Authorea (Authorea),
Год журнала:
2023,
Номер
unknown
Опубликована: Окт. 19, 2023
Climate
change
affects
biodiversity
in
diverse
ways,
necessitating
the
exploration
of
multiple
climate
dimensions
using
standardized
metrics.
However,
existing
methods
for
quantifying
these
metrics
are
scattered
and
tools
comparing
alternative
on
same
footing
lacking.
To
address
this
gap,
we
developed
“climetrics”
which
is
an
extensible
reproducible
R
package
to
spatially
quantify
explore
through
a
unified
procedure.
Six
widely
used
currently
implemented,
including
1)
Standardized
Local
Anomalies;
2)
Changes
Probabilities
Extremes;
3)
Areas
Analogous
Climates;
4)
Novel
5)
Distances
6)
Change
Velocity.
For
velocity,
three
different
algorithms
implemented
available
within
including;
a)
Distanced-based
Velocity
(“dVe”);
b)
Threshold-based
(“ve”);
c)
Gradient-based
(“gVe”).
The
also
provides
additional
calculate
monthly
mean
variables
over
years,
map
temporal
trend
(slope)
given
variable
at
pixel
level,
classify
Köppen-Geiger
(KG)
zones.
climetrics
seamlessly
integrated
with
rts
efficient
handling
raster
time-series
data.
functions
designed
be
user-friendly,
making
them
suitable
less-experienced
users.
Detailed
comments
descriptions
their
help
pages
vignettes
facilitate
further
customization
by
advanced
In
summary,
offers
framework
various
metrics,
it
useful
tool
characterizing
exploring
spatiotemporal
patterns.
Anthropogenic
biodiversity
decline
threatens
the
functioning
of
ecosystems
and
many
benefits
they
provide
to
humanity1.
As
well
as
causing
species
losses
in
directly
affected
locations,
human
influence
might
also
reduce
relatively
unmodified
vegetation
if
far-reaching
anthropogenic
effects
trigger
local
extinctions
hinder
recolonization.
Here
we
show
that
plant
diversity
is
globally
negatively
related
level
activity
surrounding
region.
Impoverishment
natural
was
evident
only
when
considered
community
completeness:
proportion
all
suitable
region
are
present
at
a
site.
To
estimate
completeness,
compared
number
recorded
with
dark
diversity-ecologically
absent
from
site
but
region2.
In
sampled
regions
minimal
footprint
index,
an
average
35%
were
locally,
less
than
20%
highly
regions.
Besides
having
potential
uncover
overlooked
threats
biodiversity,
provides
guidance
for
nature
conservation.
Species
remain
regionally
present,
their
populations
be
restored
through
measures
improve
connectivity
between
fragments
population
persistence.
Abstract
Increases
in
the
frequency,
intensity,
and
duration
of
extreme
climate
events
(ECEs)
are
already
impacting
ecosystems,
with
many
strongest
effects
associated
high‐elevation
areas.
Most
research
on
ecological
impacts
change
has
focused
climatic
averages,
which
might
differ
from
ECEs.
Rhododendron
,
a
diverse
genus
alpine
subalpine
woody
plant,
plays
crucial
role
ecosystem
stability
biodiversity
hotspots
Himalayas
Hengduan
Mountains.
Here,
we
compared
predicted
average
those
including
ECEs
189
species
China
for
historical
period
(1981–2010)
future
(2071–2100)
under
two
emissions
scenarios
(SSP2‐4.5
SSP5‐8.5).
We
analyzed
changes
suitable
habitat
patterns
richness,
weighted
endemism,
phylogenetic
diversity,
identifying
areas
coinciding
high‐risk
as
priority
conservation
Inclusion
altered
projected
across
all
an
increase
over
3%
to
decrease
exceeding
10%,
distribution
most
strongly
influenced
by
extremes
drought
high
temperatures.
found
fewer
than
18%
diversity
loss
were
currently
protected,
mainly
located
Daxue,
Daliang,
Wumeng,
Jade
Dragon
Snow
Mountains,
well
Nyingchi.
suggest
inclusion
is
critical
when
projecting
distributions
effective
planning
change.
Land,
Год журнала:
2025,
Номер
14(2), С. 310 - 310
Опубликована: Фев. 2, 2025
In
the
Atlantic
region
of
northern
Spain,
heat
extremes
were
historically
rare,
but
in
recent
decades,
they
have
become
more
intense
and
persistent.
This
article
characterizes
events
Asturias
(NW
Spain)
between
2001
2023,
focusing
on
their
frequency,
intensity,
duration,
as
well
temporal
trends.
Additionally,
it
explores
synoptic
patterns
linked
to
these
episodes
enhance
understanding
occurrence
evolution
over
study
period.
The
research
is
based
official
meteorological
records,
distinguishes
officially
declared
heatwaves
(DHs)
significant
(SHEs)
identified
through
regional
press
reports.
methodology
enables
capture
a
broader
spectrum
heat-related
impacts.
During
period,
17
documented
(11
DHs
6
SHEs).
duration
significantly
increased,
particularly
since
2016,
standing
last
two
years
(2022
2023).
Both
SHEs
progressively
shifted
toward
early
late
periods
astronomical
summer,
with
some
occurring
during
spring
autumn
second
half
period
(years
2017,
2022,
Three
atmospheric
been
responsible
for
extreme
episodes;
Type
1
(warm
tropical
continental
air
masses,
combined
stability)
10
episodes.
Furthermore,
urban
areas
main
river
valleys
most
affected
areas,
while
coastal
regions
remained
largely
unaffected.
aims
contribute
how
are
evolving
temperate
climate
area
under
influence
global
warming,
providing
insights
inform
improve
adaptation
strategies
mitigating
Communications Earth & Environment,
Год журнала:
2024,
Номер
5(1)
Опубликована: Окт. 10, 2024
Forest
regeneration
is
a
crucial
strategy
for
mitigating
and
adapting
to
global
warming.
Yet
its
precise
impact
on
local
climate
remains
uncertain,
factor
that
complicates
decision-making
when
it
comes
prioritizing
investments.
Here,
we
developed
maps
illustrating
how
natural
forest
influences
key
drivers—land
surface
temperature
(LST),
albedo,
evapotranspiration—using
models
fitted
at
1-km
spatial
resolution
with
random
classifier.
We
found
can
alter
annual
mean
LST
by
0.01
°C,
−0.59
−0.50
−2.03
°C
in
Boreal,
Mediterranean,
Temperate,
Tropical
regions,
respectively.
These
variations
underscore
the
region-specific
effects
of
regeneration.
Importantly,
reduces
across
64%
1
billion
hectares
75%
148
million
potentially
restorable
land
under
different
scenarios.
findings
improve
understanding
help
regulate
climate,
supporting
adaptation
efforts.
Natural
enhance
reducing
temperature.
regenerations
reduce
areas
regions
according
an
analysis
combines
data,
machine
learning,
scenario
analysis.
Marine
heatwaves
(MHWs)
can
cause
thermal
stress
in
marine
ectotherms,
experienced
as
a
pulse
against
the
press
of
anthropogenic
warming.
When
exceeds
organismal
capacity
to
maintain
homeostasis,
organism
survival
becomes
time-limited
and
result
mass
mortality
events.
Current
methods
detecting
categorizing
MHWs
rely
on
statistical
analysis
historic
climatology,
do
not
consider
biological
effects
basis
MHW
severity.
The
reemergence
tolerance
landscape
models
provides
physiological
framework
for
assessing
lethal
by
accounting
both
magnitude
duration
extreme
heat
Here,
we
used
simulation
approach
understand
suite
profiles
probability
across
1)
adaptation
strategies,
2)
interannual
temperature
variation,
3)
seasonal
timing
MHWs.
We
identified
isoclines
broadly
connecting
acute
(low
duration-high
magnitude)
chronic
(long
duration-low
events
with
equivalent
organisms.
While
most
attention
has
been
given
events,
show
similar
be
more
common
but
neglected
spikes.
Critically,
fixed-baseline
definition
does
accurately
categorize
mortality.
By
letting
responses
define
extremeness
event,
build
mechanistic
understanding
from
basis.
then
transferred
scales
ecological
organization
better
predict
ecosystem
shifts
Conservation Biology,
Год журнала:
2024,
Номер
38(4)
Опубликована: Март 10, 2024
Abstract
Central
America
and
the
Caribbean
are
regularly
battered
by
megadroughts,
heavy
rainfall,
heat
waves,
tropical
cyclones.
Although
21st‐century
climate
change
is
expected
to
increase
frequency,
intensity,
duration
of
these
extreme
weather
events
(EWEs),
their
incidence
in
regional
protected
areas
(PAs)
remains
poorly
explored.
We
examined
historical
projected
EWEs
across
region
based
on
32
metrics
that
describe
distinct
dimensions
(i.e.,
duration,
frequency)
cyclones,
droughts,
rainfall
compared
trends
PAs
with
unprotected
lands.
From
early
21st
century
onward,
exposure
increased
region,
were
predicted
be
more
exposed
extremes
than
(as
shown
autoregressive
model
coefficients
at
p
<
0.05
significance
level).
This
was
particularly
true
for
which
have
a
significantly
higher
average
(tested
Wilcoxon
tests
0.01)
intensity
affected
severely
carbon‐intensive
scenarios.
also
less
droughts
0.01).
However,
could
threaten
connectivity
between
increasingly
common
this
region.
estimated
approximately
65%
study
area
will
experience
least
one
drought
episode
intense
longer
lasting
previous
droughts.
Collectively,
our
results
highlight
new
conservation
strategies
adapted
threats
associated
need
tailored
implemented
promptly.
Unless
urgent
action
taken,
significant
damage
may
inflicted
unique
biodiversity
Journal of Biogeography,
Год журнала:
2024,
Номер
51(12), С. 2546 - 2555
Опубликована: Сен. 13, 2024
ABSTRACT
Aim
Climate
change
poses
a
challenge
to
the
Azores'
biodiversity,
with
consequences
that
remain
unexplored.
To
shed
light
on
potential
impacts
of
climate
change,
we
have
developed
large
ensemble
species
distribution
models
(SDMs)
for
found
in
coastal
marine
environments
and
examined
their
spatiotemporal
turnover
stability.
Location
The
Azorean
archipelago.
Taxon
Coastal
(mammals,
fish,
turtles,
seabirds,
kelp
forest
corals).
Methods
SDMs
were
fitted
comprising
10
machine
learning
algorithms
fivefold
cross‐validation
resampling
procedure,
thus
yielding
maximum
number
50
per
species.
These
then
utilised
projecting
under
different
future
scenarios.
projected
distributions
employed
assess
changes
stability
ranges
throughout
entire
modelled
period
(2030–2100)
community
compositions
by
examining
alpha
diversity
beta
over
10‐year
periods.
Results
We
show
our
model
assumptions
12%
units
could
lose
suitable
end
century,
this
increasing
up
25%
high
carbon
emissions
scenario.
refugia,
which
are
areas
long‐term
range
stability,
expected
be
mainly
located
northernmost
part
A
substantial
loss
is
anticipated
mammals
birds,
likely
trigger
major
islands
Santa
Maria,
São
Miguel,
Pico
Faial.
For
climates
less
pronounced.
However,
cause
reshuffling
pelagic
fish
assemblage,
important
local
fisheries
each
island.
Main
Conclusions
Our
provide
insights
into
how
may
alter
species,
offering
guidance
conservation
management
efforts
these
North
Atlantic
ecosystems.
Climate
change
affects
biodiversity
in
a
variety
of
ways,
necessitating
the
exploration
multiple
climate
dimensions
using
appropriate
metrics.
Despite
existence
several
metrics
tools
for
comparing
alternative
on
same
footing
are
lacking.
To
address
this
gap,
we
developed
‘climetrics'
which
is
an
extensible
and
reproducible
R
package
to
spatially
quantify
explore
through
unified
procedure.
Six
widely
used
implemented,
including
1)
standardized
local
anomalies;
2)
changes
probabilities
extremes;
3)
areas
analogous
climates;
4)
novel
5)
distances
6)
velocity.
For
velocity,
three
different
algorithms
implemented
including;
distanced‐based
velocity
(‘
dVe
');
threshold‐based
ve
gradient‐based
gVe
').
The
also
provides
additional
calculate
monthly
mean
variables
over
years,
map
temporal
trend
(slope)
given
variable
at
pixel
level,
classify
Köppen‐Geiger
(KG)
zones.
'climetrics'
integrated
with
'rts'
efficient
handling
raster
time‐series
data.
functions
designed
be
user‐friendly,
making
them
suitable
less‐experienced
users.
Detailed
descriptions
help
pages
vignettes
facilitate
further
customization
by
advanced
In
summary,
offers
framework
quantifying
various
metrics,
it
useful
tool
characterizing
exploring
their
spatiotemporal
patterns.