Scientific Reports,
Год журнала:
2024,
Номер
14(1)
Опубликована: Дек. 28, 2024
Abstract
Orchard
meadows,
a
specific
agroforestry
system
characterised
by
scattered
high-stem
fruit
trees,
are
traditional
element
of
several
cultural
landscapes
in
Central
Europe
and
provide
important
ecosystem
services.
Since
the
middle
20th
century,
orchard
meadows
have
drastically
declined
across
Europe.
Spatial
information
on
drivers
patterns
such
decline
regions
is
lacking.
In
this
study,
we
aimed
to
first
detailed
insights
into
development
South
Tyrol.
We
assessed
current
distribution
Tyrol
(Northern
Italy)
analysed
their
over
last
75
years.
Aerial
images
from
1950s
up
2020s
were
examined,
changes
statistically
analysed.
The
results
revealed
that
historical
meadow
area
has
decreased
more
than
6,000
ha
(−95%)
past
years,
showing
one
largest
reductions
loss
was
highest
at
lower
elevations
(–5,155
ha),
shallow
slopes
(–4,313
expositions
towards
south
(–5,035
ha).
due
agricultural
intensification
establishment
modern
orchards
(56%)
intensively
managed
grasslands
(8%),
urbanisation
(23%),
reforestation
(6%),
other
types
land
use/land
cover
(6.5%).
Only
0.5%
been
preserved.
suggest
high
risk
disappearing
Tyrolean
landscape,
resulting
genetic
diversity
many
local
or
indigenous
varieties
(especially
apples
pears).
Immediate
action
needed
safeguard
population
appropriate
management
measures
highlight
multiple
values
valuable
alternative
intensive
arable
farming.
Journal of Environmental Management,
Год журнала:
2025,
Номер
377, С. 124600 - 124600
Опубликована: Фев. 22, 2025
Forest
fires
are
increasing
in
frequency
and
intensity
worldwide
due
to
the
anthropogenic
climate
change,
threatening
people's
lives
causing
huge
economic
environmental
damages.
Recent
forest
fire
events
suggest
that
also
an
urgent
issue
European
Alps,
but
studies
assessing
hazard
under
future
scenarios
still
rare.
Thus,
this
study
aims
analyse
impacts
of
change
on
probability
across
Alps
surrounding
areas.
In
specific,
we
(1)
explain
current
based
a
set
parameters,
(2)
map
conditions
area
using
geographically
weighted
regression.
Our
results
mainly
depends
lightning
strikes,
annual
mean
temperature,
precipitation
seasonality.
Overall,
our
indicate
increase
hazard,
which
is
already
significant
SSP126
(+15.5%),
while
highest
increases
occur
SSP370
(30.6%)
SSP585
(35.4%).
However,
less
pronounced
fire-prone
regions
southwestern
France,
will
greatly
Northern
Eastern
regions.
findings
emphasize
need
address
these
climate-related
challenges
by
decision-making
management
through
fire-smart
management.
Nevertheless,
further
efforts
needed
overcome
limitations
related
data
availability
uncertainties
scenarios.
Diversity and Distributions,
Год журнала:
2025,
Номер
31(2)
Опубликована: Фев. 1, 2025
ABSTRACT
Aim
The
integration
of
high‐quality
field
data
with
high‐resolution
remote
sensing
can
give
detailed
insights
into
the
spatial
distribution
biodiversity
and
provide
valuable
information
for
conservation
at
a
scale
relevant
management
action.
We
developed
framework
based
on
surveys
modelling
species
richness
abundance
butterflies
high
resolution
to
inform
about
butterfly
analyse
their
drivers
effect
landscape
factors.
Location
Western
Austria.
Methods
combined
structured
175
grassland
sites
in
western
Austria
variables
describing
topography,
characteristics,
composition
configuration
different
radii
around
site.
For
predictions
abundance,
generalised
linear
models
elastic
net
regularisation
were
used
compared
stepwise
variable
selection.
To
influence
selected
effect,
topography
applied.
Results
richness,
Spearman
rank
correlation
between
predicted
measured
values
was
0.62.
predictive
power
lower
0.52.
Models
from
smaller
(125
250
m)
generally
showed
better
performance
than
those
larger
(500
1000
m).
found
an
elevation,
maximum
productivity,
northness,
forest
ecotone
density
most
models.
Main
Conclusions
Integrating
techniques
substantially
enhances
our
ability
understand
patterns
identify
key
resolution.
Our
study
highlights
positive
edges,
small
woody
features,
moderate
productivity
abundance.
