Download Economic Valuation of Biodiversity Conservation

Contributed Paper
Economic Valuation of Biodiversity Conservation: the
Meaning of Numbers
BERTA MARTÍN-LÓPEZ,∗ CARLOS MONTES, AND JAVIER BENAYAS
Social-Ecological Systems Laboratory, Department of Ecology, c. Darwin, 2. Edificio Biologı́a, Universidad Autónoma de Madrid
28049, Madrid, Spain
Abstract: Recognition of the need to include economic criteria in the conservation policy decision-making
process has encouraged the use of economic-valuation techniques. Nevertheless, whether it is possible to accurately assign economic values to biodiversity and if so what these values really represent is being debated.
We reviewed 60 recent papers on economic valuation of biodiversity and carried out a meta-analysis of
these studies to determine what factors affect willingness to pay for biodiversity conservation. We analyzed
the internal variables of the contingent-valuation method (measure of benefits, vehicle of payment, elicitation format, or timing of payment) and anthropomorphic, anthropocentric and scientific factors. Funding
allocation mostly favored the conservation of species with anthropomorphic and anthropocentric characteristics instead of considering scientific factors. We recommend researchers and policy makers contemplate
economic valuations of biodiversity carefully, considering the inherent biases of the contingent-valuation
method and the anthropomorphic and anthropocentric factors resulting from the public’s attitude toward
species. Because of the increasing trend of including economic considerations in conservation practices, we
suggest that in the future interdisciplinary teams of ecologists, economists, and social scientists collaborate
and conduct comparative analyses, such as we have done here. Use of the contingent-valuation method in
biodiversity conservation policies can provide useful information about alternative conservation strategies
if questionnaires are carefully constructed, respondents are sufficiently informed, and the underlying factors
that influence willingness to pay are identified.
Keywords: attitudes toward animals, biodiversity conservation, conservation policy, economic valuation of
biodiversity, meta-analysis, willingness to pay
Valoración Económica de la Conservación de la Biodiversidad: el Significado de los Números
Resumen: El reconocimiento de la necesidad de incluir criterios económicos en el proceso de toma de
decisiones sobre polı́ticas de conservación ha impulsado el uso de técnicas de valoración económica. Sin
embargo, aún se debate si es posible asignar valores económicos precisos a la biodiversidad, ası́ como lo
que esos valores realmente representan. Revisamos 60 artı́culos recientes sobre valoración económica de la
biodiversidad y realizamos un meta análisis de estos estudios para determinar los factores que afectan la
disposición a pagar por la conservación de la biodiversidad. Analizamos las variables internas del método
de valoración contingente (medida de los beneficios, forma de pago, formato de respuesta o frecuencia
de pago) y de factores antropomórficos, antropocéntricos y cientı́ficos. La asignación de recursos favoreció
principalmente a la conservación de especies con caracterı́sticas antropomórficas y antropocéntricas en vez de
considerar factores cientı́ficos. Recomendamos que los investigadores y polı́ticos contemplen cuidadosamente
las valoraciones económicas de la biodiversidad, considerando los sesgos inherentes del método de valoración
contingente y los factores antropomórficos y antropocéntricos resultantes de las actitudes del público hacia
las especies. Debido a la creciente tendencia por incluir consideraciones económicas en las prácticas de
conservación, sugerimos que equipos interdisciplinarios de ecólogos, economistas y cientı́ficos sociales en el
futuro colaboren y dirijan análisis comparativos, tal como hemos hecho aquı́. El uso del método de valoración
∗ email
[email protected]
Paper submitted May 2, 2007; revised manuscript accepted October 30, 2007.
624
Conservation Biology, Volume 22, No. 3, 624–635
C 2008 Society for Conservation Biology
DOI: 10.1111/j.1523-1739.2008.00921.x
Martı́n-López et al.
625
contingente en las polı́ticas de conservación de la biodiversidad puede proporcionar información útil sobre
estrategias de conservación alternativas si los cuestionarios son cuidadosamente elaboradas, los encuestados
estén suficientemente informados y se identifican los factores que influyen sobre la disposición a pagar.
Palabras Clave: actitudes hacia los animales, conservación de la biodiversidad, meta análisis, polı́tica de conservación, valoración económica de la biodiversidad, disposición a pagar
Introduction
Social sciences need to be incorporated into conservation
science and practice because biodiversity conservation
is as much about people as it is about other species
(Mascia et al. 2003). For instance, environmental economics can inform conservation biologists and policy
makers about why species are endangered, the opportunity costs of protection activities, and the economic
incentives for conservation (Shogren et al. 1999). Scientists argue that economic criteria need to be a part of the
design and implementation of conservation policies (MEA
2005). Similarly, many institutional programs, such as the
Convention on Biological Diversity (CBD) or the Natural
Resource Management program (OECD 2002), recognize
the importance of understanding the economic value of
biodiversity for conservation policy making. Economicvaluation techniques have recently moved from scientific
forums to management practices in the design of systems that pay landowners for ecosystem services (payments for environmental services [PES]). For example,
the World Bank is developing PES schemes based on
economic-valuation techniques in several countries of
Central and South America and Africa.
Among the economic-valuation techniques, the
contingent-valuation method has been used widely to
measure the economic value of species. The procedure
is based on a hypothetical market in which people are
asked through questionnaires to express their maximum
willingness to pay (WTP) for the protection of biodiversity (Loomis & White 1996). Although contingent valuation has been commonly used in policy-related research,
there are numerous critiques in the literature that concern their content and questionnaire design and the validity and reliability of their results (Mitchell & Carson
1989; Venkatachalam 2004). It is necessary to identify
and measure the inherent biases of contingent-valuation
studies in order to reduce internal inconsistency (White
et al. 2001).
Debate continues on the factors, from anthropomorphic to scientific, that affect WTP for biodiversity conservation (e.g., Tisdell et al. 2007). Other factors, such as
species’ usefulness to humans, may also play important
roles in determining WTP for biodiversity conservation.
Our objectives here were to report and analyze the
underlying factors that explain the economic values of
species; obtain evidence about the relationship between
human attitudes to animals and the WTP for conservation;
generate useful criteria to incorporate economic values
in conservation policies, and explore the crucial need for
interdisciplinary research teams.
Methods
Data Collection
To address the controversies surrounding the economic
valuation of biodiversity, we performed an extensive
meta-analysis of contingent-valuation studies. We used
the following criteria to select studies for inclusion in
the analysis. First, studies had to be published in peerreviewed journals to avoid unknown and inaccessible
studies. Nevertheless, we included gray literature if it was
included in some of the studies published in the peerreviewed literature (Hageman 1985; King et al. 1988;
Duffield, unpublished [1991], 1992; Duffield et al. 1993;
Tanguay et al. 1993, 1995; Brown et al. 1994). Second, because some studies reported multiple estimates
of WTP, we used the best estimation if it was identified by the authors; otherwise, we averaged their WTP,
unless the variation in estimated values was related to
our explanatory variables. All WTP estimates were converted to 2005 U.S. dollar values (Consumer Price Index,
http://www.bls.gov/cpi/home.htm). Third, the studies
included in the analysis determine WTP for single species,
instead of biodiversity in general terms.
Data Analysis
To examine financial support for biodiversity conservation, we considered variables that economic-valuation
theory suggests are important and variables that explain
human attitudes toward biodiversity (Table 1).
Contingent-valuation surveys are context-dependent,
that is, the values estimated are subject to various aspects of the questionnaire design. Although some elements of the survey are expected to be neutral (e.g.,
questions about family size should not influence an individual’s response to the WTP question), others have a
significant influence on a respondents’ valuation (Bateman et al. 2002), such as the measure of benefits, vehicle
of payment, how information was gathered (elicitation
method), and timing of payment (Table 1).
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Economic Valuation of Biodiversity
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Table 1. Description of variables used in the analyses of willingness to pay (WTP).
Variables
Type
Economic
benefit measure
nominal
vehicle payment
dummy
elicitation method
nominal
timing of payment
Anthropomorphic
length
weight
eye sizea
phylogeny
ecosystems
dummy
dummy
continuous
continuous
continuous
nominal
dummy
dummy
dummy
dummy
nominal
dummy
Anthropocentric
usefulness
economically negative
population sampled
Scientific
change in species
population size
IUCN statusb
mean length of a species (cm)
mean weight of a species (kg)
axial length of eye (mm)
mammals
birds
reptiles
fish
invertebrate
1, mammal; 0, otherwise
1, bird; 0, otherwise
1, reptile; 0, otherwise
1, fish; 0, otherwise
forest
mountain
urban cultivated
dryland
inland water
marine-inland water
marine coastal
marine
1, marine, anadromous, or marine-coastal
species; 0, otherwise
1, useful; 0, otherwise
dummy
1, economic negative; 0, otherwise
dummy
1, resident; 0, visitor
continuous
change in species population size
proposed in questionnaire (%)
5, CR; 4, EN; 3, VU; 2,
NT; 1, LC; 0, nonendangered
1, functional role; 0,
nonfunctional role in ecosystem
1, endemic species in the region of
economic study; 0, otherwise
ordinal
dummy
geographical range
dummy
b CR,
WTP to secure a gain
WTP to avoid loss
WTP to biodiversity plan
1, WTP by coercive payments
0, WTP by voluntary payments
open-ended
payment card
dichotomous choice
multiple choice
1, continuous; 0, discrete choice
1, lump sum; 0, annual payment
dummy
ecological role
a We
Attributes
Analysis
Kruskal–Wallis
Mann–Whitney
Kruskal–Wallis
Mann–Whitney
Mann–Whitney
Spearman correlation
Kruskal–Wallis
multivariate regression
Kruskal–Wallis
multivariate regression
Mann–Whitney and
multivariate regression
Mann–Whitney and
multivariate regression
Mann–Whitney
simple regression
Kruskal–Wallis and
multivariate regression
Mann–Whitney and
multivariate regression
Mann-Whitney
compiled existing data on eye axial lengths from Howland et al. (2004).
critically endangered; EN, endangered; VU, vulnerable; NR, near threatened; LC, least concern.
We classified the types of benefit measures as WTP to
avoid a loss, WTP to secure a gain, and WTP to invest in a
biodiversity plan. Usually the estimates from contingentvaluation studies are derived from either WTP to avoid
loss of a species (e.g., amount one is willing to pay to prevent a species from going extinct) or WTP for a proposed
gain in numbers (e.g., amount one is willing to pay to im-
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prove the chance of survival of a species by 50–99%).
Another common measure of WTP is the amount a person is willing to pay to a conservation plan for a species.
We classified payment vehicles as voluntary or coercive. Coercive payments included taxes, fees, or charges.
Voluntary payments were donations or gifts (Bateman
et al. 2002).
Martı́n-López et al.
Stated-preference (elicitation) methods differed in how
much information they conveyed to and collected from
respondents (Bateman et al. 2002). The open-ended
stated-preference format asked respondents what maximum amount they would be willing to pay for species
conservation. The payment-card formats contained a
range of values from which the individuals chose their
maximum WTP. Dichotomous-choice elicitation methods required respondents to answer yes or no when asked
if they were willing to pay a given amount for species
conservation. In previous approaches, researchers assumed respondents had no uncertainty regarding their
preferences. Nevertheless, allowing only yes-or-no answers can result in respondents who are uncertain answering yes in support of biodiversity conservation programs (Brown et al. 1996). To allow for respondents’
uncertainty, Welsh and Bishop (1993) developed the
multiple-bounded approach, which contains elements of
both the payment card and dichotomous-choice formats.
As for the payment-card format, respondents were presented with an ordered sequence of WTP amounts, but
rather than circling a single value, the respondents were
given a multiple-choice response option, including “definitely yes,” “probably yes,” “unsure,” “probably no,” and
“definitely no” to each amount presented. Accordingly,
we classified the elicitation questions into open-ended,
payment-card, dichotomous-choice, and multiple-choice
formats.
Comparisons of different contingent-valuation studies
indicate there were systematic differences between values elicited with continuous (open-ended and paymentcard) and discrete choice (dichotomous and multiplechoice) formats (Brown et al. 1996). In general, values
collected with discrete-choice formats exceed values collected with open-ended (Reaves et al. 1999) or paymentcard formats (Welsh & Poe 1998). For that reason we
also classified the elicitation formats into continuous and
discrete-choice formats.
For timing of payment some researchers asked respondents to express their WTP as an annual amount, whereas
others used a single lump sum payment. The expected effect was that a one-time payment would be larger than an
annual payment stretched over time into the immediate
future.
Among variables that can explain social preferences,
we studied 3 factors: (1) anthropomorphic, associated
with the likeability and similarity of species to humans,
(2) anthropocentric, related to the usefulness of species,
and (3) scientific, which determine whether scientific
knowledge influences estimates of WTP (Table 1).
The scientific literature indicates that conservation
support is positively related to the perceived attractiveness of nonhuman species, which usually is an extension of human similarity (i.e., the similarity principle)
(Plous 1993; Gunnthorsdottir 2001). Perceived similar-
627
ity between humans and nonhuman species is related to
the phylogenetic level (Eddy et al. 1993) and to physical characteristics such as length, weight, and eye size
(Herzog & Burghardt 1988). To study the effect of phylogenetic level, we classified species into mammals, birds,
reptiles, fishes, and invertebrates. These categories sometimes cause some species to be perceived as charismatic
fauna. Moreover, usually the charismatic species are related to different ecosystems (e.g., Asian elephant [Elephas maximus] with Indian forests, giant panda [Ailuropoda melanoleuca] with Chinese bamboo forests,
and giraffes [Giraffa camelopardalis] with African savannahs). For that reason we studied the effect of the
ecosystem on WTP. We classified the ecosystems according to the Millennium Ecosystem Assessment (MEA
2003). Because many fish species are anadromous, we
also included marine-inland water as an ecosystem type
(Table 1).
In addition, individuals can favor conservation of those
species with anthropocentric characteristics (DeKay &
McClelland 1996; Martı́n-López et al. 2007). In general,
species useful to humans are positively related to WTP,
and those that produce economic damages are negatively related to WTP estimates. To study in detail the
social role of species, we categorized them as species
that (1) generate crop damages, (2) generate economic
loss by predation on cattle, (3) are hunted or fished
for recreation, and (4) are a nonconsumptive tourism
resource.
Nevertheless, many wild species are perceived as having opposing attributes; sometimes they are considered
pests and other times they are considered valuable assets.
For instance, elephants are widely considered a pest by
local people in rural regions (Bandara & Tisdell 2003); on
the other hand, elephants attract tourism in protected areas (Wilkie & Carpenter 1999). The dual character of the
elephant as both agricultural pest and valuable economic
asset reflects the difficulty in classifying it as a useful or
economically negative species. Similarly, humans have
positive attitudes toward socially controversial animals
in the context of abstract existence values, but these attitudes quickly become negative when the presence of the
species is associated with economic costs in their immediate surroundings (Kaltenborn et al. 2006). This means
visitors have a higher WTP than local people (Loomis &
Larson 1994; Loomis & White 1996). For that reason we
studied the WTP estimates for visitor and for resident
respondents.
Finally, any preservation decision is likely to consider scientific knowledge about the species. We studied the relationship between WTP and degree of endangerment, in terms of 2 variables: change in population
size of a species proposed in the contingent-valuation
questionnaire and the endangerment categories of the
IUCN (World Conservation Union) Red List. To study the
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628
effect of IUCN categories, we classified the species in the
studies we examined as critically endangered (CR), endangered (EN), vulnerable (VU), near threatened (NR),
least concern (LC) (IUCN 2006), or not endangered.
Other scientific variables that can influence WTP are
knowledge of the ecological role of species and whether
the species is endemic.
To test the effect of these variables on WTP values for
species conservation, we used different statistical analyses. We used descriptive statistics to summarize the distribution of contingent-valuation studies by allocation of
study, taxonomic group, and ecosystem. To test the individual effect of nominal and dummy variables on WTP,
we used nonparametric statistics (Mann–Whitney and
Kruskal–Wallis). When the Kruskal–Wallis test achieved
90% significance, we used Dunn’s multiple comparison
posttest to compare WTP estimates of one group with
another. We also used correlation and simple regression
analyses to test the effect of continuous variables on WTP.
To obtain evidence about the relationship between human attitudes toward animals and WTP, we examined
the joint effect of anthropomorphic, anthropocentric,
and scientific variables through multivariate regression
analysis. Here, we used only those variables for which
data were available for all the species we examined. To
improve the model we expressed the frequency of pay-
ment as a dichotomous variable (lump sum). The dependent variable was the natural log of WTP.
Results
Contingent Valuation of Biodiversity
The number of selected studies was 60 (Table 2). The distribution of valuations by place indicated that 65% of the
economic-valuation studies were localized in the United
States, 15% in Europe, 8% in Australia, 6% in Canada, and
6% in Sri Lanka. The dominance of the United States is
due in part to the history of economic valuation there
(Gen 2004).
The final data set included 50 species distributed
among mammals (56%), birds (20%), reptiles (2%), fishes
(20%), and invertebrates (2%). Nevertheless, the studies
dedicated to these groups manifested a taxonomic bias
because 64% of studies focused on mammals, 23% on
birds, and only 1% on reptiles and crustaceans (Table
2). Similarly, the economic-valuation research showed
preference for studying species that live in marine and
forest ecosystems; these were 40% and 33% of studies,
respectively. In contrast, species that live in dryland and
urban-cultivated ecosystems were studied in only 4% and
1% of cases, respectively.
Table 2. Summary of economic values of species.
Taxa
Mammal
Rodentia
Artiodactyla
Carnivora
Common name
Scientific name
Mean value
(US$2005)a
Eurasian red squirrel
water vole
bighorn sheep
Sciurus vulgaris
Arvicola terrestris
Ovis canadensis
2.87
15.24
21.94
elk (red deer)
moose
woodland caribou
Cervus elaphus
Alces alces
Rangifer tarandus
206.93
145.49
44.74
coyote
California sea otter
European otter
giant panda
Canis latrans
Enhydra lutris nereis
Lutra lutra
Ailuropoda melanoleuca
5.49
36.76
24.40
13.81
gray wolf
C. lupus
19.26
gray seals
grizzly bear
Hawaiian monk seal
Halichoerus grypus
Ursus arctos horribilis
Monachus schauinslandi
12.83
38.89
93.87
Mediterranean monk seal
northern elephant seal
Steller sea lion
M. monachus
Mirounga angustirostris
Eumetopias jubatus
17.54
31.53
73.83
Reference
White et al. 2001
White et al. 1997
King et al. 1988
Brookshire et al. 1983
Bulte & Kooten 1999
Hammack & Brown 1974
Horne & Petäjistö 2003
Tanguay et al. 1993, 1995
Adamowicz et al. 1998
Stevens et al. 1991, 1994
Hageman 1985, 1986
White et al. 1997
Kontoleon & Swanson 2003
Hsee & Rottenstreich 2004
Duffield, unpublished data
Duffield 1992
Duffield et al. 1993
USFWS 1994
Chambers & Whitehead 2003
Bosetti & Pearce 2003
Brookshire et al. 1982
Samples & Hollyer 1990
Brown et al. 1994
Langford et al. 1998
Hageman 1986
Giraud et al. 2002
(continued)
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Martı́n-López et al.
629
Table 2. (continued)
Taxa
Cetacea
Common name
Scientific name
Mean value
(US$2005)a
Reference
beluga whale
blue whale
Delphinapterus leucas
Balaenoptera musculus
14.20
44.57
bottlenose dolphin
gray whale
Tursiops truncatus
Eschrichtius robustus
23.17
34.70
humpback whale
Megaptera novaeangliae
Lagomorpha
Perissodactyla
Proboscidea
brown hare
Pentro horse
Asian elephant
Lepus europaeus
Equus caballus
Elephas maximus
0.00
33.89
1.94
Diprotodontia
mahogany glider
tree kangaroos
29.88
53.10
Leadbeater’s possum
Petaurus gracilis
Dendrolagus bennettianus
D. lumholtzi
Gymnobelideus leadbeateri
Tkac 1998
Hageman 1985, 1986
Bulte & Kooten 1999
Hageman 1986
Hageman 1985, 1986
Loomis & Larson 1994
Samples et al. 1986
Samples & Hollyer 1992
Brown et al. 1994
Wilson & Tisdell 2003
White et al. 2001
Cicia et al. 2003
Bandara & Tisdell 2003
Bandara 2004
Bandara & Tisdell 2005
Tisdell et al. 2005b
Tisdell & Wilson 2004
25.83
Jakobsson & Dragun 1996
Harlequin Duck
wild goose
Wild Turkey
Whooping Crane
Peregrine Falcon
Bald Eagle
Histrionicus histrionicus
Anser sp.
Meleagris gallopavo
Grus americana
Falco peregrinus
Haliaeetus leucocephalus
11.15
11.91
11.59
53.42
29.89
114.67
Northern Spotted Owl
Strix occidentalis caurina
59.43
Mexican Spotted Owl
S. occidentalis lucida
74.38
Red-cockaded Woodpecker
Picoides borealis
12.10
White-backed Woodpecker
Dendrocopos leucotos
66.39
loggerhead sea turtle
Caretta caretta
16.98
Atlantic salmon
Salmo salar
arctic grayling
chinook salmon
Thymallus arcticus arcticus
Oncorhynchus tshawytscha
cutthroat trout
steelhead
shortnose sturgeon
Colorado squawfish
O. clarki
O. mykiss
Acipenser brevirostrum
Ptychocheilus lucius
17.02
64.47
30.86
10.91
striped shiner
Luxilus chrysocephalus
6.83
kelp bass
white croaker
riverside fairy shrimp
Paralabrax clathratus
Genyonemus lineatus
Streptocephalus woottoni
Marsupial
Bird
Anseriformes
Galliformes
Gruiformes
Falconiformes
Strigiformes
Piciformes
Reptile
Fish
Salmoniformes
Acipensiriformes
Cipriniformes
Perciformes
Crustacean
128.34
9.45
22.69
126.66
43.35
43.35
24.85
Tkac et al. 1998
Macmillan et al. 2002
Stevens et al. 1991
Bowker & Stoll 1988
Kotchen & Reiling 1998
Boyle & Bishop 1987
Stevens et al. 1991
Swanson 1993
Bulte & Kooten 1999
Rubin et al. 1991
Hagen et al. 1992
Loomis & González-Cabán 1998
Bulte & Kooten 1999
Loomis & Ekstrand 1997, 1998
Giraud et al. 1999
Bulte & Kooten 1999
Reaves et al. 1999
Fredman 1995
Fredman & Boman 1996
Whitehead 1992
Wilson & Tisdell 2003
Stevens et al. 1991
Bulte & Kooten 1999
Duffield & Patterson 1992b
Hanemann et al. 1991
Olsen et al. 1991
Duffield & Patterson 1992
Olsen et al. 1991
Kotchen & Reiling 1998
Cummings et al. 1994
Bulte & Kooten 1999
Boyle & Bishop 1987
Bulte & Kooten 1999
Carson et al. 1994
Carson et al. 1994
Stanley 2005
a Values
refer to the mean of values from the studies cited in Reference column.
presented at the Allied Social Science Association annual meeting: Field Testing Existence Values: An Instream Flow Trust Fund
Montana Rivers.
b Paper
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Table 3. Effect of study design on willingness to pay (WTP) for conserving biodiversity.
Variable
Benefit measure
Payment vehicle
Elicitation method
Timing of payment
Attribute
WTP to secure a gain
WTP to avoid loss
WTP to biodiversity plan
coercive
voluntary
open-ended
payment card
dichotomous choice
multiple choice
continuous format
discrete choice format
annual payment
lump sum
Valuea
55.06
24.75
10.29
40.16
29.06
34.58
26.74
42.29
49.96
36.96
48.90
40.72
79.33
Nonparametric result b
Kruskal–Wallis, χ2 = 8.30, df = 2, p = 0.02;
Dunn’s multiple comparison, p < 0.01
Mann–Whitney, U = 753; z = −1.64, p = 0.10
Kruskal–Wallis, χ2 = 5.52, df = 3, n.s.
Mann–Whitney, U = 649.5; z = −2.23, p = 0.03
Mann–Whitney, U = 532.5; z = −2.57, p = 0.01
a Value
b n.s.,
refers to mean WTP (US$2005).
not significant.
Effect of Study Design on the Economic Value of Species
WTP differed significantly with the choice of benefit measured in the hypothetical market, in which WTP to secure
a gain generated the highest values and WTP to biodiversity plan resulted in the lowest values. Willingness to
pay was significantly higher for coercive payments than
voluntary payments. Similarly, discrete-choice elicitation
formats generated significantly higher values than continuous formats. Willingness to pay for biodiversity conservation was significantly greater for one-time payments
than for annual payments (Table 3).
Effect of Anthropomorphic, Anthropocentric, and Scientific
Factors on WTP
Nonparametric analysis demonstrated that the effect of
the anthropomorphic and anthropocentric factors on
WTP was higher than scientific factors (Table 4). All physical variables (length, weight, and eye size) had a positive
and significant effect on WTP. Willingness to pay did
not differ among taxonomic groups or ecosystems. Nevertheless, the effect of the ecosystem on WTP differed
by taxonomic group (mammals and fishes). The Dunn’s
multiple comparisons test for WTP of mammal species
distinguished 3 statistically different ecosystem groups:
marine, forest or mountain, and inland waters and dry
lands. In addition, WTP for fish differed significantly between continental and marine or anadromous species
(Table 4).
Although whether a species is useful did not have an
effect on WTP, WTP differed significantly between those
species that have a negative economic impact and those
that do not (Table 4). When we compared the mean
WTP for species conservation among the categories of
(1) species that generate crop damage ($6.41), (2) species
that cause damage to cattle ($21.21), (3) species that are
a fishing or hunting resource ($54.60), and (4) species
that are a nonconsumptive tourist resource ($44.57), we
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found significant differences (Kruskal–Wallis, χ2 = 5.42,
df = 3, p = 0.10). Dunn’s test also showed significant differences (p < 0.01) between species that cause economic
loss and those that are exploited for recreation.
Although for the global data set the mean WTP was
higher for visitors than for residents, there were no significant effects. Nevertheless, visitor and resident WTP
for carnivore conservation differed significantly (Mann–
Whitney, U = 36; z = −2.68, p = 0.007). Carnivores
were usually valued higher by visitors ($147.80) than by
residents ($62.21).
The level of endangerment had an effect on the public’s decision to invest in biodiversity conservation when
it was stated in the questionnaire in terms of change in
a species’ population size (Fig. 1). There was an exponential relation (y = 10.88e0.0108x , R2 = 84.7%, n = 55)
between the change in population size and WTP. Nevertheless, when we analyzed the effect of the degree of endangerment on the basis of IUCN categories, there were
no significant differences. Ecological role and endemism
variables did not significantly influence WTP.
Allocation of Funds for Biodiversity Conservation
Because of the strong correlations between length of an
animal and eye size (Spearman’s rho = 0.794, p < 0.0001)
and between weight and eye size (Spearman’s rho =
0.914, p < 0.0001), we used only the eye-size variable
as an indicator of the anthropomorphic effect because it
was the most significant (Table 4).
Forty-six percent and 40% of the variation in WTP was
explained by the explanatory variables in the full and reduced model, respectively (Table 5). The effect of eye
size was positive and significant at the 10% level. The
taxonomic-class dummies had the expected effect on
WTP: higher forms of life were assigned higher economic
values by the respondents. Nevertheless, mammals and
birds did not have a significant effect, whereas reptiles
Martı́n-López et al.
631
Table 4. Effect of anthropomorphic, anthropocentric, and scientific factors on willingness to pay (WTP) for conserving biodiversity.a
Factor
Anthropomorphic
physical characteristics
phylogeny
ecosystems
mammals
birds
fish
Variable
Valueb
length
weight
eye size
mammals
birds
reptiles
fish
crustacean
forest
mountain
urban cultivated
dryland
inland water
marine-inland water
marine coastal
marine
marine coastal
marine
forest
mountain
dryland
inland water
forest
urban cultivated
inland water
marine–inland water
marine
inland water
–
–
–
43.39
44.49
16.98
37.56
24.85
56.37
38.67
29.89
13.13
19.52
55.82
44.36
40.36
46.53
61.77
49.85
46.36
11.22
19.82
60.32
29.89
22.09
68.85
39.19
10.50
Spearman’s rho = 0.31, p = 0.06
Spearman’s rho = 0.33, p = 0.05
Spearman’s rho = 0.43, p = 0.01
Kruskal–Wallis, χ2 = 0.74, df = 4, n.s.
usefulness
uselessness
economically negative
economically positive
resident
visitor
44.33
32.97
13.95
44.06
43.36
74.78
Mann–Whitney, U = 246; z = −0.13, n.s.
CR
EN
VU
NT
LC
not endangered
yes
no
endemism
nonendemism
17.54
39.87
36.08
42.84
48.04
41.13
36.18
49.59
40.36
42.33
Kruskal–Wallis, χ2 = 0.89, df = 5, n.s.
Anthropocentric
Scientific
IUCN
ecological role
geographical range
Nonparametric results
Kruskal–Wallis, χ2 = 8.64, df = 7, n.s.
Kruskal–Wallis, χ2 = 10.96, df = 5, p = 0.05;
Dunn’s multiple comparison, p < 0.01
Kruskal–Wallis, χ2 = 3.10, df = 2, n.s.
Kruskal–Wallis, χ2 = 6.10, df = 2, p = 0.05;
Dunn’s multiple comparison, p < 0.02
Mann–Whitney, U = 55; z = −2.29, p = 0.02
Mann–Whitney, U = 1629.5; z = −0.53, n.s.
Mann–Whitney, U = 255.5; z = −0.88, n.s.
Mann–Whitney, U = 276; z = −0.48, n.s.
a Abbreviations: n.s., not significant; IUCN, World Conservation Union; CR, critically endangered; EN, endangered; VU, vulnerable; NT,
nonthreatened; LC, least concern.
b Value refers to mean willingness to pay (US$2005)
had a significant negative effect in both expanded and
reduced models. Fishes presented only a significant negative effect in the reduced model. In addition, WTP for
marine species was statistically greater than for species
that live in continental ecosystems.
In the case of anthropocentric criteria, although a
species’ usefulness did not have an effect on WTP, the
economic impact of species was significantly negatively
related to WTP. Scientific criteria such as the degree of
endangerment measured by the IUCN categories and a
species’ ecological role did not have a significant effect on
WTP. Finally, one-time payments were considered more
favorably than annual payments.
Discussion
Because there are budget constraints on biodiversity
conservation, the contingent-valuation technique is
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Volume 22, No. 3, 2008
Economic Valuation of Biodiversity
632
Figure 1. Mean willingness to pay (WTP; US$2005) in
relation to changes in the population size of a species.
becoming increasingly important as a supplement to biological information in helping to define objectives and
priorities in conservation biology (White et al. 2001).
Nevertheless, the economic valuation of biodiversity is
affected not only by the inherent variables of contingent valuation (measurement of benefits, payment vehicle, elicitation format, or timing of payment) but also by
the public’s attitudes toward biodiversity. Therefore, for
effective conservation management, apart from knowledge of the economic value that people assign to biodiversity conservation, it is also important to determine
the underlying factors influencing WTP for biodiversity
conservation.
Willingness to pay for species conservation is strongly
determined by human attitudes toward these species.
People’s attitudes toward animals are generally based
on 2 distinct motivational considerations: affect, representing people’s affective responses to animals, and
utility, representing people’s perceptions of animals’ instrumental value (Serpell 2004). People’s affective responses toward species are influenced by anthropomorphic (Kellert & Berry 1980; Eddy et al. 1993; Plous 1993)
and anthropocentric variables (Serpell 1986; Herzog &
Burghardt 1988). On one hand, species that are phylogenetically close and physically similar to humans are
likely to attract more conservation support than dissimilar species (Gunnthorsdottir 2001; White et al. 2001;
Martı́n-López et al. 2007). On the other hand, species
perceived as useful or beneficial to humans are regarded
more positively than those perceived as useless or detrimental (DeKay & McClelland 1996; Martı́n-López et al.
2007).
In contrast to previous studies (e.g., DeKay & McClelland 1996), we found phylogeny did not explain well
WTP for biodiversity conservation. This might be partly
due to the combination of species included in each taxonomic class (Tisdell et al. 2005a). For example, support for turtle species may be almost as strong as for
some birds and mammals, although on the whole there
is stronger support for the latter (Tisdell et al. 2006).
Similarly, Stanley (2005) found considerable support for
the conservation of the Riverside fairy shrimp (Streptocephalus wootoni), even though it is an invertebrate
(Tisdell et al. 2005a). Nonetheless, because the economic valuation of Riverside fairy shrimp constitutes the
only study of a crustacean, Stanley’s results may not be
Table 5. Meta-analysis regressions for willingness to pay (WTP) for species conservation.
Full model
Variable
Constant
Ln (eye size)
Mammal
Bird
Reptile
Fish
Marine
Usefulness
Economic impact
World Conservation Union
Ecological role
Lump sum
n
R2
Adjusted R2
F
p
Akaike’s information criteria
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Volume 22, No. 3, 2008
coefficient
−3.873
0.554
1.743
1.383
−3.738
−2.226
0.437
0.491
−1.012
−0.115
−0.332
1.049
54
0.46
0.39
2.11
0.041
11.58
t ratio
−1.139
1.895
1.210
1.020
−2.115
−1.624
1.102
1.236
−1.862
−1.036
−1.034
2.859
Reduced model
p
coefficient
t ratio
p
0.261
0.065
0.233
0.314
0.040
0.112
0.077
0.223
0.070
0.306
0.307
0.007
−3.383
0.506
1.622
1.140
−3.177
−1.843
0.224
−0.988
1.750
1.134
0.854
−1.847
−1.408
0.597
0.328
0.087
0.263
0.397
0.061
0.076
0.053
−0.616
−1.215
0.031
1.033
54
0.40
0.37
2.36
0.033
5.35
2.801
0.007
Martı́n-López et al.
representative of WTP for the conservation of other invertebrates. On the other hand, as the similarity principle suggests, our reduced regression analysis showed
that fish have a significant negative effect on WTP. Nevertheless, the effect of fish on WTP is ambiguous because salmoniform species have an important cultural
and recreational value in the Pacific Northwest (U.S.A.)
(Loomis & White 1996). The higher amounts of WTP
for anadromous fishes may apply to all recreational fisheries. Thus, species that are hunting or fishing resources
were the ones most valued by the public. In addition,
among anthropocentric variables, a key variable determining WTP for biodiversity conservation was the economic damage caused by species, which was clearly and
negatively related to WTP.
With regard to scientific criteria, our results revealed
that respondents’ previous knowledge of changes in
species population size was the only significant variable
in determining economic value. The fact that information regarding endangerment status influences allocation
of funding for biodiversity conservation is supported by
the results of other experimental studies (e.g., Fredman
1995; Tkac 1998; Bandara & Tisdell 2005; Tisdell & Wilson 2006). Accordingly, endangered species are liable to
be greatly disadvantaged in competing for conservation
funds when the public is poorly informed about them
(Tisdell & Wilson 2006). Accurate information on conservation status of species can be important for improving
social decisions regarding biodiversity conservation. One
of the most obvious examples of the importance of public information in biodiversity conservation is the environmental campaigns developed to prevent commercial
whaling and sealing. Through these campaigns, whales
and seals acquired an iconic value for the conservation
movement in the 1970s (Corkeron 2004).
To provide useful and reliable information to policy
makers about biodiversity conservation, it seems appropriate to pay great attention to the underlying anthropomorphic and anthropocentric factors of species, particularly in those cases when the contingent-valuation
surveys do not provide knowledge of the scientific issues
concerning species. Understanding human attitudes toward biodiversity is essential to the work of correcting
the inherent bias associated with species valuation. To
understand the underlying motives behind WTP for biodiversity conservation, contingent-valuation studies should
be improved through the incorporation of other scientific disciplines, such as environmental psychology or human ecology. Therefore, conservation decision-making
processes call for interdisciplinary knowledge in which
conservation biologists and economists collaborate with
anthropologists and psychologists (Mascia et al. 2003;
Saunders et al. 2006). Implementing contingent valuation for biodiversity is a difficult task because the public
has a low level of understanding of what biodiversity
is and why it matters (Christie et al. 2006). Providing
633
accurate information about endangerment level, population status, geographical range, and the ecological role
of species can increase the reliability of the contingentvaluation method.
Consequently, use of the contingent-valuation method
in biodiversity conservation policies can provide useful
information about alternative conservation strategies if
questionnaires are carefully constructed, respondents are
sufficiently informed, and the underlying factors that influence willingness to pay are identified.
Acknowledgments
We thank 3 anonymous reviewers for helpful suggestions
on an early version of the paper and E. Main for careful
editing of the manuscript. Funding was provided by the
Department of Environment of the Andalusian Regional
Government (Project NET413308/1) and by the Spanish
Ministry of the Environment (Project 13/2006).
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