Environmental Monitoring and Assessment,
Journal Year:
2024,
Volume and Issue:
197(1)
Published: Dec. 21, 2024
Abstract
This
study
aims
to
evaluate
the
changes
in
forest
cover
from
1994
2015,
identify
key
drivers
of
recovery,
and
predict
future
trends.
Using
high-resolution
remote
sensing
data,
we
mapped
canopy
density
into
detailed
categories
(closed
>
50%,
open
10–50%,
deforested
<
10%)
differentiate
processes
like
degradation,
deforestation,
densification,
reforestation,
afforestation.
A
multinomial
logistic
regression
was
used
explore
relationship
between
socioeconomic,
proximity,
planning,
policy
potential
drivers.
Future
trends
were
modeled
using
Land
Change
Modeler.
The
analysis
showed
that
81.5%
area
remained
unchanged,
14%
experienced
4.5%
faced
disturbances.
Factors
such
as
elevation,
proximity
roads,
participation
payment
for
environmental
services
(PES)
programs
significantly
influenced
recovery
Predictive
modeling
2035
suggests
will
increase
by
7%,
reaching
77%
coverage
area,
closed
areas
rise
12%
compared
1994.
findings
underscore
effectiveness
conservation
efforts
natural
regeneration
enhancing
cover,
offering
valuable
insights
global
management
policy-making
efforts.
Scientific Reports,
Journal Year:
2025,
Volume and Issue:
15(1)
Published: Feb. 10, 2025
Climate
change
and
human
activities
are
placing
significant
pressure
on
the
carrying
capacity
of
Himalayan
alpine
ecosystem.
This
study
focuses
seven
transboundary
protected
areas
national
parks
in
Himalayas,
including
China's
Everest
National
Nature
Reserve
Nepal's
Sagarmatha
Park,
Manaslu
Conservation
Area,
Langtang
Gauri
Sankar
Makalu
Barun
Kanchenjunga
Area.
We
used
Vulnerability
Scoping
Diagram
(VSD)
model
to
assess
ecological
vulnerability,
analyzing
land
use
changes
landscape
patterns
from
2000
2020
identify
key
drivers
changes.
The
fragmentation
landscapes
initially
increased
then
decreased,
with
values
4.05,
3.99,
3.86
observed,
indicating
a
general
reduction
regional
vulnerability.
south
slope
demonstrated
lower
vulnerability
than
north
slope.
Key
factors
influencing
patch
density
included
annual
average
temperature,
population
density,
precipitation.
Annual
precipitation,
normalized
vegetation
index
were
primary
largest
index.
shape
was
most
affected
by
index,
slope,
while
spread
primarily
influenced
precipitation
homogeneity
strongly
related
water
provides
representative
case
for
cooperation
conservation,
offering
insights
into
sustainable
development
strategies
cross-border
regions
Himalayas.
Environmental Challenges,
Journal Year:
2024,
Volume and Issue:
16, P. 100964 - 100964
Published: June 14, 2024
This
study
performs
a
comparative
analysis
of
tree
composition,
biomass,
and
carbon
stock
across
different
management
regimes
namely,
Van
Panchayat
forest
(VP),
Reserve
(RF),
Civil
&
Soyam
(C&SF)
in
the
state
Uttarakhand,
with
focus
on
P.
roxburghii
(Chir-pine)
forests.
Collectively,
these
cover
approximately
60
%
area
state.
In
this
assessment,
total
five
species
(Pinus
roxburghii,
Quercus
leucotrichophora,
Myrica
esculenta,
Acacia
catechu,
Pinus
wallichiana)
were
identified
regimes.
The
emerged
as
dominant
all
regimes,
relative
density
92.79,
94.39,
92.31
forest,
respectively.
However,
co-dominant
are
varying
sites.
biomass
notably
higher
(236.31
112.25
t
ha−1)
compared
to
(224.85
106.80
(193.58
91.95
ha−1).
These
findings
suggest
that
forests
exhibit
superior
status
terms
density,
emerges
crucial
species,
underscoring
its
ecological
significance
region.
underscore
critical
role
effective
practices
fostering
sustainable
accumulation
sequestration
Himalayan
Chir-pine
Thus,
it
helps
mitigate
impacts
climate
change
biodiversity
conservation,
Environmental Monitoring and Assessment,
Journal Year:
2024,
Volume and Issue:
197(1)
Published: Dec. 21, 2024
Abstract
This
study
aims
to
evaluate
the
changes
in
forest
cover
from
1994
2015,
identify
key
drivers
of
recovery,
and
predict
future
trends.
Using
high-resolution
remote
sensing
data,
we
mapped
canopy
density
into
detailed
categories
(closed
>
50%,
open
10–50%,
deforested
<
10%)
differentiate
processes
like
degradation,
deforestation,
densification,
reforestation,
afforestation.
A
multinomial
logistic
regression
was
used
explore
relationship
between
socioeconomic,
proximity,
planning,
policy
potential
drivers.
Future
trends
were
modeled
using
Land
Change
Modeler.
The
analysis
showed
that
81.5%
area
remained
unchanged,
14%
experienced
4.5%
faced
disturbances.
Factors
such
as
elevation,
proximity
roads,
participation
payment
for
environmental
services
(PES)
programs
significantly
influenced
recovery
Predictive
modeling
2035
suggests
will
increase
by
7%,
reaching
77%
coverage
area,
closed
areas
rise
12%
compared
1994.
findings
underscore
effectiveness
conservation
efforts
natural
regeneration
enhancing
cover,
offering
valuable
insights
global
management
policy-making
efforts.
