One Earth,
Journal Year:
2024,
Volume and Issue:
7(1), P. 59 - 71
Published: Jan. 1, 2024
The
cascading
effects
of
biodiversity
decline
on
human
well-being
present
a
pressing
challenge
for
sustainable
development.
Conservation
efforts
often
prioritize
safeguarding
specific
species,
habitats,
or
intact
ecosystems
but
overlook
biodiversity's
fundamental
role
in
providing
Nature's
Contributions
to
People
(NCP)
human-modified
landscapes.
Here,
we
systematically
review
154
peer-reviewed
studies
estimate
the
minimum
levels
(semi-)natural
habitat
quantity,
quality,
and
spatial
configuration
needed
landscapes
secure
functional
integrity
essential
sustaining
NCP
provision.
We
find
that
provision
multiple
is
threatened
when
landscape
falls
below
an
area
20%–25%
each
km2.
Five
almost
completely
disappear
level
10%
habitat.
exact
required
depends
local
context
NCP.
Today,
about
two-thirds
lands
have
insufficient
habitat,
requiring
action
regeneration.
Our
findings
serve
as
generic
guideline
target
conservation
actions
outside
natural
areas.
Forests,
Journal Year:
2024,
Volume and Issue:
15(1), P. 215 - 215
Published: Jan. 21, 2024
Forest
aboveground
biomass
(AGB)
is
integral
to
the
global
carbon
cycle
and
climate
change
study.
Local
regional
AGB
mapping
crucial
for
understanding
stock
dynamics.
NASA’s
ecosystem
dynamics
investigation
(GEDI)
combination
of
multi-source
optical
synthetic
aperture
radar
(SAR)
datasets
have
great
potential
local
estimation
mapping.
In
this
study,
GEDI
L4A
data
ground
sample
plots
worked
as
true
values
explore
their
difference
estimating
forest
using
Sentinel-1
(S1),
Sentinel-2
(S2),
ALOS
PALSAR-2
(PALSAR)
data,
individually
in
different
combinations.
The
effects
types
validation
were
investigated
well.
S1
S2
performed
best
with
R2
ranging
from
0.79
0.84
RMSE
7.97
29.42
Mg/ha,
used
truth
data.
While
product
working
reference,
range
0.36
0.47
31.41
37.50
Mg/ha.
between
plot
reference
shows
obvious
dependence
on
types.
summary,
dataset
its
SAR
better
when
average
less
than
150
predictions
underperformed
across
study
sites.
However,
can
work
source
a
certain
level
accuracy.
Sensors,
Journal Year:
2022,
Volume and Issue:
23(1), P. 349 - 349
Published: Dec. 29, 2022
Agroforestry
systems
(AFS)
offer
viable
solutions
for
climate
change
because
of
the
aboveground
biomass
(AGB)
that
is
maintained
by
tree
component.
Therefore,
spatially
explicit
estimation
their
AGB
crucial
reporting
emission
reduction
efforts,
which
can
be
enabled
using
remote
sensing
(RS)
data
and
methods.
However,
multiple
factors
including
spatial
distributions
within
AFS,
structure,
composition,
variable
extents
hinder
an
accurate
RS-assisted
across
AFS.
The
aim
this
study
to
(i)
evaluate
potential
spaceborne
optical,
SAR
LiDAR
estimations
in
AFS
(ii)
estimate
different
various
climatic
regions.
was
carried
out
three
regions
covering
Côte
d’Ivoire
Burkina
Faso.
Two
reference
sources
were
assessed:
derived
from
field
measurements
allometric
equations
predictions
GEDI
level
4A
(L4A)
product.
Vegetation
indices
texture
parameters
generated
optical
(Sentinel-2)
(Sentinel-1
ALOS-2)
respectively
used
as
predictors.
Machine
learning
regression
models
trained
evaluated
means
coefficient
determination
(R2)
RMSE.
It
found
prediction
error
reduced
31.2%
after
stratification
based
on
conditions.
For
prediction,
combination
random
forest
algorithm
Sentinel-1
-2
returned
best
score.
L4A
product
applicable
only
Guineo-Congolian
region,
but
approx.
nine
times
higher
than
ground
truth.
Moreover,
varied
cocoa
(7.51
±
0.6
Mg
ha−1)
rubber
(7.33
0.33
cashew
(13.78
0.98
mango
(12.82
0.65
Guinean
region.
farms
Sudanian
region
showed
highest
(6.59
82.11
ha−1).
mainly
determined
diameter
(R2
=
0.45),
height
0.13)
density
0.10).
Nevertheless,
RS-based
remain
challenging
spectral
similarities
between
assessment
uncertainties
should
complement
maps
Ecological Informatics,
Journal Year:
2023,
Volume and Issue:
79, P. 102408 - 102408
Published: Dec. 3, 2023
As
agricultural
land
expansion
is
the
primary
driver
of
deforestation,
agroforestry
could
be
an
optimal
use
strategy
for
climate
change
mitigation
and
reducing
pressure
on
forests.
Agroforestry
a
promising
method
carbon
sequestration.
With
recent
advancements
in
geospatial
data
science
technology,
ability
to
predict
aboveground
biomass
(AGB)
assess
ecosystem
services
rapidly
expanding.
This
study
was
conducted
Belpada
Block
Balangir,
Odisha,
forest-dominated
region
eastern
India.
We
recorded
species
occurrence
measured
plant
parameters,
including
Circumference
at
Breast
Height
(CBH),
height,
geolocation,
196
plots
(0.09
ha)
intervention
sites
noted
tree
species.
used
Sentinel-1
Sentinel-2
multi
sensor
achieve
synergy
AGB
estimation.
Three
machine
learning
models
were
used:
Random
Forest
(RF),
Support
Vector
Machine
(SVM),
Artificial
Neural
Network
(ANN).
The
RF
model
exhibited
highest
level
prediction
accuracy
(R2
=
0.69
RMSE
17.07
Mg/ha),
followed
by
ANN
0.63
19.35
SVM
0.54,
21.97
Mg/ha.
spectral
vegetation
indices
that
are
(Normalized
Difference
Vegetation
Index
(NDVI),
Soil-Adjusted
(SAVI),
Enhanced
(EVI),
Modified
Simple
Ratio
(MSR),
(MSAVI),
(DVI),
SAR
backscatter
values,
found
important
variables
prediction.
findings
revealed
interventions
plantations
resulted
average
stock
increase
15
Mg/ha
over
five
years
area.
Plant
Value
(PVI),
which
indicates
importance
local
economy
storage,
showed
Tectona
grandis
dominant
with
PVI
value
(88.35),
Eucalyptus
globulus
(56.87),
Mangifera
indica
(53.75),
Azadirachta
(15.45).
approach
enables
monitoring
efforts
systems,
thereby
promoting
effective
management
strategies.
Current Opinion in Environmental Sustainability,
Journal Year:
2023,
Volume and Issue:
62, P. 101293 - 101293
Published: May 20, 2023
Agroforests
exist
in
many
forms,
for
example,
across
Indonesia,
but
are
largely
absent
from
policy
documents.
Development
planners
have
long
seen
them
as
backward,
agroforests,
or
domesticated
forests,
with
high
(agro)
biodiversity,
reconcile
instrumental
(goal-oriented)
and
relational
(harmony-oriented)
values
of
nature
various
stakeholders.
combine
farmer-managed,
remnant,
tolerated
spontaneously
established
trees;
they
blend
market
demands
local
needs
labor-efficient,
nature-based
land
use.
Could
explicit
recognition
interfacing
these
values,
help
achieve
the
Kunming-Montreal
Global
Biodiversity
Framework?
In
cultural
context,
men
women
may
express
appreciation
agroforest
structure
function
differently.
The
scarcity
remaining
natural
forests
increases
agroforests'
role
diverse
reservoirs.
under
threat
publicly
subsidized
conversion
to
monoculture
tree
crop
plantations,
exposing
farmers
economic
ecological
risk.
Reimagining
biodiversity
conservation
solutions
where
agroforests
remain
part
landscape
is
an
opportunity
not
be
missed.
Agriculture Ecosystems & Environment,
Journal Year:
2023,
Volume and Issue:
360, P. 108795 - 108795
Published: Nov. 2, 2023
Global
models
of
biodiversity
and
ecosystem
services
base
their
calculations
on
land
use
classifications,
where
agricultural
is
only
divided
into
a
few
categories
management
intensity.
These
classifications
were
not
developed
to
underpin
models.
This
why
crop
diversity
the
presence
non-crop
plants
or
livestock
in
are
considered
these
despite
effect
they
have
agrobiodiversity
supply
services.
Therefore,
results
neglecting
current
diversified
systems
diversification
practices
In
this
paper,
we
present
new
global
classification
organized
as
matrix
intensity
ranges.
The
based
literature
review
expert
interviews
illustrated
by
examples
around
world.
first
step
build
cover
maps
that
consider
systems,
which
could
then
be
used
structure
makes
it
flexible
adjustable
for
different
purposes,
such
exploring
potential
preserving
through
land-use
scenarios
assessing
trade-offs
between
diversity.
