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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). Conservation Biology Volume 22, No. 3, 2008 Economic Valuation of Biodiversity 626 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- Conservation Biology Volume 22, No. 3, 2008 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 Conservation Biology Volume 22, No. 3, 2008 Economic Valuation of Biodiversity 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) Conservation Biology Volume 22, No. 3, 2008 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 Conservation Biology Volume 22, No. 3, 2008 Economic Valuation of Biodiversity 630 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 Conservation Biology Volume 22, No. 3, 2008 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 Conservation Biology 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 Conservation Biology 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. 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