Ecology and Evolution,
Journal Year:
2024,
Volume and Issue:
14(11)
Published: Nov. 1, 2024
ABSTRACT
The
great
gerbil
(
Rhombomys
opimus
)
is
a
gregarious
rodent
in
Central
Asia
and
one
of
the
major
pests
found
desert
forest
grassland
areas.
distribution
changes
migration
routes
R.
under
climate
change
remain
unexplored.
This
study
employed
multi‐model
ensemble,
correlation
analysis,
jackknife
method,
minimum
cumulative
resistance
(MCR)
model
to
simulate
potential
habitat
current
future
(2030
2050)
scenarios
estimate
its
possible
routes.
results
indicate
that
ensemble
integrating
Random
Forest
(RF),
Gradient
Boosting
Machine
(GBM),
Maximum
Entropy
Model
(MaxEnt)
performed
best
within
present
context.
predicted
with
an
area
curve
(AUC)
0.986
True
Skill
Statistic
(TSS)
0.899,
demonstrating
excellent
statistical
accuracy
spatial
performance.
Under
scenarios,
northern
Xinjiang
southeastern
Kazakhstan
will
core
areas
distribution.
However,
optimal
region
expand
relative
one.
expansion
increase
rising
CO
2
emission
levels
over
time,
potentially
enlarging
suitable
by
up
39.49
×
10
4
km
.
In
terms
distribution,
for
shifting
toward
higher
latitudes
elevations.
For
specific
routes,
tends
favor
paths
through
farmland
grassland.
can
provide
guidance
managing
controlling
scenarios.
Understanding
and
forecasting
changes
in
marine
habitats
due
to
global
climate
warming
is
crucial
for
sustainable
fisheries.
Using
future
environmental
data
provided
by
Global
Climate
Models
(GCMs)
occurrence
records
of
Chub
mackerel
the
North
Pacific
Ocean
(2014-2023),
we
built
eight
individual
models
four
ensemble
simulate
current
habitat
distribution
forecast
under
three
scenarios
(SSP1-2.6,
SSP2-4.5,
SSP5-8.5)
2050s
2100s.
Ensemble
outperformed
ones,
with
weighted
average
algorithm
model
achieving
highest
accuracy
(AUC
0.992,
TSS
0.926).
Sea
surface
temperature
(SST)
chlorophyll-a
(Chla)
significantly
influenced
distribution.
Predictions
indicate
high
suitability
areas
are
concentrated
beyond
200-nautical-mile
baseline.
Under
scenarios,
expected
decline,
a
shift
towards
higher
latitudes
deeper
waters.
High
will
be
reduced.
Forests,
Journal Year:
2024,
Volume and Issue:
15(11), P. 1935 - 1935
Published: Nov. 3, 2024
Quercus
vulcanica
(Boiss.
et
Heldr.
ex)
Kotschy
(Kasnak
oak),
one
of
the
18
species
naturally
distributed
in
Anatolia,
is
an
endemic
with
a
restricted
distribution
range.
In
accordance
International
Union
for
Conservation
Nature
(IUCN)
Red
List
Endangered
Species
classification,
designated
as
low
risk
(LC:
Least
Concern).
However,
it
predicted
that
habitat
will
narrow
and
become
endangered
result
potential
climate
change
scenarios
future.
The
aim
this
study
was
to
estimate
temporal
spatial
Anatolia
during
LGM,
well
examine
impact
present
future
changes
on
species.
context,
principal
component
analysis
applied
19
bioclimatic
variables
Community
Climate
System
Model
Version
4
(CCSM4)
model,
nine
identified
use
modeling.
Habitat
suitability
estimated
using
Biodiversity
Modeling
(BIOMOD)
ensemble
modeling
method,
which
combines
results
different
algorithms
through
R
package
‘biomod2’,
applying
both
committee
averaging
weighted
average
approaches.
To
evaluate
performance
models,
Area
Under
Curve
(AUC)
Receiver
Operating
Characteristics
(ROC),
True
Skill
Statistics
(TSS),
KAPPA
Boyce
Index
were
calculated.
contributions
environmental
determined
per-algorithm-model
basis.
analyses
show
contribute
most
are
Bio8.
capable
occupying
suitable
areas
across
majority
Last
Glacial
Maximum
(LGM).
It
anticipated
projections
indicate
notable
reduction
extent
species,
remaining
confined
vicinity
Ilgaz
Mountains,
Köroğlu
Mountains
Bolkar
Mountains.
Given
increasing
destruction
vulcanica,
plant,
be
adversely
affected
by
human
impacts
change,
highest
importance
develop
adaptation
strategies
view
protecting
species’
sustainability
Ecology and Evolution,
Journal Year:
2024,
Volume and Issue:
14(11)
Published: Nov. 1, 2024
ABSTRACT
The
great
gerbil
(
Rhombomys
opimus
)
is
a
gregarious
rodent
in
Central
Asia
and
one
of
the
major
pests
found
desert
forest
grassland
areas.
distribution
changes
migration
routes
R.
under
climate
change
remain
unexplored.
This
study
employed
multi‐model
ensemble,
correlation
analysis,
jackknife
method,
minimum
cumulative
resistance
(MCR)
model
to
simulate
potential
habitat
current
future
(2030
2050)
scenarios
estimate
its
possible
routes.
results
indicate
that
ensemble
integrating
Random
Forest
(RF),
Gradient
Boosting
Machine
(GBM),
Maximum
Entropy
Model
(MaxEnt)
performed
best
within
present
context.
predicted
with
an
area
curve
(AUC)
0.986
True
Skill
Statistic
(TSS)
0.899,
demonstrating
excellent
statistical
accuracy
spatial
performance.
Under
scenarios,
northern
Xinjiang
southeastern
Kazakhstan
will
core
areas
distribution.
However,
optimal
region
expand
relative
one.
expansion
increase
rising
CO
2
emission
levels
over
time,
potentially
enlarging
suitable
by
up
39.49
×
10
4
km
.
In
terms
distribution,
for
shifting
toward
higher
latitudes
elevations.
For
specific
routes,
tends
favor
paths
through
farmland
grassland.
can
provide
guidance
managing
controlling
scenarios.