Cambridge Prisms Extinction,
Год журнала:
2024,
Номер
2
Опубликована: Янв. 1, 2024
Abstract
Biodiversity
is
in
rapid
decline,
but
the
extent
of
loss
not
well
resolved
for
poorly
known
groups.
We
estimate
number
extinctions
Australian
non-marine
invertebrates
since
European
colonisation
continent.
Our
analyses
use
a
range
approaches,
incorporate
stated
uncertainties
and
recognise
explicit
caveats.
plausible
bounds
species,
two
approaches
estimating
extinction
rate,
Monte
Carlo
simulations
to
select
combinations
projected
distributions
from
these
variables.
conclude
that
9,111
(plausible
1,465
56,828)
species
have
become
extinct
over
this
236-year
period.
These
estimates
dwarf
formally
recognised
(10
species)
single
invertebrate
listed
as
under
legislation.
predict
39–148
will
2024.
This
inconsistent
with
recent
pledge
by
government
prevent
all
extinctions.
high
rate
largely
consequence
pervasive
taxonomic
biases
community
concern
conservation
investment.
Those
characteristics
also
make
it
challenging
reduce
loss,
there
uncertainty
about
which
are
at
most
risk.
outline
responses
likelihood
further
Remote Sensing,
Год журнала:
2025,
Номер
17(10), С. 1685 - 1685
Опубликована: Май 10, 2025
The
complex
interaction
between
nature
and
human
factors
has
led
to
frequent
forest
fires,
but
their
combined
effects
in
different
areas
remain
unclear.
Taking
the
Northeast
China
as
study
area,
this
integrates
structural
equation
modeling
(SEM)
Vine
Copula
analysis
quantify
these
drivers
over
2001–2022.
Results
show
that
70.42%
of
fires
were
caused
by
humans,
clustering
populated
low-elevation
areas.
SEM
revealed
partial
correlations
0.48
(weather
conditions)
0.59
(human
activities)
with
fire
frequency;
canopy
moisture
was
negatively
correlated
(−0.38).
indicated
a
joint
probability
0.32
footprint
index
(HFI)
under
high
temperatures.
This
can
provide
framework
for
region-specific
management
temperate
forests
combining
various
influences.
Evolutionary Applications,
Год журнала:
2025,
Номер
18(5)
Опубликована: Май 1, 2025
ABSTRACT
Genetic
rescue
is
a
conservation
management
strategy
that
reduces
the
negative
effects
of
genetic
drift
and
inbreeding
in
small
isolated
populations.
However,
such
populations
might
already
be
vulnerable
to
random
fluctuations
growth
rates
(demographic
stochasticity).
Therefore,
success
depends
not
only
on
composition
source
target
but
also
emergent
outcome
interacting
demographic
processes
other
stochastic
events.
Developing
predictive
models
account
for
feedback
between
(‘demo‐genetic
feedback’)
therefore
necessary
guide
implementation
minimize
risk
extinction
threatened
Here,
we
explain
how
mutual
reinforcement
drift,
inbreeding,
stochasticity
increases
We
then
describe
these
can
modelled
by
parameterizing
underlying
mechanisms,
including
deleterious
mutations
with
partial
dominance
variances
increase
as
abundance
declines.
combine
our
suggestions
model
parameterization
comparison
relevant
capability
flexibility
five
open‐source
programs
designed
building
genetically
explicit,
individual‐based
simulations.
Using
one
programs,
provide
heuristic
demonstrate
simulated
delay
virtual
would
otherwise
exposed
greater
due
demo‐genetic
feedback.
use
case
study
Australian
marsupials
published
data
used
or
all
stages
development
application,
parameterization,
calibration,
validation.
highlight
either
empirical
sequence
variation
(or
hybrid
approach)
suggest
model‐based
decision‐making
should
informed
ranking
sensitivity
predicted
probability/time
parameters
(e.g.,
translocation
size,
frequency,
populations)
among
different
genetic‐rescue
scenarios.
Global Change Biology,
Год журнала:
2024,
Номер
30(7)
Опубликована: Июль 1, 2024
Abstract
Climate
change
is
the
most
significant
threat
to
natural
World
Heritage
(WH)
sites,
especially
in
oceans.
Warming
has
devastated
marine
faunas,
including
reef
corals,
kelp,
and
seagrass.
Here,
we
project
future
declines
species
ecosystem
functions
across
Australia's
four
WH
coral
regions.
Model
simulations
estimating
species‐level
abundances
probabilities
of
ecological
persistence
were
combined
with
trait
space
reconstructions
at
“present,”
2050
(+1.5°C
warming),
2100
(+2°C)
explore
biogeographical
overlaps
identify
key
functional
differences
forecast
changes
function
through
time.
Future
climates
varied
by
region,
Shark
Bay
projected
warm
(>1.29°C),
followed
Lord
Howe,
when
standardized
park
size.
By
2050,
~40%
Great
Barrier
Reef
will
exceed
critical
thresholds
set
warmest
summer
month
(mean
monthly
maximum
[MMM]),
triggering
mortality.
Functional
diversity
was
greatest
Ningaloo.
At
+1.5°C
warming,
regions
drastically
their
responses,
declined
20.2%
richness
(~70
extinctions)
lost
all
reefs.
+2°C,
models
predicted
a
complete
collapse
functions,
consistent
IPCC
forecasts.
This
variability
suggests
bespoke
management
approach
needed
for
each
region
understanding
vulnerability
climate
change,
identifying
thresholds,
quantifying
uncertainty
impacts.
knowledge
aid
focusing
management,
policy
conservation
actions
direct
resources,
rapid
action,
biodiversity
targets
these
reefs
global
priority.
As
reassemble
into
novel
or
different
configurations,
determining
winners
losers
be
meeting
landmark
goals.
Cambridge Prisms Extinction,
Год журнала:
2024,
Номер
2
Опубликована: Янв. 1, 2024
Abstract
Biodiversity
is
in
rapid
decline,
but
the
extent
of
loss
not
well
resolved
for
poorly
known
groups.
We
estimate
number
extinctions
Australian
non-marine
invertebrates
since
European
colonisation
continent.
Our
analyses
use
a
range
approaches,
incorporate
stated
uncertainties
and
recognise
explicit
caveats.
plausible
bounds
species,
two
approaches
estimating
extinction
rate,
Monte
Carlo
simulations
to
select
combinations
projected
distributions
from
these
variables.
conclude
that
9,111
(plausible
1,465
56,828)
species
have
become
extinct
over
this
236-year
period.
These
estimates
dwarf
formally
recognised
(10
species)
single
invertebrate
listed
as
under
legislation.
predict
39–148
will
2024.
This
inconsistent
with
recent
pledge
by
government
prevent
all
extinctions.
high
rate
largely
consequence
pervasive
taxonomic
biases
community
concern
conservation
investment.
Those
characteristics
also
make
it
challenging
reduce
loss,
there
uncertainty
about
which
are
at
most
risk.
outline
responses
likelihood
further