Frontiers in Environmental Science,
Год журнала:
2022,
Номер
10
Опубликована: Авг. 31, 2022
Wildfires
burn
heterogeneously
across
the
landscape
and
create
complex
forest
structures.
Quantifying
structural
changes
in
post-fire
forests
is
critical
to
evaluating
wildfire
impacts
providing
insights
into
severities.
To
advance
understanding
of
severities
at
a
fine
scale,
attributes
individual
tree
level
need
be
examined.
The
advent
drone
laser
scanning
(DLS)
mobile
(MLS)
has
enabled
acquisition
high-density
point
clouds
resolve
structures
trees.
Yet,
few
studies
have
used
DLS
MLS
data
jointly
examine
their
combined
capability
describe
assess
2017
Elephant
Hill
British
Columbia,
Canada,
we
scanned
trees
that
experienced
range
2
years
using
both
MLS.
After
fusing
data,
reconstructed
quantitative
structure
models
compute
14
biometric,
volumetric,
crown
attributes.
At
level,
our
suggest
smaller
pre-fire
tend
experience
higher
levels
scorch
than
larger
Among
with
similar
sizes,
those
within
mature
stands
(age
class:
>
50
years)
had
lower
young
15—50
years).
small-
medium-diameter
trees,
experiencing
high
crowns
unevenly
distributed
branches
compared
unburned
In
contrast,
large-diameter
were
more
resistant
scorch.
plot
low-severity
fires
minor
effects,
moderate-severity
mostly
decreased
height,
high-severity
significantly
reduced
diameter
breast
biomass.
Our
exploratory
factor
analyses
further
revealed
dominated
by
large
sizes
relatively
wide
spacing
could
less
severely
characterized
regenerating
fuel
density
continuity.
Overall,
results
demonstrate
fused
DLS-MLS
can
effective
quantifying
structures,
which
facilitates
foresters
develop
site-specific
management
plans.
findings
imply
abundance
configuration
vital
controlling
New Phytologist,
Год журнала:
2024,
Номер
242(1), С. 93 - 106
Опубликована: Фев. 20, 2024
Summary
Serotiny
is
an
adaptive
trait
that
allows
certain
woody
plants
to
persist
in
stand‐replacing
fire
regimes.
However,
the
mechanisms
by
which
serotinous
cones
avoid
seed
necrosis
and
nonserotinous
species
landscapes
with
short
cycles
competitors
remain
poorly
understood.
To
investigate
whether
ovulate
cone
traits
enhance
survival
differ
between
species,
we
examined
24
within
Pinaceae
Cupressaceae
based
on
physical
measurements
heating
simulations
using
a
computational
fluid
dynamics
model.
Fire‐relevant
were
largely
similar
types;
those
differed
(e.g.
density
moisture)
conferred
little
advantage
under
simulated
fire.
The
most
important
influencing
size
depth
cone,
was
found
be
allometric
function
of
mass
for
both
types.
Thus,
should
not
suffer
significantly
greater
than
equal
size.
Closed
containing
mature
seeds
may
achieve
substantial
regeneration
after
if
they
are
sufficiently
large
relative
duration
temperature.
our
knowledge,
this
comprehensive
study
effects
fire‐relevant
conifer
supported
physics‐based
simulation.
Accurately
predicting
the
mortality
of
trees
that
initially
survive
a
fire
event
is
important
for
management,
such
as
planning
post-fire
salvage,
planting,
and
prescribed
fires.
Although
crown
scorch
has
been
successfully
used
to
predict
(greater
than
one-year
post-fire),
it
remains
unclear
whether
other
first-order
effect
metrics
(e.g.,
stem
char)
information
on
growing
conditions
can
improve
predictions.
Droughts
also
elevate
may
interact,
synergistically,
with
effects
influence
tree
survival.
We
logistic
regression
test
drought
exposure,
indicated
by
summarized
monthly
Palmer
Drought
Severity
Index
(PDSI)
over
ten-years
could
predictions
delayed
(4–9
years
post-fire)
at
individual
level
in
fire-affected
forest
inventory
analysis
(FIA)
plots
California
(USA).
included
scorch,
bark
thickness,
char,
soil
slope,
aspect
model
predictors.
selected
six
most
prevalent
species
include
model:
canyon
live
oak,
Douglas-fir,
Jeffrey
pine,
incense-cedar,
ponderosa
white
fir.
Mean
mortality,
based
count,
across
all
FIA
was
17%,
overall
accuracy
good
(AUC
=
79%).
Our
performed
well,
correctly
survivor
(sensitivity
0.98)
but
had
difficulty
smaller
number
(specificity
0.27)
standard
probability=0.5
threshold.
Crown
influential
predictor
mortality.
Increasing
associated
greater
risk
species,
exhibiting
75%
having
probability
dying
exceeded
0.5.
levels
char
(first
order
indicators)
were
increasing
less
scorch.
expected
exposure
would
increase
we
found
(median
minimum
PDSI)
modest
decrease
However,
did
find
high
likely
PDSI).
Delayed
decreased
terrain
slope
increased.
Taken
together,
our
results
suggest
substantial
damage
be
more
vulnerable
if
exposed
an
effective
up
10
post-fire.
Methods in Ecology and Evolution,
Год журнала:
2025,
Номер
unknown
Опубликована: Фев. 3, 2025
Abstract
With
rapid
environmental
change
occurring
globally
there
is
an
urgent
need
for
new
field
survey
methods
that
enable
fast
and
efficient
collection
of
ecological
information
from
impacted
systems.
Advances
in
360‐degree
(panospheric)
camera
technology
now
allow
the
geospatially
explicit
visual
records
properties
far
more
cheaply,
quickly
efficiently
than
traditional
methods.
However,
generalisable
workflows
software
platforms
to
manage,
extract,
process
use
large
panospheric
image
datasets
are
still
lacking.
Here
we
develop
a
flexible,
integrative
workflow
acquisition,
preparation
extraction
macroscopic
data
imagery.
We
introduce
open‐source
R
package
Panospheric
Image
Annotator
(pannotator),
which
allows
user
visualise
annotate
images
extract
cropped
geocoded
sub‐images
repeatable,
systematic
way
using
customisable
drop‐down
menus
help
files.
demonstrate
pannotator
panoramic
collected
study
area
at
Uluṟu‐Kata
Tjuṯa
National
Park
central
Australia,
was
affected
by
severe
drought
fire
2018–2020.
In
this
study,
180
were
captured
GoPro
Max
cameras
imported
into
annotation.
extracted
three
key
attributes
(plant
species
distribution,
understorey
cover
tree
health)
show
how
these
can
be
used
spatially
reconstruct
richness
community
structure,
plant
size
class,
mortality
burn
history.
Modern
immersive
sampling
offer
transformative
solution
capturing
extracting
biogeographical
surveys.
More
generally,
may
any
georeferenced
imagery
generate
with
embedded
geolocation
downstream
artificial
intelligence/machine
learning–based
applications.
Sustainability,
Год журнала:
2025,
Номер
17(6), С. 2680 - 2680
Опубликована: Март 18, 2025
The
confluence
of
global
warming,
the
urban
heat
island
effect,
and
alterations
in
nature
underlying
surfaces
has
led
to
a
continuous
escalation
frequency,
scale,
intensity
fires
within
green
spaces.
Mitigating
or
eliminating
adverse
effects
such
on
service
functions
ecosystems,
while
enhancing
resilience
greening
systems
disaster
prevention
risk
reduction,
become
pivotal
challenge
modern
development
management.
Academic
focus
progressively
broadened
from
isolated
forest
domains
encompass
more
intricate
environments
Wildland–Urban
Interface
(WUI)
urban–suburban
forests,
with
particular
emphasis
distinctive
characteristics
in-depth
research.
This
study
employs
combination
CiteSpace
bibliometric
analysis
narrative
literature
review
comprehensively
examine
three
critical
aspects
fire
safety
as
follows:
(1)
evaluation
fire-resistant
performance
landscape
plants
spaces;
(2)
mechanisms
behavior
systems;
(3)
assessment
prediction
risks.
Our
findings
indicate
that
play
crucial
role
controlling
spread
spaces
by
providing
physical
barriers
inhibiting
combustion
processes,
thereby
mitigating
propagation.
However,
diversity
non-native
greenery
species
present
challenges.
existing
research
lacks
standardized
experimental
indicators
often
focuses
single-dimensional
analyses,
leading
conclusions
are
limited,
inconsistent,
even
contradictory.
Furthermore,
most
current
models
designed
primarily
for
forests
wildland–urban
interface
regions.
Empirical
semi-empirical
dominate
this
field,
yet
future
advancements
will
likely
involve
coupled
integrate
climate
environmental
factors.
Fire
represent
hotspot,
machine
learning-
deep
learning-based
approaches
increasingly
gaining
prominence.
These
advanced
methods
have
demonstrated
superior
accuracy
compared
traditional
techniques
predicting
synthesis
aims
elucidate
state,
trends,
deficiencies
Future
should
explore
screening
highly
resistant
plants,
goal
bolstering
ecological
theoretical
underpinnings
realization
sustainable
security.
Summary
The
mechanistic
links
between
fire‐caused
injuries
and
post‐fire
tree
mortality
are
poorly
understood.
Current
hypotheses
differentiate
effects
of
fire
on
carbon
balance
hydraulic
function,
yet
critical
uncertainties
remain
about
the
relative
importance
each
how
they
interact.
We
utilize
two
prescribed
burns
with
Douglas‐fir
ponderosa
pine
to
examine:
evidence
for
changes
in
function
dynamics,
such
impacts
relate
injuries;
which
most
likely
lead
mortality;
these
vary
by
species
burn
timing
(fall
vs
spring).
find
that
non‐structural
carbohydrates
(NSC)
immediate,
persistent,
correlated
crown
injury
severity,
strongly
related
mortality.
By
contrast,
delayed
not
directly
attributable
injuries,
although
some
burned
trees
do
exhibit
signs
increased
dysfunction
water
stress
before
death.
This
suggests
may
indirectly
affect
relations,
possibly
through
an
interaction
direct
NSC.
These
findings
offer
a
more
nuanced
understanding
fire's
effect
important
context
activity
forests
globally.
New Phytologist,
Год журнала:
2022,
Номер
234(5), С. 1654 - 1663
Опубликована: Фев. 19, 2022
The
plume
of
hot
gases
rising
above
a
wildfire
can
heat
and
kill
the
buds
in
tree
crowns.
This
reduce
leaf
area
rates
photosynthesis,
growth,
reproduction,
may
ultimately
lead
to
mortality.
These
effects
vary
seasonally,
but
mechanisms
governing
this
seasonality
are
not
well
understood.
A
trait-based
physical
model
combining
buoyant
energy
budget
theories
shows
bud
necrosis
height
originate
from
temporal
variation
climate,
fire
behaviour,
and/or
functional
traits.
To
assess
relative
importance
these
drivers,
we
parameterized
with
time-series
data
for
air
temperature,
fireline
intensity,
traits
Pinus
contorta,
Picea
glauca,
Populus
tremuloides.
Air
all
varied
significantly
through
time,
causing
significant
seasonal
predicted
height.
Bud
intensity
explained
almost
height,
temperature
explaining
relatively
minor
amounts
variation.
on
crowns
appears
behaviour.
Our
approach
results
provide
needed
insight
into
linking
environmental
plant
performance
via