environmental
interactions)
plays
a
central
role
in
measuring
predicting
system-level
properties.
As
we
move
toward
advanced
technological
engineering
cells
organisms,
the
possibility
bioengineering
ecosystems
(from
gut
microbiome
to
wildlands)
opens
several
questions
that
will
require
quantitative
models
find
answers.
Here,
present
comprehensive
survey
modeling
approaches
for
managing
three
kinds
synthetic
sharing
presence
engineered
strains.
These
include
test
tube
examples
hosting
relatively
low
number
interacting
species,
mesoscale
closed
(or
ecospheres),
macro-scale,
ecosystems.
potential
outcomes
ecosystem
designs
their
limits
be
relevant
different
disciplines,
including
biomedical
engineering,
astrobiology,
space
exploration
fighting
climate
change
impacts
on
endangered
We
propose
possible
captures
broad
range
scenarios
tentative
roadmap
open
problems
further
exploration.
Nature Communications,
Год журнала:
2024,
Номер
15(1)
Опубликована: Сен. 13, 2024
Microbial
carbon
use
efficiency
(CUE)
affects
the
fate
and
storage
of
in
terrestrial
ecosystems,
but
its
global
importance
remains
uncertain.
Accurately
modeling
predicting
CUE
on
a
scale
is
challenging
due
to
inconsistencies
measurement
techniques
complex
interactions
climatic,
edaphic,
biological
factors
across
scales.
The
link
between
microbial
soil
organic
relies
stabilization
necromass
within
aggregates
or
association
with
minerals,
necessitating
an
integration
processes
approaches.
In
this
perspective,
we
propose
comprehensive
framework
that
integrates
diverse
data
sources,
ranging
from
genomic
information
traditional
assessments,
refine
cycle
models
by
incorporating
variations
CUE,
thereby
enhancing
our
understanding
contribution
cycling.
Abstract
The
interactions
between
soil
carbon
and
nitrogen
(C‐N)
processes
with
environmental
factors,
particularly
moisture,
are
critical
to
maintaining
ecosystem
functions.
However,
the
lagged
effects
of
future
change
in
moisture
on
C‐N
dynamics
remain
poorly
understood.
Here,
we
employed
Microbial‐ENzyme
Decomposition
model
simulate
long‐term
impacts
variation
using
standardized
index
(SSI)
across
four
Shared
Socioeconomic
Pathways
(SSPs).
Our
results
demonstrated
that
exhibited
both
cumulative
responses
fluctuations
over
extended
periods.
Active
microbes
were
closely
associated
short‐term
(3‐month)
whereas
organic
C
(SOC)
total
N
(TN)
stronger
correlations
periods
(72
months).
Under
SSP5‐8.5
scenario,
SOC
TN
decreased
wet
conditions
but
increased
during
droughts,
increases
28.9%
13.1%,
respectively,
under
extreme
drought
conditions.
We
found
active
microbial
biomass
was
significantly
more
sensitive
than
biomass,
especially
Furthermore,
enzymes
key
drivers
transformations,
displaying
highest
correlation
SSI
(nonlinear
coefficient
based
mutual
information
=
0.81).
This
study
establishes
a
foundational
relationship
variables
accounting
for
lag
effects,
enhance
our
understanding
complex
these
climate
scenarios.
