Valuing type and scope of ecosystem conservation: A meta-analysis

Abstract

Ecosystem conservation programs are increasingly incorporating both preservation and restoration strategies for ensuring the flow of ecosystem services from public lands. While preservation and restoration have similar end ecological objectives, differences in these conservation types may create systematic variation in willingness to pay (WTP) for their benefits. There has also been conflicting evidence of whether or not the amount, or scope, of conservation influences the demand for environmental improvements in manners consistent with neoclassical economics (greater value for more conservation). To investigate the sensitivity of conservation values to type and scope, we conducted a meta-analysis of existing evidence. We synthesized 127 data points from 22 primary studies that provided WTP estimates for preservation, forest restoration, and freshwater restoration conducted primarily on public lands. Estimates were derived from choice experiments, contingent rankings, and dichotomous choice contingent valuation studies for conservation programs in Europe, Canada, and the U.S. from 1987 to 2013. We found strong evidence for systematic variation of WTP depending on conservation type and scope. Values for preservation were greater than both forest and freshwater restoration; and freshwater restoration was valued greater than forest restoration. Meta-estimates were found to be sensitive to scope effects, as value increased with conservation intensity but at diminishing marginal rates. We provide quantitative policy analysis in the form of within-sample predictions of mean WTP for each conservation type and scope and conclude with recommendations.

Full text

Please
cite
this
article
in
press
as:
Hjerpe,
E.,
et
al.,
Valuing
type
and
scope
of
ecosystem
conservation:
A
meta-analysis.
J.
Forest
Econ.
(2015),
http://dx.doi.org/10.1016/j.jfe.2014.12.001
ARTICLE IN PRESS
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Journal
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(2015)
xxx–xxx
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at
ScienceDirect
Journal
of
Forest
Economics
j
ournal
homepage:
www.elsevier.com/locate/jfe
Valuing
type
and
scope
of
ecosystem
conservation:
A
meta-analysis
Evan
Hjerpea,∗,
Anwar
Hussainb,
Spencer
Phillipsc
aConservation
Economics
Institute,
United
States
bAuburn
University
Forest
Policy
Center
and
Conservation
Economics
Institute,
United
States
cKey-Log
Economics,
United
States
a
r
t
i
c
l
e
i
n
f
o
Article
history:
Received
23
August
2013
Accepted
12
December
2014
JEL
classification:
Q57
Q51
Q24
Keywords:
Conservation
economics
Willingness
to
pay
Meta-analysis
Preservation
Ecological
restoration
Ecosystem
services
a
b
s
t
r
a
c
t
Ecosystem
conservation
programs
are
increasingly
incorporating
both
preservation
and
restoration
strategies
for
ensuring
the
flow
of
ecosystem
services
from
public
lands.
While
preservation
and
restoration
have
similar
end
ecological
objectives,
differences
in
these
conservation
types
may
create
systematic
variation
in
will-
ingness
to
pay
(WTP)
for
their
benefits.
There
has
also
been
conflicting
evidence
of
whether
or
not
the
amount,
or
scope,
of
conservation
influences
the
demand
for
environmental
improve-
ments
in
manners
consistent
with
neoclassical
economics
(greater
value
for
more
conservation).
To
investigate
the
sensitivity
of
con-
servation
values
to
type
and
scope,
we
conducted
a
meta-analysis
of
existing
evidence.
We
synthesized
127
data
points
from
22
pri-
mary
studies
that
provided
WTP
estimates
for
preservation,
forest
restoration,
and
freshwater
restoration
conducted
primarily
on
public
lands.
Estimates
were
derived
from
choice
experiments,
contingent
rankings,
and
dichotomous
choice
contingent
valua-
tion
studies
for
conservation
programs
in
Europe,
Canada,
and
the
U.S.
from
1987
to
2013.
We
found
strong
evidence
for
systematic
variation
of
WTP
depending
on
conservation
type
and
scope.
Val-
ues
for
preservation
were
greater
than
both
forest
and
freshwater
restoration;
and
freshwater
restoration
was
valued
greater
than
∗Corresponding
author
at:
PO
Box
755,
Boise,
ID
83712,
United
States.
Tel.:
+1
208
869
1675.
E-mail
address:
evan@conservationecon.org
(E.
Hjerpe).
http://dx.doi.org/10.1016/j.jfe.2014.12.001
1104-6899/©
2015
Published
by
Elsevier
GmbH.
on
behalf
of
Department
of
Forest
Economics,
Swedish
University
of
Agricultural
Sciences,
Umeå.

Please
cite
this
article
in
press
as:
Hjerpe,
E.,
et
al.,
Valuing
type
and
scope
of
ecosystem
conservation:
A
meta-analysis.
J.
Forest
Econ.
(2015),
http://dx.doi.org/10.1016/j.jfe.2014.12.001
ARTICLE IN PRESS
G Model
JFE-25231;
No.
of
Pages
19
2
E.
Hjerpe
et
al.
/
Journal
of
Forest
Economics
xxx
(2015)
xxx–xxx
forest
restoration.
Meta-estimates
were
found
to
be
sensitive
to
scope
effects,
as
value
increased
with
conservation
intensity
but
at
diminishing
marginal
rates.
We
provide
quantitative
policy
analysis
in
the
form
of
within-sample
predictions
of
mean
WTP
for
each
conservation
type
and
scope
and
conclude
with
recommendations.
©
2015
Published
by
Elsevier
GmbH.
on
behalf
of
Department
of
Forest
Economics,
Swedish
University
of
Agricultural
Sciences,
Umeå.
Introduction
Conservation
efforts
on
public
lands
are
increasingly
centered
on
holistic
approaches
that
maintain
and
repair
networks
of
connected
ecosystems.
Because
many
public
lands
have
been
degraded
by
past
industrial
extraction
however,
ecosystem
conservation
efforts
are
now
comprised
of
both
preserva-
tion
and
ecological
restoration
strategies.1Together,
these
conservation
strategies
aim
to
maintain
or
improve
ecosystem
structures,
processes,
and
functions
that
ultimately
produce
biodiversity,
clean
drinking
water,
raw
materials,
recreational
opportunities,
and
other
services
beneficial
to
humans.
The
myriad
values
that
people
hold
for
nature
are
tied
to,
and
can
be
classified
as
diverse
flows
of
services
that
ecosystems
provide
to
mankind.
These
ecosystem
services
include
provisioning
services,
such
as
timber
for
houses
and
other
commodities,
but
are
substantially
comprised
of
non-market
services
such
as
climate
regulation,
provision
of
biodiversity,
and
spiritual
inspiration
(Pagiola
et
al.,
2004).
To
the
extent
that
decision
criteria
derived
from
economic
paradigms
(e.g.,
efficiency,
or
maximization
of
net
present
value)
dominate
planning
and
funding
of
public
lands
management,
it
is
imperative
that
information
derived
from
commodity
and
other
markets
are
augmented
with
suitable
information
about
the
value
of
non-market
goods
and
services
provided
by
pristine
or
restored
ecosystems.
This
broader
ecosystem
conservation
approach
requires
novel
scientific
methods
for
understanding
the
impacts
and
benefits
(Garber-Yonts
et
al.,
2004).
Because
values
for
changes
in
ecosystem
services
are
not
easily
ascertained
from
market
transac-
tions,
non-market
valuation
techniques
are
required.
Stated
preference
methods
are
well
suited
for
determining
the
demand
and
implicit
prices
for
ecosystem
conservation
and
changes
in
the
production
of
services
that
result,
due
to
their
ability
to
capture
existence
and
bequest
values.
However,
the
vast
and
often
conflicting
array
of
willingness
to
pay
(WTP)
estimates
for
ecosystem
services,
the
cost
of
primary
studies,
and
the
need
for
timely
availability
of
relevant
estimates
underscore
the
importance
of
meta-analyses.
Meta-analysis
provides
a
means
to
statistically
quantify
and
integrate
evidence
from
multiple
primary
studies
of
similar
phenomena
(Glass,
1976).
Meta-regression
analysis,
or
the
regres-
sion
of
regressions,
has
been
the
preferred
choice
of
quantitative
syntheses
in
economics
due
to
the
ease
of
replication
and
sensitivity
analysis
of
alternate
model
specifications
(Stanley
and
Jarrell,
1989).
Best
practices
for
meta-analysis
techniques
in
environmental
valuation
have
been
explored
in
general
(Nelson
and
Kennedy,
2009)
and
more
specifically
for
non-market
valuation
(Smith
and
Pattanayak,
2002).
While
there
are
a
handful
of
meta-analyses
that
have
synthesized
willingness
to
pay
estimates
for
individual
or
subsets
of
ecosystem
services
associated
with
preservation
or
restoration
of
cer-
tain
ecosystem
types,
(e.g.,
Van
Houtven
et
al.,
2007;
Lindhjem,
2007;
Latinopoulos,
2010;
Ojea
and
Loureiro,
2011),
there
have
been
no
meta-analyses
focused
on
synthesizing
willingness
to
pay
for
various
ecosystem
conservation
strategies.
Additionally,
there
is
mixed
evidence
as
to
the
sensitivity
of
willingness
to
pay
estimates
to
the
amount
of
conservation.
These
two
primary
research
interests
need
further
assessment:
(1)
how
the
type
of
conservation
(i.e.,
preservation
or
restoration)
influences
1Ecological
restoration
refers
to
the
re-establishment
of
the
characteristics
of
an
ecosystem
that
were
prevalent
before
degradation.
It
involves
the
removal
or
amelioration
of
the
factor
causing
environmental
degradation
and
the
re-establishment
of
key
ecosystem
components
to
influence
the
rate
and
direction
of
recovery
(Benayas
et
al.,
2009).
Preservation
is
more
of
a
hands-off
approach
and
specifically
refers
to
making
land
unavailable
for
development
and
exploitation.

Please
cite
this
article
in
press
as:
Hjerpe,
E.,
et
al.,
Valuing
type
and
scope
of
ecosystem
conservation:
A
meta-analysis.
J.
Forest
Econ.
(2015),
http://dx.doi.org/10.1016/j.jfe.2014.12.001
ARTICLE IN PRESS
G Model
JFE-25231;
No.
of
Pages
19
E.
Hjerpe
et
al.
/
Journal
of
Forest
Economics
xxx
(2015)
xxx–xxx
3
willingness
to
pay,
and
(2)
how
sensitive
willingness
to
pay
meta-estimates
are
to
the
quantity
and
intensity,
or
scope,
of
conservation.
The
type
of
conservation
program
being
offered,
be
it
preservation
or
restoration,
is
likely
to
influ-
ence
willingness
to
pay
for
conservation
due
to
varying
trade-offs
and
implications
associated
with
each.
Furthermore,
different
types
of
ecological
restoration
programs,
such
as
forest
or
freshwater
restoration,
may
influence
willingness
to
pay
estimates.
Preservation
and
restoration
programs
have
similar
ecological
motives
(providing
quality
ecosystem
services
associated
with
more
natural
areas)
and
are
fundamentally
different
from
other
land
management
strategies
focused
on
the
extraction
of
commodities.
Despite
their
similarities,
preservation
and
restoration
have
a
number
of
differences.
Preservation
is
implemented
to
prevent
degradation,
whereas
restoration
is
implemented
to
fix
degra-
dation.
Since
preservation
is
typically
applied
to
more
pristine
lands
that
have
the
potential
to
be
exploited,
and
restoration
is
applied
to
already
degraded
lands,
the
starting
point
of
total
stocks
of
ecosystem
services
is
likely
to
be
greater
for
a
given
preservation
policy
site
than
for
restoration
policy
sites.
The
public
is
also
likely
to
be
sensitive
to
the
quantity,
or
scope,
of
conservation
effort,
as
typically
conveyed
in
terms
of
changes
in
ecosystem
services
and
attributes.
As
individuals
look
to
maximize
their
well-being
(and
utility),
levels
of
conservation
are
purchased
at
various
prices,
contributing
differently
to
overall
utility
maximization.
Assuming
individuals
have
constrained
budgets,
they
are
likely
to
be
sensitive
to
the
cost
associated
with
different
amounts
of
conservation.
However,
the
identification
of
scope
effects
for
ecosystem
services
is
complicated
by
various
study
designs
and
measurement
differences
–
requiring
new
approaches
at
classifying
quantities
of
conservation
effort.
In
this
article,
we
synthesized
existing
values
for
ecosystem
conservation
to
test
fundamental
hypotheses
and
provide
within-sample
predictions.
Out-of-sample
predictions
are
a
further
appli-
cation
of
meta-analyses
that
are
used
to
transfer
synthesized
benefits
to
new
policy
regions
–
known
as
the
benefit
transfer
method
(Rosenberger
and
Loomis,
2001).
While
we
do
not
provide
a
benefit
transfer
application
of
our
meta-regression
model
in
this
manuscript,
we
have
set
the
meta-analysis
up
for
potential
benefit
transfer
applications
in
the
future.
We
follow
best
practice
recommendations
for
meta-analysis
in
environmental
economics
from
Nelson
and
Kennedy
(2009),
specifically
for
prob-
lem
definition,
model
specification,
capturing
data
heterogeneity
in
estimation,
sensitivity
analysis,
and
applications.
Literature
review
and
hypotheses
With
regard
to
particular
ecosystems
and
attributes,
meta-analysis
has
shed
light
on
the
economic
values
of
wetlands
(Brouwer
et
al.,
1999;
Woodward
and
Wui,
2001),
endangered
species
(Loomis
and
White,
1996),
water
quality
improvement
(Johnston
et
al.,
2003,
2005),
coastal
and
freshwater
ecosystems
(Wilson
and
Carpenter,
1999;
Latinopoulos,
2010),
and
forest
recreation
(Rosenberger
and
Loomis,
2000).
Recently,
three
meta-analyses
have
focused
on
willingness-to-pay
estimates
for
forest
ecosystem
services
(Lindhjem,
2007;
Barrio
and
Loureiro,
2010;
Ojea
and
Loureiro,
2011).
Collectively
these
meta-analyses
have
advanced
our
understanding
of
the
patterns
implicit
in
willingness-to-pay
estimates
for
various
ecosystem
services
and
their
effectiveness
in
benefit
transfer,
but
have
produced
conflicting
results
on
scope
effects
and
have
not
isolated
conservation
types.
Willingness
to
pay
for
ecosystems
services
depends
on
how
the
services
are
produced.
Czajkowski
et
al.
(2009)
and
Lehtonen
et
al.
(2003),
for
example,
argue
that
respondents
seem
to
be
concerned
not
only
with
the
outcomes
of
conservation
programs
but
with
the
means
of
achieving
these
outcomes
as
well
(i.e.,
whether
preservation
or
restoration
is
adopted).
Christie
et
al.
(2006),
on
the
other
hand,
report
that
there
is
no
evidence
that
the
public
cares
how
biodiversity
and
ecosystem
services
are
produced.
The
former
view,
however,
seems
more
plausible
for
a
couple
of
reasons.
First,
certain
con-
servation
actions
are
likely
to
be
preferred
over
others
because
varying
opportunity
costs
associated
with
each
conservation
strategy
are
not
likely
to
be
borne
uniformly
by
regions
and
socioeconomic
groups.
Second,
preservation
could
be
expected
to
command
a
premium
because
the
richness
and
abundance
of
biodiversity
and
ecosystem
services
(i.e.,
total
stocks
and
starting
points,
not
necessar-
ily
marginal
change
achieved
with
conservation
program)
associated
with
intact
ecosystems
exceeds
the
corresponding
levels
induced
by
active
restoration
of
degraded
ecosystems
(Benayas
et
al.,
2009).

Please
cite
this
article
in
press
as:
Hjerpe,
E.,
et
al.,
Valuing
type
and
scope
of
ecosystem
conservation:
A
meta-analysis.
J.
Forest
Econ.
(2015),
http://dx.doi.org/10.1016/j.jfe.2014.12.001
ARTICLE IN PRESS
G Model
JFE-25231;
No.
of
Pages
19
4
E.
Hjerpe
et
al.
/
Journal
of
Forest
Economics
xxx
(2015)
xxx–xxx
While
preservation
and
restoration
projects
can
have
similar
goals,
they
are
not
substitutes.
As
such,
they
can
invoke
different
values
felt
for
a
loss
or
a
gain
that
may
carry
more
weight.
Behavioral
economists
have
confirmed
loss-aversion
and
endowment
effects
(Thaler,
1980),
where
individuals
may
find
that
avoiding
the
loss
of
ecosystem
services
through
preservation
is
of
greater
value
than
the
equivalent
gain
of
ecosystem
services
through
restoration.
Other
factors
may
also
be
in
play,
including
the
differing
levels
of
human
intervention
involved
in
preservation
and
restoration.
Preservation
is
more
“hands
off,”
while
ecological
restoration
aims
to
use
active,
anthropogenic
intervention
to
correct
anthropogenically-caused
degradation.
Some
people
may
have
inherent
preferences
for
hands-on
or
hands-off
types
of
management,
while
others
may
doubt
the
effectiveness
of
our
ability
to
provide
a
technological
fix
to
degraded
nature
(Katz,
1992).
Scope,
or
embedding,
effects
have
been
separated
into
commodity
and
temporal
effects;
the
former
occurs
when
respondents
are
not
sensitive
to
the
amount
of
ecosystem
services
whereas
the
latter
occurs
when
survey
respondents
do
not
adequately
differentiate
between
a
one-time
payment
and
a
series
of
payments
(Stevens
et
al.,
1997).
Insensitivity
to
the
scope
of
ecosystem
services
being
offered
has
been
a
primary
critique
of
the
reliability
of
contingent
valuation
methods
(Arrow
et
al.,
1993).
As
such,
scope
effects
concerning
the
sensitivity
of
WTP
to
changes
in
the
scale
of
ecosystem
service
provision
have
been
the
focus
of
intense
research.
Kahneman
and
Knetsch
(1992)
claimed
that
the
scope
test
had
not
been
satisfied
and
interpreted
WTP
estimates
as
manifestations
of
a
“warm
glow
effect”
rather
than
the
result
of
utility
maximization.
Their
claims
of
scope
insensitivity
in
valuing
environmental
goods
spurred
greater
scrutiny
of
the
topic
and
have
been
subsequently
countered
by
other
studies
(Carson
and
Mitchell,
1993;
Smith
and
Osborne,
1996;
Carson,
1997;
Veisten
et
al.,
2004).
These
latter
studies
illustrated
scope
sensitivity
and
suggested
that
greater
specification
of
the
ecosystem
service
(i.e.,
attribute
description)
and
its
provision
(i.e.,
management
type)
can
reconcile
scope
concerns.
Questions
of
how
much
more
value
should
be
generated
by
greater
provision
of
ecosystem
services
are
still
unsettled.
Diminishing
marginal
utility
for
greater
ecosystem
services
is
expected
under
neoclassical
assumptions
and
researchers
have
illustrated
value
increases
only
up
to
certain
thresholds
of
conservation,
such
as
the
minimum
species
population
required
for
survival
(Bulte
and
Van
Kooten,
1999).
Testing
of
commodity
scope
effects
for
conservation
values
in
meta-analyses
is
particularly
chal-
lenging
due
to
problems
of
aggregating
dissimilar
measures
of
commodities,
as
primary
studies
often
portray
changes
in
ecosystem
attributes
in
both
absolute
and
relative
terms.
Van
Houtven
et
al.
(2007)
confirmed
scope
effects
using
primarily
relative
measurements
of
improvement
from
primary
studies.
Lindhjem
(2007),
on
the
other
hand,
could
not
confirm
scope
effects
based
on
the
absolute
size
of
forest
conservation
(hectares
or
percentage
increases).
Ojea
and
Loureiro
(2011)
provide
a
recent
approach
in
testing
for
scope
effects
by
coding
all
ecosystem
attribute
changes,
including
absolute
and
relative
measurements,
into
absolute
measurements
such
as
hectares
of
forest
or
wildlife
population
num-
bers.
In
their
meta-analysis,
Ojea
and
Loureiro
(2011)
confirmed
scoped
effects
for
absolute
measures,
but
not
for
relative,
leading
to
a
recommendation
for
primary
studies
to
utilize
absolute
measure-
ment.
Yet,
as
described
in
Lindhjem
(2007),
this
approach
is
fraught
with
difficulties
for
ecosystem
goods
and
services
due
to
their
complexity
and
the
wide
range
of
values
that
people
hold
for
the
same
measurement.
For
example,
Ojea
and
Loureiro’s
(2011)
approach
converts
a
relative
change
in
an
attribute
(e.g.,
improved
bird
habitat)
to
just
the
number
of
acres
that
this
attribute
change
will
occur
on
–
losing
significant
information
about
this
attribute.
It
is
not
surprising
that
they
were
unable
to
confirm
scope
sensitivity
with
relative
measures,
given
their
classification
of
primary
data
points.
Without
prior
research
on
WTP
for
type
of
conservation
strategy,
and
with
mixed
results
from
prior
research
on
WTP
for
scope
of
conservation,
our
investigation
specifically
tests
the
following
hypotheses
concerning
conservation
Type
and
Scope:
H01:
ˇ1=
ˇ2=
ˇ3;
where
ˇx=
coefficient
for
WTP
for
three
types
of
conservation
(forest
restoration,
freshwater
restoration,
and
preservation);
H02:
ˇ4<
ˇ5<
ˇ6;
where
ˇx=
coefficient
for
WTP
for
three
levels
of
conservation
(attribute-specific,
program
low,
program
high).

Please
cite
this
article
in
press
as:
Hjerpe,
E.,
et
al.,
Valuing
type
and
scope
of
ecosystem
conservation:
A
meta-analysis.
J.
Forest
Econ.
(2015),
http://dx.doi.org/10.1016/j.jfe.2014.12.001
ARTICLE IN PRESS
G Model
JFE-25231;
No.
of
Pages
19
E.
Hjerpe
et
al.
/
Journal
of
Forest
Economics
xxx
(2015)
xxx–xxx
5
This
study
provides
the
first
meta-regression
estimates
of
WTP
by
type
of
ecosystem
conservation.
Willingness
to
pay
estimates
for
preservation
and
restoration
on
public
lands
were
statistically
inferred
using
data
from
primary
studies
that
applied
stated
preference
valuation
methods.
Results
of
this
meta-analysis
can
help
stated
preference
modelers
improve
research
design
for
greater
utility
in
meta-
analyses
and
provide
the
basis
for
future
transfer
of
benefits
to
other
situations.
Meta-regression
methods
It
has
been
said
that
meta-analyses
are
as
much
art
as
science.
We
believe
that
nothing
illustrates
this
balance
more
than
achieving
consistency
in
measuring
and
synthesizing
primary
data
points
of
the
same
phenomenon
(McFadden,
1997).
This
consistency
is
the
necessary
degree
of
meaningful
com-
binations
of
primary
data
from
identical
concepts
that
can
be
adequately
analyzed
within
a
common
analytical
framework
–
consistency
that
is
often
not
attained
in
non-market
valuation
meta-analyses
(Smith
and
Pattanayak,
2002).
To
synthesize
and
compare
apples
to
apples,
we
first
deal
with
an
inherent
problem
in
meta-analyses
–
“the
tradeoff
between
expanding
the
meta-sample
to
improve
statistical
estimation
and
reducing
the
sample
to
ensure
comparability
across
studies”
(Van
Houtven
et
al.,
2007).
Data
selection
The
concept
of
primary
data
heterogeneity
(Nelson
and
Kennedy,
2009)
includes
both
commodity
heterogeneity
(Van
Houtven
et
al.,
2007),
or
commodity
consistency
(Bergstrom
and
Taylor,
2006),
and
welfare
change
measure
consistency
(Bergstrom
and
Taylor,
2006).
In
order
to
adequately
synthesize
willingness
to
pay
for
conservation,
we
limited
our
data
selection
to
those
studies
measuring
similar
“effect-sizes”
conducted
with
similar
valuation
techniques.
Other
sources
of
data
heterogeneity
can
include
survey
response
rates
and
publication
bias.
Below,
we
detail
how
the
data
were
selected
and
how
we
dealt
with
primary
data
heterogeneity.
The
data
for
this
research
were
compiled
from
22
primary
studies
that
were
conducted
from
1985
through
2013.
These
primary
studies
were
found
based
on
a
literature
review
of
primary
search
engines
(EconLit,
ScienceDirect,
and
Google
Scholar)
and
web
site
searches
that
inventoried
valuation
studies.
Specifically,
these
sites
included
the
Environmental
Valuation
Reference
Inventory
(www.evri.ca),
the
United
States
Forest
Service
site
on
ecosystem
services
(www.fs.fed.us/ecosystemservices/
index.shtml),
and
the
Ecosystem
Services
Bibliography
(blog.lib.umn.edu/polasky/ecosystem).
Key
words
searched
for
included:
willingness
to
pay,
preservation,
restoration,
and
conservation.
Snow-
balling
techniques
were
also
employed
as
existing
meta-analyses
were
used
to
find
candidate
studies.
The
studies
met
the
following
criteria:
a)
focused
on
preservation
and/or
restoration
of
forested
and
freshwater
ecosystems
primarily
on
public
lands
rather
than
individual
species;
b)
used
dichotomous
choice
contingent
valuation
(DCCV),
choice
experiment
(CE),
and/or
contingent
ranking
(CR);
and
c)
reported
mean
or
median
willingness
to
pay
per
individual
or
household
(see
Table
1).
Almost
all
the
primary
studies
were
published
in
peer-reviewed
journals.
Given
past
findings
on
publication
bias
(e.g.,
Rosenberger
and
Stanley,
2006),
we
also
scoured
dissertations,
book
chapters,
technical
reports
and
other
gray
literature
–
finding
only
one
suitable
candidate
that
has
been
included.
Full
datasets
are
available
from
the
authors.
The
decision
to
focus
on
the
type
of
ecosystem
conservation
effort
rather
than
species
was
made
because
valuing
individual
species
misses
ecological
complementarity
among
species
and
substitution
effects
(Loomis
and
White,
1996),
and
does
not
capture
values
for
the
numerous
supporting
ecosys-
tem
services
spurred
by
this
complementarity.
Highly
valued
species
are
not
necessarily
the
species
most
important
for
maintaining
biodiversity
and
naturalness
(Czajkowski
et
al.,
2009).
According
to
Montgomery
(2002)
the
species
focused
approach
is
consistent
with
policies
that
emphasize
charis-
matic
megafauna
(large
animals
that
people
relate
to
such
as
eagles,
bears,
and
caribou)
while
leaving
much
of
the
landscape
open
for
exploitation.
Furthermore,
forest
and
freshwater
ecosystems
were
chosen
due
to
their
intertwined
ecological
connections
and
adjacency.
Other
ecosystem
conservation
types,
such
as
the
preservation
and
restoration
of
marine
and
desert
ecosystems,
were
excluded
due
to
a
lack
of
commodity
consistency
and
a
paucity
of
primary
studies
in
these
realms.
In
order
to
focus

Please
cite
this
article
in
press
as:
Hjerpe,
E.,
et
al.,
Valuing
type
and
scope
of
ecosystem
conservation:
A
meta-analysis.
J.
Forest
Econ.
(2015),
http://dx.doi.org/10.1016/j.jfe.2014.12.001
ARTICLE IN PRESS
G Model
JFE-25231;
No.
of
Pages
19
6
E.
Hjerpe
et
al.
/
Journal
of
Forest
Economics
xxx
(2015)
xxx–xxx
Table
1
Primary
studies
used
in
the
analysis
of
willingness
to
pay
for
ecosystem
conservation.
Primary
study
(year
of
publication) Survey
Year
Elicitation
formataNiAdjusted
WTP2010b
Mean
SD
Min
Max
Adamowicz
et
al.
(1998) 1995
DCCV;
CE 2
175.970 54.065 137.740 214.200
Caparros
et
al.
(2008)
2003
CE;
CR
7
65.664
90.686
0.742
219.343
Czajkowski
et
al.
(2009) 2007
CE
7
5.188
4.578
2.433
15.455
Farber
and
Griner
(2000) 1996
CR
8
89.449 51.913 7.644 169.413
Garber-Yonts
et
al.
(2004) 1999
DCCV:
CE 15
133.241 121.169 44.501 480.349
Garrod
and
Willis
(1997) c1995
CR
16
28.667
15.445
8.638
47.301
Hagen
et
al.
(1992) 1992
DCCV
2
365.580
54.268
327.207
403.954
Hailu
et
al.
(2000) 1995
DCCV;
CE
4
141.809
105.636
65.241
291.004
Hanley
et
al.
(2006) 2001
CE
8
24.262 17.200 9.129 50.237
Holmes
et
al.
(2004)
2003
DCCV
6
21.183
27.521
1.292
63.710
Kramer
et
al.
(2004) 1991
DCCV
2
37.351
11.683
29.090
45.612
Lehtonen
et
al.
(2003)
2002
DCCV;CE
4
158.301
75.962
66.188
246.001
Loomis
(1987)
1985
DCCV
2
156.246
108.505
79.521
232.970
Loomis
(1996)
1995
DCCV
3
95.387
10.151
84.418
104.449
Loomis
et
al.
(2000)
1998
DCCV
1
337.116
0
337.116
337.116
Macmillan
et
al.
(2001)
1995
DCCV
6
29.074
8.949
20.128
44.449
Meyerhoff
et
al.
(2009) 2004
CE
17
11.369
7.735
4.393
30.997
Mueller
et
al.
(2013) 2011
DCCV
2
184.762
9.727
177.884
191.640
Ovaskainen
and
Kniivila
(2005) 2000
DCCV
3
87.132 35.364 47.346 114.988
Siikamaki
and
Layton
(2007)
1999
CR;
DCCV
2
62.913
16.777
51.050
74.776
Weber
and
Stewart
(2009)
2006
DCCV;
CE
7
53.689
54.183
7.939
169.382
Wilson
et
al.
(2010)
2006
CR;
DCCV
3
71.986
72.644
16.509
154.212
All
127
70.868
87.845
0.742
480.349
aDCCV
(dichotomous
choice
contingent
valuation);
CE
(choice
experiment);
CR
(contingent
ranking).
Ni=
Number
of
observations
taken
from
primary
study
j.
bWTP
expressed
in
2010
prices
based
on
country-specific
CPI
followed
by
conversion
into
purchasing
power
parity
US
dollars
using
Penn
PPI.
The
Penn
PPI
was
obtained
from:
Alan
Heston,
Robert
Summers
and
Bettina
Aten,
Penn
World
Table
Version
7.1,
Center
for
International
Comparisons
of
Production,
Income
and
Prices
at
the
University
of
Pennsylvania,
July
2012.
http://pwt.econ.upenn.edu/php
site/pwt
index.php
cReported
WTP
estimates
for
Garrod
and
Willis
(1997)
were
scaled
up
100%,
prior
to
purchasing
power
adjustment,
due
to
reported
marginal
WTP
at
1%
increments.
The
scaling
ensured
consistency
with
WTP
estimates
from
other
primary
studies.
strictly
on
type
and
scope
of
ecosystem
conservation
strategy,
we
eliminated
many
general
economic
valuations
of
environmental
improvements
that
might
be
achieved
off-site
and
in
the
markets.
For
example,
we
did
not
include
valuations
of
reductions
in
pollution
or
other
degradation
that
would
be
achieved
by
national
policies
focused
on
capping,
reducing,
and/or
trading
pollution
credits
or
through
improved
industrial
practices.
These
policy
evaluations
have
been
conducted
for
many
environmental
issues
such
as
eutrophication,
acid
rain,
air
quality,
and
climate
change.
Our
focus
was
on
synthesizing
willingness
to
pay
for
policies
that
would
preserve
or
restore
natural
structure,
function,
and
processes
on
specific
landscapes
(see
examples
in
WTP
Primary
Data
section
below).
We
focused
on
stated
preference
methods
that
utilize
Hicksian
consumer
surplus,
and
did
not
include
revealed
preference
methods
such
as
travel
cost
and
hedonic
pricing
that
utilize
Marshallian
consumer
surplus.
Our
focus
on
stated
preference
methods
is
due
to
their
superior
ability
to
incorpo-
rate
non-users
of
the
resource
in
question
and
in
particular,
existence
and
bequest
values.
We
further
restricted
the
stated
preference
valuation
studies
to
ones
that
used
DCCV,
CE,
and/or
CR,
because
they
resulted
in
a
more
homogenous
dataset
on
willingness
to
pay
estimates.
These
methods
are
consistent
with
random
utility
hypothesis
and
statistically
derive
willingness
to
pay
estimates,
making
assump-
tions
about
underlying
probability
distribution
and
use
estimation
procedures
for
discrete
choice
data
(e.g.,
logit,
conditional
logit,
nested
logit).
During
the
past
quarter
century,
numerous
studies
have
quantified
economic
values
held
by
households
in
the
U.S.,
Canada,
and
Europe
for
ecosystem
services
and
rare
charismatic
species;
but
a
majority
of
the
earlier
studies
were
based
on
open-ended
con-
tingent
valuation,
payment
card,
and
iterative
bidding.
A
shift
toward
the
use
of
dichotomous
choice
contingent
valuation,
and
choice
experiments
in
general,
followed
after
its
recommendation
by
the

Please
cite
this
article
in
press
as:
Hjerpe,
E.,
et
al.,
Valuing
type
and
scope
of
ecosystem
conservation:
A
meta-analysis.
J.
Forest
Econ.
(2015),
http://dx.doi.org/10.1016/j.jfe.2014.12.001
ARTICLE IN PRESS
G Model
JFE-25231;
No.
of
Pages
19
E.
Hjerpe
et
al.
/
Journal
of
Forest
Economics
xxx
(2015)
xxx–xxx
7
NOAA
panel
(see
Arrow
et
al.,
1993),
despite
evidence
of
‘yea-saying’
in
dichotomous
choice
studies
that
can
lead
to
higher
WTP
estimates
than
traditional
open-ended
studies
(Hanley
et
al.,
1998).
The
evolution
of
stated
preference
methods
toward
choice
experiments
is
particularly
important
for
our
analysis
and
testing
for
scope
effects,
as
choice
experiments
allow
for
overall
valuation
of
programs,
while
being
able
to
tease
out
valuation
of
individual
attributes
that
may
comprise
a
program
(Morrison
et
al.,
2002).
Typically,
choice
experiments
and
contingent
rankings
require
respondents
to
choose
between
different
consumption
bundles,
described
in
terms
of
their
attributes
and
the
level
taken
by
these
attributes.
A
price
term
is
usually
one
of
these
attributes.
With
repeated
choice
sets
and
varying
attribute
levels,
researchers
can
infer
the
influence
of
individual
attributes,
marginal
WTP
for
changes
in
attributes,
and
implied
WTP
for
a
total
conservation
program
that
changes
more
than
one
attribute
simultaneously
(Hanley
et
al.,
1998).
Model
specification
We
hypothesize
that
willingness
to
pay
for
ecosystem
conservation
depends
on
the
degree
of
change
in
ecosystem
attributes
and
resulting
services
from
an
initial
reference
level,
as
well
as
on
the
context
and
socioeconomic
characteristics
of
the
affected
or
interested
population.
Our
specifica-
tion
also
includes
characteristics
of
the
valuation
method
as
additional
factors
that
could
potentially
influence
willingness
to
pay.
Formally,
WTPij =
F([ESS1−
ESS0],
C,
V)(1)
In
this
equation,
WTPij is
the
estimate
(i)
of
willingness
to
pay
for
conservation
reported
in
the
jth
primary
study
included
in
the
meta-analysis.
This
willingness
to
pay
is
a
composite
measure
made
up
of
use
and
non-use
values
for
the
incremental
change
in
ecosystem
services.
ESS0is
the
initial
or
reference
level
of
ecosystem
service
provision
and
ESS1is
the
new
level
after
changes
are
accomplished
through
the
conservation
action.2Subtracting
ESS0from
ESS1provides
the
marginal
change
in
the
quality
and
quantity
of
ecosystem
services
resulting
from
the
conservation
action.
C
is
a
vector
of
variables
indicating
the
context
of
the
study
and
the
socioeconomic
characteristics
of
the
subject
population.
And
V
is
a
vector
of
valuation
characteristics.
We
hypothesize
the
change
in
ecosystem
services
from
ESS0to
ESS1is
strictly
a
result
of
what
management
action
(Type)
is
implemented
and
at
what
intensity
(Scope)
it
is
implemented.
Because
the
change
in
ecosystem
service
level
(i.e.,
from
ESS0to
ESS1)
is
ultimately
dependent
on
the
type
of
conservation
action
and
the
scope
of
action,
we
can
reduce
our
equation
to:
WTPij =
F(T,
S,
C,
V)
(2)
In
the
reduced
form,
T
denotes
the
type
of
conservation
(e.g.,
preservation,
freshwater
restoration,
or
forest
restoration)
and
S
denotes
the
scope
of
conservation
(e.g.,
the
frequency
and
intensity
of
ecosystem
attribute
changes).
It
is
the
specification
of
T
and
S
in
Eq.
(2)
that
distinguishes
this
meta-
analysis
from
other
meta-analyses
that
have
synthesized
willingness
to
pay
for
changes
in
ecosystem
service
production.
Previous
meta-analyses
attempted
to
determine
differences
in
WTP
for
species
or
habitat
type
in
isolation,
while
this
study
emphasizes
habitat
types
(e.g.,
freshwater
versus
forest),
how
conservation
is
achieved
(e.g.,
preservation
versus
restoration),
and
the
level
of
conservation
effort.
The
distinction
is
important
because
it
is
similar
to
how
public
management
agencies
implement
land
management
plans
and
how
conservation
policy
is
framed.
In
the
following
section,
we
provide
2The
majority
of
primary
studies
used
in
this
meta-analysis
measured
WTP
based
on
estimated
changes
in
ecological
(e.g.,
amount
of
native
trees)
and
social
attributes
(e.g.,
amount
of
timber
harvesting
jobs)
resulting
from
the
type
and
scope
of
conservation
effort.
Changes
in
attributes
were
conveyed
in
survey
text
in
terms
of
ecosystem
services
(e.g.,
increased
water
clarity
and
quality
–
the
attribute
–
would
provide
for
greater
fishing
and
recreational
opportunities
–
the
ecosystem
services).
As
such,
the
willingness
to
pay
estimates
reflect
the
value
that
respondents
hold
for
a
composite
of
new
individual
and
bundled
ecosystem
services
(ESS1)
that
would
result
from
the
changed
attribute.
That
is,
respondents
interpret
a
changed
attribute
in
terms
of
the
associated
change
in
ecosystem
services,
or
the
perceived
change
in
benefits
provided
to
them
by
the
new
level
of
the
attribute.

Please
cite
this
article
in
press
as:
Hjerpe,
E.,
et
al.,
Valuing
type
and
scope
of
ecosystem
conservation:
A
meta-analysis.
J.
Forest
Econ.
(2015),
http://dx.doi.org/10.1016/j.jfe.2014.12.001
ARTICLE IN PRESS
G Model
JFE-25231;
No.
of
Pages
19
8
E.
Hjerpe
et
al.
/
Journal
of
Forest
Economics
xxx
(2015)
xxx–xxx
greater
detail
on
the
classification
of
type
(T),
scope
(S),
context
(C),
and
valuation
characteristics
(V)
for
primary
data
points.
Willingness
to
pay
primary
data
Adjusted
willingness
to
pay
estimates
for
ecosystem
conservation,
the
dependent
variable
in
this
meta-analysis,
were
compiled
from
22
primary
studies
and
are
exhibited
in
Table
1
(n
=
127).
The
pri-
mary
studies
employed
survey
techniques
to
convey
and
value
tradeoffs
of
conservation
programs
in
terms
of
changes
in
ecosystem
and
social
attributes
and
the
correlating
marginal
changes
in
ecosys-
tem
service
provision.
We
expressed
initial
WTP
estimates
in
2010
prices
using
country-specific
CPIs
followed
by
conversion
into
PPP
dollars
using
the
Penn
purchasing
power
parity
index.
To
test
whether
or
not
certain
ecosystem
conservation
strategies
were
favored
over
others,
willing-
ness
to
pay
estimates
were
classified
for
changes
in
ecosystem
attributes
resulting
from
preservation
and
two
types
of
restoration:
forest
and
freshwater.
Preservation
strategies
were
limited
to
forested
ecosystems
primarily
on
public
lands,
and
inherently
include
both
freshwater
and
forest
resources
contained
in
forested
watersheds.
We
were
able
to
categorize
restoration
by
landscape
type
(forest
or
freshwater)
because
restoration
projects
are
inevitably
conducted
at
a
finer
resolution
than
preser-
vation,
given
the
different
activities
required
to
restore
riparian
resources
and
structural
components
of
a
forest.
Classification
of
WTP
for
preservation,
freshwater
restoration,
and
forest
restoration
was
straightforward
for
most
primary
studies,
as
they
reported
estimates
directly
for
attributes
for
each
of
these
conservation
types
(see
Hanley
et
al.,
1998;
Mueller
et
al.,
2013).
When
the
type
of
ecosystem
conservation
was
not
explicitly
stated,
we
interpolated
the
classification
from
survey
and
study
site
context
provided
in
manuscripts.
For
example,
Meyerhoff
et
al.
(2009)
used
choice
experiments
to
measure
WTP
for
changes
in
attributes
resulting
from
“nature-oriented
silviculture.”
This
term,
and
their
description
of
the
conservation
strategy
to
respondents,
is
entirely
consistent
with
forest
restora-
tion.
Others
conveyed
conservation
strategies
to
respondents
in
terms
of
“biodiversity
reserves”
(e.g.,
Garber-Yonts
et
al.,
2004)
or
“protected
natural
areas”
(e.g.,
Wilson
et
al.,
2010)
–
clearly
indicating
preservation
strategies.
To
measure
scope
effects
in
our
meta-analysis,
we
followed
the
terminology
and
classification
put
forth
by
Hanley
et
al.
(1998)
and
Caparros
et
al.
(2008),
among
others.
Specifically,
we
categorized
all
WTP
estimates
into
three
levels
of
conservation
intensity:
attribute-specific,
program
low,
and
pro-
gram
high.
These
levels
of
conservation
intensity
reflect:
(a)
the
number
of
environmental
attributes,
as
conveyed
to
respondents
of
primary
studies,
that
will
change
due
to
the
proposed
conservation;
and
(b)
the
scale
of
these
changes
away
from
the
status
quo,
as
conveyed
to
respondents
of
primary
studies.
This
classification
allowed
us
to
avoid
the
problem
of
comparing
different
quantities
of
land
units
(e.g.,
acres
and
river
miles)
and
limiting
our
pool
of
estimates
to
absolute
measurement
only.3We
concluded
that
the
primary
investigators
sufficiently
portrayed
the
range
of
ecosystem
changes
that
would
result
from
conservation
and
that
both
absolute
and
relative
measurements
were
important
to
capture.
Measures
of
attribute-specific
WTP
were
determined
by
varying
the
levels
of
these
attributes
and
marginal
implicit
prices
for
them.
Changes
in
attributes
were
presented
in
either
absolute
terms
(e.g.,
with
preservation,
woodland
caribou
populations
would
increase
from
400
to
600
–
Adamowicz
et
al.,
1998,
p.