The
US
national
parks
system
encompasses
diverse
environmental
and
tourism
management
regimes,
together
governed
by
the
1916
Organic
Act
its
dual
mandate
of
conservation
provision
public
enjoyment.
However,
with
introduction
transformative
science
policy
in
2000’s,
mission
scope
has
since
expanded
to
promote
overarching
science-based
objectives.
Yet
despite
this
paradigm
shift
instituting
“science
for
parks,
science”,
there
is
scant
research
exploring
impact
on
knowledge.
We
address
gap
developing
a
spatiotemporal
framework
evaluating
alignment,
here
operationalized
via
quantifiable
measures
supply
demand
scientific
Specifically,
we
apply
machine
learning
algorithm
(Latent
Dirichlet
analysis)
comprehensive
park-specific
text
corpus
(combining
official
needs
statements
-demand-
metadata
-supply-)
define
joint
topic
space,
which
thereby
facilitates
quantifying
direction
degree
alignment
at
multiple
levels.
Results
indicate
an
overall
robust
misaligned
topics
tending
be
over-researched
(as
opposed
over-demanded),
may
favorable
many
but
inefficient
from
park
perspective.
further
that
exacerbated
misalignment
mandated
domains.
In
light
these
results,
argue
improved
decision
support
mechanisms
achieve
more
timely
efforts
towards
distinctive
needs,
fostering
convergent
knowledge
co-production
leveraging
full
value
as
living
laboratories.
Abstract
This
article
discusses
“academic
housekeeping”
undertaken
within
IPCC,
understood
as
the
work
that
is
rarely
made
visible
or
rewarded,
but
nevertheless
essential
to
success
of
organization.
It
explores
conditions,
motivations,
and
implications
for
individual
researchers
involved
in
with
particular
emphasis
on
invisible,
un(der)recognised
unrewarded
they
engage
in.
The
empirical
material
consists
an
interview
study
IPCC
assessment
work.
concludes
a
discussion
experts,
expert
organisations,
academic
institutions.
Environmental Research Letters,
Год журнала:
2024,
Номер
19(11), С. 111011 - 111011
Опубликована: Окт. 10, 2024
Abstract
This
perspective
article
explores
the
role
of
data
visualisation
in
decision-making
under
deep
uncertainty
(DMDU),
a
growing
discipline
tackling
complex
socio-environmental
challenges,
such
as
climate
impacts
and
adaptation,
natural
resource
management,
preparedness
for
extreme
events.
We
discuss
both
analysis
(or
exploratory
)
purposes,
well
communication
explanatory
including
to
stakeholders
public.
identify
lack
comprehensive
guidelines
on
how
visualisations
are
currently
used
their
potential
enhancing
DMDU
processes.
Drawing
literature
insights
from
recent
workshop,
we
key
challenges
analysts
face
when
visualising
data:
managing
complexity
dimensionality,
effectively
communicating
uncertainty,
ensuring
user
engagement
interpretability.
propose
research
agenda
address
these
by
taxonomising
evaluating
effectiveness
different
visual
forms
contexts,
fostering
interdisciplinary
collaboration.
argue
that,
through
efforts,
can
improve
usability
analyses,
ultimately
aiding
more
informed
adaptive
uncertainty.
Environmental Policy and Governance,
Год журнала:
2024,
Номер
unknown
Опубликована: Дек. 21, 2024
Abstract
For
environmental
governance
research
(EGR)
to
be
actionable
catalyze
solutions
for
challenges
in
policy
and
praxis,
it
must
allow
knowledge
cumulation
that
demonstrates
the
applicability
of
EGR
existing
future
issues,
improves
robustness
validity
EGR,
identifies
conditions,
causal
mechanisms
other
underlying
features
governance.
It
is
recognized
cannot
produce
such
without
integrating
various
disciplines
connect
issues
with
their
political
dimensions
implications.
Yet,
resembles
a
“fragmented
adhocracy”
lacks
standardized
theoretical
frameworks,
concepts,
approaches.
To
overcome
this
disciplinary
fragmentation
develop
effectively
aggregate
evidence,
critical
understand
processes
identify
practices
can
impede
integration
knowledge.
This
narrative
review
examines
argue
(1)
lies
interdisciplinary
integration;
(2)
will
only
fulfill
its
goals
informing
praxis
if
between
researchers
considered
as
precondition
Oxford Open Climate Change,
Год журнала:
2023,
Номер
3(1)
Опубликована: Янв. 1, 2023
Abstract
Moving
away
from
hazardous
areas
may
be
an
important
adaptive
response
under
intensifying
climate
change,
but
to
date
such
movement
has
been
controversial
and
conducted
with
limited
government
or
private-sector
support.
Research
emphasized
resident
perspectives
on
mobility,
understanding
how
professionals
view
it
open
new
avenues
shape
future
outcomes.
Based
76
interviews
involved
in
responses
South
Florida,
we
evaluate
perceptions
of
adaptation
goals,
the
potential
role
mobilities
pathways
supporting
those
associated
constraints
enablers.
The
practitioners
interviewed
anticipate
multiple
types
will
occur
region,
at
increasing
scales.
Interviewees
perceive
present,
especially
migration
gentrification
where
plays
some
role,
as
causing
distributional
inequities
financial
sociocultural
disruptions,
they
existing
strategies
best
serving
who
already
have
adequate
resources,
despite
practitioners’
personal
commitments
social
justice
goals.
Although
many
feel
prepared
for
their
own,
roles
related
mobilities,
judge
region
a
whole
being
unprepared
support
retreat
see
inevitable,
need
more
ambitious
long-term
transition
plan.
Achieving
this
difficult,
indicate
that
remain
hard
talk
about
politically.
Nevertheless,
interviewees
believe
households
are
considering
moving
risks.
Discussions
through
far
beyond,
encourage
mindful
choices
engagement
climate-driven
transformations.
The
US
national
parks
system
encompasses
diverse
environmental
and
tourism
management
regimes,
together
governed
by
the
1916
Organic
Act
its
dual
mandate
of
conservation
provision
public
enjoyment.
However,
with
introduction
transformative
science
policy
in
2000’s,
mission
scope
has
since
expanded
to
promote
overarching
science-based
objectives.
Yet
despite
this
paradigm
shift
instituting
“science
for
parks,
science”,
there
is
scant
research
exploring
impact
on
knowledge.
We
address
gap
developing
a
spatiotemporal
framework
evaluating
alignment,
here
operationalized
via
quantifiable
measures
supply
demand
scientific
Specifically,
we
apply
machine
learning
algorithm
(Latent
Dirichlet
analysis)
comprehensive
park-specific
text
corpus
(combining
official
needs
statements
-demand-
metadata
-supply-)
define
joint
topic
space,
which
thereby
facilitates
quantifying
direction
degree
alignment
at
multiple
levels.
Results
indicate
an
overall
robust
misaligned
topics
tending
be
over-researched
(as
opposed
over-demanded),
may
favorable
many
but
inefficient
from
park
perspective.
further
that
exacerbated
misalignment
mandated
domains.
In
light
these
results,
argue
improved
decision
support
mechanisms
achieve
more
timely
efforts
towards
distinctive
needs,
fostering
convergent
knowledge
co-production
leveraging
full
value
as
living
laboratories.