Modeling of Forest Fire Risk Areas of Amazonas Department, Peru: Comparative Evaluation of Three Machine Learning Methods
Forests,
Journal Year:
2025,
Volume and Issue:
16(2), P. 273 - 273
Published: Feb. 5, 2025
Forest
fires
are
the
result
of
poor
land
management
and
climate
change.
Depending
on
type
affected
eco-system,
they
can
cause
significant
biodiversity
losses.
This
study
was
conducted
in
Amazonas
department
Peru.
Binary
data
obtained
from
MODIS
satellite
occurrence
between
2010
2022
were
used
to
build
risk
models.
To
avoid
multicollinearity,
12
variables
that
trigger
selected
(Pearson
≤
0.90)
grouped
into
four
factors:
(i)
topographic,
(ii)
social,
(iii)
climatic,
(iv)
biological.
The
program
Rstudio
three
types
machine
learning
applied:
MaxENT,
Support
Vector
Machine
(SVM),
Random
(RF).
results
show
RF
model
has
highest
accuracy
(AUC
=
0.91),
followed
by
MaxENT
0.87)
SVM
0.84).
In
fire
map
elaborated
with
model,
38.8%
region
possesses
a
very
low
occurrence,
21.8%
represents
high-risk
level
zones.
research
will
allow
decision-makers
improve
forest
Amazon
prioritize
prospective
strategies
such
as
installation
water
reservoirs
areas
zone.
addition,
it
support
awareness-raising
actions
among
inhabitants
at
greatest
so
be
prepared
mitigate
control
generate
solutions
event
occurring
under
different
scenarios.
Language: Английский
Identification of the Optimal Substrate for Sexual Propagation of Cinchona officinalis L.: Implications for Conservation and Sustainable Use
Forest Science,
Journal Year:
2025,
Volume and Issue:
unknown
Published: March 19, 2025
Language: Английский
Advancements in ecological niche models for forest adaptation to climate change: a comprehensive review
Biological reviews/Biological reviews of the Cambridge Philosophical Society,
Journal Year:
2025,
Volume and Issue:
unknown
Published: April 3, 2025
ABSTRACT
Climate
change
poses
significant
challenges
to
the
health
and
functions
of
forest
ecosystems.
Ecological
niche
models
have
emerged
as
crucial
tools
for
understanding
impact
climate
on
forests
at
population,
species,
ecosystem
levels.
These
also
play
a
pivotal
role
in
developing
adaptive
conservation
management
strategies.
Recent
advancements
model
development
led
enhanced
prediction
accuracy
broadened
applications
models,
driven
using
high‐quality
data,
improved
algorithms,
application
landscape
genomic
information.
In
this
review,
we
start
by
elucidating
concept
rationale
behind
context
forestry
adaptation
change.
We
then
provide
an
overview
occurrence‐based,
trait‐based,
genomics‐based
contributing
more
comprehensive
species
responses
addition,
summarize
findings
from
338
studies
highlight
progress
made
tree
including
data
sources,
future
scenarios
used
diverse
applications.
To
assist
researchers
practitioners,
exemplar
set
accompanying
source
code
tutorial,
demonstrating
integration
population
genetics
into
models.
This
paper
aims
concise
yet
continuous
refinements
serving
valuable
resource
effectively
addressing
posed
changing
climate.
Language: Английский
Current and Future Spatial Distribution of the Aedes aegypti in Peru Based on Topoclimatic Analysis and Climate Change Scenarios
Insects,
Journal Year:
2025,
Volume and Issue:
16(5), P. 487 - 487
Published: May 2, 2025
Dengue,
a
febrile
disease
that
has
caused
epidemics
and
deaths
in
South
America,
especially
Peru,
is
vectored
by
the
Aedes
aegypti
mosquito.
Despite
seriousness
of
dengue
fever,
expanding
range
Ae.
aegypti,
future
distributions
vector
context
climate
change
have
not
yet
been
clearly
determined.
Expanding
on
previous
findings,
our
study
employed
bioclimatic
topographic
variables
to
model
both
present
distribution
mosquito
using
Maximum
Entropy
algorithm
(MaxEnt).
The
results
indicate
10.23%
(132,053.96
km2)
23.65%
(305,253.82
Peru’s
surface
area
possess
regions
with
high
moderate
probabilities,
respectively,
predominantly
located
departments
San
Martín,
Piura,
Loreto,
Lambayeque,
Cajamarca,
Amazonas,
Cusco.
Moreover,
based
projected
scenarios,
it
anticipated
areas
probability
will
undergo
expansion;
specifically,
extent
these
estimated
increase
4.47%
2.99%
years
2070
2100,
under
SSP2-4.5
HadGEM-GC31-LL
model.
Given
increasing
epidemic
Peru
recent
years,
seeks
identify
tools
for
effectively
addressing
this
pressing
public
health
concern.
Consequently,
research
serves
as
foundational
framework
assessing
highest
likelihood
response
second
half
21st
century.
Language: Английский
Potential Distribution and Identification of Critical Areas for the Preservation and Recovery of Three Species of Cinchona L. (Rubiaceae) in Northeastern Peru
Forests,
Journal Year:
2024,
Volume and Issue:
15(2), P. 321 - 321
Published: Feb. 8, 2024
The
genus
Cinchona
L.
has
important
medicinal,
cultural,
and
economic
value
is
the
emblematic
tree
of
Peru.
mainly
found
in
cloud
forests
Andes.
However,
expansion
agriculture
livestock
farming
department
Amazonas
degrading
these
ecosystems
reduced
size
genus’s
populations.
In
this
work,
we
model
potential
distribution
under
current
conditions
three
species
(C.
capuli
Anderson,
C.
macrocalyx
Pav.
Ex
DC.,
pubescens
Vahl.)
to
identify
areas
with
a
high
likelihood
presence
their
key
conservation
reforestation
zones.
We
fitted
maximum
entropy
(MaxEnt)
using
nineteen
bioclimatic
variables,
topographic
nine
edaphic
solar
radiation.
Under
conditions,
covers
17.22%
(7243.98
km2);
macrocalyx,
29.11%
(12,238.91
pubescens,
22.94%
(9647.63
km2)
study
area,
which
was
mostly
located
central
southern
Amazonas.
Only
24.29%
(25.51%
capuli,
21.02%
26.35%
pubescens)
distributions
are
within
protected
areas,
while
10,987.22
km2
surface
area
degraded,
29.80%
probable
occurrence
38.72%
34.82%
pubescens.
Consequently,
it
necessary
promote
additional
strategies
for
Cinchona,
including
establishment
new
recovery
degraded
habitats,
order
protect
species.
Language: Английский